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Master’s Degree Studies in
International and Comparative Education, No. 23
—————————————————
Prepared for Teaching?
A Comparative Study of Novice Teachers
in the Federal Republic of Germany
Jochen Mühlbach
April, 2014
Institute of International Education,
Department of Education
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Table of Content
Table of Content ............................................................................................ 2
List of Figures ............................................................................................... 4
List of Abbreviations ..................................................................................... 5
Chapter 1
Introduction ................................................................................................... 7
1.1. Background of the study ........................................................................................ 7
1.2. Aims and Objectives .............................................................................................. 9
1.3. Limitations and delimitations of the research ........................................................ 9
1.4. Significance of the study ...................................................................................... 10
Chapter 2
Concepts and Practices ................................................................................ 11
2.1. Teacher Education in Germany ........................................................................... 11
2.2. The practice shock ............................................................................................... 13
Chapter 3
The Economics of Education as a Theoretical Framework ........................ 14
3.1. An economic perspective on education ............................................................... 14
3.2. Cost-benefit analysis in education ....................................................................... 15
Chapter 4
Methodology of the Research ..................................................................... 17
4.1. Research design ................................................................................................... 17
4.2. The research instrument ....................................................................................... 18
4.2.1. The Questionnaire ............................................................................................. 18
4.2.2. The Construction of the questionnaire .............................................................. 18
4.3. Ethical consideration ............................................................................................ 22
4.4. Conducting the research ....................................................................................... 22
4.4.1. The Participants ................................................................................................ 22
4.4.2. The process of the data collection ..................................................................... 23
Chapter 5
Technical information about the dataset ..................................................... 25
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Chapter 6
Analysis and Findings of the German Sample ............................................ 27
6.1. Development needs of German novice teachers .................................................. 28
6.1.1. High needs of professional development .......................................................... 29
6.1.2. Intermediate needs of professional development .............................................. 32
6.1.3. Low needs of professional development .......................................................... 35
6.1.4. Gender disparities ............................................................................................. 36
6.2. Teaching in the Target class ................................................................................ 37
6.3. Bivariate Analysis of Variables ........................................................................... 39
6.4. Split-Sample Analysis .......................................................................................... 41
6.5. Summary and interpretation of the findings from the German sample ............... 44
Chapter 7
International Comparison ............................................................................ 47
7.1. The International Sample ..................................................................................... 47
7.2. Findings from the international comparison ........................................................ 49
7.2.1. Professional development needs (international comparison) ........................... 49
7.2.2. Teaching in the Target Class (international comparison) ................................. 54
7.3. Summary and interpretation of the findings (international comparison) ............. 57
Chapter 8
Discussion ................................................................................................... 59
Chapter 9
Suggestions for Subsequent Research ......................................................... 61
References ....................................................................................................... 63
Annex A: The Questionnaire ………………………………………………………… 66
Annex B: Frequencies, Statistics and Tables (German Sample) …………………….. 70
Annex C: Frequencies, Statistics and Tables (International Sample) …………........... 91
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List of Figures
Figure 6-1. Average professional development needs (German sample)
Figure 6-2. Professional development needs: Student discipline and behaviour
problems (German sample)
Figure 6-3. Professional development needs: Teaching students with special learning
needs (German sample)
Figure 6-4. Professional development needs: Student assessment practices (German
sample)
Figure 6-5. Professional development needs: Knowledge and understanding of
instructional practices in main subject fields (German sample)
Figure 6-6. Professional development needs: Teaching in a multicultural and
multilingual setting (German sample)
Figure 6-7. Professional development needs: ICT skills for teaching (German sample)
Figure 6-8. Professional development needs: School management and administration
(German sample)
Figure 6-9. Professional development needs: Means of all skill areas (German
sample)
Figure 6-10. Professional development needs: Gender distribution (German sample)
Figure 6-11. Target class: Time spent on classroom activities (German sample)
Figure 6-12. Target class: Classroom disciplinary climate (German sample)
Figure 6-13. Split-sample: Professional development needs and time spend on teaching
(German sample)
Figure 6-14. Split-sample: Professional development needs and classroom disciplinary
climate (German sample)
Figure 6-15. Split-sample: Classroom disciplinary climate and classroom activities
(German sample)
Figure 7-1. The international sample
Figure 7-2. Average professional development needs (international sample)
Figure 7-3. Professional development needs: Student discipline and behaviour
problems (international sample)
Figure 7-4. Professional development needs: Teaching students with special learning
needs (international sample)
Figure 7-5. Professional development needs: Knowledge and understanding of
instructional practices in main subject field(s) (international sample)
5
Figure 7-6. Professional development needs: Gender distribution (international
sample)
Figure 7-7. Target class: Time spent on classroom activities (international sample)
Figure 7-8. Target class: Classroom disciplinary climate (international sample)
Note: Some figures had to be scaled down for an improved readability.
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List of Abbreviations
ECTS European Credit Transfer System
GEW Gewerkschaft Erziehung und Wissenschaft
KMK Kultusministerkonferenz der Länder
ISCED International Standard Classification of Education
MGCFA Multiple Group Confirmatory Factor Analysis
OECD Organisation for Economic Cooperation and Development
PISA Programme for International Student Assessment
TE Teacher Education
TALIS Teaching and Learning International Survey
SPSS Statistical Package for the Social Sciences
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Chapter 1
Introduction
1.1. Background of the study
In the mid-2000’s the Organization for Economic Cooperation and Development
(OECD) started working on a survey to examine the teaching and learning environment
in the schools of their member countries: The Teaching and Learning International
Survey (TALIS). In comparison to other popular OECD surveys as the PISA study, for
instance, its focus was on the perceptions of teachers and school leaders who were
asked about their working environment, their schools and their classrooms. The
survey’s overall aim was to provide an opportunity for teachers and principals to
contribute to education analysis and policy development with their personal input. In
addition to that, a cross-country analysis incorporated in the survey should help
countries to identify challenges in order to learn from effective policy approaches of
other OECD member states. The main data collection for this survey then occurred in
2008 and it was finally published in 2009. In total 24 countries took part in this first
cycle of which the majority were OECD members.
For the evaluation of the study the obtained data was categorised into specific
groups of teachers and principals to be analysed separately. However, another group of
the sample received special attention in the analysis. This group consisted of those
teachers that had less than two years of paid teaching experience – the so-called ‘new
teachers’ or ‘novice teachers’. Among many findings the researchers of TALIS could
ascertain that particularly these new teachers indicated little confidence in their ability
to be effective teachers. Their perceived self-efficacy in teaching was notably lower
compared to experienced teachers that had 3 or more years of paid teaching experience
in 23 out of 24 countries (OECD, 2012; OECD 2009).
They also revealed that new teachers use comparably less of their time on actual
teaching than the more experienced teachers. The largest proportion of this non-teaching
time is spent trying to keep order in classrooms. Simultaneously, difficulties in
providing effective instructions were commonly reported. The difference in comparison
to experienced teachers regarding these issues was significant, as well as the personal
impression of novice teachers that they had a high need to develop their overall
classroom management skills. One quarter of teacher novices mentioned insufficient
skills in this area, whereas this was only mentioned by less than one sixth of
experienced teachers. Coincidently, this was considered to be a large impact on their
own development as teachers (Jensen, 2012).
These findings led to the question of whether new teachers that have just finished
their teacher training actually feel prepared to teach in classrooms. A feeling of
unpreparedness would directly raise the question whether the teacher education (TE)
8
systems of these countries – each of with different from one another – are providing the
necessary skills and capacities for aspiring teachers to be prepared for their future
working environment. This phenomenon is also known as the ‘practice-shock’. It
addresses the discrepancy of the learned theory and those skills that would actually be
required for the first classroom experience, if those were not part of the teacher
education (Rizza, 2011). Findings as such are particularly crucial in the context of
teacher effectiveness. This has namely substantial influence on students and their
performance as a large number of studies could show. In other words, high-quality
education should be provided to students by any teacher regardless of years worked in
that profession if a school system should be effective (Leigh, 2010; OECD, 2005;
OECD, 2009). In fact, new teachers should be educated in a way to be capable of
providing teaching quality at a level that is at least as high as that of other teachers. As
findings could show that this is not the fact, those teachers that are novices in teaching
are going to be a central aspect of the second cycle of the TALIS survey that is
supposed to be published in 2014.
However, these findings all refer to teachers from those countries that participated in
TALIS 2008. One country that had not been part of this survey and will neither have
participated in the upcoming cycle of TALIS is the Federal Republic of Germany
(OECD, 2013a). Beyond being one of the OECD largest member states by population
and being characterised with one of the organisation’s strongest economies (OECD
Statistical Database), also educational factors result in this country being worthwhile to
consider in these circumstances. There might, for instance, be the country’s gradual
improvement throughout the recent OECD education surveys that were used as quality
indicators in education (BMBF, 2013). More relevant in such terms might yet be that
the German TE system has undergone profound reforms to improve educational quality
and to additionally enhance their teachers teaching skills. Whether the German TE
system is thus producing qualified teachers appears to be a crucial question also in
economic terms. As the educational outcome of such higher education programmes that
the state invests significant amounts of resources in can certainly only be to receive
ideally qualified individuals.
The scope of this study will therefore base on the experiences of German teachers
that received their teacher education in such a system. Hence, the research questions for
this study are:
1. Is the TE system of the Federal Republic of Germany capable of preparing their
teachers adequately for teaching?
2. What skills do German novice teachers consider to be important to have
acquired in their teacher education to perform well in their profession?
3. How do German novice teachers perform in classrooms?
4. How do the German novice teachers compare in these terms to teachers from
other countries that are also new in their profession?
9
1.2. Aims and Objectives
In order to be able to answer these research questions properly the study has to follow
an overarching aim of identifying whether, or not, and to what extent German teachers
that are new in their profession feel adequately prepared for their first classroom
experiences after having completed a TE study programme at higher education
institutes. As such objective is considered as rather vague it was subdivided into aims
that are more precise. Aims of this study are thus to
find out in which areas linked to the teaching profession the German novice
teachers feel prepared in, and in which they do not,
find out about their classroom performance in those classes they teach,
identify possible links between their feeling of preparedness and their classroom
performance, and to
find out how these findings compare to novice teachers from other countries that
have participated in the OECD TALIS survey.
1.3. Limitations and delimitations of the research
This study’s focus is primarily on those teachers that have less than two years of paid
teaching experience and that received their TE in the Federal Republic of Germany. It
will be mainly about their experiences in classrooms and subjective impressions of their
own professional performance. A comparison will therefore only be drawn between
them and novice teachers that have received teacher education in other countries than
Germany, but a supplementary comparison to experienced teachers will not be in focus
of this study. Since the research will have to rely of subjective indications, issues that
are related to the phenomenon of social desirability bias cannot be entirely excluded.
Limitations will have to be conceded regarding the German TE system, as well. That is
mainly for the reason that Germany’s higher education system and hence its TE system
is highly decentralised. Different education plans between the various states and
universities are, despite an overarching assembly of ministers responsible for decision
making, not uncommon. Such variances have to be considered when speaking about a
general system of TE. Yet, issues of centralisation and decentralisation of higher
education systems were not addressed in the TALIS 2008 survey. This bears a risk of
negatively affecting the representativeness of the sample and the comparison of the
populations if this research was only concentrated on specific TE systems of certain
German states. This factor shall be minimised by obtaining data from teacher novices
that have been educated in as many German states (and hence TE systems) as possible.
Additionally, it must be acknowledged that the researcher was educated as a teacher
in Germany which can be seen as an advantage regarding language barriers and
background knowledge about the German TE. This experience could, though, also lead
10
to the risk of bias and negligence of important facts that are taken for granted. A
research approach that is closely related to the OECD TALIS will therefore assist to
minimise such risks as far as possible.
1.4. Significance of the study
This study is of high significance for various reasons. In reference to other studies the
relevance of highly qualified teachers has already been explained. To be able to provide
high-quality education these teachers must previously have received education for their
profession that equipped them with those skills that are necessary for adequate teaching
and positive learning outcomes. Regarding systems of teacher education this issue has
yet another dimension. As will be outlined in the later chapters of this study TE
programmes of higher education are valuable investments in terms of state’s economics.
If the teachers that graduate from such programmes are, though, not adequately
prepared for their profession an economic mismatch is evident. Yet more relevantly,
comparable studies on new teachers in the Federal Republic of Germany are as of now
not existent. As previously mentioned this country’s teachers have neither participated
in TALIS 2008 nor in TALIS 2013. After the release of the first TALIS report in 2009
its relevance had yet resulted in the implementation of a German study based on the
survey’s questionnaires and was conducted by the German teachers union GEW. The
GEW study, however, had in comparison to this particular study not the new teachers in
its focus and further applied different sampling mechanisms in the data collection
(Demmer & Saldern, 2010).
11
Chapter 2
Concepts and Practices
2.1. Teacher Education in Germany
As mentioned in the introduction part of this document the German teacher education
system has a very distinctive feature to itself. It consists of classical higher education
programmes but provides further guidance after graduation for new teachers that have
just begun to teach in schools.
The initial part of this can be seen as a course of higher education to which the
admission requirements are met when an applicant has attained the German higher
education entrance qualification (Hochschulreife1). This equals a successful graduation
after 13 years2 of schooling by passing the final Abitur examination. The courses for TE
are offered at higher education institutes, referring to universities in the majority of
states. An exception – and as well an indicator that the German TE system is
characterised by minor contextual variations throughout the different states – is the state
Baden-Württemberg where this stage of TE is offered at colleges of education
(Pädagogische Hochschule). Due to Germany’s participation in the Bologna-process in
1999 the majority of higher education programmes has been reformed towards an
accreditation as Bachelor’s and Master’s study courses. This has had a substantial effect
upon the system of German TE which is now split into Bachelor’s and Master’s courses
at initial stage. Regarding the content of these courses, the reform included that TE in
Germany contains of an integrative – commonly tripartite - study of at least two subject
areas and the general science of education. This also led to a higher emphasis on
practical studies in schools, already at Bachelor’s level. The share of practical training
in this first stage of TE has thus been substantially increased. However, the main focus
is still situated on theoretical studies (EURYDICE, 2012).
Regarding educational sciences (and not the specific subject areas), prospective
teachers are therefore supposed to acquire skills and obtain competencies that are of
high significance in the field of teaching. In particular the Kultusministerkonferenz
(KMK) – an assembly of ministers for education of each German state – refers to
knowledge about the necessity of education, the profession and role of teachers, didactic
methods, the learning processes of their future pupils, classroom-communication,
appropriate use of media, differentiated instruction and assessment in terms of
heterogeneity, and educational science. These competencies shall mainly be acquired
theoretically at the higher education institution, but also in practice by model
simulations or in schools (KMK, 2012; KMK, 2004).
Furthermore, TE commonly at Master’s level requires a specification concerning
teaching careers. The offered types of teacher education in terms of these very careers
1 Sometimes terms in German have to be used for precision. These are then marked in italics.
2 In some states only 12 years of schooling are required.
12
differ though in the various German states and higher education institutions. Specific
careers are for that reason unavailable in certain states and most universities or TE
colleges concentrate on one career type. The six different types are the following:
Type 1: Teaching careers at the ‘Grundschule’ (first 4 years of primary schooling) or
primary level,
Type 2: General teaching careers at primary level and all or individual lower secondary
level school types,
Type 3: Teaching careers at all or individual lower secondary level school types,
Type 4: Teaching careers for the general education subjects at upper secondary level or
for the ‘Gymnasium’,
Type 5: Teaching careers in vocational subjects at upper secondary level or at
vocational schools, and
Type 6: Teaching careers in special education (EURYDICE, 2012, p.13).
The time that it takes teacher aspirants to graduate from their higher education
programmes is as a consequence closely related to these very career types and varies
from four to five years, or respectively, from 210 to 300 credits as specified in the
European Credit Transfer System (ECTS) (further differences apply for the earlier
mentioned state of Baden-Württemberg). Such career choices have then major influence
on the final placement in schools (according to their types) and the subsequent
preparatory service.
In the German TE system all teaching career studies at a higher education institution
are namely followed by the so called Referendariat, a preparatory service for teachers.
In this period the focus is on practical experiences that are partly gained through sitting
in on classes, but mainly through guided and independent teaching at schools.
Additionally, this service consists of further didactical and theoretical studies (that are
supposed to be subject related) at teacher training institutes. Its main objective is hence,
to provide guidance over the teachers’ first months in their profession and to enhance
their teaching skills and competencies. In order to enable theoretical and didactical
reflection processes and evaluation beyond training institutes, the teacher aspirants are
commonly mentored by one (or more) experienced teacher(s) in the role of teacher
educators. In most cases preparatory service lasts for 18 to 24 months (it can however
be reduced or extended and there are notable variations between states) and is
completed by theoretical and practical examinations (EURYDICE, 2012).
Novice teachers in the Referendariat are paid a certain salary throughout their
preparatory service. The amounts differ though according to the respective career type
as well as to the state the preparatory service is done in (Bundesministerium der Justiz,
1975).
13
2.2. The practice shock
The term ‘practice shock’ refers, in broader terms, basically to the feeling of
unpreparedness that individuals have to face in their first employment that is related to
their previous education. Ulvik et al. identify the significance of this phenomenon
especially in teachers that have had some kind of teacher education or training. Those
teachers feel unprepared for the challenges they have to deal with in the reality of
classrooms and the complexity of classroom-society. Related to idealistic expectations
of teaching that may neglect the diversity of classrooms, such situations occur typically
in spite of the novices’ previous education as teachers if this TE was not capable of
equipping them with the needed practical skills in order to overcome these very
challenges. This mismatch between theoretical knowledge and practical competencies –
both certainly necessary for high quality teaching – commonly results from TE systems
that are merely concentrated on specific subject studies that emphasise theoretical
knowledge which is however detached from classrooms. This is therefore an issue of an
adequate integration of theory and practice in TE (Ulvik, et al.,2009; Achinstein &
Barrett, 2004).
Ulvik and Smith describe this issue with the use of the philosophical terms of
techné, epistéme and phrónesis.
“Student teachers need techné (knowing how) and by connecting the skills of
teaching to epistéme (knowing that), through reflection, they will gradually
start developing phrónesis (practical wisdom).” (Ulvik & Smith, 2012, p.520).
To finally achieve a process of phrónesis it is though mostly required to be guided
so that reflection and evaluation can be encouraged from an exterior level. In the case of
aspiring teachers this would thus mean that they are accompanied by more experienced
teachers. However, the proportion of theory and practical experiences must inevitably
be balanced as otherwise existing teaching mechanisms could remain unquestioned and
thereby reproduced (ibid).
Implementing practical experiences into TE systems is though not impossible and its
benefits are frequently observed in systems that include a designated phase of
practicum. These enable opportunities for aspiring teachers to practically apply
previously studied theory in supervised contexts. For instance, Ezer et al. could observe
notable positive experiences of TE students during and after their practicum phase. The
majority of students examined, reported significant improvements regarding their
professional skills and motivation, and felt thereby more prepared for possible work-
related challenges of the future (Ezer et al., 2010).
14
Chapter 3
The Economics of Education as a Theoretical Framework
3.1. An economic perspective on education
It has to be regarded as undeniable that the discipline of education is at policy level not
independent of financing, expenses and hence an authority’s economical division. An
important factor in this scheme is necessarily the kind of education an individual
receives and whether this will be relevant for a nation’s economy when the acquired
skills are transferred to the labour marked. This principle was already expressed by
Smith in the 18th
century stating that such individual:
“educated at the expense of much labour and time to any of those
employments which require extraordinary dexterity and skill, may be
compared to one of those expensive machines. The work which he learns to
perform, it must be expected, over and above the usual wages of common
labour, will replace to him the whole expense of his education, with at least
the ordinary profits of an equally valuable capital." (Smith, 1776, p.107)
A factor of highest importance regarding policy making in education is thus the
question whether a nation’s expenses for educating an individual to perform a certain
task are at an appropriate rate regarding the benefits that individual will have for the
labour market. In other words and in relation to the quotation above, whether the money
spent for such an expensive machine pays off over time and thus leading to a positive
economic balance. Such vague ideas in terms of human capital and in this context
expected rates of return were originally formulated in Marshall’s principles of
economics who described the training of a worker to perform tasks he could have not
performed without this particular training as a national investment that though also
includes indirect benefits (Marshall, 1890). As Psacharopoulos and Patrinos point out
there is hence a theoretical link between education and productivity. Certainly, theories
regarding the economics of education have been redefined and more explicitly
formulated since the times of Smith and Marshall - the authors specifically refer to the
influence of the modern human capital school of the late 1950’s, however, the concept
has in its basics remained persistent. These more advanced schools of thoughts yet
explicitly identified that expenditure classified as an investment in education builds
human capital which can be compared in similar ways as it can be done with investment
in physical capital. This means that such investment should inevitably have a certain
rate of return that should be estimated, measured and possibly even predicted
(Psacharopoulus & Patrinos, 2004). In its principles this theory hence contains the idea
of education and training as a sort of investment. An investment is thereby the process
of spending resources on assets that will assure benefits over a longer period of time.
Investing in education and training must in this context be seen as a long lasting process
that enables future benefits for the individual and increases the quality and productivity
of the labour force (Woodhall, 1987).
15
3.2. Cost-benefit analysis in education
In any economical focus the previously mentioned benefits of an investment must be
regarded as vitally important. It is easily understandable that acquiring assets on a
specific rate of expenses should result in favourable returns that result in a profit for the
investor. In terms of purchasing goods as industrial machinery, for example, the
estimation of such profits may be simple as seeing if an acquirement has (if adequate)
an immediate effect on the production. The most important factor regarding a positive
economic ratio is here whether this effect will last long enough to compensate the given
expenses. In terms of education and human capital, however, such balance is not as
simple to predict as it is by far more complex. Yet, being able to analyse how profitable
it might be to invest resources in educating and training an individual rather than
investing these resources in other processes or acquiring previously mentioned goods
that have direct impact is an important factor in the development of a society or a
nation. The question of how profitable education might be is therefore based on a large
number of economic models and techniques.
Cost-benefit analysis approaches in education are thus aiming to identify the total
costs of educating an individual in order to compare these with the expected returns that
might later on result from this investment. As said already these techniques are rather
complex as one cannot only take financial calculations, as for instance to acquire certain
goods into account. In order to consider the entire costs of education, which is a long-
term investment with a large variety of expenses, all resources devoted to that process
have to be included. In economists’ terminology such array is called the ‘opportunity
cost’. Woodhall states in this context that the
“opportunity cost includes the value of all the goods and services used in the
education, not only the time of teachers and other staff, the use of books,
equipment, furniture, heat, light, materials, and school or college buildings, but
also the time of students and pupils, which does not form part of the money
costs of education, but is part of the real resource cost.” (Woodhall, 1987, p.2)
This mainly points out that aside from all the mentioned inputs (a list that could
certainly even be extended) the time that education takes is a vital factor in cost-benefit
analyses of education. From the individual’s perspective, this specific time that one
dedicates to receive education is commonly termed ‘earning forgone’, as it is not used
to earn money in the labour market. From the economy’s perspective, this time
describes the potential loss of labour output if that individual had been employed
throughout that time (Woodhall, 1987, Belli et al., 1998). In an economic model all
these elements that affect the opportunity cost variable in education can be considered
the input into a production process, whereas the graduates from that specific educational
stage but also its dropouts would be considered as the output of this process. This
economic tool of Input-Output analysis is frankly primarily designed for industrial
production processes and to a certain extent not more than a simplified picture of such
very process. However, after Tinbergen it is also applicable to education as education
and training may in terms of human capital and from an economic approach be seen as a
production process (Tinbergen, 1987).
16
Especially at output level such models have yet to be more comprehensive than
only measuring graduates and dropouts. Even though hard to measure, a highly
significant factor in this process is the quality of education that an individual receives. It
appears evident that the product of any industrial process has to be of optimum quality
as far as input allows. A product that is inadequate in its quality despite large costs of its
production is clearly dissatisfying. This factor, in turn, is at least just as important in
terms of education. Consequently, in the context of this document the final product of
teacher education would be those teachers that graduated from the programme.
The field of economics of education in terms of teacher education programmes has
not particularly been discussed in publications in this area. As stated before, measuring
the output of teacher education programmes – the novice teachers – according to quality
has only been considered recently (OECD, 2005). Regarding the quality of the
education process these teachers should yet be adequately skilled that they are well
prepared to work in their profession. From an economic perspective the resources that
are invested in the process of teacher education would therefore be considered as best-
invested if the graduating teachers (the desired part of the output) fulfil this criterion.
17
Chapter 4
Methodology of the Research
Methods of social research can be generally divided into two different kinds:
quantitative and qualitative research methods. Quantitative methods aim to clarify social
phenomena on the basis of numerical data of a large number of cases that can further on
be generalised to a certain population. These commonly follow deductive approaches
that try to identify theoretical truth, and examine specific hypotheses, through samples.
The larger and the more representative a sample is, the more applicable will the
obtained data in terms of generalising it to a population be. Quantitative research
methods often use research instruments that allow this kind of sampling like self-
completion questionnaires or structured interviews (Bryman, 2012).
Qualitative research methods, however, aim to investigate specific cases in their
given contexts. The approaches that examine the relationship between theory and the
research are rather inductive. In the context of social research these methods therefore
study the subjective views and relations of individuals and are able to analyse their
behaviour, attitudes or values. Commonly used research methods in order to obtain
adequate data are rather unstructured and leave room for any kind of answers or
findings in e.g. observations or interviews (ibid).
4.1. Research design
The essential feature of this study and its research is to be identified in its comparative
aspect. This provides the opportunity of putting information about the German novice
teachers and their teaching experiences into relation with that of teachers from other
countries that are also new in their profession. The latter information has already been
gathered within the research of the OECD TALIS survey and can thus be used as
secondary data. Clearly, the underlying research of teachers in Germany has to follow
the same principles as that study did, or otherwise findings from comparison would be
of little use.
The design for this research is therefore initially of cross-sectional nature as it is
supposed to examine a large number of cases at a single point in time and that gathers
quantifiable data. Such a design allows analysis about issues of preparedness that are
considered to be of high significance for this study. In addition to that, it enables the
possibility to compare the obtained information with the TALIS 2008 sample which
was based on a similar design.
18
4.2. The research instrument
4.2.1. The Questionnaire
The main data of this research was collected with a self-completion questionnaire. This
quantitative measurement tool encompasses a variety of items regarding the
professional experiences of new teachers. In order to be comparable to the results of
OECD’s TALIS survey these items had to be identical with the respective items of this
survey. To minimise the risk of a decreasing validity the development of this
questionnaire for the German participants had to be guided by the translation and
adaption procedures that are presented in the technical report of the TALIS 2008 survey.
This report features furthermore indicators of quality assurance that could be applied in
the construction process of the questionnaire (OECD, 2010a). Thus, quality criteria of
validity, reliability and objectivity could be properly maintained and the study could
also be reproduced in terms of being replicable.
The exact construction of this research tool, its items translation and modification
and a more in-depth view on the original TALIS questionnaire will be in focus of the
next section.
4.2.2. The Construction of the questionnaire
As previously elaborated the questionnaire that was used as the main tool for the data
collection of this research was constructed from the official OECD TALIS survey
questionnaire. As that survey not only focuses on teachers but also on principals, it
consists of two sets of questions that are directed towards either the principals or the
teachers. For the research of this study the principals’ questionnaire had to be neglected
and only the teachers’ questionnaire was used. This form, used to obtain information
from teachers in the TALIS 2008 survey, consists of 43 questions in total which are
structured into the following 5 sections.
1. Background Information (Questions 1 – 10)
2. Professional Development (Questions 11 – 20)
3. Teacher Appraisal and Feedback (Questions 20 – 28)
4. Teaching Practices, Beliefs and Attitudes (Questions 29 – 33)
5. Teaching in a Particular Class (Questions 34 – 43)
The fifth section of this questionnaire aims to receive information about the
teaching and classroom routines in one particular class that the participant is teaching.
To provide an overview as objective and as generalisable as possible, this section
follows a cover introduction. In this the teachers are asked to answer the subsequent
questions in regards to one particular class at level 2 of the ‘International Standard
Classification of Education’ (ISCED) that they typically teach at the school they are
19
employed. To simplify the process a class should be chosen that is taught at a specific
time given in this introduction. This formulation was implemented to optimise the
process of randomisation when selecting the target class even if that could not equal a
strictly randomised selection (OECD, 2010a).
With a total amount of 43 questions - of which again 23 questions (what equals
more than 50 percent) have sub-categories with up to 19 sub-questions - the TALIS
2008 questionnaire is relatively long and should take approximately 45 minutes to
complete (OECD, 2008). For the scope of this study, however, a large amount of
information that can be obtained by the TALIS 2008 teacher questionnaire would be
irrelevant. Considering that, the usage of the entire questionnaire for this research would
have been unreasonable and could have possibly limited the participation and return
rate. Instead, the most relevant questions in regard of the study’s scope were extracted
from the TALIS 2008 teacher questionnaire. The categories “Teacher Appraisal and
Feedback” and “Teaching Practices, Beliefs and Attitudes” could, in this process, be
neglected as they (in these terms) would not obtain any relevant information. The
questionnaire was therefore composited by selecting questions from the remaining three
categories of TALIS 2008. These categories were then maintained to improve the
questionnaire’s structure which separated it into the three following sections:
1. General background information
2. Professional development
3. Information about teaching in a particular class
The third section of these was in its German translation renamed into the - for the
German language adequate - term Unterichtsalltag, which describes recurring
classroom routines.
Whereas the TALIS questionnaire required wider background information of its
participants, the questionnaire of this study was supposed to be as discrete and as
anonymised as possible. It thus only contained three questions in this first section that
were of high relevance for the data analysis. In order to safeguard high rates of validity
and representivity, this research aims to collect data from as many German TE-systems
as possible, and requires participants that have completed their academic TE in different
German states. The state in which the novice teachers completed their TE must
therefore be indicated in this section. To further assure that the participants represent the
desired sample criterion of novice teachers that have not had more than two years of
paid teaching experience, this relevant personal information was required as well. In
addition to that, the questionnaire asked to indicate the gender in order to enable the
possibility of identifying potential gender differences in the analysis of.
The questionnaire’s second section focuses on the professional development of the
novice teachers. For this only one question was taken from the TALIS 2008
questionnaire. This question specifically asks the participants to indicate in which work-
related areas they consider to have need(s) for additional professional development on a
four-point Likert-scale. For being the 18th
question of the TALIS 2008 teacher
questionnaire it is assigned to the Variable BTG18. For this study it was named Q1 as it
represents the first contextual question of this questionnaire. In the course of this, the
areas of development needs equal the respective items and were – following the
guidelines of the TALIS technical report by the OECD – translated into German. In
20
order to obtain data that is comparable to the TALIS dataset, this questionnaire asks for
development needs in the same areas which are:
1. Content and performance standards in the main subject fields
2. Student assessment practices
3. Knowledge and understanding of the main subject fields
4. Knowledge and understanding of instructional practices (knowledge mediation)
in the main subject fields
5. ICT skills for teaching
6. Teaching students with special learning needs
7. Student discipline and behaviour problems
8. School management and administration
9. Teaching in a multicultural and multilingual setting
10. Student counselling
This question (number 18) of TALIS 2008 has in its basics been reused for the
TALIS 2013 questionnaire, in which it features all items of the previous teacher
questionnaire. Yet, some four items were added in the second cycle of TALIS so that
the 2013 teacher questionnaire also asks for development needs in the areas of
approaches to individualised learning,
teaching cross-curricular skills (e.g. problem solving, learning-to-learn),
approaches to developing cross-occupational competencies for future work or
future studies, and
new technologies in the workplace (OECD, 2013b).
In order to enable a possible comparison of the German novice teachers with the
TALIS 2013 data-set in a subsequent study these four items were included in this
study’s questionnaire, as well. Information that was obtained from these items would,
however, be irrelevant for the results of this particular study. Those items will therefore
not be incorporated in the analysis of the dataset.
As its third section asks about information regarding teaching in a particular class,
this questionnaire necessarily had to feature a translated version of the TALIS
introduction to the subsequent questions. Usage of the term ‘ISCED level 2’ would have
presumably caused confusion among the participants since it is not commonly used in
the German education system. Beyond that, terms to classify this level of education vary
between the different education systems of the federalised German states. To clarify
what kind of class should be chosen the participants were given two (equal) criteria of
‘school-year level 7-9’ and ‘Sekundarstufe 1.2’.3
This last section of the questionnaire consists of three questions. Question Q2
equals the TALIS 2008 question number 38 and its variable BTG38. This question asks
for the average amount of students in the target class. To obtain data that has certain
validity standards, the OECD researchers set an international valid range from 10 to 50
students per class for this item. All indications outside of this would have to be
discarded in the analysis. The main purpose of this question is, to be exact, not
primarily analysis-orientated, but to improve the participants’ imagination of their target
3 The German Primarstufe encompasses level 1-4 in the majority of states whereas some states count
level 1-6. The German Sekundarstufe 2 starts in most states at level 10.
21
class in order to answer the questions that will follow more accurately (asking for
characteristics of the target class is also used as such strategy in the OECD survey
[OECD, 2010a]). Yet, this variable can finally be used to identify any impact the
average class size might have on indicators of preparedness that are relevant for the
study.
Differing from the second question of this section, Q3, is of high significance for
the study. It aims directly to the teachers’ classroom performances. Separated into three
types of classroom activities the participant is asked to indicate the percentages of how
much time is typically spent on each of these items when teaching the target class.
Equal to the items of question 41 of the TALIS 2008 questionnaire (in which those
represent the Variables BTG41A to BTG41C) these activities are:
A. Administrative tasks (with an international valid range from 0 to 20)
B. Keeping order in the classroom (with an international valid range from 0 to 30)
C. Actual teaching and learning (with an international valid range from 50 to 100)
(OECD, 2008)
Identical to Q2, all indications that lie outside of those valid ranges would have to
be excluded from the analysis of the data. In addition to that, all entries would have to
be discarded that in sum do not reach or exceed 100 percent. To avoid the latter
participants are explicitly advised to make sure that their percentages sum up to 100.
The last question of this study’s questionnaire, Q4, corresponds to question number
43 of the TALIS 2008 questionnaire. It consists of four statements that the participants
have to agree to on a four-point Likert scale. These constitute the variables BTG43A to
BTG43D. The statements are:
A. When the lesson begins, I have to wait quite a long time for students to quieten
down.
B. Students in this class take care to create a pleasant learning atmosphere.
C. I lose quite a lot of time because of students interrupting the lesson.
D. There is much noise in this classroom (OECD, 2008).
The corresponding items of the variables BTG43A, BTG43C and BTG43D of this
question are phrased negatively. In order to compute these to an indicator about the
classroom atmosphere these would have to be inverted. High score points on such
scaled category would refer to a positive teaching and learning climate, and vice versa
(OECD, 2010a).
In order to inform the participants about the scope of the study a cover page for the
questionnaire was created. This cover page contains information about the questionnaire
itself and how much time its completion should approximately take. In addition to that,
the participants were assured that the information they provided in that questionnaire
will be kept confidential and that there was no intention of linking any information to
them as individuals or the schools they work at. They were also informed that filling out
the questions and items was voluntarily and that they could abandon the completion
process whenever they wanted to.
22
4.3. Ethical consideration
As Bryman highlights, it is highly important to follow certain kinds of ethics when
conducting research. For instance, research must not harm participants and is supposed
to secure their privacy at all times (Bryman, 2012). Especially since names or other
aspects related to the personality of the participants are irrelevant for this research, it
was stressed to conduct this research as anonymously as possible. The only individual
information that had to be indicated were the months of teaching experience, the gender
of the participants, and the states or higher education institutes where the TE was
completed. These were crucially related to the research questions. Aspects of
confidentiality and the scope of the research were outlined on the cover page of the
questionnaire so that the participants were clear about the study’s purposes and their
rights when participating in the research.
4.4. Conducting the research
4.4.1. The Participants
As described in the introduction, the empirical part of this study requires young teachers
- or so called novice teachers - as participants. When setting the scope of the data
collection on such teachers in Germany, it must be assured that the final sample would
still be comparable to the results of the TALIS study. It must therefore strictly follow
the OECD criteria of young teachers. In the report, teachers with two years or less of
paid teaching experience were categorised as new, or novices, in their profession. The
report also tells that particularly when focusing on issues of preparedness it would have
been more interesting to exclusively focus on teachers in their first year after their initial
education. The sample size was then, however, regarded as insufficient to only focus on
that particular group of teachers, and was increased by raising the experience limit to
two years (OECD, 2012).
Regarding the potential German participants for the sample of this study, a
significant factor in the exceptionality of Germany’s teacher education system has to be
considered. Namely, that the German teacher education at higher education institutes,
described more clearly in the second section of this document, is followed by a phase of
supervised work after graduation. In that guidance is still provided by both, mentors
within the schools and by supervisors beyond that. The crucial aspect here is that those
teachers in the preparatory service of their education are already teaching in classrooms
and receive salaries. They hence fully meet the criterion of young teachers by the
OECD TALIS survey. In terms of comparability standards of this research these novice
teachers that have graduated from higher education programmes therefore have to form
the German sample and are in direct focus of this study.
23
To obtain information from such teachers it is to mention that they (after having
started to work in schools) are supposed to gather in small training groups - the so
called Studienseminare (study seminars) - to receive further education. This is part of a
specific preparatory service in their profession lasting for the first 18 to 24 months after
they begin to teach in classrooms. Meetings normally take place in two-week intervals,
depending on holidays and exam periods, but there are differences between the various
states of the country. In some states, these training groups meet more frequently, in
others less often - a time factor that had to be minded in the data collection as the
study’s questionnaire was supposed to be distributed to the novice teachers in those
seminars. Since these are led by official study seminar supervisors (most commonly
teachers as well) those had to approve the data collection and enable access into their
seminars. Such approach for the data collection entails a further advantage. In regards of
teaching careers, it had been decided by the OECD TALIS researchers to not include
teachers in the study that either teach adults or students with special learning needs
(OECD, 2010a). This meant for the German sample that teachers with teaching careers
in vocational and special needs education would have not met the sampling criteria that
had to be maintained for comparability reasons. Hence, study seminars for these
particular career types could have already been excluded in the data collection process.
The same applied to study seminars for primary education careers as the TALIS focus
was on teachers that teach at secondary level. The fact that there are different school
types at that particular level in Germany (that even differ between the various states)
could by this sampling approach be minded, as well, by addressing all study seminars
for teaching careers at secondary level.
4.4.2. The process of the data collection
After the construction of the questionnaire had been completed and it had been tested in
a pilot study of seven novice teachers, initial contact to the first group of study seminar
supervisors was sought to be established in January 2014. For the reason that a the
majority of German states mid-year report cards (Halbjahreszeugnisse) were handed out
to students in the month of January, this point in time was chosen as most promising to
have the best rate of approval to conduct the research. An earlier date to establish
contact was supposed to be less auspicious due to the registration of the students’ mid-
year marks in which teachers are usually occupied. The winter holiday would have led
to an inconvenient interruption in the process of establishing contact, as well. In order to
assure a sample of participants that had received teacher education in as many German
states as possible, it was planned to carry out the data collection in the larger city states
of federal Germany – Berlin and Hamburg –in terms of population which are
characterised by large rates of fluctuation. For the actual data collection the study
seminar, supervisors were given the option of having the questionnaires distributed by
the researcher in their seminars, or to distribute the questionnaires themselves after they
had been sent by mail. In the latter case they would have received further instructions
and material to safeguard the study’s confidentiality (e.g. additional envelope that had to
24
be sealed by the teachers). The month of February was at this point designated for the
actual conduct of the research.
However, two weeks after the initial attempts to establish contact the response rate
was extremely low. Even with a certification of the significance of the study most
requests for participation in the research remained unanswered and if they were replied
to, these replies were negative. Thus, in the early stage of that process the area in which
the research should have been carried out had to be extended. In the following all study
seminar supervisors or their superiors, respectively, of the northern states of Schleswig-
Holstein, Lower Saxony, and Mecklenburg-Vorpommern4 were addressed in the same
matter. This resulted in a slightly better rate of positive replies, meaning that the first
questionnaires could be sent out or distributed personally. Yet, it was presumed that the
desired sample size could have not been met so one week later the area in which study
seminar supervisors (where contact details were available or could be acquired) were
contacted for participation in the study was extended by eight additional German states
– Brandenburg, Hesse, North Rhine-Westphalia, Rhineland-Palatine, Saarland, Saxony,
Saxony-Anhalt, and Thuringia. In comparison to the previous requests, the study
seminar supervisors were asked to distribute the questionnaires of the study themselves
and the possibility of a distribution by the researcher in person was removed. Even if
the majority of contacted persons still did not answer or declined, the quantity of
requests eventually led to a rate of participation that could supposedly have guaranteed
a satisfying sample size. For consistency reasons, however, the remaining states of
Bavaria and Bremen5 were at a later point included into the area in which study seminar
supervisors or their superiors were contacted in these matters. Thus, the requests had
eventually covered all of the German Federal Republic.
As the data collection was ultimately finalised at the 31th of March seminar groups
of novice teachers from Hamburg, Hesse, Lower Saxony, North Rhine-Westphalia,
Saxony-Anhalt, and Schleswig-Holstein had participated in the research of this study.
4 The researcher was based in Hamburg in the north of Germany. To facilitate a distribution of the
questionnaires in person these states were at that point given priority. 5 The state of Baden-Württemberg was not included here as it has a system of teacher education that is to
such extent different from the other German states that participants that completed their TE in this state
will have to be excluded from the sample, either way.
25
Chapter 5
Technical information about the dataset
In order to adequately work with the obtained information from the research, it had to
be coded into a dataset in which it is transformed into numbers. This facilitates analysis
mechanisms of such quantitative data (Bryman, 2012). For that the IBM SPSS
(Statistical Package for the Social Sciences) software for statistical analysis was used.
An advantage of this specific software was that the sample of the OECD TALIS 2008
survey - that was intended to be used for a comparison of the datasets - could be
acquired in SAV-format which is used for this software. The sample of TALIS did not
have to be recoded into another format, but the German sample had to be coded into the
existing SPSS dataset.
Because of this, the variables of the TALIS 2008 SPSS dataset were essentially
kept the same. As it was aimed to have a sample of German novice teachers that is as
representative as possible the participants were in the questionnaire’s background
information section asked in which German state they had completed their higher
education for teaching. For the OECD TALIS survey such information had not been
considered, so a new variable (that only applied for the German teachers) had to be
created for that item. The other items of the introductory section of the questionnaire
were coded into variables of the existing dataset. The item regarding the participants’
gender was also the first question in the TALIS questionnaire and thus formed the
variable BTG01. The third item regarding teaching experience in months had to be
converted into years and then matched the 9th
question of the TALIS questionnaire or
variable BTG09, respectively. All information that exceeded the criterion of two-year
teaching experience was, though, coded into the dataset, but later excluded from the
sample.
For the questions of the other two sections of ‘professional development’ (Q1) and
‘teaching in a particular class’ (Q2 – Q4), the categorisation into the variables of TALIS
2008 was already described in section 4.2.2. of this document. The items of Q1 that had
been part of TALIS 2008 were represented by variables BTG18A to BTGA18K. Those
items that were added to the questionnaire to enable a later comparison of the sample
with the results of the TALIS 2013 survey were not coded into the SPSS dataset. The
items of Q2 to Q4 were identical with the items of the TALIS 2008 questionnaire and
could directly be coded into the corresponding variables of BTG38 for Q2, BTG41A to
BTG41C for Q3, and BTG43A to BTG43D for Q4. Those answers in this last section of
the questionnaire that did not meet the mentioned international valid range criteria
formulated by the OECD researchers regarding the variables of BTG38 and BTG41
were, nevertheless, coded into the dataset, but later sorted out by specific filter
mechanisms in the analysis. Instead of leaving those variables blank that had not been
answered, had been answered in incorrect form, or could not clearly be identified on the
paper sheets, were coded as ‘omitted’.
New variables were computed by recoding the inverted variables of Q4 or
BTG43A, BTG43C, and BTG43D; respectively. These transformed variables then
26
received the additional letter ‘I’ for inverted and thereby formed three additional
variables. This measure was applied on the whole dataset to finally compute the four
positively phrased variables (BTG43A_I, BTG43B, BTG43C_I, and BTG43D_I) into
an index that provides information about the classroom climate and teaching
atmosphere. This step was necessary for the analysis despite the fact that the indicator
(var.: CCLIMATE) had been used for the original TALIS analysis. The statistical
analysis technique of ‘Multiple Group Confirmatory Factor Analysis (MGCFA)’ that
had facilitated the computation of such indicator could, however, not be applied for the
sample of German teachers as the MGCFA is not a feature of the IBM SPSS software,
but would have required an additional software package (OECD, 2010a; OECD,
2010b). Regardless of the more precise information that such indicator could have
provided due to its complex calculations that take a large number of factors into account
(Koh & Zumbo, 2008), implementing MGCFA would have not been feasible for this
research.
In order to distinguish the German teachers from those teachers of the other
countries in the dataset, the variables for categorisation had to be adapted to the German
sample as well. These were the variables of the countries’ ID (IDCNTRY) and the
country ID for reporting (IDCNTRYR). IDCNTRY is a numeric variable that assigns
the ISO 3166-1 codes to the cases. The applied ISO 3166-1 numeric code for Germany
(276) and the respective ISO 3166-1 alpha-3 code (DEU) were used for this variable.
IDCNTRYR assigns the numbers from one to twenty-four to the countries of the dataset
in alphabetical order (OECD, 2010b). This order was changed by assigning the number
twenty-five to Germany. As it was planned to present the results in statistically
ascending or descending order, such order would have been of little relevance for this
study.
As a last step of preparation, those cases that were not needed for the analysis; or
more precisely, those teachers with more than two years of teaching experience were
excluded from the sample to have a more organised dataset that encompasses only cases
of new teachers.
27
Chapter 6
Analysis and Findings of the German Sample
After collecting data throughout the months of February and March 2014, the data
collection process was finalised by the last day of March and none of the questionnaires
that were received after that deadline went into the final sample of German novice
teachers. The total amount of filled out questionnaires that had been received until that
point was 267. A total of 38 questionnaires were returned blank or not returned at all. 18
questionnaires were returned after deadline. This results in a rate of return of 88.2 %6
that thereby fully satisfies the OECD TALIS overall response rate requirement of 56 %
(OECD, 2010a) and represents a highly acceptable response rate (Bryman, 2012).
Out of those 267 questionnaires that were returned in time, 14 questionnaires did
not meet the sample’s requirements and had to be excluded from the sample. In 10 out
of these cases the participants taught at specific schools for students with special
educational needs and were not eligible by the OECD TALIS sampling criteria. Two
cases had received teacher education in a country other than Germany and therefore did
not meet the sampling criteria of this study that has the German TE system in its focus.
One participant indicated to already teach for more than two years, and one neither
provided information about teaching experience nor the state in which graduated from
higher education and had therefore be taken out of the sample, as well. Exclusion of
these cases resulted in a final sample size of NDEU = 253.
This sample then consisted of novice teachers that had completed their initial
teacher education in 13 different states of federal Germany. The states of Rhineland-
Palatine Saarland, and Baden-Württemberg could not be represented in the sample. The
latter, however, would have been excluded from the sample either way, as its system of
teacher education differs significantly from the other states’. For that reason, this state
had already been excluded from the data collection process (compare 4.4.2.). Regarding
the other two states that were not represented in the sample, attempts of including such
cases had been made, but remained unsuccessful, as mentioned previously. In terms of
gender, 174 cases represent female and 79 cases male participants. This shows a ratio of
male novice teachers to female novice teachers of almost one quarter to three quarters.
This, after all, adequately represents the situation in Germany where significantly more
women are eligible for higher education than men and teaching is - at comparable rates -
predominantly a career chosen by females (BMFSFJ, 2010; Nieskens, 2009).
The findings that will be presented in the following are in its structure guided
according to the questions of the questionnaire and then followed by the presentation of
cross-item analyses.
6 Without those questionnaire that were valid but returned after the deadline the return rate would have
been 87.5 %.
28
6.1. Development needs of German novice teachers
This section is going to feature the analysis of that information that was obtained in
terms of the German teachers’ development needs. The various areas of skills that are –
according to the OECD TALIS selection - relevant for teaching and formed the items of
the questionnaire were used as the basis for this analysis. A list of these skill areas was
presented in the previous sections (compare 4.2.2.). The ten items were attached to a
four-point Likert-scale on which the level of professional development need for each
item should be indicated. On the Likert-scale 1 represents ‘no need at all’ and 2 a ‘low
level of need’, respectively. 3 represents a ‘moderate level of need’ and 4 a ‘high level
of need’, respectively. Thus, at an item range from 1 to 4 values of 2 or lower show that
participants consider to have acquired the respective skills during their education
without any or little need of further development in that area. Values of 3 or higher
show the opposite. Those participants consider their acquired skills in that area as
inadequate and see the need for additional professional development. In terms of
displayed averages (means), values that lie above the 2.5-centre of such scale indicate
the latter.
Before looking into the areas in which the German teachers stated to have
development needs, this analysis begins with a closer look into the novice teachers’
general need for professional development. Such indicator was computed by summing
up the means of all variables in the sample. A simple sum of values (with a given range
from 10 to 40) may have been more declarative and plainly presentable in these
circumstances, however, an indicator that solely sums up a set of variables can only be
accurate if there are no missing values in the respective variables. Given the size of the
sample this had been unlikely and was, indeed, not the case. For that reason, the
variables’ means form the basis for this indicator that has a range from 1 to 4 and its
centre at X = 2.5.
For the German teachers the analysis showed an average development need of
2.807 with a wide dispersion of a minimum of 1.4 and a maximum of 3.8 (sd = .43). As
this average was above that indicators’ centre (at the 2.5-line) it revealed a considerable
overall need for professional development for the German teachers. The individual
cases displayed this even more distinctively. Only 17.8 percent of cases had a score in
this indicator that was smaller than 2.5, referring to a low overall need of professional
development. In turn, 76.1 percent of cases had scores higher than 2.5 and thus showed
a certain grade of general development need in their profession (the remaining 5.9
percent equal scores of exactly 2.5). The results of this indicator can be seen in Figure
6-1 in which a reference line marks the X-axis at 2.5 - the centre of this scale. Scores
that show more than one decimal place in this figure resulted from means that could not
be calculated from all ten variables because of missing values.
7 For an improved reading most figures with multiple decimal places are rounded to two decimal places.
29
Figure 6-1. Average professional development needs (German sample)
In the following, those skill areas that the teachers had to indicate their professional
development needs in will be presented more in-depth and with a closer look into these
particular areas. For structural reason this presentation will be split into three groups of
intensity in terms of the teachers’ needs. The first one for those skills that received the
highest scores of development needs, the second features skills that are marked by
mean-scores above the 2.5 threshold, and finally skills that the German teachers seem to
have acquired in their TE programmes and feel confident in.
6.1.1. High needs of professional development
It could already be shown that the group of German novice teachers that participated in
this study are characterised by a notable need for professional development in their
teaching competencies. To draw conclusions from this study it is yet more interesting in
which areas of teaching they feel least skilled after graduating from higher education TE
programmes.
30
On top of this list, and thus the skill that the new teachers of this sample showed
the largest development needs in was how to manage ‘student discipline and behaviour
problems’. With a mean of 3.21 (sd = .795) and no missing values this item was clearly
of high relevance for the participants of this study. A twofold mode for values of 3 and
4 additionally indicates that the majority of new teachers had either a moderate (41.1%)
or a high level of need (41.1%) when it comes to issues of classroom management and
students disturbance in class. This represents almost five sixths of cases in the sample
that feel incapable of adequately coping with such occurrences. Only 2.8 percent of
participants stated to have no need at all in this item and a mere 15 percent had a low
level of need, respectively, as can be seen in Figure 6-2.
Figure 6-2. Professional development needs: Student discipline and behaviour problems
(German sample)
Slightly less high but also substantial needs for professional development showed
the variable for ‘teaching students with special learning needs’ with a mean of 3.08. A
mode of 4 for this item that refers to a high level of need shows that this skill was
considered to be little developed for the majority (47.8%) of teachers. A considerably
high standard deviation of 1.044 (the highest in this item group), however, revealed the
existence of cases in the sample that felt adequately trained to teach such students. More
than one quarter of cases had either no need (10.3%) or a low level of need (19%)8 of
professional development in such terms. Yet, as shown in Figure 6-3 the largest part of
the sample with more than 70 percent cases required additional support in order
adequately teach students with special learning needs in their classrooms.
8 When percentages do not match up to 100% this is due to omitted values.
31
Figure 6-3. Professional development needs: Teaching students with special learning needs
(German sample)
A high rate of professional development needs could also be identified for the item
of ‘student assessment practices’ that was marked by a mean of 3.06 (sd = .784). Only
four teachers (1.6%) stated to have no problems with student assessment practices and a
fewer than one quarter of teachers (22.9%) had little need to further develop their skills
in this area. 191 out of 353 teachers of the German sample saw a moderate (43.1%) or
high (32.4%) level of need to further develop their skills to properly assess students of
their classes. A total of 75.5 percent of cases consequently seemed to have missed
acquiring these skills in their education (Figure 6-4).
32
Figure 6-4. Professional development needs: Student assessment practices (German sample)
6.1.2. Intermediate needs of professional development
The following four variables refer to a medium amount of professional development
need in its relating areas of teaching. The first skill of this group, ‘Knowledge and
understanding of instructional practices (knowledge mediation) in my main subject
field(s)’ must be generally considered as one of the most relevant for this profession as
it largely summarises one’s pedagogic competencies in teaching. However, a mean of
2.93 and the smallest standard deviation of all variables (sd = .699) revealed an
undeniable need for improvement among the German teachers in this field. 60.1 percent
of them stated to have a ‘moderate level of need’, and 17.8 percent even a ‘high level of
need’ to improve such competencies. Only 29.3 percent of the sample said to have
either a ‘low level of need’ or ‘no need at all’ when it comes to knowledge mediation, as
can be seen in Figure 6-5.
33
Figure 6-5. Professional development needs: Knowledge and understanding of instructional
practices in main subject fields (German sample)
Comparatively high means of professional development needs of 2.85
characterised also the items of ‘teaching in a multicultural or multilingual setting’
(sd = .872) and ‘ICT skills for teaching’ (sd = .878). As Figures 6-6 and 6-7 show, more
than two thirds of the teachers of this sample considered their ICT- and ‘multicultural’
skills as too low for teaching and had a moderate to high level of development needs to
perform adequate in these areas. Almost a quarter of participants expressed their needs
to improve such skills as high and - on both items - not even 8 percent of them could
imagine their capabilities in these areas to be that developed that no further
improvement was needed.
34
Figure 6-6. Professional development needs: Teaching in a multicultural and multilingual
setting (German sample)
Figure 6-7. Professional development needs: ICT skills for teaching (German sample)
35
The fourth variable that was marked by a mean of professional development needs
higher than 2.5 in this study is corresponding to the item of ‘school management and
administration’ (mean = 2.82, sd = .878). A total of 164 teachers (64.8%) indicated a
general need to improve skills in this area. 60 of these (23.7%) even have a ‘high level
of need’, whereas only a little more than one third of the sample show that they have
sufficiently acquired these skills (Figure 6-8).
Figure 6-8. Professional development needs: School management and administration (German
sample)
6.1.3. Low needs of professional development
There were also three items in this group of skills in which the German teachers
appeared relatively confident. The means of neither of these variables exceeded the
2.5-score line. These were the items of ‘knowledge and understanding of my main
subject fields’ with a mean of 2.45 (sd = .796), ‘student counselling’ also with a mean
of 2.45 (sd = .97), and ‘content and performance standards in my main subject fields’
(mean = 2.32, sd = .858), respectively.
For the latter two the majority of cases referred to a level of need which was low or
not existent. They furthermore were marked by the lowest medians of the sample
(median = 2). Only for the first item more teachers considered their level of need to be
either moderate or high (51.4%), than other way round (47.8%). However, the analysis
36
showed that twice as many teachers did not have any need at all for professional
development (12.6%) in this, as had a high level of need (6.3%).
A combined figure (Figure 6-9) of the means of all items for teaching skills can be
found below. The reference line at X = 2.5 separates those skills in which the German
teachers appeared to have considerable development needs from those in which they felt
largely confident.
Figure 6-9. Professional development needs: Means of all skill areas (German sample)
6.1.4. Gender disparities
Finally, it could be identified that female participants indicated to have larger needs for
professional development than their male counterparts. Most noticeable were the
differences between men and women in terms of development needs regarding
‘ICT skills for teaching’ and ‘teaching students with special learning needs’ that had
varieties of 0.45 and 0.44 in their mean values. Gaps were also detected in the skill
areas of ‘knowledge and understanding of main subject fields’ and ‘student assessment
practices’ in which female participants indicated higher score points than the male
participants (differences of 0.22 and 0.21). Despite the fact that these differences were
considerably high regarding the item range, the gaps did not exceed the items’ standard
37
deviation boundaries for neither the females’, the males’ nor the total item scores due to
large variances in the variables’ values. At the same time, the analysis could reveal
items in which the female participants appear to be more confident. The differences in
the areas of ‘content and performance standards in their main subject fields’, ‘school
management and administration’, and ‘knowledge and understanding of instructional
practices (knowledge mediation) in the main subject fields’ were with score point
differences of 0.02 to 0.08, insignificantly minor (Figure 6-10). Thus, the overall
professional development need of female teachers is at a mean of 2.85 higher than of
male teachers at a mean of 2.69 in terms of the listed skill areas for teaching.
Figure 6-10. Professional development needs: Gender distribution (German sample)
6.2. Teaching in the Target class
In the last section of the questionnaire the participants were supposed to provide
information about a specific class that they teach at the ISCED-2 level. 251 out of 253
participants followed these instructions and in two cases the back of the questionnaire
was left blank. For these it could not be identified whether the participants did not teach
38
at ISCED-2 level, did not want to provide any information about a target class or did
simply forgot to fill out the back of the questionnaire. The findings from the valid items
of this section will be presented in the following.
The size of the target class in focus of this section was the item the teachers should
begin with. With a minimum class size of 13 and a maximum of 33 all answers were
within the OECD valid range for this item. The average target class of these teachers
was of a size of 24 students (mean = 23.96), but most common were class sizes of 26 or
27 students (modea = 26, modeb = 27). In more than 80% of cases the target class size
was between 20 and 30 students.
Following that item, the teachers had to indicate in percentages how much time of a
lesson they spend on three different kinds of classroom activities. In total only 226 cases
met the criteria for these items to be valid. 6 cases had to be excluded because they were
either omitted or the percentages did not sum up to 100 percent. 3 cases did not meet
the OECD valid range of for the first item [0-20], and 18 were above the limit for the
second item [0-30].
Thus only considering the valid cases for the analysis, it could be revealed that the
German teachers clearly spend most of their time during lessons with actual teaching
and learning. On average they use 81.34 percent of their designated time in classrooms
for that activity. Despite a standard deviation of 10.18 this share appeared to be of
notable size. Furthermore, only a little more than one quarter of the sample (26.5%)
indicated to use less than 80 percent of their lesson time for its actual purposes.
Whereas 7.17 percent of time (sd = 4.41) are generally spent on administrative tasks, the
remaining share of 11.4 percent of time (sd = 7.92) is used to keep order in the
classroom. Considering the particular valid ranges for those classroom activities apart
from teaching and learning of up to 20 and 30 percent, these rates appeared to be
remarkably low (Figure 6-11).
Figure 6-11. Target class: Time spent on classroom activities (German sample)
The scope of the survey’s final question that consisted of four inter-related items
was to obtain information about the teaching and learning atmosphere in the particular
target class. As previously described, these four items were partially inverted and then
combined to an overall indicator about the classroom disciplinary climate. Out of the
253 participants, three did not fill out any of the items of this question and were
therefore not part of the following analysis. One other case had to be excluded for the
reason that one item was missing. The indicator must, however, be constructed from all
four items to provide valid information about the classroom disciplinary climate. With a
39
minimum at x = -1.5 and a maximum at x = 1.5 this indicator is constructed around a
neutral centre at x = 0. Scores higher than that refer to a positive teaching and learning
atmosphere, and reversely, negative scores to the opposite.
With a positive overall mean of 0.37, a standard deviation of .68 and a mode at
x = 0.75 this indicator could reveal a generally good disciplinary climate in the German
classrooms. Less than one quarter of the sample (24.1%) described the atmosphere in
their classrooms with negative scores that refer to a poor disciplinary climate. As Figure
6-12 shows more than two thirds (67.5%) of the German teachers appeared to be largely
satisfied with their students’ behaviour during lessons and indicated positive scores.
Figure 6-12. Target class: Classroom disciplinary climate (German sample)
6.3. Bivariate Analysis of Variables
The following section will focus on relationships between certain variables of the
dataset that are supposed be detected by bivariate analysis mechanisms. Bivariate
analysis is specifically oriented to uncover whether or not two variables are related. The
findings of so-called correlations between some of the previously presented variables,
however, do not highlight causalities, but only relationships in the variables’ variations
(Bryman, 2012). As the majority of variables in this data set are ordinal and only some
variables were measured as scales (and thus interval/ratio variables) Spearman’s
rho (ρ)9 was chosen as a bivariate analysis method. This correlation coefficient differs
between levels of significance at the 0.05 and the 0.01 level of which the latter refers to
a much stronger relationship than the first.
9 If correlations in this dataset were analysed by other bivariate analysis methods such as Pearson’s r, for
instance, the findings would for that particular reason be far less exact.
40
The first bivariate analyses were performed to identify whether there are inter-
relations between the areas of professional development needs in this sample. As the
scores of most variables were considerably high, however, a large number of positive
correlations between certain variables could be identified. For that reason only the most
conspicuous items will be presented at this point.
For instance, the analyses showed that participants that had a high need of
improving their professional skills in cases of ‘knowledge and understanding of
instructional practices’ also had significantly high professional development needs
regarding ‘student assessment practices’, ‘student discipline and behaviour problems’,
‘content and performance standards’, and ‘knowledge and understanding of the main
subject fields’ (all at the 0.01 level and in that order). Those teachers that indicated
problems in knowledge mediation and seem to lack such pedagogical skills for teaching,
thus also had significant problems in those areas listed above.
For the respective item of ‘student discipline and behaviour problems’ - that
already correlated with the previous item - the bivariate analysis showed that
participants with professional development needs in that area also had significantly high
scores for ‘student assessment practices’ and ‘teaching in a multicultural and
multilingual setting’ (all at the 0.01 level and in that order) and ‘ICT skills for teaching’
(at the 0.05 level).
The strongest correlations between all of these items was found regarding ‘teaching
students with special learning needs’ and ‘teaching in a multicultural and multilingual
setting’; and regarding ‘content performance standards’ and ‘student assessment
practices’. Noteworthy is also the fact that the bivariate analysis techniques could not
detect any variables in this set that were negatively significant.
The subsequent bivariate analyses were then performed for the variables of the
questionnaire’s section about teaching in a target class. Due to the fact that the values of
those items (that were designed to show how much time is spend on different kinds of
classroom activities during a lesson) were percentages that in total sum up to 100
percent relationships between them are inevitable. Thus, correlations of high
significance in such bivariate analysis were highly likely. Considering that it is obvious
that the percentage of time spent on ‘actual teaching and learning’ is less if the shares
for the other activities are higher. Therefore, this variable correlates negatively with the
classroom activities of ‘administrative tasks’ (ρ = -.670) and ‘keeping order in the
classroom’ (ρ = -.881). It could though also be detected that teachers that spend more
time of their lesson on keeping order in the classroom also spend more time on
administrative tasks. These two variables correlate positively with a coefficient of
ρ = .312. Additionally, it could be revealed that those participants that indicated high
needs for professional development in terms of ‘student discipline and behaviour
problems’ also spent more time on ‘keeping order in the classroom’ (ρ = .215) and thus
had less time for ‘actual teaching and learning’ (ρ = -.183).10
No relationship between
the size of the target class and any of these three variables could, though, be identified.
In terms of classroom disciplinary climate the bivariate analyses of this indicator
and other variables showed further correlations. For instance, teachers that reported a
positive disciplinary climate in their classrooms spent significantly less time on
10
All correlations were significant at the 0.01 level of Spearman’s Rho.
41
‘keeping order in the classroom’ and had thus more time for ‘actual teaching and
learning’ than their counterparts. Both correlations were significant at the 0.01 level of
Spearman’s Rho and had correlation coefficients of ρ = -.539 for the first and ρ = .407
for the latter. Those teachers that teach in classrooms with a positive disciplinary
climate furthermore had less professional development needs in terms of ‘student
discipline and behaviour problems’ (ρ = -.341, significant at the 0.01 level) and
‘teaching in a multicultural and multilingual setting’ (ρ = -.162, significant at the
0.05 level).
6.4. Split-Sample Analysis
Complementarily to the previous bivariate analyses, split-sample analyses were
performed for this group of German teachers, as well. This type of information
processing facilitates revealing further differences among a selection of variables on the
basis of certain criteria.11
Such criteria were set for the corresponding items of the last
section of this research’s questionnaire.
At first the sample was split by the criterion of ‘time spend on actual teaching and
learning’. As only those values that were between 50 and 100 were considered to be
internationally valid and could be used for the previous analyses, the centre of this range
was chosen as a threshold to split the sample into two groups. These groups were those
teachers that averagely spend more than 75 percent of their time on actual teaching and
learning (group G1) and those that spend less than 75 percent (but at least 50 percent)
on that activity (group G2).12
By this a comparative analysis between these two groups,
but within the sample – a split-sample analysis - could be performed.
In regards of professional development needs notable differences between these
two groups of teachers were in fact - with minor exceptions – not evident. Along with
the overall need for professional development (G1: 2.78, G2: 2.81), the professional
development needs appeared to be slightly smaller for the group of teachers that spend
more than 75 percent of their lesson on actual teaching and learning in six out of ten
skill categories. The highest differences could be identified for skills of ‘student
discipline and behaviour problems’ (G1: 3.11, G2: 3.42) and ‘knowledge and
understanding of main subject fields’ (G1: 2.38, G2: 2.64). The skill areas of
‘knowledge and understanding of instructional practices (knowledge mediation)’
(G1: 2.96, G2: 2.98) and ‘teaching in a multicultural and multilingual setting’ (G1: 2.82,
G2: 2.84) showed almost identical results for both groups. In turn, there were also four
categories of teaching skills in which this group of teachers had slightly higher needs
for professional development than those teachers that spend less than 75 percent on this
teaching activity. Almost identical were the results for ‘ICT skills for teaching’
11
The process of splitting the sample was realised post-testing on the basis of certain variable values and
must not be mistaken for split-sample testing approaches which follow a different design than this
research. 12
Cases that indicated scores of exactly 75 percent were excluded from this analysis.
42
(G1: 2.87, G2: 2.86). The skill areas of ‘school management and administration’
(G1: 2.85, G2: 2.51), ‘student counselling’ (G1: 2.45, G2: 2.30), and ‘teaching students
with special learning needs’ (G1: 3.05, G2: 2.95) were though marked by smaller
professional development needs for the second group of teachers (Figure 6-13). With
standard deviations of at least .664 none of these differences were significant to one
another in such split-sample comparison. However, some areas of teaching skills appear
to be more relevant in order to adequately use the time of a lesson than others for the
teachers in this sample.
Figure 6-13. Split-sample: Professional development needs and time spend on teaching
(German sample)
The following split-sample analyses were performed in regards of classroom
disciplinary climate. Two groups of teachers were formed according to this indicator
being positive or negative. Namely, the sample was split into one group of teachers that
reported an index value higher than zero (group G3), and into a second group for which
this indicator had a value below that (group G4). As in the previous, cases that lied on
that specific threshold of zero were excluded from the analysis. These two groups were
then compared with one another.
The results from such comparison were more informative than the previous split-
sample analysis. In terms of professional development needs, already the combined
overall indicator from these variables revealed sound differences between the two
groups. With standard deviations of .43 for both values the group of teachers that
indicated a poor disciplinary climate in their classrooms (G4) reported notably higher
overall needs for professional development in their teaching skills (G3: 2.77, G4: 2.91).
Regarding skills in order to prevent or cope with student discipline and behaviour
problems, differences could be revealed between these two groups that were marginally
2
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4
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43
significant. Teachers that described their classrooms with a poor disciplinary climate
also reported with a standard deviation of .59 notably higher professional development
needs in that area than their counterparts (G3: 3.08, G4: 3.55). Along with that, seven of
the remaining nine skill areas were higher for this group of teachers, yet the differences
were not as evident as the previous. The area of ‘teaching in a multicultural and
multilingual setting’ showed the largest differences among these teachers (G3: 2.78, G4:
3.03), whereas the results for ‘content and performance standards’ were almost identical
(G3: 2.32, G4: 2.37). The same accounts for those skills in which those teachers that
reported a positive classroom disciplinary climate had higher professional development
needs than the group they were compared with. These differences regarding ‘knowledge
and understanding of main subject fields’ (G3: 2.46, G4: 2.38) and ‘ICT skills for
teaching’ (G3: 2.86, G4: 2.82) were negligibly minor in these terms (Figure 6-14).
Figure 6-14. Split-sample: Professional development needs and classroom disciplinary climate
(German sample)
Finally, a split-sample analysis for the groups G3 and G4 was performed in regards
of time spend on the three classroom activities that information was obtained about. No
significant differences between these groups could in this be identified for the time
spend on administrative tasks in a lesson (G3: 7.15%, G4: 8.02%; sdG3 = 4.51, sdG4 =
4.40). Differences of significant relevance could, however, be revealed for the other two
classroom activities. The split-sample comparison by means of classroom disciplinary
climates showed that teachers who teach classes which are marked by a negative
teaching and learning atmosphere (G4) spend almost twice as much time on keeping
order during their lessons as the group (G3) of teachers that reported positive classroom
disciplinary climates (G3: 9.10%, G4: 18.00%). With standard deviations of 6.31 for G3
and 6.52 for G4 this difference is statistically significant from both sides. The same
accounts for the time spend on actual teaching and learning. Those teachers whose
classrooms are characterised by a positive classroom disciplinary climate (G3) could
2
2,5
3
3,5
4
Ov
eral
l dev
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G3
G4
44
use significantly more time of their lesson on this activity than the teachers that formed
group 4 (G3: 83.62, G4: 73.98; sdG3 = 8.64, sdG4 = 11.56). It could thus clearly be
identified that for these teachers a link between the classroom disciplinary climate and
the latter two classroom activities is evident (Figure 6-15).
Figure 6-15. Split-sample: Classroom disciplinary climate and classroom activities (German
sample)
6.5. Summary and interpretation of the findings from the German
sample
An early summary of these findings will be presented in this section before findings
from the comparison of the international sample will be focused on. If applicable, initial
interpretations will already be part of this presentation, but discussed more thoroughly
in the final chapter of this study.
At the very beginning of this section the analysis could identify that the sample of
German novice teachers could be characterised by a considerably high overall amount
of professional development needs. In only three out of ten categories that were defined
as relevant for teaching by the OECD researchers for the TALIS 2008 questionnaire did
the German teachers receive scores relating to little need or no need at all. That means
in turn that they considered their skills in the remaining seven categories to be
inadequate for teaching. These findings are particularly crucial regarding the fact that all
of these teachers have just recently completed a four- to five-year study programme of
teacher education to be adequately equipped for this profession. These findings,
however, indicate that this is not the case.
7,15 9,1
83,62
8,02
18
73,98
0
10
20
30
40
50
60
70
80
90
100
Administrative
tasks
Keeping order in
the classroom
Actual teaching
and learning
Time spend
in %
G3
G4
45
Yet, more relevant appears to be a closer look into those items (or skills in other
words) that the new teachers claimed to have the largest needs for professional
development in. A selection of those items with significantly high score points are, for
instance, student discipline and behaviour problems, teaching students with special
learning needs, teaching in a multicultural und multilingual setting, student assessment
practices, and knowledge and understanding of instructional practices. A more in-depth
focus on these particular skills that the German teachers appear to lack in their
professional performance draws inferences about the system of teacher education that
they have been education in. Focusing on the first three of those items listed above it
gets obvious that they entirely relate to the students in the teachers’ classrooms. More
precisely, the items refer to students that most commonly require specific teaching
approaches to be reached and adequately taught by the teacher. One can assume that
especially students that challenge teachers by ‘discipline and behaviour problems’ are
those that teachers perceive as unpleasant. They do not fit a type of students that learn
and listen quietly, that do not disturb the lesson and perform well in class - or in other
words, that are easy to teach. Simultaneously, students with special learning needs,
another cultural background or another first language certainly need to be addressed and
taught by the teacher in a way that satisfies their needs. In most cases this kind of
teaching differs from teaching in a classroom that solely consists of the previously
mentioned student type (the ‘easy to teach’-students).
The reality in classrooms is, though, that they are heterogenic with many different
kinds of students all with their respective personalities and character traits. Regarding
the German Federal Republic in particular, learning groups most likely include students
with special learning needs - as German classrooms shall be inclusive and, thus, open
for all kinds of students (Klemm, 2013; KMK, 2011). Learning groups are also likely to
entail students with cultural backgrounds or first languages different from German – as
the federal republic of Germany is officially considered to be a ‘country of immigration’
(Einwanderungsland) which inevitably leads to a multicultural society (Astheimer,
2013). For that reason a ‘one fits all’ teaching approach clearly appears to be
mismatching such teaching environments. Aspiring teachers have to be given
opportunities during their education to acquire skills in order to adequately reach all
students in their future classrooms. That the analysis nevertheless revealed that the
teachers of the sample indicated significant problems teaching all these students in their
classrooms must lead to the conclusion that they have not acquired such relevant skills.
Additionally, the latter two items of the ones listed above show that they lack skills
of student assessment practices and knowledge and understanding of instructional
practices. These are clearly pedagogical skills necessary for teaching. In particular the
latter relates to knowledge mediation competencies that the teachers apparently wish to
improve. Knowledge mediation, however, can be regarded as the method of enabling
one’s own knowledge to others, or in other words, the pedagogical discipline of
teaching. The need of professional development regarding student assessment practices
shows then that the teachers seem to neither have acquired skills to examine whether
their students have actually understood the learning contents they were taught, or
whether they have obtained knowledge about the specific subjects of the lessons.
The analysis could, though, show that the new German teachers seem to be
appropriately educated at the theoretical level as they stated to be equipped with
adequate knowledge in their subject fields and about content performance standards. In
46
relation to the previously summarised findings one can say that they clearly know what
to teach, but they do not know how distribute their knowledge among their students.
They are furthermore especially struggling in heterogenic learning groups. In addition to
that, the analysis could show crucial gender disparities in terms of professional
development needs between male and female teachers. Especially considering that the
sample consists of almost three times as many women as men - a ratio which displays
the common gender distribution in that profession - should raise concerns about the
German TE system when more female teachers consider their professional skills as
inadequate as their male counterparts.
The further analyses could then illustrate a picture of the classrooms those novice
teachers teach in. On average a generally positive classroom disciplinary climate could
be identified and the German teachers only lose little amounts of time on classroom
activities different from teaching. Yet, negative relationships could be revealed between
these variables and professional development needs in terms of student discipline and
behaviour problems. Generally said, the scores for the classroom disciplinary climate
and the time spend on actual teaching and learning were significantly lower, if
participants indicated a high need of professional development in that area. In analyses
that were performed after the sample had been split by applying certain criteria, it was
further revealed that some teaching skills are more closely linked to the teachers’
performances and the teaching and learning atmosphere in classrooms than others. The
relevance of skills that relate to student discipline and behaviour problems must
- besides others - be stressed in particular in this background. Additionally, significant
links between classroom activities and the disciplinary climate in classrooms were
brought to light for the teachers of this sample.
47
Chapter 7
International Comparison
7.1. The International Sample
As the analysis of the previous section could provide a thorough picture of the novice
teachers that received their teacher education in Germany, the following section
broadens that image by adding an international comparison. For such comparison the
sample of German teachers was incorporated into the TALIS 2008 dataset. This dataset
was then scaled-down by excluding those teachers that were already experienced in
teaching – meaning that all cases that indicated to have worked and taught as teachers
for more than two years were first selected and then taken from the sample. This sample
then consisted purely of novice teachers from those countries that participated in TALIS
2008 and the German Federal Republic. With an exception for Iceland13
all novice
teachers of the TALIS group were part of this sample in order to enable a wide-scale
comparison. It has to be mentioned that only teachers from the Flemish part of Belgium
were represented for the reason that the country’s French-speaking region, Wallonia,
did not participate in the original TALIS survey in the first place. All in all, the sample
comprised a total number of 5 228 cases from 24 different countries. A list of the
countries incorporated in the sample and the respective frequencies of how many
teachers they encompassed can be seen in Figure 7-1.
In the year 2008 when the TALIS survey was conducted the majority of
participating countries were OECD members, however, seven countries additionally
joined the survey – Brazil, Bulgaria, Estonia, Lithuania, Malaysia, Malta, and Slovenia.
For the reason that two of these countries – Estonia and Slovenia – joined the OECD in
2010, only the remaining five countries are today not members of that organisation.
Thus, 19 of the 24 countries included in this sample were OECD member states. With
only 49 cases the smallest group of novice teachers were those from the Netherlands.
Brazil with 429 cases represented was the sample’s largest country. In terms of country
sizes, the German teachers that were in focus of the previous sections formed the sixth-
largest group with 253 cases (4.8%). Among the OECD member states they ranked
fourth as only teachers from Turkey (372 cases), the Flemish community of Belgium
(317 cases), and Italy (300 cases) were represented more often.
13
There is no data about Icelandic teachers from TALIS 2008 available as Icelandic officials deny access
to that sample for secondary analyses.
48
Figure 7-1. The international sample
49
7.2. Findings from the international comparison
7.2.1. Professional development needs (international comparison)
The following section will analyse how the novice teachers from other countries
compare to the German teachers regarding the extent of their professional development
needs in the various areas of teaching. As an in-depth look into all of these is considered
to be too excessive for the scope of this study only the teachers’ overall professional
development needs and the most relevant variables will be taken into account for an
international comparison.
In terms of general professional development needs some 38 cases had to be
excluded from the sample as their items were entirely left blank. Hence, an overall
indicator could be computed for 5190 cases (in which all countries were represented).
The scores of this indicator that had a scale from 1 to 4 score points ended up spreading
a comparably wide range from 2.31 score points at the lowest and 3.38 at the highest.
As can be seen in Figure 7-2 the lowest overall need for professional development was
indicated by the Hungarian teachers (sd = .53). Besides that, the indicator showed for
four more countries that their teachers could be characterised by relatively low
professional development needs; namely below the 2.5 score point line that was used as
threshold to distinguish low and high scores. These countries were Malta (2.41), Mexico
(2.43), Denmark (2.44), and Turkey (2.46); whereas the Irish teachers were marked by a
score exactly at that threshold with a mean of professional development needs of 2.50.
The teachers from the remaining 19 countries all had average scores that referred to a
generally high need of professional development. On top of this list were the Malaysian
teachers with the highest score mean of 3.38 (sd = .48). Also above an imaginary line at
X = 3 were those teachers from Korea (3.24) and Italy (3.00) that revealed to have
substantially high overall needs to improve their teaching skills. The previously
presented German teachers were with their overall mean score of 2.80 also in the top of
this ranking and had even higher professional development needs than the sample’s
average (mean = 2.72).
50
Figure 7-2. Average professional development needs (international sample)
It could thereby already be shown that the German teachers’ scores and needs for
professional development were considerably high compared to those of teachers from
other countries. But how does it look for those skills that the German teachers needed
the most to perform adequately in their classrooms? This will be presented in the
following.
As identified before, the skills that German teachers seemed to lack the most were
related to students discipline and behaviour problems. In this item they had an average
need of professional development of 3.21. Setting this average score into comparison
with those novice teachers from other countries (5149 cases valid for comparison)
revealed that the German teachers amount for professional development in this field is
notably higher than the international average of 3.00 score points sharp. In an
international ranking regarding such issues their scores are thus to be found in the upper
half, yet not in the top of it. That is because the largest needs to improve these very
skills were indicated by teachers from Malaysia (3.52), Korea (3.50), and Estonia
(3.28). Also Slovenian, Italian, and Lithuanian teachers revealed higher needs than the
German teachers for skills regarding student discipline and behaviour problems, the
remaining scores of the sample were lower. Teachers from Mexico (2.57), Denmark
(2.62), and Turkey (2.66) were those that considered their skills to be most sufficient in
this area. Noteworthy to mention is also that Hungarian teachers, even if characterised
by the lowest overall need for professional development in teaching skills, were
nevertheless located higher than the sample’s average when it comes to students not
following orders and disturbing the lesson (Figure 7-3).
51
Figure 7-3. Professional development needs: Student discipline and behaviour problems
(international sample)
In terms of skills to teach students with special learning needs the average score of
the whole sample was with 2.98 just gradually smaller than for the previous item. For
the German teachers a score mean of 3.08 (5139 cases valid) had already been
identified. This results in those teachers being ranked above the international average in
this area of development needs, as well. Substantially higher scores were reported by
teachers from Norway (3.30), Spain and Brazil (both 3.25) that ranked the highest in
such comparison. As can be seen in Figure 7-4 only teachers from Italy, Korea,
Portugal, Slovenia, and Ireland were also marked by larger professional development
needs than their German counterparts. Teachers from Bulgaria (2.65), Poland (2.66) and
the Flemish Community of Belgium (2.69), however, considered their skills as most
adequate when they shall teach students with special learning needs in their classrooms.
52
Figure 7-4. Professional development needs: Teaching students with special learning needs
(international sample)
The skill area of instructional practices and knowledge mediation had also been
classified as highly relevant and showed relatively high score points in the analysis of
the German sample. The mean need for professional development of such knowledge
mediation techniques was with 2.93 just slightly beneath the 3-point score line.
Compared to teachers from other countries these scores were yet again above the
international average of 2.77. The highest needs for professional development in this
skill area could be revealed for teachers from Malaysia (3.67), Korea (3.50), and
Lithuania (3.34). Scores higher than the German teachers’ could further be detected
among Italian, Dutch, and Estonian teachers with score means above the 3-point score
line. Teachers from Malta (2.08), Mexico (2.22), and Turkey (2.29), though, appeared to
be comparatively confident with their knowledge mediation skills as can be seen in
Figure 7-5.
53
Figure 7-5. Professional development needs: Knowledge and understanding of instructional
practices in main subject field(s) (international sample)
Given the fact that the overall need for professional development of the group of
German novice teachers had already been higher than the international average, findings
as such appear plausible in relation to the whole sample. However, taking all variables
into account of this wide-scale international comparison, it stands out that the German
teachers indicated to be more confident than the international average in terms of their
professional skills in only three out of ten areas. These were the skills of content and
performance standards (score: 2.32 / int. average: 2.77), student counselling (score: 2.45
/ int. average: 2.73), and knowledge and understanding of the main subject fields
(score: 2.45 / int. average: 2.59). These were also those items that were categorised as of
‘low level of need’ for the German sample.
Whereas it could for the German sample be identified that female novice teachers
appear to have larger professional development needs than male, the findings for the
international sample showed that this is not the case for all groups of teachers in the
international sample. As can be seen in Figure 7-6 there were also countries in the
sample in which male novice teachers seemed to be characterised by larger amounts of
professional development needs than their female counterparts. This could be revealed
54
for teachers from Ireland, Spain, Malaysia, Australia, and Bulgaria for instance, even if
such gender differences must be considered minor in these cases. Teachers from
countries like Portugal or Malta, however, had even larger gender disparities than the
German teachers when it comes to professional development needs. Male teachers from
these countries indicated notably smaller needs to improve their skills.
Figure 7-6. Professional development needs: Gender distribution (international sample)
7.2.2. Teaching in the Target Class (international comparison)
The findings from analysing how novice teachers teach their target classes will be in
focus of this section. Firstly the class sizes will be compared which will be followed by
a closer look into the teachers’ time spent on various classroom activities. Finally, the
classroom disciplinary climates will be presented country wise.
The analysis of international classroom sizes showed a wide range of averages of
how many students are taught together in one class. Of the whole sample 5059
55
participants had provided information about the size of their target classes, and 169 had
not. Though, some further 345 cases had to be excluded from the sample as their values
did not meet the OECD international valid range for this item.
The analysis then revealed that novice teachers from Belgium (Flemish
Community) had by average the fewest students in their classrooms (17.14). Also new
teachers from Lithuania (17.98), Slovenia (18.02), and Hungary (18.15) had
considerably small sizes of classrooms. Novice teachers from Korea (36.71) on the
other hand reported target class sizes that had by average more than twice as many
students as those teachers’ classes. Teachers from Mexico (33.98), Malaysia (32.84),
and Brazil (31.23) also had classroom sizes of averagely more than 30 students. The
German teachers’ classrooms (23.96) were in these terms slightly smaller than the
overall average of the whole sample (24.55).
For the three variables of classroom activities that had to be indicated in
percentages, 281 cases were omitted or did not sum up to 100 percent. Additionally, 756
more cases had to be excluded from the analysis as their values did not meet the criteria
that the OECD researchers found to represent international validity. 4191 cases could
thus be analysed.
In this analysis it could be identified that new teachers in Germany were indeed in
the top of the list when it comes to time spent on actual teaching and learning. Their
average amount of time (81.34%) spent on this activity was higher than the whole
sample’s average of 77.9 percent of time. In the entire sample there were only two
groups of teachers that indicated to spend more time on actual teaching and learning –
those from Hungary (81.44%) and Bulgaria (83.8%). In total, only teachers from six
countries spent more than 80 percent of their time on that activity field. The least
amount of time on this was spent by teachers from the Netherlands (72.95%), Mexico
(73.96%), and Malaysia (74.74%). Teachers from Brazil (74.86) additionally belong to
those who averagely spent less than three quarters of their time on their actual lesson.
Apart from spending the least amount of time on actual teaching and learning,
teachers from the Netherlands were also those that used most of their time keeping order
in their classrooms (17.61%). Italian (16.58%) and Australian teachers (16.03%)
indicated to lose large amounts of time by interfering when their students disturb the
lesson, as well. The German teachers, however, were among those teachers that had to
spend the smallest shares of their lesson on such activities (11.4%) and were far below
the samples average of 13.93 percent of time. Only teachers from Bulgaria (10.68%)
used less time on keeping order in their classrooms. These teachers showed to lose only
considerably small amounts of time on administrative tasks (5.51%), as well. Yet,
Hungarian teachers spent even less time on that activity (5.46%), whereas teachers from
Mexico (13.33%), Brazil (10.1%), and the Flemish Community of Belgium (9.48%)
would be on top of such ranking. The novice teachers from Germany were again below
the international average (8.13%) in such terms with a share of 7.17 percent of their
time. A combined graphic of all findings regarding classroom activities for each country
can be found in Figure 7-7. The countries are ordered by the amount of time their
teachers indicated to spend on actual teaching and learning in ascending form and the
figure’s reference line marks the international average for this at point 77.9 on the
X-axis.
56
Figure 7-7. Target class: Time spent on classroom activities (international sample)
The indicator of classroom disciplinary climate was the last measure implemented
in the dataset for comparison. Out of the sample’s 5228 cases a total of 177 had to be
excluded for the computation of such indicator (that had a range of from -1.5 to 1.5) for
the reason that either all or some of this indicator’s variables were left blank.
The international average of all countries in that was of positive nature with a score
of 0.18. Negative scores for disciplinary climates in novice teachers’ classrooms could
only be identified for five countries. The poorest atmosphere during their lessons was
indicated by teachers from Norway (-0.1), followed by those from Spain (-0.08), Brazil
(-0.05), Hungary (-0.032), and Australia (-0.02). The best climate in terms of students
discipline in class was pictured by Mexican teachers (0.54); and the second best by
those from Germany (0.37). These teachers appeared to be largely satisfied with their
students’ behaviour during lessons. All results of this indicator and those of the groups
of teachers from other countries are shown in Figure 7-8 separated by country.
57
Figure 7-8. Target class: Classroom disciplinary climate (international sample)
7.3. Summary and interpretation of the findings (international
comparison)
To summarise, these comparisons of the findings from 24 countries revealed interesting
and relevant information. For the novice teachers from Germany that were the group in
particular focus of this study a comparison with new teachers from other countries could
set the previous findings into adequate relation. It could be shown that the amounts of
needs for professional development that were mentioned by this group of teachers do
not only appear high on an isolated scale that was used by the study’s questionnaire, but
in fact they are also higher than of most other groups of teachers from the various
countries that they were compared with. This accounts in particular for those skills that
the German teachers apparently lack the most and that were previously revealed as
being practical skills relevant for teaching and for a successful performance in
classrooms. In only three skill areas indicated these teachers professional development
needs lower than the international average. These areas of teaching that they felt
seemingly confident in were in turn rather of theoretic kind.
58
However, in comparison to the majority of teachers from other countries they are
able to use very large amounts of their time in class for actual teaching and learning
despite their impression of insufficient skills for teaching. Teachers not from Germany
that indicated professional development needs at a similar extent lose considerably more
time on activities different from teaching. Consequently, the share of time that German
novice teachers have to spend on keeping order in the classroom is one of the lowest of
the international sample. These findings appear particularly surprising when considering
that they are among those teachers that indicated the highest needs to improve their
skills in terms of student discipline and behaviour problems. Teachers from such
countries as Italy, the Netherlands, or Malaysia, for instance, stated that they have by
comparison much less time available for actual teaching and learning and were more
often required to use their lesson time to keep order in the classroom.
In addition to that, the student disciplinary climate in those classrooms that these
German teachers teach in appears to be much better than in other countries. Even if they
are seemingly insecure in terms of their current teaching skills they are averagely not
challenged by their student’s behaviour in class so that their classrooms can be marked
by a positive teaching and learning atmosphere. Contrarily to them appear to be teachers
from Mexico, Hungary, or Australia, for example. New teachers from Mexico are
among those who in relation to others indicated little need for professional development
and teach in classrooms with the best student disciplinary climate, but spend
comparably little time on actual teaching and learning. Hungarian teachers on the other
hand also indicated moderate to low amounts of professional development needs, but
are able to use much time for their actual lessons, although their classes have a poor
student disciplinary climate. Such atmosphere for teaching and learning is not
experienced as good by Australian novice teachers and they lose comparably large
amounts of time on keeping order in their classroom, yet they do not consider their
skills in terms of student discipline and behaviour problems as inadequate as the
majority of other teachers do.
What these findings mean in relation to teacher education programmes and systems
as well as the economics of education shall finally be discussed in the concluding
section of this study.
59
Chapter 8
Discussion
This research could lucidly reveal that new teachers that have received their teacher
education in the Federal Republic of Germany have substantial professional
development needs in the discipline of teaching. Their self-evaluations of respective
teaching skills were remarkably poor and characterised by an impression of low self-
esteem in their profession. Great stress has to be laid upon those particular skill areas
they feel unprepared in. These are namely those skills that can be considered as
practical skills for teaching, or more precisely, skills of practical and didactical nature
that are of high relevance in classrooms. On the other hand the teachers could be
identified as competent in terms of theoretical skills and knowledge about teaching.
These findings leave room for conclusions about the German TE system in which the
study’s participants were educated to become teachers. That the German novice teachers
appear largely insecure regarding their practical skills despite having recently graduated
from TE programmes shows clearly that they have not been able to acquire such skills
during their education. This must be regarded as an inadequacy in that system that failed
to provide opportunities for these novice teachers to learn how to act and perform in
classrooms. This especially accounts for critical situations and occurrences during
lessons in which the participants of the study do not feel capable of reacting in adequate
ways.
Regarding the premises of German teacher education and its recent reforms these
findings are crucial. It had been particularly aimed to develop such practical skills that
are considered vital for solid classroom performances of teachers. The German teacher
novices, however, indicated in this study that their education programmes for teaching
could not meet these objectives. They felt unprepared at a considerably high level even
in comparison to novice teachers from other countries. The findings much rather
suggest a proportion of TE learning contents of mere theoretic nature as these were the
areas of teaching that the new teachers feel most competent in. In economic terms this
furthermore means that those teachers that graduate from TE programmes in Germany
cannot be considered optimally qualified. This would only be the fact if novice teachers
do not see any or just little needs to develop the relevant skills in their profession. To
elaborate, economic cost-benefit analysis of inputs and outputs is certainly difficult to
measure in education and beyond that the exact input of resources into German teacher
education is unclear. Yet, an output as such, which is namely teachers that do not feel
adequately prepared for teaching, cannot be regarded as fully satisfying. In addition to
that, it might be questioned whether teachers would feel even less prepared for their
profession in regard of these practical skills if they started their preparatory service at an
earlier stage. In economic terms, this would question whether a reduction of opportunity
costs from funding side would result in a ‘product’ of poorer quality. Much rather it
should be emphasised that in order to receive teachers that feel adequately qualified and
prepared for teaching, teacher education programmes would have to stress the mediation
and acquisition of practical teaching skills to a much greater degree. That this has been
realised by policy making side in the field of education can clearly be seen in the
60
intentions incorporated in the recent educational reforms at higher education level and
TE in particular. Yet, the findings of this study show that novice teachers did not
perceive this as sufficient in their education.
The study’s findings, however, also reveal that the novice teachers from the
Federal Republic of Germany perform considerably well in classrooms compared to
those from other countries. This, certainly, relativises the economic aspect as it reveals
that the German novice teachers, despite their comparably high amount of professional
development, are able to perform better in their respective classrooms than the majority
of novice teachers they were compared with. On the other hand, this does by
implication not necessarily mean that those teachers that graduated from German TE
programmes are in spite of their own personal impression adequately prepared for
teaching. Such statement would firstly require an analysis of their teaching practices in
much greater depth as it has been done in this study. Secondly, these findings are
merely measured in relation to other novice teachers. It would thus require a further
analysis that compares novice and experience teachers in order to find out whether there
are differences in classroom performances between these groups, or not (of which only
the latter would justify such conclusion).
For that reason, this study first and foremost allows the conclusion that the novice
teachers in its focus do not feel entirely prepared for their profession and that they could
not acquire relevant teaching skills during their teacher education programmes in the
Federal Republic of Germany. As of now the German teacher education system would
require a much larger amount of approaches that enhance practical teaching skills in
order to counteract such effects. The fact that novice teachers as part of their
preparatory service receive subsequent supervision and guidance as well as further
education and training to optimise their classroom experiences can yet be considered a
factor that moderates such insufficiencies in TE programmes. It can be argued whether a
point in time when first work-related classroom experiences have already been made
might be adequate for this, but that would have to be discussed at a different place.
61
Chapter 9
Suggestions for Subsequent Research
As mentioned in previous sections of this study this research opens room for various
subsequent studies that further analyse the experiences of new teachers. These could be
the following:
A subsequent comparative study of the German sample and the TALIS
2013 dataset
The report for the second TALIS study from 2013 will be released later in 2014. As this
study encompassed a larger number of countries and additional teaching skills in the
section for professional development needs comparative findings are considered as
promising. It will be possible to apply the information from the German sample for such
study again since those items that were added to TALIS 2013 had already been
incorporated in this study’s questionnaire.
A comparative study of new and experienced teachers in the Federal
Republic of Germany
Such study would enable further conclusions about the German TE system as it was
already explained in this study’s discussion section. Information about classroom
performances would in this be required from German teachers that have taught in
schools for more than five years (which was the TALIS 2008 criterion for experienced
teachers).
A qualitative study on novice teacher’s subjective impressions about their
TE programmes
Such study could be seen as complementary to this study. It would thus provide more
thorough information about the German system of teacher education.
A study on the impact of the preparatory service on German novice
teachers
This might certainly be the most difficult issue to research. Findings about effects the
preparatory service has on novice teachers on their subjective views on their own
professional performance might be worthwhile to complement this study.
62
An economic analysis of the costs of German teacher education
programmes in relation to the findings from this study
A study as such could identify economic factors of input into teacher education
programmes more thoroughly. In regards of the findings from this study more sound
conclusions could be drawn from that which might support further reforms in the
German TE system.
63
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66
Annex A:
The Questionnaire
Note: Only the translated German questionnaire was added to the Annexes. The
original TALIS 2008 and TALIS 2013 questionnaires can be retrieved from the official
OECD TALIS webpage:
http://www.oecd.org/edu/school/talis.htm
67
68
69
70
Annex B:
Frequencies, Statistics and Tables (German Sample)
BACKGROUND/GENDER
Frequency Percent Valid Percent
Cumulative
Percent
Valid FEMALE 174 68,8 68,8 68,8
MALE 79 31,2 31,2 100,0
Total 253 100,0 100,0
a) Professional Development Needs
FREQUENCIES
AVERAGE DEVELOPMENT NEED
Frequency Percent Valid Percent
Cumulative
Percent
Valid 1,40000 1 ,4 ,4 ,4
1,60000 1 ,4 ,4 ,8
1,66667 1 ,4 ,4 1,2
1,80000 2 ,8 ,8 2,0
1,90000 4 1,6 1,6 3,6
2,00000 5 2,0 2,0 5,5
2,10000 8 3,2 3,2 8,7
2,20000 7 2,8 2,8 11,5
2,30000 8 3,2 3,2 14,6
2,40000 8 3,2 3,2 17,8
2,50000 15 5,9 5,9 23,7
2,60000 19 7,5 7,5 31,2
2,70000 24 9,5 9,5 40,7
2,80000 32 12,6 12,6 53,4
2,88889 3 1,2 1,2 54,5
2,90000 21 8,3 8,3 62,8
3,00000 20 7,9 7,9 70,8
71
3,10000 21 8,3 8,3 79,1
3,20000 16 6,3 6,3 85,4
3,30000 14 5,5 5,5 90,9
3,33333 1 ,4 ,4 91,3
3,40000 10 4,0 4,0 95,3
3,50000 4 1,6 1,6 96,8
3,55556 1 ,4 ,4 97,2
3,60000 4 1,6 1,6 98,8
3,66667 1 ,4 ,4 99,2
3,70000 1 ,4 ,4 99,6
3,80000 1 ,4 ,4 100,0
Total 253 100,0 100,0
Frequencies Development needs
N
Mean Median Mode Std. Deviation Valid Missing
PROFDEV/NEEDS/STUDE
NT DISCIPLINE 253 0 3,21 3,00 3
a ,795
PROFDEV/NEEDS/SPECIA
L LEARNING NEEDS 250 3 3,08 3,00 4 1,044
PROFDEV/NEEDS/STUDE
NT ASSESSMENT 253 0 3,06 3,00 3 ,784
PROFDEV/NEEDS/KNOWL
EDGE INSTRUC PRACT 252 1 2,93 3,00 3 ,699
PROFDEV/NEEDS/ICT
SKILLS 252 1 2,85 3,00 3 ,878
PROFDEV/NEEDS/MULTIC
ULTURAL SETTING 252 1 2,85 3,00 3 ,872
PROFDEV/NEEDS/SCHOO
L MANAGEMENT 251 2 2,82 3,00 3 ,878
PROFDEV/NEEDS/KNOWL
EDGE MAIN SUBJECTS 251 2 2,45 3,00 3 ,796
PROFDEV/NEEDS/STUDE
NT COUNSELLING 252 1 2,45 2,00 2 ,970
PROFDEV/NEEDS/CONTE
NT PERFORM
STANDARDS
252 1 2,32 2,00 3 ,858
Table Caption
a. Multiple modes exist. The smallest value is shown
72
PROFDEV/NEEDS/CONTENT PERFORM STANDARDS
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 49 19,4 19,4 19,4
LOW LEVEL OF NEED 90 35,6 35,7 55,2
MODERATE LEVEL OF
NEED 97 38,3 38,5 93,7
HIGH LEVEL OF NEED 16 6,3 6,3 100,0
Total 252 99,6 100,0
Missing OMITTED 1 ,4
Total 253 100,0
PROFDEV/NEEDS/STUDENT ASSESSMENT
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 4 1,6 1,6 1,6
LOW LEVEL OF NEED 58 22,9 22,9 24,5
MODERATE LEVEL OF
NEED 109 43,1 43,1 67,6
HIGH LEVEL OF NEED 82 32,4 32,4 100,0
Total 253 100,0 100,0
PROFDEV/NEEDS/KNOWLEDGE MAIN SUBJECTS
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 32 12,6 12,7 12,7
LOW LEVEL OF NEED 89 35,2 35,5 48,2
MODERATE LEVEL OF
NEED 114 45,1 45,4 93,6
HIGH LEVEL OF NEED 16 6,3 6,4 100,0
Total 251 99,2 100,0
Missing OMITTED 2 ,8
Total 253 100,0
73
PROFDEV/NEEDS/KNOWLEDGE INSTRUC PRACT
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 8 3,2 3,2 3,2
LOW LEVEL OF NEED 47 18,6 18,7 21,8
MODERATE LEVEL OF
NEED 152 60,1 60,3 82,1
HIGH LEVEL OF NEED 45 17,8 17,9 100,0
Total 252 99,6 100,0
Missing OMITTED 1 ,4
Total 253 100,0
PROFDEV/NEEDS/ICT SKILLS
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 20 7,9 7,9 7,9
LOW LEVEL OF NEED 58 22,9 23,0 31,0
MODERATE LEVEL OF
NEED 113 44,7 44,8 75,8
HIGH LEVEL OF NEED 61 24,1 24,2 100,0
Total 252 99,6 100,0
Missing OMITTED 1 ,4
Total 253 100,0
PROFDEV/NEEDS/SPECIAL LEARNING NEEDS
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 26 10,3 10,4 10,4
LOW LEVEL OF NEED 48 19,0 19,2 29,6
MODERATE LEVEL OF
NEED 55 21,7 22,0 51,6
HIGH LEVEL OF NEED 121 47,8 48,4 100,0
Total 250 98,8 100,0
Missing OMITTED 3 1,2
Total 253 100,0
74
PROFDEV/NEEDS/STUDENT DISCIPLINE
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 7 2,8 2,8 2,8
LOW LEVEL OF NEED 38 15,0 15,0 17,8
MODERATE LEVEL OF
NEED 104 41,1 41,1 58,9
HIGH LEVEL OF NEED 104 41,1 41,1 100,0
Total 253 100,0 100,0
PROFDEV/NEEDS/SCHOOL MANAGEMENT
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 18 7,1 7,2 7,2
LOW LEVEL OF NEED 69 27,3 27,5 34,7
MODERATE LEVEL OF
NEED 104 41,1 41,4 76,1
HIGH LEVEL OF NEED 60 23,7 23,9 100,0
Total 251 99,2 100,0
Missing OMITTED 2 ,8
Total 253 100,0
PROFDEV/NEEDS/MULTICULTURAL SETTING
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 18 7,1 7,1 7,1
LOW LEVEL OF NEED 64 25,3 25,4 32,5
MODERATE LEVEL OF
NEED 109 43,1 43,3 75,8
HIGH LEVEL OF NEED 61 24,1 24,2 100,0
Total 252 99,6 100,0
Missing OMITTED 1 ,4
Total 253 100,0
75
PROFDEV/NEEDS/STUDENT COUNSELLING
Frequency Percent Valid Percent
Cumulative
Percent
Valid NO NEED AT ALL 46 18,2 18,3 18,3
LOW LEVEL OF NEED 88 34,8 34,9 53,2
MODERATE LEVEL OF
NEED 77 30,4 30,6 83,7
HIGH LEVEL OF NEED 41 16,2 16,3 100,0
Total 252 99,6 100,0
Missing OMITTED 1 ,4
Total 253 100,0
Report – Professional development needs by gender
BACKGROUND/GENDER
FEMALE MALE Total
Mean
Std.
Deviation Mean
Std.
Deviation Mean
Std.
Deviation
PROFDEV/NEEDS/CONTE
NT PERFORM
STANDARDS
2,29 ,847 2,37 ,884 2,32 ,858
PROFDEV/NEEDS/STUDE
NT ASSESSMENT 3,13 ,757 2,92 ,829 3,06 ,784
PROFDEV/NEEDS/KNOWL
EDGE MAIN SUBJECTS 2,52 ,776 2,30 ,822 2,45 ,796
PROFDEV/NEEDS/KNOWL
EDGE INSTRUC PRACT 2,92 ,699 2,94 ,704 2,93 ,699
PROFDEV/NEEDS/ICT
SKILLS 2,99 ,811 2,54 ,945 2,85 ,878
PROFDEV/NEEDS/SPECIA
L LEARNING NEEDS 3,22 ,954 2,78 1,169 3,08 1,044
PROFDEV/NEEDS/STUDE
NT DISCIPLINE 3,25 ,777 3,11 ,832 3,21 ,795
PROFDEV/NEEDS/SCHOO
L MANAGEMENT 2,81 ,879 2,84 ,883 2,82 ,878
PROFDEV/NEEDS/MULTIC
ULTURAL SETTING 2,91 ,891 2,71 ,819 2,85 ,872
PROFDEV/NEEDS/STUDE
NT COUNSELLING 2,47 ,931 2,41 1,056 2,45 ,970
76
b) Teaching in the Target Class
Time spend on classroom activities (in percent)
TARGETCL/AC
TIV/ADMININST
RATIVE
TARGETCL/AC
TIV/KEEPING
ORDER
TARGETCL/AC
TIV/TEACHING
LEARNING
N Valid 226 226 226
Missing 0 0 0
Mean 7,17 11,40 81,34
Median 5,00 10,00 85,00
Mode 5 5 80
Std. Deviation 4,410 7,921 10,183
Minimum 0 0 50
Maximum 20 30 99
Administrative tasks
Frequency Percent Valid Percent
Cumulative
Percent
Valid 0 2 ,9 ,9 ,9
1 15 6,6 6,6 7,5
2 11 4,9 4,9 12,4
3 10 4,4 4,4 16,8
4 4 1,8 1,8 18,6
5 87 38,5 38,5 57,1
7 2 ,9 ,9 58,0
8 3 1,3 1,3 59,3
10 73 32,3 32,3 91,6
15 9 4,0 4,0 95,6
20 10 4,4 4,4 100,0
Total 226 100,0 100,0
77
Keeping order in the classroom
Frequency Percent Valid Percent
Cumulative
Percent
Valid 0 1 ,4 ,4 ,4
1 4 1,8 1,8 2,2
2 7 3,1 3,1 5,3
3 6 2,7 2,7 8,0
4 6 2,7 2,7 10,6
5 61 27,0 27,0 37,6
6 3 1,3 1,3 38,9
7 4 1,8 1,8 40,7
8 2 ,9 ,9 41,6
9 1 ,4 ,4 42,0
10 56 24,8 24,8 66,8
12 2 ,9 ,9 67,7
15 20 8,8 8,8 76,5
18 2 ,9 ,9 77,4
19 1 ,4 ,4 77,9
20 25 11,1 11,1 88,9
22 1 ,4 ,4 89,4
25 8 3,5 3,5 92,9
30 16 7,1 7,1 100,0
Total 226 100,0 100,0
78
Actual teaching and learning
Frequency Percent Valid Percent
Cumulative
Percent
Valid 50 2 ,9 ,9 ,9
55 1 ,4 ,4 1,3
60 15 6,6 6,6 8,0
65 8 3,5 3,5 11,5
70 19 8,4 8,4 19,9
75 15 6,6 6,6 26,5
80 45 19,9 19,9 46,5
83 1 ,4 ,4 46,9
84 1 ,4 ,4 47,3
85 44 19,5 19,5 66,8
86 1 ,4 ,4 67,3
87 1 ,4 ,4 67,7
88 7 3,1 3,1 70,8
89 4 1,8 1,8 72,6
90 35 15,5 15,5 88,1
91 1 ,4 ,4 88,5
92 5 2,2 2,2 90,7
93 4 1,8 1,8 92,5
94 5 2,2 2,2 94,7
95 5 2,2 2,2 96,9
96 1 ,4 ,4 97,3
97 3 1,3 1,3 98,7
98 2 ,9 ,9 99,6
99 1 ,4 ,4 100,0
Total 226 100,0 100,0
79
Statistics
Index of classroom disciplinary
climate
N Valid 249
Missing 0
Mean 2,8705
Mode 3,25
Std. Deviation ,68468
Minimum 1,00
Maximum 4,00
Index of classroom disciplinary climate
Frequency Percent Valid Percent
Cumulative
Percent
Valid 1,00 1 ,4 ,4 ,4
1,25 1 ,4 ,4 ,8
1,50 9 3,6 3,6 4,4
1,75 14 5,6 5,6 10,0
2,00 19 7,6 7,6 17,7
2,25 16 6,4 6,4 24,1
2,50 21 8,4 8,4 32,5
2,75 35 14,1 14,1 46,6
3,00 34 13,7 13,7 60,2
3,25 38 15,3 15,3 75,5
3,50 28 11,2 11,2 86,7
3,75 15 6,0 6,0 92,8
4,00 18 7,2 7,2 100,0
Total 249 100,0 100,0
80
c) Correlations
Correlations – Professional development needs / Classroom activities (Spearman’s Rho)
TARGETCL
/ACTIV/KE
EPING
ORDER
TARGETCL
/ACTIV/TEA
CHING
LEARNING
PROFDEV/
NEEDS/CO
NTENT
PERFORM
STANDAR
DS
PROFDEV/
NEEDS/ST
UDENT
ASSESSM
ENT
PROFDEV/
NEEDS/KN
OWLEDGE
MAIN
SUBJECTS
PROFDEV/
NEEDS/KN
OWLEDGE
INSTRUC
PRACT
PROFDEV/
NEEDS/ICT
SKILLS
PROFDEV/
NEEDS/SP
ECIAL
LEARNING
NEEDS
PROFDEV/
NEEDS/ST
UDENT
DISCIPLIN
E
PROFDEV/
NEEDS/SC
HOOL
MANAGEM
ENT
PROFDEV/
NEEDS/MU
LTICULTU
RAL
SETTING
PROFDEV/
NEEDS/ST
UDENT
COUNSEL
LING
TARGETCL/AC
TIV/KEEPING
ORDER
Correlation
Coefficient
1,000 -,881** -,004 ,056 ,082 ,046 ,014 ,087 ,215
** -,086 ,124 -,021
Sig. (2-
tailed)
. ,000 ,955 ,403 ,223 ,488 ,835 ,196 ,001 ,199 ,064 ,753
N 226 226 225 226 224 225 225 223 226 224 225 225
TARGETCL/AC
TIV/TEACHING
LEARNING
Correlation
Coefficient
-,881** 1,000 -,048 -,066 -,109 -,042 ,025 -,096 -,183
** ,084 -,124 ,003
Sig. (2-
tailed)
,000 . ,473 ,326 ,105 ,531 ,712 ,154 ,006 ,213 ,063 ,970
N 226 226 225 226 224 225 225 223 226 224 225 225
PROFDEV/NEE
DS/CONTENT
PERFORM
STANDARDS
Correlation
Coefficient
-,004 -,048 1,000 ,332** ,222
** ,227
** ,068 ,018 ,036 ,169
* ,084 ,011
Sig. (2-
tailed)
,955 ,473 . ,000 ,001 ,001 ,313 ,794 ,592 ,011 ,208 ,873
N 225 225 225 225 223 224 224 222 225 223 224 224
PROFDEV/NEE
DS/STUDENT
ASSESSMENT
Correlation
Coefficient
,056 -,066 ,332** 1,000 ,153
* ,279
** ,226
** ,136
* ,329
** ,119 ,224
** ,028
Sig. (2-
tailed)
,403 ,326 ,000 . ,022 ,000 ,001 ,043 ,000 ,076 ,001 ,679
N 226 226 225 226 224 225 225 223 226 224 225 225
PROFDEV/NEE
DS/KNOWLED
GE MAIN
SUBJECTS
Correlation
Coefficient
,082 -,109 ,222** ,153
* 1,000 ,192
** ,169
* -,031 -,018 -,004 ,021 ,134
*
Sig. (2-
tailed)
,223 ,105 ,001 ,022 . ,004 ,011 ,648 ,790 ,954 ,753 ,045
N 224 224 223 224 224 224 224 222 224 222 223 224
PROFDEV/NEE
DS/KNOWLED
GE INSTRUC
PRACT
Correlation
Coefficient
,046 -,042 ,227** ,279
** ,192
** 1,000 ,076 ,081 ,293
** ,050 ,081 ,079
Sig. (2-
tailed)
,488 ,531 ,001 ,000 ,004 . ,258 ,229 ,000 ,457 ,226 ,240
N 225 225 224 225 224 225 225 223 225 223 224 225
81
PROFDEV/NEE
DS/ICT SKILLS
Correlation
Coefficient
,014 ,025 ,068 ,226** ,169
* ,076 1,000 ,082 ,127 ,309
** ,087 ,154
*
Sig. (2-
tailed)
,835 ,712 ,313 ,001 ,011 ,258 . ,221 ,056 ,000 ,192 ,021
N 225 225 224 225 224 225 225 223 225 223 224 225
PROFDEV/NEE
DS/SPECIAL
LEARNING
NEEDS
Correlation
Coefficient
,087 -,096 ,018 ,136* -,031 ,081 ,082 1,000 ,078 ,270
** ,519
** ,265
**
Sig. (2-
tailed)
,196 ,154 ,794 ,043 ,648 ,229 ,221 . ,246 ,000 ,000 ,000
N 223 223 222 223 222 223 223 223 223 221 222 223
PROFDEV/NEE
DS/STUDENT
DISCIPLINE
Correlation
Coefficient
,215** -,183
** ,036 ,329
** -,018 ,293
** ,127 ,078 1,000 ,116 ,206
** ,045
Sig. (2-
tailed)
,001 ,006 ,592 ,000 ,790 ,000 ,056 ,246 . ,083 ,002 ,507
N 226 226 225 226 224 225 225 223 226 224 225 225
PROFDEV/NEE
DS/SCHOOL
MANAGEMENT
Correlation
Coefficient
-,086 ,084 ,169* ,119 -,004 ,050 ,309
** ,270
** ,116 1,000 ,321
** ,266
**
Sig. (2-
tailed)
,199 ,213 ,011 ,076 ,954 ,457 ,000 ,000 ,083 . ,000 ,000
N 224 224 223 224 222 223 223 221 224 224 223 223
PROFDEV/NEE
DS/MULTICUL
TURAL
SETTING
Correlation
Coefficient
,124 -,124 ,084 ,224** ,021 ,081 ,087 ,519
** ,206
** ,321
** 1,000 ,158
*
Sig. (2-
tailed)
,064 ,063 ,208 ,001 ,753 ,226 ,192 ,000 ,002 ,000 . ,018
N 225 225 224 225 223 224 224 222 225 223 225 224
PROFDEV/NEE
DS/STUDENT
COUNSELLING
Correlation
Coefficient
-,021 ,003 ,011 ,028 ,134* ,079 ,154
* ,265
** ,045 ,266
** ,158
* 1,000
Sig. (2-
tailed)
,753 ,970 ,873 ,679 ,045 ,240 ,021 ,000 ,507 ,000 ,018 .
N 225 225 224 225 224 225 225 223 225 223 224 225
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
82
Correlations – Classroom disciplinary climate / Classroom activities (Spearman’s Rho)
Classroom
Disciplinary
Climate
TARGETCL/ACT
IV/ADMININSTR
ATIVE
TARGETCL/ACT
IV/KEEPING
ORDER
TARGETCL/ACT
IV/TEACHING
LEARNING
Classroom
Disciplinary
Climate
Correlation
Coefficient 1,000 -,053 -,539
** ,407
**
Sig. (2-tailed) . ,428 ,000 ,000
N 224 224 224 224
TARGETCL/A
CTIV/ADMINI
NSTRATIVE
Correlation
Coefficient -,053 1,000 ,310
** -,668
**
Sig. (2-tailed) ,428 . ,000 ,000
N 224 224 224 224
TARGETCL/A
CTIV/KEEPIN
G ORDER
Correlation
Coefficient -,539
** ,310
** 1,000 -,882
**
Sig. (2-tailed) ,000 ,000 . ,000
N 224 224 224 224
TARGETCL/A
CTIV/TEACHI
NG
LEARNING
Correlation
Coefficient ,407
** -,668
** -,882
** 1,000
Sig. (2-tailed) ,000 ,000 ,000 .
N 224 224 224 224
**. Correlation is significant at the 0.01 level (2-tailed).
83
Correlations – Professional development needs / Classroom disciplinary climate (Spearman’s Rho)
Classroom
Disciplinary
Climate
PROFDEV/N
EEDS/CONT
ENT
PERFORM
STANDARD
S
PROFDEV/N
EEDS/STUD
ENT
ASSESSME
NT
PROFDEV/N
EEDS/KNO
WLEDGE
MAIN
SUBJECTS
PROFDEV/N
EEDS/KNO
WLEDGE
INSTRUC
PRACT
PROFDEV/N
EEDS/ICT
SKILLS
PROFDEV/N
EEDS/SPEC
IAL
LEARNING
NEEDS
PROFDEV/N
EEDS/STUD
ENT
DISCIPLINE
PROFDEV/N
EEDS/SCH
OOL
MANAGEME
NT
PROFDEV/N
EEDS/MULT
ICULTURAL
SETTING
PROFDEV/
NEEDS/STU
DENT
COUNSELLI
NG
Classroom
Disciplinary
Climate
Correlation
Coefficient
1,000 ,035 -,111 -,001 -,095 ,057 -,072 -,341** -,017 -,162
* -,009
Sig. (2-tailed) . ,586 ,081 ,993 ,137 ,368 ,258 ,000 ,786 ,011 ,885
N 249 248 249 247 248 248 246 249 247 248 248
PROFDEV/NEE
DS/CONTENT
PERFORM
STANDARDS
Correlation
Coefficient
,035 1,000 ,318** ,213
** ,235
** ,057 -,006 ,004 ,163
* ,054 ,013
Sig. (2-tailed) ,586 . ,000 ,001 ,000 ,369 ,927 ,945 ,010 ,396 ,845
N 248 248 248 246 247 247 245 248 246 247 247
PROFDEV/NEE
DS/STUDENT
ASSESSMENT
Correlation
Coefficient
-,111 ,318** 1,000 ,157
* ,274
** ,211
** ,106 ,297
** ,137
* ,224
** ,054
Sig. (2-tailed) ,081 ,000 . ,014 ,000 ,001 ,097 ,000 ,032 ,000 ,394
N 249 248 249 247 248 248 246 249 247 248 248
PROFDEV/NEE
DS/KNOWLED
GE MAIN
SUBJECTS
Correlation
Coefficient
-,001 ,213** ,157
* 1,000 ,182
** ,161
* -,009 -,019 -,013 ,025 ,086
Sig. (2-tailed) ,993 ,001 ,014 . ,004 ,011 ,889 ,766 ,842 ,691 ,179
N 247 246 247 247 247 247 245 247 245 246 247
PROFDEV/NEE
DS/KNOWLED
GE INSTRUC
PRACT
Correlation
Coefficient
-,095 ,235** ,274
** ,182
** 1,000 ,124 -,001 ,255
** ,049 ,054 ,083
Sig. (2-tailed) ,137 ,000 ,000 ,004 . ,051 ,984 ,000 ,441 ,397 ,191
N 248 247 248 247 248 248 246 248 246 247 248
PROFDEV/NEE
DS/ICT SKILLS
Correlation
Coefficient
,057 ,057 ,211** ,161
* ,124 1,000 ,062 ,145
* ,235
** ,087 ,145
*
Sig. (2-tailed) ,368 ,369 ,001 ,011 ,051 . ,331 ,023 ,000 ,172 ,022
N 248 247 248 247 248 248 246 248 246 247 248
PROFDEV/NEE
DS/SPECIAL
LEARNING
NEEDS
Correlation
Coefficient
-,072 -,006 ,106 -,009 -,001 ,062 1,000 ,075 ,279** ,502
** ,243
**
Sig. (2-tailed) ,258 ,927 ,097 ,889 ,984 ,331 . ,238 ,000 ,000 ,000
N 246 245 246 245 246 246 246 246 244 245 246
PROFDEV/NEE
DS/STUDENT
DISCIPLINE
Correlation
Coefficient
-,341** ,004 ,297
** -,019 ,255
** ,145
* ,075 1,000 ,097 ,218
** ,031
Sig. (2-tailed) ,000 ,945 ,000 ,766 ,000 ,023 ,238 . ,128 ,001 ,628
84
N 249 248 249 247 248 248 246 249 247 248 248
PROFDEV/NEE
DS/SCHOOL
MANAGEMENT
Correlation
Coefficient
-,017 ,163* ,137
* -,013 ,049 ,235
** ,279
** ,097 1,000 ,312
** ,295
**
Sig. (2-tailed) ,786 ,010 ,032 ,842 ,441 ,000 ,000 ,128 . ,000 ,000
N 247 246 247 245 246 246 244 247 247 246 246
PROFDEV/NEE
DS/MULTICUL
TURAL
SETTING
Correlation
Coefficient
-,162* ,054 ,224
** ,025 ,054 ,087 ,502
** ,218
** ,312
** 1,000 ,169
**
Sig. (2-tailed) ,011 ,396 ,000 ,691 ,397 ,172 ,000 ,001 ,000 . ,008
N 248 247 248 246 247 247 245 248 246 248 247
PROFDEV/NEE
DS/STUDENT
COUNSELLING
Correlation
Coefficient
-,009 ,013 ,054 ,086 ,083 ,145* ,243
** ,031 ,295
** ,169
** 1,000
Sig. (2-tailed) ,885 ,845 ,394 ,179 ,191 ,022 ,000 ,628 ,000 ,008 .
N 248 247 248 247 248 248 246 248 246 247 248
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Correlations – Student enrolment / Classroom activities (Spearman’s Rho)
TARGETCL/STU
DENT
ENROLMENT
TARGETCL/ACT
IV/ADMININSTR
ATIVE
TARGETCL/ACT
IV/KEEPING
ORDER
TARGETCL/ACT
IV/TEACHING
LEARNING
TARGETCL/STUD
ENT ENROLMENT
Correlation
Coefficient 1,000 -,034 -,068 ,071
Sig. (2-tailed) . ,606 ,309 ,286
N 226 226 226 226
TARGETCL/ACTIV
/ADMININSTRATIV
E
Correlation
Coefficient -,034 1,000 ,312
** -,670
**
Sig. (2-tailed) ,606 . ,000 ,000
N 226 226 226 226
TARGETCL/ACTIV
/KEEPING ORDER
Correlation
Coefficient -,068 ,312
** 1,000 -,881
**
Sig. (2-tailed) ,309 ,000 . ,000
N 226 226 226 226
TARGETCL/ACTIV
/TEACHING
LEARNING
Correlation
Coefficient ,071 -,670
** -,881
** 1,000
Sig. (2-tailed) ,286 ,000 ,000 .
N 226 226 226 226
**. Correlation is significant at the 0.01 level (2-tailed).
85
Correlations – Student enrolment / Classroom disciplinary climate (Spearman’s Rho)
TARGETCL/ST
UDENT
ENROLMENT
Classroom
Disciplinary
Climate
TARGETCL/STUDENT
ENROLMENT
Correlation Coefficient 1,000 ,008
Sig. (2-tailed) . ,900
N 249 249
Classroom Disciplinary
Climate
Correlation Coefficient ,008 1,000
Sig. (2-tailed) ,900 .
N 249 249
86
d) Split-sample
Statistics - Time spend on actual teaching and learning > 75
N
Mean Std. Deviation Valid Missing
AVERAGE DEVELOPMENT
NEED 166 0 2,7823293 ,43296293
PROFDEV/NEEDS/CONTE
NT PERFORM
STANDARDS
165 1 2,30 ,878
PROFDEV/NEEDS/STUDE
NT ASSESSMENT 166 0 3,03 ,797
PROFDEV/NEEDS/KNOWL
EDGE MAIN SUBJECTS 165 1 2,38 ,776
PROFDEV/NEEDS/KNOWL
EDGE INSTRUC PRACT 166 0 2,96 ,699
PROFDEV/NEEDS/ICT
SKILLS 166 0 2,87 ,854
PROFDEV/NEEDS/SPECIA
L LEARNING NEEDS 164 2 3,05 1,061
PROFDEV/NEEDS/STUDE
NT DISCIPLINE 166 0 3,11 ,841
PROFDEV/NEEDS/SCHOO
L MANAGEMENT 166 0 2,85 ,871
PROFDEV/NEEDS/MULTIC
ULTURAL SETTING 165 1 2,82 ,869
PROFDEV/NEEDS/STUDE
NT COUNSELLING 166 0 2,45 ,931
87
Statistics - Time spend on actual teaching and learning < 75
N
Mean Std. Deviation Valid Missing
AVERAGE DEVELOPMENT
NEED 45 0 2,8071605 ,43952553
PROFDEV/NEEDS/CONTE
NT PERFORM
STANDARDS
45 0 2,33 ,879
PROFDEV/NEEDS/STUDE
NT ASSESSMENT 45 0 3,11 ,775
PROFDEV/NEEDS/KNOWL
EDGE MAIN SUBJECTS 44 1 2,64 ,810
PROFDEV/NEEDS/KNOWL
EDGE INSTRUC PRACT 44 1 2,98 ,664
PROFDEV/NEEDS/ICT
SKILLS 44 1 2,86 ,905
PROFDEV/NEEDS/SPECIA
L LEARNING NEEDS 44 1 2,95 1,033
PROFDEV/NEEDS/STUDE
NT DISCIPLINE 45 0 3,42 ,657
PROFDEV/NEEDS/SCHOO
L MANAGEMENT 43 2 2,51 ,856
PROFDEV/NEEDS/MULTIC
ULTURAL SETTING 45 0 2,84 ,928
PROFDEV/NEEDS/STUDE
NT COUNSELLING 44 1 2,30 ,978
88
Statistics - CDC > 0
N
Mean Std. Deviation Valid Missing
AVERAGE DEVELOPMENT
NEED 168 0 2,7726190 ,42795404
PROFDEV/NEEDS/CONTE
NT PERFORM
STANDARDS
168 0 2,32 ,856
PROFDEV/NEEDS/STUDE
NT ASSESSMENT 168 0 3,02 ,789
PROFDEV/NEEDS/KNOWL
EDGE MAIN SUBJECTS 166 2 2,46 ,814
PROFDEV/NEEDS/KNOWL
EDGE INSTRUC PRACT 167 1 2,89 ,703
PROFDEV/NEEDS/ICT
SKILLS 167 1 2,86 ,878
PROFDEV/NEEDS/SPECIA
L LEARNING NEEDS 165 3 3,05 1,070
PROFDEV/NEEDS/STUDE
NT DISCIPLINE 168 0 3,08 ,826
PROFDEV/NEEDS/SCHOO
L MANAGEMENT 167 1 2,80 ,889
PROFDEV/NEEDS/MULTIC
ULTURAL SETTING 168 0 2,78 ,844
PROFDEV/NEEDS/STUDE
NT COUNSELLING 167 1 2,45 ,955
89
Statistics - CDC < 0
N
Mean Std. Deviation Valid Missing
AVERAGE DEVELOPMENT
NEED 60 0 2,9098148 ,43432978
PROFDEV/NEEDS/CONTE
NT PERFORM
STANDARDS
59 1 2,37 ,889
PROFDEV/NEEDS/STUDE
NT ASSESSMENT 60 0 3,18 ,792
PROFDEV/NEEDS/KNOWL
EDGE MAIN SUBJECTS 60 0 2,38 ,783
PROFDEV/NEEDS/KNOWL
EDGE INSTRUC PRACT 60 0 3,02 ,725
PROFDEV/NEEDS/ICT
SKILLS 60 0 2,82 ,873
PROFDEV/NEEDS/SPECIA
L LEARNING NEEDS 60 0 3,20 ,971
PROFDEV/NEEDS/STUDE
NT DISCIPLINE 60 0 3,55 ,594
PROFDEV/NEEDS/SCHOO
L MANAGEMENT 59 1 2,95 ,918
PROFDEV/NEEDS/MULTIC
ULTURAL SETTING 59 1 3,03 ,928
PROFDEV/NEEDS/STUDE
NT COUNSELLING 60 0 2,57 1,015
Statistics - CDC > 0
TARGETCL/AC
TIV/ADMININST
RATIVE
TARGETCL/AC
TIV/KEEPING
ORDER
TARGETCL/AC
TIV/TEACHING
LEARNING
N Valid 157 157 157
Missing 0 0 0
Mean 7,15 9,10 83,62
Std. Deviation 4,511 6,310 8,636
90
Statistics - CDC < 0
TARGETCL/AC
TIV/ADMININST
RATIVE
TARGETCL/AC
TIV/KEEPING
ORDER
TARGETCL/AC
TIV/TEACHING
LEARNING
N Valid 48 48 48
Missing 0 0 0
Mean 8,02 18,00 73,98
Std. Deviation 4,403 8,518 11,562
91
Annex C:
Frequencies, Statistics and Tables (International Sample)
*COUNTRY ID
FOR REPORTING
(ALPHABETICAL
ORDER)* Mean N Std. Deviation
AUS - Australia 2,5953508 236 ,46830975
AUT - Austria 2,5451901 190 ,50445737
BFL - Belgium
(Flemish
Community)
2,6667372 315 ,49520306
BGR - Bulgaria 2,5610483 139 ,55060989
BRA - Brazil 2,6789627 426 ,60015342
DEU - Germany 2,8043039 253 ,42589719
DNK - Denmark 2,4435490 152 ,51938159
ESP - Spain 2,6756387 187 ,51919422
EST - Estonia 2,8142044 200 ,50706569
HUN - Hungary 2,3132756 99 ,53092319
IRL - Ireland 2,5030864 153 ,49071499
ITA - Italy 2,9952515 296 ,47579239
KOR - Korea 3,2415638 189 ,33600612
LTU - Lithuania 2,9916838 162 ,53329725
MEX - Mexico 2,4316631 225 ,72045755
MLT - Malta 2,4135642 154 ,51881916
MYS - Malaysia 3,3751870 416 ,47898648
NLD - Netherlands 2,8641204 48 ,43596666
NOR - Norway 2,7398532 193 ,44301500
POL - Poland 2,6062520 249 ,54181920
PRT - Portugal 2,5701709 130 ,45262505
SVK - Slovak
Republic 2,5265036 218 ,52082514
SVN - Slovenia 2,6684514 193 ,47691164
Total 2,7191456 5190 ,58862347
TUR - Turkey 2,4550939 367 ,63287731
92
a) Professional Development Needs
*COUNTRY ID FOR
REPORTING
(ALPHABETICAL
ORDER)*
PROFD
EV/NEE
DS/CO
NTENT
PERFO
RM
STAND
ARDS
PROFD
EV/NEE
DS/STU
DENT
ASSES
SMENT
PROFD
EV/NEE
DS/KN
OWLED
GE
MAIN
SUBJE
CTS
PROFD
EV/NEE
DS/KN
OWLED
GE
INSTRU
C
PRACT
PROFD
EV/NEE
DS/ICT
SKILLS
PROFD
EV/NEE
DS/SPE
CIAL
LEARNI
NG
NEEDS
PROFD
EV/NEE
DS/STU
DENT
DISCIP
LINE
PROFD
EV/NEE
DS/SC
HOOL
MANAG
EMENT
PROFD
EV/NEE
DS/MU
LTICUL
TURAL
SETTIN
G
PROFD
EV/NEE
DS/STU
DENT
COUNS
ELLING
AUS -
Australia
Mean 2,74 2,79 2,37 2,48 2,49 2,92 2,81 2,38 2,30 2,66
N 236 236 235 233 235 236 236 236 235 236
Std.
Deviation ,782 ,753 ,829 ,805 ,824 ,774 ,840 ,787 ,766 ,833
AUT -
Austria
Mean 2,62 2,77 2,55 2,79 2,31 2,96 3,09 1,72 2,24 2,44
N 187 190 188 188 189 190 189 188 188 189
Std.
Deviation ,823 ,908 ,938 ,857 1,006 ,875 ,892 ,937 ,908 ,871
BFL -
Belgium
(Flemish
Community)
Mean 2,74 2,90 2,88 2,86 2,41 2,69 2,89 2,26 2,36 2,67
N 315 313 314 311 312 314 314 314 314 314
Std.
Deviation ,782 ,720 ,861 ,781 ,813 ,785 ,794 ,747 ,812 ,810
BRA - Brazil Mean 2,72 2,59 2,34 2,46 2,66 3,25 2,83 2,55 2,81 2,60
N 424 422 423 420 420 420 419 419 423 421
Std.
Deviation ,861 ,922 ,905 ,885 ,992 ,930 ,905 ,928 ,924 ,917
BGR -
Bulgaria
Mean 2,87 2,70 2,51 2,57 2,58 2,65 2,72 2,16 2,34 2,47
N 133 134 134 133 134 132 133 127 130 131
Std.
Deviation ,820 ,876 1,039 ,923 ,983 ,899 ,916 ,963 ,903 ,939
DNK -
Denmark
Mean 2,60 2,64 2,17 2,36 2,65 3,06 2,62 1,71 2,13 2,47
N 151 152 149 150 151 151 151 149 151 150
Std.
Deviation ,865 ,751 ,833 ,846 ,903 ,866 ,971 ,816 ,954 ,800
EST -
Estonia
Mean 2,93 2,69 2,91 3,06 2,69 3,08 3,28 2,04 2,45 2,99
N 198 198 198 198 200 199 200 198 196 200
93
Std.
Deviation ,797 ,794 ,868 ,738 ,865 ,791 ,804 ,898 ,919 ,780
HUN -
Hungary
Mean 2,28 2,18 2,02 2,53 1,77 3,02 3,10 1,85 2,09 2,27
N 99 99 98 98 99 99 99 99 98 99
Std.
Deviation ,869 ,813 ,873 ,852 ,935 ,958 ,953 ,787 ,838 ,831
IRL - Ireland Mean 2,43 2,46 2,02 2,33 2,33 3,10 2,69 2,38 2,53 2,77
N 151 151 151 153 153 152 153 152 152 152
Std.
Deviation ,753 ,772 ,804 ,752 ,945 ,804 ,790 ,913 ,906 ,872
ITA - Italy Mean 2,88 3,08 3,01 3,18 2,94 3,24 3,24 2,44 3,09 2,83
N 291 292 291 288 290 290 290 288 289 289
Std.
Deviation ,788 ,704 ,837 ,770 ,807 ,786 ,808 ,845 ,810 ,767
KOR -
Korea
Mean 3,32 3,25 3,41 3,50 3,04 3,18 3,50 2,86 2,80 3,56
N 189 187 188 188 188 187 189 189 187 189
Std.
Deviation ,552 ,554 ,609 ,571 ,649 ,652 ,561 ,686 ,697 ,519
LTU -
Lithuania
Mean 3,24 3,10 3,27 3,34 2,91 2,95 3,24 2,31 2,47 2,94
N 158 156 157 157 159 159 156 156 154 155
Std.
Deviation ,777 ,805 ,859 ,789 ,926 ,884 ,804 ,975 ,923 ,850
MYS -
Malaysia
Mean 3,61 3,50 3,61 3,67 3,34 2,71 3,52 3,27 3,18 3,36
N 416 416 411 415 416 414 416 416 416 416
Std.
Deviation ,575 ,617 ,631 ,595 ,736 1,166 ,673 ,693 ,900 ,704
MLT - Malta Mean 2,29 2,42 1,94 2,08 2,18 2,95 2,69 2,41 2,47 2,69
N 154 154 154 152 154 154 154 152 153 154
Std.
Deviation ,806 ,798 ,909 ,759 ,980 ,858 ,866 ,909 ,851 ,821
MEX -
Mexico
Mean 2,48 2,38 2,08 2,22 2,49 2,80 2,57 2,20 2,48 2,63
N 222 224 224 225 221 224 223 222 223 225
Std.
Deviation ,978 ,990 1,062 ,978 1,007 1,046 ,988 ,997 ,981 1,005
NLD -
Netherlands
Mean 3,08 3,19 3,06 3,17 2,71 2,92 3,00 2,09 2,38 3,04
N 48 48 48 47 48 48 48 47 48 48
Std.
Deviation ,846 ,673 ,755 ,868 ,798 ,846 ,899 ,775 ,815 ,849
NOR - Mean 2,93 3,17 2,54 2,69 2,47 3,30 3,08 2,15 2,44 2,61
94
Norway N 191 193 191 190 192 193 193 190 192 193
Std.
Deviation ,633 ,680 ,708 ,721 ,837 ,656 ,759 ,872 ,817 ,791
POL -
Poland
Mean 2,78 2,63 2,57 2,83 2,58 2,66 3,00 2,04 2,13 2,82
N 241 245 245 245 245 242 248 244 244 245
Std.
Deviation ,850 ,876 1,033 ,894 ,983 1,047 ,944 ,974 ,967 ,878
PRT -
Portugal
Mean 2,62 2,61 2,18 2,60 2,04 3,17 2,78 2,67 2,61 2,44
N 130 130 130 130 130 129 129 126 130 128
Std.
Deviation ,707 ,676 ,802 ,711 ,935 ,849 ,790 ,829 ,812 ,637
SVK -
Slovak
Republic
Mean 2,52 2,52 2,62 2,64 2,35 2,90 2,90 2,12 2,23 2,47
N 217 218 212 215 217 216 216 217 216 217
Std.
Deviation ,746 ,849 ,902 ,772 ,870 ,800 ,810 ,834 ,829 ,828
SVN -
Slovenia
Mean 2,77 2,92 2,33 2,87 2,40 3,11 3,24 1,94 2,30 2,79
N 193 193 190 193 193 193 193 192 192 191
Std.
Deviation ,716 ,803 ,937 ,765 ,990 ,821 ,774 ,933 ,955 ,865
ESP - Spain Mean 2,44 2,61 1,94 2,51 2,73 3,25 3,04 2,59 2,84 2,80
N 186 185 186 186 184 186 186 186 186 186
Std.
Deviation ,824 ,795 ,910 ,846 ,947 ,761 ,777 ,927 ,809 ,784
TUR -
Turkey
Mean 2,51 2,51 2,27 2,29 2,27 2,87 2,66 2,35 2,44 2,35
N 367 364 358 363 363 361 361 359 361 362
Std.
Deviation ,908 ,883 ,979 ,926 ,994 ,974 ,950 ,971 ,967 ,924
DEU -
Germany
Mean 2,32 3,06 2,45 2,93 2,85 3,08 3,21 2,82 2,85 2,45
N 252 253 251 252 252 250 253 251 252 252
Std.
Deviation ,858 ,784 ,796 ,699 ,878 1,044 ,795 ,878 ,872 ,970
Total Mean 2,77 2,80 2,59 2,77 2,60 2,98 3,00 2,38 2,56 2,73
N 5149 5153 5126 5130 5145 5139 5149 5117 5130 5142
Std.
Deviation ,864 ,858 ,990 ,905 ,960 ,920 ,880 ,953 ,935 ,891
95
b) Teaching in the Target Class
TARGETCL/STUDENT ENROLMENT
*COUNTRY ID FOR
REPORTING
(ALPHABETICAL ORDER)* Mean Median N Std. Deviation
AUS - Australia 24,36 25,00 222 4,707
AUT - Austria 22,59 23,00 177 6,306
BFL - Belgium (Flemish
Community) 17,14 17,00 262 4,999
BGR - Bulgaria 22,27 24,00 125 5,895
BRA - Brazil 31,23 30,00 385 8,737
DEU - Germany 23,96 24,00 251 4,129
DNK - Denmark 20,51 21,00 147 3,982
ESP - Spain 22,56 23,00 168 5,786
EST - Estonia 20,08 19,00 167 7,454
HUN - Hungary 18,15 16,50 88 5,812
IRL - Ireland 21,97 23,00 140 5,026
ITA - Italy 21,01 21,00 281 4,024
KOR - Korea 36,71 37,00 189 5,614
LTU - Lithuania 17,98 17,00 130 6,614
MEX - Mexico 33,98 35,00 176 9,461
MLT - Malta 20,76 21,00 130 5,976
MYS - Malaysia 32,84 33,00 395 7,728
NLD - Netherlands 24,83 25,00 48 3,943
NOR - Norway 23,39 24,00 171 5,751
POL - Poland 19,94 20,00 228 5,605
PRT - Portugal 19,41 20,00 122 5,716
SVK - Slovak Republic 21,18 20,00 209 6,425
SVN - Slovenia 18,02 18,00 167 4,609
Total 24,55 24,00 4714 8,646
TUR - Turkey 29,22 26,00 336 9,792
96
Report
*COUNTRY ID FOR REPORTING (ALPHABETICAL
ORDER)*
TARGETCL/AC
TIV/ADMININST
RATIVE
TARGETCL/AC
TIV/KEEPING
ORDER
TARGETCL/AC
TIV/TEACHING
LEARNING
AUS - Australia Mean 7,49 16,03 76,42
N 167 167 167
Std. Deviation 4,213 8,352 9,920
AUT - Austria Mean 7,26 12,88 79,74
N 165 165 165
Std. Deviation 4,973 8,143 10,082
BFL - Belgium (Flemish
Community)
Mean 9,48 15,35 75,14
N 246 246 246
Std. Deviation 4,721 8,365 10,349
BRA - Brazil Mean 10,10 15,11 74,86
N 293 293 293
Std. Deviation 5,023 8,118 10,779
BGR - Bulgaria Mean 5,51 10,68 83,80
N 111 111 111
Std. Deviation 4,191 7,005 8,955
DNK - Denmark Mean 6,85 13,40 79,59
N 125 125 125
Std. Deviation 4,971 8,035 10,507
EST - Estonia Mean 6,33 13,32 80,13
N 165 165 165
Std. Deviation 3,894 8,925 10,642
HUN - Hungary Mean 5,46 13,10 81,44
N 84 84 84
Std. Deviation 3,445 7,902 8,628
IRL - Ireland Mean 7,39 12,56 80,10
N 135 135 135
Std. Deviation 4,258 8,542 10,680
ITA - Italy Mean 8,24 16,58 75,21
N 226 226 226
Std. Deviation 4,574 8,284 10,407
KOR - Korea Mean 6,10 14,11 79,76
N 161 161 161
Std. Deviation 4,770 7,773 10,400
97
LTU - Lithuania Mean 8,10 12,63 79,28
N 126 126 126
Std. Deviation 5,288 8,288 11,759
MYS - Malaysia Mean 9,45 15,81 74,74
N 334 334 334
Std. Deviation 5,720 8,059 10,708
MLT - Malta Mean 6,89 14,35 78,75
N 122 122 122
Std. Deviation 5,363 8,673 11,547
MEX - Mexico Mean 13,33 12,82 73,96
N 171 171 171
Std. Deviation 5,252 6,806 9,157
NLD - Netherlands Mean 9,45 17,61 72,95
N 38 38 38
Std. Deviation 4,914 7,890 10,454
NOR - Norway Mean 8,81 13,88 77,35
N 159 159 159
Std. Deviation 4,765 8,772 10,864
POL - Poland Mean 8,69 11,68 79,55
N 216 216 216
Std. Deviation 3,890 8,198 9,872
PRT - Portugal Mean 8,16 14,77 76,97
N 111 111 111
Std. Deviation 4,941 8,710 10,676
SVK - Slovak Republic Mean 7,21 13,24 79,47
N 181 181 181
Std. Deviation 4,165 7,844 9,802
SVN - Slovenia Mean 7,42 12,20 80,29
N 173 173 173
Std. Deviation 3,922 7,867 9,859
ESP - Spain Mean 7,30 15,91 76,89
N 160 160 160
Std. Deviation 4,627 8,534 10,798
TUR - Turkey Mean 7,85 13,54 78,46
N 296 296 296
Std. Deviation 4,410 7,607 10,112
DEU - Germany Mean 7,17 11,40 81,34
N 226 226 226
Std. Deviation 4,410 7,921 10,183
98
Total Mean 8,13 13,93 77,90
N 4191 4191 4191
Std. Deviation 4,937 8,252 10,616
Report
Classroom Disciplinary Climate
*COUNTRY ID FOR
REPORTING
(ALPHABETICAL ORDER)* Mean N Std. Deviation
AUS - Australia -,0169 222 ,67225
AUT - Austria ,3675 183 ,79654
BFL - Belgium (Flemish
Community) ,2042 306 ,68259
BGR - Bulgaria ,3130 131 ,59674
BRA - Brazil -,0470 410 ,58304
DEU - Germany ,3705 249 ,68468
DNK - Denmark ,0740 152 ,66664
ESP - Spain -,0802 184 ,71146
EST - Estonia ,1561 197 ,71878
HUN - Hungary -,0319 94 ,67226
IRL - Ireland ,2717 150 ,73156
ITA - Italy ,1944 288 ,67234
KOR - Korea ,2713 188 ,49416
LTU - Lithuania ,2597 155 ,58449
MEX - Mexico ,5359 216 ,53877
MLT - Malta ,0850 153 ,69548
MYS - Malaysia ,3102 415 ,60567
NLD - Netherlands ,0978 46 ,61119
NOR - Norway -,0986 180 ,81257
POL - Poland ,2714 245 ,64162
PRT - Portugal ,0801 128 ,63365
SVK - Slovak Republic ,0374 214 ,63246
SVN - Slovenia ,3075 187 ,62677
Total ,1796 5051 ,67567
TUR - Turkey ,1906 358 ,69472
