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A Research Proposal on
Teacher motivation in application of Mason’s problem solving model in teaching
secondary school mathematics
By
S.Kartigeyan A/L K.Saundarajan
MPP 141169
FACULTY OF EDUCATION
UNIVERSITI TEKNOLOGI MALAYSIA
81310 UTM SKUDAI, JOHOR, MALAYSIA
APRIL 2015
TABLE OF CONTENT
CHAPTER 1 : INTRODUCTION
1.1 Problem Background
1.2 Problem Statement
1.3 Purpose of Research
1.4 Objectives of Research
1.5 Research Questions & Hypotheses
1.6 Variables
1.7 Conceptual Framework
1.8 Significance of Research
1.9 Research Limitations
CHAPTER 2 : LITERATURE REVIEW
2.1 Motivation
2.1.1Teacher motivation
2.2 Problem solving
2.2.1Problem solving models & heuristics
2.2.2John Mason’s problem solving model
2.2.2.1 Specialisation
2.2.2.2 Generalisation
2.2.2.3 Rubric
2.2.2.4 The three phases
2.3 Problems & issues faced by teachers in
application of problem solving models
Chapter 3 : METHODOLOGY
3.1 Research design
3.1.1Rationale for research design
3.2 Population & sample
3.3 Instrument
3.3.1Validity of instrument
3.4 Data collection
3.5 Data analysis
REFERENCES
APPENDIX
INTRODUCTION
1.1 PROBLEM BACKGROUND
Mathematics is considered so far the most important branch of knowledge in the
world. . It forms the very basis of human understanding towards other disciplines of
knowledge. Similarly, mathematics serves as the backbone for all technological
inventions and advancements in the current world. As a developing country, Malaysia,
through education, need to produce as many capable mathematicians as possible in the
coming times as the global competition in education and economy has intensified.
In order to produce students with such capabilities in mathematics, the mathematical
thinking process should be nurtured among students. According to Shigeo Katagiri
( 2012), mathematical thinking is essential for making students understand the necessity
of using knowledge and skills, and to learn how to do independent learning. Thinking
mathematically is not an end in itself. It is a process by which we increase our
understanding of the world and extend our choices. Because it is a way of proceeding, it
has widespread application, not only to attacking problems which are mathematical or
scientific, but more generally ( Mason, 2010 ).
1.2 PROBLEM STATEMENT
In 2012 PISA ( Programme for International Student Assessment ), students
representing Malaysia only able to rank 52 out of 65 countries which took part in the
PISA. Furthermore,Malaysians scored an average 440 points in mathematics and 426
points in Science, below the TIMSS ( Trends in International Mathematics and
Science Studies ) average scale ( The Star,2012 ).However, Asian countries topped
the list in the ranking of the Pisa 2012 results.Shanghai, Singapore, Hong Kong,
Taiwan and Korea were the top five economies in the latest results released.Vietnam
which was ranked at the 17th gained attention as the only third world economy in the
top 20 best-performing list.A difference of 38 points on the Pisa scale was equivalent
to one year of schooling. A comparison of scores showed that students in Shanghai
were performing as though they had four or more years of schooling than 15-year-
olds in Malaysia.Malaysia was continuously ranked in the bottom third in Pisa and
Trends in International Mathematics and Science Studies (Timms). Despite having the
highest budget allocation for the Ministry of Education ( RM 251.6 billion in 2014 ),
Malaysian students still fail to perform when it comes to mathematical and science
related problem solving. Thus, the pedagogy for problem solving in Malaysian schools
becomes questionable in terms of its implementation, mastery and efficiency. An
effective problem solving model seems non-existent in Malaysian schools as
there is no marked improvement in student performance in science and
mathematics for the past 15 years.
1.3 PURPOSE OF RESEARCH
The purpose of this study is to understand the teachers motivation to apply Mason’s
problem solving model in teaching secondary school mathematics. A total of 25
secondary school mathematics teachers from Kuala Lumpur will be selected for this
study.
1.4 OBJECTIVES OF RESEARCH
( 1 ) to determine the motivation level of secondary school maths teachers to apply
Mason’s problem solving model.
( 2 ) to study the level of mastery on problem solving models among Malaysian
secondary school maths teachers.
( 3 )to devise and execute suitable strategy to provide exposure to Malaysian
secondary school maths teachers towards Mason’s problem solving model.
( 4 ) to determine the feasibility and efficiency of Mason’s problem solving model in
Malaysian mathematics curriculum
1.5 RESEARCH QUESTIONS
This Research will be guided by the following Research Questions:-
(1) What is/are the teachers opinion and subsequently, the motivation level to adopt a
model and implement them in school ?
(2) Do they follow an existing problem solving model, if any, and why ?
(3) What is the extend of reach of Mason’s problem solving model among Malaysian
secondary school mathematics teachers ?
(4) Given the proper exposure,what is their opinion and tendency to apply Mason’s
problem solving model in schools ?
(5)
1.7 CONCEPTUAL FRAMEWORK
1.8 SIGNIFICANCE OF THE RESEARCH
IMPLEMENTATION OF
MASON’S MODEL IN
SCHOOLS
TEACHERS FEEDBACK AND
MOTIVATION TOWARDS
MASONS’S MODEL
INTRODUCING MASON’S
MODEL TO SCHOOL
TEACHERS
CONCLUSION OR GENERALISATION ON FEASIBILITY
& EFFECTIVENESS OF MASON’S MODEL
The results derived from the study can be used to determine how problems solving is
being taught out in Malaysian Secondary schools. The study will provide information on
the extend of teachers knowledge about problem solving models and how they carry out
problem solving sessions in schools. Furthermore, Mason’s problem solving model can
be field tested in Malaysian schools and its benefits and limitations,if any, can be
determined from this study. Thus, the findings of this study can shed light on the poor
performance of Malaysian students in mathematics in terms of problem solving abilities.
1.9 RESEARCH LIMITATIONS
All the sample participants involved in the study will be selected from several
secondary schools in Johor. The sampling is done by considering the time and the cost
factors of the research. Thus, limiting factor with the highest impact to the research will
be the absence of probability sampling. The results of this research may suffer deviations
due to different gender, social-economic background, technological exposure and
infrastructure availability, if generalization is made to represent the student population of
Malaysia. Being a developed urban territory, the sample derived from Johor alone would
pose a challenge in representing the student population of Malaysia. However, the results
of this study can serve as a basis for future research for similar type of sample. In
addition, the results can be always improved from time to time by increasing the sample
size and applying various probability sampling techniques to further improve the
reliability of this research.
Chapter 2 : Literature Review
2.1 Motivation
Motivation can be defined as a strong reason(s) for a person’s particular behaviour or
act. Motivation is a general willingness of someone to do something. According to
Atkinson & Birch ( 1970 ), motivation is multidisciplinary in nature and not directly
observable. Maslow ( 1943 ) defines motivation as tensions arose due to a persons
physiological and psychological needs and the pursuit toward the fulfillment of the needs.
2.1.1 Teacher motivation
Teacher motivation can be defined as the preference between the two states of teachers,
which is ‘to do the job well’ or ‘to get the job done’ ( Johnson, 2000 ).Easily put, teacher
motivation outlines why an individual wants to enter teaching profession.
( Sinclair,2008 ). Teacher motivation determines the performance of a teacher in school
and it is influenced by several factors such as availability of resources, quality of working
colleagues, working environment and type of students ( Freeman and Freeman, 1994 ).
According to Butler( 2007 ), teacher motivation is based on four gouls, which are mastery
(learning and developing professional competence), ability-approach (demonstrating superior
teaching ability), ability-avoidance (avoiding demonstrating inferior teaching ability), and
work-avoidance (getting through the day with minimal effort).
2.2 Problem solving
According to Hilbert ( 1900 ), mathematics is all about seeking answer for a problem,
where all mathematicians feel a need for solving it. Thus, problems are considered the
driving force for a mathematician. As for the definition of a mathematical problem, Polya
( 1957 ) states that a problem is not something easily solved or mastered by rigorous
repetition or exercises. Schoenfeld ( 1992 ), in turn, used the term ‘non-routine’ to
describe the nature of the novelty of a mathematical problem. A problem should contain a
certain level of appropriate difficulty.“A task for which the solution method is not known
in advance” (NCTM, 2000, p. 52). According to Mayer and Wittrock, problem solving is
“cognitive processing directed at achieving a goal when no solution method is obvious to
the problem solver” (2006, p. 287). As in the words of Karl Duncer, ‘a problem arises
when a living creature has a goal but does not know how this goal is to be reached;
Whenever one cannot go from the given situation to the desired situation simply by
action, then there has to be recourse to thinking. Such thinking has the task of devising
some action, which may mediate between the existing and desired situations’ (1945, p. 1).
Problem solving is a systematic procedure in order to identify, approach and solve a
given problem.Polya (1945 & 1962) described mathematical problem solving as finding a
way to a rather difficult problem or obstacle and eventually solve the problem.Krulik and
Rudnick (1980) also define problem solving as ‘the means by which an individual uses
previously acquired knowledge, skills, and understanding to satisfy the demands of an
unfamiliar situation. The student must synthesize what he or she has learned, and apply it
to a new and different situation. (p. 4) According to Lester & Kehle ( 2003 ),
mathematical problem solving involves higher order thinking and reasoning. Schonfeld
( 1992 ) dismissed anything solved routinely as problem solving since problem solving
should be non-routine. Students must feel the element of difficulty and challenge at some
point during problem solving ( Hiebert, Carpenter, Fennema, Fuson, Wearne, Murray,
Olivier, and Human ,1997) . Francesco & Maher ( 2005 ) states that a meaningful
reasoning must occur during the process of problem solving. In addition to being non-
routine, the problem solving process must be developmentally appropriate to the students
( Lesh & Zawojewski, 2007 ). Problem solving regarded as the heart of mathematics
because the skill is not only for learning the subject but it emphasizes on developing
thinking skill method as well ( Sakorn Pimta, Sombat Tayruakham and Prasart
Nuangchalerm, 2009 ).
2.2.1 Problem solving models or heuristics
As for the subject of problem solving itself a challenging process, several ‘mental
shortcuts’ or heuristics have been proposed by prominent mathematicians and educators
to ‘ease the mental load’ in cognitive thinking during problem solving. Application of an
heuristics or a problem solving model have increased problem solving ability among
students ( Kantowski, 1977 ).
John Dewey can be regarded as one of the proponents in introducing problem solving
heuristics in early 20th century. He proposed a 5 step model popularly known as the
Dewey Sequence ( 1933) :
Step 1 : Define the problem
Step 2 : Analyze the problem
Step 3 : Determine the criteria for solution
Step 4 : Inventory several solutions
Step 5 : Evaluate the proposed solutions
The Dewey Sequence mainly utilizes reflective thinking in approaching and solving a
problem.
However, it is the Polya’s model which garnered an international fame and a global
attention towards problem solving. Polya in his book How to Solve It (p5-p17) , have
proposed a four-step problem solving heuristics as follows :
Step 1 : Understanding a problem - students understands the need of the question
and become interested in solving it
Step 2 : Devising a plan - students finds the ‘bright idea’ to be the best
possible solution for the given problem
Step 3 : Carrying out the plan - students carry out the conceived idea towards
the solution
Step 4 : Looking back - students reexamine their working to look for
errors, if any and eventually consolidate the
knowledge learned.
According to Polya, ‘Mathematical thinking is not purely “formal”; it is not concerned
only with axioms, definitions and strict proofs, but many other things belong to it:
generalising from observed cases, inductive arguments, arguments from analogy,
recognising a mathematical concept in, or extracting it from a concrete situation.The
mathematics teacher has an excellent opportunity to acquaint his students with these
highly informal thought processes… stated incompletely but concisely: let us teach
proving by all means, but let us also teach guessing’ (Polya, 1965, p. 100). Polya ( 1965 )
insisted on proposing problems which are interesting and worthwhile. Teachers are meant
to be facilitators for stimulating the students to think mathematically by providing a
‘smart guess’ for a given problem, which should be of non-routine, for the students
follow the heuristics and solve the problems themselves.
Schoenfeld (1985) developed a theoretical framework used to induce what is
called by mathematical thinking. This framework comprises four domains where any
attempt on problem solving must take into account. These are as follows:
Resources. (The relevant mathematical knowledge—intuition, facts,
algorithms, understanding—possessed by the individual.)
Heuristics. (Strategies and techniques—drawing figures, introducing
suitable notation, exploiting similar problems, reformulating—for making
progress on unfamiliar problems.)
Control. (Global decisions—planning, monitoring, metacognitive acts—
with regard to selecting and using resources and heuristics.)
Belief systems. (The mathematical worldview—conscious and
unconscious—of an individual which may determine his or her behavior.)
According to Schoenfeld ( 1985 ), having only mastered the prerequisite content
knowledge for a mathematical problem is not adequate to solve the problem. But, a a
sound knowledge in heuristics, that is the ability to devise and deploy various problem
solving techniques and strategies, are deemed far superior compared to having ample
resources ( Schoenfeld, 1985 ). Furthermore, the set of belief systems developed in
students over the years will also hinder their ability to think mathematically to solve a
given problem in a creative way.
Apart from this, Krulic and Rudnick ( 1980 ) provided a somewhat improvised
problem solving heuristics from Polya’s 4 step model, which is the Krulic-Rudnick 5 step
model :
Step 1 : Read - understanding the problem, identifying key points,
paraphrasing
Step 2 : Explore - looking for patterns, determine the concepts and principle,
attempt to make connections
Step 3 : Select a strategy - making tentative hypothesis or conclusion for
solution method
Step 4 : Solve - carrying out the selected strategy to solve the
problem
Step 5 : Review and extend - verifying the final answer and looks out
alternative methods or strategies.
Contrary to traditional beliefs in mathematics education, Krulic and Rudnick ( 1980 )
regard algorithms as inferior since they do not promote higher order thinking among
students .
2.2.2 John Mason’s Problem Solving Model
As a contemporary problem solving model, the researcher believes that Mason’s problem
solving model as a feature of stand alone properties which makes it superior compared to
other proposed model, although for beginners, the model might be challenging to
comprehend. First of all, Mason in his book Thinking Mathematically ( pix-px) have
stated that Mason’s problem solving approach make use of this following assumptions :
1. You can think mathematically
2. Mathematical thinking can be improved by practice with reflection,
3. Mathematical thinking is provoked by contradiction, tension and surprise
4. Mathematical thinking is supported by a atmosphere of questioning, challenging and
reflecting,
5. Mathematical thinking helps in understanding yourself and the world
The basic building blocks for Mason’s problem solving model stems from two
processes, which are specializing and generalizing.
2.2.2.1 Specializing
The process begins by simplifying the question, making it more specific or more special
until some progress is possible. By doing so, students will get a ‘feel’ for the question and
this paves the way for a systematic generalization hence artfully test a generalisation.
2.2.2.2 Generalisation
This process proceeds specialisation where it involves moving from a few instance to
making guesses about wide class of cases. In other words it means detecting a pattern
leading to:
-What seems likely to be true (a conjecture)
-Why it is likely to be true (a justification)
-Where it is likely to be true, that is, a more general setting of the question(another
question!).
By doing generalisation, students will be able to reflect on their specialized information
to induce a general underlying pattern to solve a problem.
2.2.2.3 Rubric
To facilitate the thinking process, Mason’s model incorporates what he calls as rubric, or
a graphical, mind map format to clearly represent the thinking process involved during a
problem solving. The model uses the following rubric words to guide the thinking flow
during problem solving :
STUCK! : Whenever you realize that you are stuck, write down STUCK!
AHA! : Whenever an idea comes to you or you think you see something, write it
down.
CHECK: Check any calculations, reasoning, specialization.
REFLECT: When you have done all that you can or wish to, take time to reflect on what
happened.
Diagram 2.2.2.3.1
2.2.2.4 The three phases of problem solving
The thought process involved during the specialisation amd generalisation processes
will stem into three phases, namely ENTRY, ATTACK and REVIEW ( refer diagram
2.2.2.1 ).
ENTRY phase is the expansion of ideas solely from the specialisation phase, where
the thinking is guided by deductive rubrics to derive specific details. Once the student is
convinced that a correct strategy has been found ( a conjecture ), the thinking process will
be directed to the next phase called Attack! through Aha! Rubric.
ATTACK phase is a combination of both specialisation and generalisation process,
where the students will be harnessing the gains from the specialisation to constantly
identify a general pattern in order to solve it. In the Attack phase, the thinking will be
guided by rubrics which are of conjecturing and justifying nature. If an attempted
ATTACK fails, the thought process will be redirected to the Entry phase through STUCK
rubric. If the mentioned attempt succeeds, then the thought process will proceed to the
final phase called REVIEW.
REVIEW phase stems fully from the generalisation process where the final answer
for the given problem is rechecked, reflected upon the whole process and extended, if
possible, to be connected with previously learned knowledge, future knowledge or new
alternatives.
2.3 Problems and issues faced by teachers in application of problem solving models
Generally, authentic problem solving is seldom practiced in classroom teaching.
Instead, teachers are more prone to present what can be obtained from the printed
resources, ‘chalk and talk’ instruction and assign similar exercises to students to be
solved ( (Smith, 1996; Stigler, Fernandez, & Yoshida, 1996; Stigler & Hiebert, 1999).
....classroom techniques involves only ‘assign-study-recite cycle’ ( Hermanovicz, 1961 ).
When analyzed, it is found that the teachers themselves are not accustomed to think
mathematically and solve problems in a systematic way as proposed by numerous
problem solving models. Prior to taking over a class, teachers had already exposed to the
traditional mathematics approach for over a decade, right from primary school till tertiary
studies. Thus, the set of beliefs towards mathematics carried by the teachers, developed
through years of conditioning, tend to heavily influence their current teaching (Lortie,
1975; Felbrich, Muller, & Blomeke, 2008 ).
Besides that, the provision of countless definitions for problem solving and various
problem solving models with obscure worked applications demotivates teachers to
employ problem solving in their teaching ( Chamberlin,2010 ). Teachers find it highly
challenging to determine which problem solving model suits their current curriculum
since there is no proven application for all the topics in the curriculum.
Although various researches have addressed the advantages as well as challenges in
problem solving, there is no adequate research to clearly define a problem solving
model’s application in line with a selected curricula.Thus, this research calls for shedding
light on practical application of a problem solving model in Malaysian secondary school
mathematical curriculum.
CHAPTER 3 : METHADOLOGY
3.1 RESEARCH DESIGN
The research employs a triangulation mixed-method design, where quantitative data
and qualitative data will be collected concurrently.The researcher have assigned equal
emphasis in both data forms.
The participants will be subjected to an one-to-one, 1 hour of introductory course on
Mason’s problem solving model and its applications in secondary school mathematics by
the researcher. The contents of the course will include carefully planned strategies,
approaches and techniques on how to effectively apply Mason’s problem solving model
in classroom mathematics teaching. It was constructed using a lesson plan and a test blue
print based on the specific objectives of the lesson plan set by the Examination Board of
Malaysia .
After the introductory course session, participants will be given a reflection template
to explain their personal experience in using the Mason’s problem solving model and an
expert-reviewed questionnaire on researchers’s inquiry about the participants’ experience
on using Mason’s problem solving model.
3.1.1 Rationale for the research design.
The researcher employs a mixed method triangulation design in order to derive the
best of both methods. From the quantitative data, researcher will be able to obtain basic
statistics on the popularity, feasibility and general perception of participants involved
towards Mason’s model. Thus, an informal generalization could be made on the grounds
of Mason’s model preference among Malaysian school teachers.
On the other hand, the qualitative data will help the researcher to further explore in
depth on the general pattern conjectured from the quantitative data. The reasons, factors
and personal experience over the preference or the non-preference towards Mason’s
model can be studied before combining both data to arrive at conclusion.
3.2 POPULATION AND SAMPLE
The population of the research will be Malaysian secondary school mathematics teachers
from Johor. Thus, the research uses purposive sampling where l0 teachers who have
taught additional mathematics or mathematics subject for at least 4 years at 15 different
secondary schools located in Johor. The participants selected are of teachers with a
minimum 5 years of teaching experience and the sample ranges from different gender,
ethnicity and working experience to further increase randomization of the sample.
3.3 INSTRUMENT
For the quantitative data, the participants will be administered a questionnaire with 8
items, reviewed and approved by a panel of field experts prior to administration.
As for the qualitative data, the reflections of participants and the visual data ( video-
recording of the interview ) will be used.
Since all the instruments were made by the researcher, the contents were trial-tested
using a group of 10 teachers from SMK Simpang Renggam, Kluang, a subset of the
population not part of the research.
3.3.1 Validity of instrument
To ascertain the validity of the instruments, face validity and content appropriateness will
be judged by the panel of field experts.
3.4 DATA COLLECTION
After attending the introductory course on Mason’s problem solving model,the
sample will be given the following items :
i. Reflection template ( refer appendix )
ii. Questionnaire ( refer appendix )
All participants will be instructed to video-record a lesson employing Mason’s
model in their respective classroom sessions. After the lesson, the participants will
complete the reflection and the questionnaire to be sent ,together with the lesson video ,to
the researcher for analysis.
3.5 DATA ANALYSIS
All the data will be sorted and analyzed in aspects of gender and years of teaching
experience. The data from the questionnaire and reflection will be analyzed for the
following objectives :
a) To recognize the similarity or uniformity between the sample in planning the
lesson
b) The similarity in perception and opinion between the participants on application
of Mason’s problem solving model.
The video-recordings of the lessons carry out will be analyzed and converted to text
form and compared with the participants’ lesson plan to test the correlation as well as to
gauge the confidence and motivation level of the participants. Finally, the questionnaire
administered will be analyzed using SPSS ANOVA .
References
Hiebert, J., Carpenter, T. P., Fennema, E., Fuson, K., Wearne, D., Murray, H., Olivier,
A., & Human, P. (1997). Making sense: Teaching and learning mathematics with
understanding. Portsmouth, NH: Heinemann.
Lesh, R., Zawojewski, J, & Carmona, L. (2003). What mathematical abilities are needed
for success beyond school in a technology-based age of information? In R. Lesh,
& H. Doerr (Eds.), Beyond constructivism: Models and modeling perspectives on
mathematics problem solving, learning, and teaching (pp. 205-221). Mahwah, NJ:
Lawrence Erlbaum Associates.
Lesh, R., & Zawojewski, J. (2007). Problem-solving and modeling. In F. Lester (Ed.),
Second handbook of research on mathematics teaching and learning (pp. 763-
804). Reston, VA: NCTM.
Lester, F. K., & Kehle, P. E. (2003). From problem-solving to modeling: The evolution
of thinking about research on complex mathematical activity. In R. Lesh, & H.
Doerr, (Eds.), Beyond constructivism: Models and modeling perspectives on
mathematics problem solving, learning, and teaching (pp. 501-518). Mahwah, NJ:
Lawrence Erlbaum Associates.
Piaget, J., & Inhelder, B. (1975). The origin of the idea of chance in children. London:
Routledgate & Kegan Paul. .
Resnick & Ford, 1981). The psychology of mathematics instruction. Hillsdale, NJ:
Lawrence Erlbaum Associates.
Schoenfeld, A. H. (1985). Mathematical problem solving. New York: Academic Press.
Schoenfeld, A. H. (1992). Learning to think mathematically: Problem solving,
metacognition, and sense making in mathematics. In D. Grouws (Ed.), Handbook
of research on mathematics teaching and learning (pp. 334-370). New York:
McMillan.
Dewey, J. (1933). How we think: A restatement of the relation of reflective thinking to the
educative process. Boston, MA: Heath.
National Commission on Excellence in Education. (1983). A nation at risk: The
imperative for educational reform. Washington, DC: U.S. Government Printing
Office.
Hilbert, D. (1900). Mathematical problems. Presentation at the second International
Congress of Mathematicians, Paris.
Kantowski, M. G. (1977). Processes involved in mathematical problem solving. Journal
for Research in Mathematics Education, 8, 163-180.
National Council of Teachers of Mathematics. (1980). An agenda for action:
Recommendations for school mathematics of the 1980s. Reston, VA: Author.
Polya, G. (1957). How to solve it (2nd ed.). Princeton, NJ: Princeton University Press.
Mason,J. ( 2010 ). Thinking mathematically (2nd ed. ). Pearson Education Limited,
Harlow.
APPENDIX
Questionnaire
Objective:
1. To find out the extend of application of Mason’s Problem Solving Model
among Malaysian mathematics teachers.
2. To discuss the results from (1) and give justifications.
1. Do you use any problem solving technique or method in mathematics ?
Yes, state ___________________________________
No, why ? ___________________________________
2. Have you heard about Mason’s problem solving Model before the introductory
course?
Yes No
3. Will you apply Mason’s problem solving model in your classroom teaching ?
Yes, then why? ._________________________________________
No, then why ?__________________________________________
4. If the answer in ( 3 ) is yes, then how frequent you will apply Mason’s model ?
Always Sometimes Never
5. If the answer in (4) is Never, then what method that you use?
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
6. Do you think Mason’s Model is effective in helping students to understand
problem solving?
Yes, then why?____________________________________________
No, then why ?_____________________________________________
7. Do you think that Mason’s Model is practically feasible at schools ?
Yes, then why? _______________________________________
No, then why? ____________________________________________
8. Will you suggest this method to others?
Yes, then why? ___________________________________________
No, then why? ___________________________________________
Reflection Template for lesson using Mason’s problem solving model.
By: ( Your Name goes here )
Student Learning Outcome Area: (This is where you name the outcome area in which you
examined your experience: civic knowledge, civic skills, civic values, civic motivation)
________________________________________________________________________
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I learned that …
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I learned this when …
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This learning matters …
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In light of this learning …
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