African Journal of Pure and Applied Science Education Volume 18, Number 1, pp 1 – 20, July 2020 www.ajopase.com; [email protected] ISSN 11187670
Fasuyi, O. A AJOPASE, Vol. 18, No. 1, July 2020
EFFECTS OF ENHANCED INQUIRY AND INQUIRY INSTRUCTIONAL STRATEGIES ON STUDENTS’ ENGAGEMENT IN SENIOR SECONDARY SCHOOL BIOLOGY.
Fasuyi Oluwaseun Abosede
Department of Science and Technology, University of Lagos, Akoka Lagos State. [email protected]
Abstract
One of the objectives of teaching Biology is to be able to apply biological principles in everyday matters that affect personal, social, environmental, community health and economic problems. In order to achieve this, engagement of students in biology classes is expedient. To this end, this study examined the effect of enhanced inquiry and inquiry strategies on students’ cognitive, emotional and behavioural engagements in Biology classes. The study adopted the quasi experimental pre-test, post-test control group research design involving a total of 232 students (137 males and 95 females). The instruments used for data collection were students’ mental ability test and classroom engagement inventory. Inferential statistics employed for data analysis is multivariate analysis of covariance. Analysis of data revealed that there is significant effect of enhanced inquiry instructional strategy on students’ cognitive and behavioural engagement only while gender had no significant effect on students’ cognitive, behavioural and emotional engagement. Mental ability on the other hand had no significant effect on emotional engagement but had a significant effect on cognitive and behavioural engagement. Recommendations included that teachers should embrace enhanced inquiry instructional strategy.
Background to the study
Biology, a field in science originates from the Greek words ‘bio’ meaning life and ‘logy’ meaning study of
Ekwu (2012) defined biology as a natural science which deals with the study of living organisms. Biology
is a natural science concerned with the study of life and living organism, including their structure, function,
growth, evolution, distribution and taxonomy (Aquaten, 2004). Biologists study the structure, function,
growth, origin, evolution and distribution of living organisms (Bagley, 2014). The inclusion of biology in
the secondary school curriculum serves as foundation for future career as well as acquiring additional
knowledge and specialization in any branch of pure and applied biology. Teaching is expedient since
curriculum has been developed. The major aim of teaching biology in schools is to facilitate the students’
acquisition of science process skills and to promote the understanding of the concept being taught with a
view of applying the knowledge of such understanding to real life situations. There are so many methods
that have been used in teaching biology. Among these different kinds of methodologies, inquiry method
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has an important place. It is well recognized that the inquiry-based learning approach is a useful pedagogy
for realizing learner-centered learning (Marshall, Smart, & Horton, 2010). The inquiry-based learning
process helps learners to develop inquiry skills, which are an important type of 21st century skill. The 5Es
(Engage, explore explain, elaborate and evaluate) learning model has also been found to be very effective
in students learning. However, there is the need to research on ways different methods could be
combined in order to enhance students’ engagement in classes. It is as a result of the quest that this study
has been undertaken in order to examine the effect of integrating 5Es model into inquiry method on
students’ engagement in biology class.
Engagement is a dependent variable in this study and will be considered. It refers to the way students
feel, think and behave in the classroom. Engagement has dimensions namely emotional, behavioural and
cognitive dimensions. Students can demonstrate either high behavioural or low behavioural engagement.
High behavioural engagement involves adhering to the rules and classroom conduct; showing persistent
effort in tasks completion while low behavioural engagement involves skipping class or being tardy for
class, disruptive behaviour in class and not trying hard to pay attention or complete tasks.
Emotional engagement involves showing involvement, commitment and feeling connected to a particular
class or teacher, feeling anxious, happy, sad or anger toward a teacher a class or school in general.
Cognitive engagement ranges from being, eager and thoroughly intrinsically motivated to learn to being
bored and unaffected by the curriculum. This may be demonstrated by actively participating ,asking and
answering questions on a consistent basis or refusing to participate or offering unenthused answers and
little motivation to work on and learn from assignment (Fredricks, Blumenfeld & Paris, 2004).
Statement of the Problem
One of the objectives of teaching Biology is to be able to apply biological principles in everyday matters
that affect personal, social, environmental, community health and economic problems. Teaching done in
most secondary schools is through lecture method whereby teachers dominate the class and students act
as passive learners only. This method allows for rote learning and learning for the sake of writing
examination only and not for application of knowledge. Students’ engagement on the other hand shows
that learning is influenced by how an individual participates in educationally purposeful activities. Also, it
is concerned with the extent to which students are engaging in a range of educational activities that
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Fasuyi, O. A AJOPASE, Vol. 18, No. 1, July 2020
research has shown as likely to lead to high quality learning. A student who is not engaged properly in
school/class may not be able to offer anything to the community at large.
It is therefore expedient to find out how different instructional approaches could determine students
cognitive, behavioural and emotional engagement in Biology classes. Therefore, this study was designed
to examine the effect of three instructional approaches on students’ cognitive, behavioural and emotional
engagement in Biology classes.
Purpose of the Study
The main purpose of this study was to examine the effects of enhanced inquiry and inquiry instructional
strategies on students’ behavioural, emotional and cognitive engagement in Biology.
Research Hypotheses
The following hypotheses were tested at 0.05 level of significance.
Ho1: There is no significant main effect of treatment (inquiry based instructional strategy, 5E, enhanced
inquiry learning strategies and lecture method) on students’ retrieval practice, engagement and
achievement in Biology.
Ho2: There is no significant main effect of gender on students’ retrieval practice, engagement and
achievement in Biology.
Ho3: There is no significant main effect of mental ability on students’ retrieval practice, engagement
and achievement in Biology.
Significance of the Study
The study would be useful to biology students, teachers, policy makers and curriculum developers.
Biology students might find the study useful because it would equip them with the proficiency that is
needed for practical application of knowledge. Also, it could enhance the development of their intellect
thereby making them more knowledgeable. Furthermore, it makes them not to be dogmatic about their
learning process. They explore more and will be actively involved in their learning process. In addition,
teachers may also benefit from this study in that it could help them in developing instructional plan that
put the needs of the students into consideration through the use of personal journal, a teacher might
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Fasuyi, O. A AJOPASE, Vol. 18, No. 1, July 2020
detect the students who are not coping with their studies. Also, it may allow them to discover their roles
in classes knowing that they are facilitators and should not be seen as the sole disseminators of
knowledge. It could also help biology teachers in that they may use the results obtained from this study
to decide on the activities that will be carried out in their classes in order to avoid disengagement of
student which could create a difficult/complex situation for teachers to navigate when the objective is
learning for all the students in the class.
Scope of the Study
This study was targeted at senior secondary school students in Lagos State. The study focused on Senior
Secondary School 2 Biology Students’ behavioural, emotional and cognitive engagement. They were
exposed to treatment on the following biology topics: digestion, transport system and circulatory system
Review of related literature
Theoretical framework
This study is based on engagement theory which explains that engagement in school is necessary for
deeper understanding and learning in school and correlates engagement with better outcomes on
assessments (Conner & Pope, 2013). Engagement theory is also related to motivation as students may be
intrinsically or extrinsically motivated. The theory of engagement is also based on the idea that when
students find lessons meaningful and have a high level of interest in the tasks they learn more effectively.
Tasks here could be related to the use of personal journals and class project which could create interest
in learners and as interest is being created students tend to learn more effectively. Likewise, group
discussion is also related to this as students are involved in discussion they tend to defend their ideas
thereby creating curiosity in them, motivation to learn then occurs therefore they tend to be engaged
during classes.
Conceptual framework.
Enhanced Inquiry
Gender
Cognitive engagement
Inquiry Behavioural engagement
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Lecture method Mental Ability
Emotional engagement
Overview of students’ engagement.
Student engagement can be defined as involvement in educationally effective practices both in and out
of the classroom which brings about a range of measurable outcomes. (Kuh, Buckley, Bridges, Hayek,
2007)
Coates (2007) describes engagement as a broad construct intended to encompass salient academic as
well as certain non-academic aspects of the student experience comprising the active and collaborative
learning, involvement in challenging academic activities and in enriching educational experiences.
Kuh (2009) explained that students gained more from their studies and other aspects of the college
experience when they devoted more time and energy to certain tasks that required more effort than
others – studying, interacting with their peers and teachers about substantive matters, applying their
learning to concrete situations and tasks in different contexts and so forth.
In a study, by Crumpton and Gregory (2011), they examined how the perception of academic relativity
contributes to students’ intrinsic motivation and their engagement in science. They discovered that there
was a correlation (r = 0.53) between students who were more intrinsically motivated and their
engagement in school. In essence, the research showed that low achieving students were likely to be more
engaged in the classroom and thus intrinsically motivated when they found the material relevant to their
lives. Shumow, Zaleski & Schmidt (2013) presented three studies conducted simultaneously in three
science classrooms. The researchers looked into the perception of how successful laboratory experiments
were at the teaching content. They found that students reported less challenge and concentration during
laboratory activities than during non-laboratory activities and higher enjoyment interest in laboratory
activities.
Conner and Popi (2013) conducted a study and found that even at high –achieving schools where students
overwhelmingly earn high marks; there was a chronic problem with a lack of engagement in the
curriculum. Furthermore, they found that the absence of cognitive and affective engagement results in
higher rate of maladaptive behaviour. They also found that while fully engaged students reported high
levels of teacher support, this was not the case with reluctantly engaged students. They therefore
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suggested that teachers should try to foster more teacher-student relationships which can additionally
help the student become more engaged in the classroom.
Furthermore, a research carried out by Green, Martin & Liem (2012) showed that both academic
motivation and self-concept positively predicted attitudes toward school. They also found that both class
participation and homework completion correlated with higher test scores, absenteeism negatively
predicted test performance
Research Design
The research design for this study was the pretest, posttest and control group, quasi experimental design.
It is diagrammatically represented below.
E1= O1 X1 O2
E2 = O3 X2 O4
C= O5 X3O6
Where E1 = 1st Experimental group (use of enhanced inquiry instructional strategy)
E2 = 2nd Experimental group (use of inquiry instructional strategy)
C = Control group (use of traditional/ lecture method)
X1 = 1st treatment
X2 = 2nd treatment
X4= No treatment for the control group
O1 O3O5= Pretest
O2 O4 O6= Post test
The study adopted the 3x3x2 factorial design because there are three factors involved in this study and
are operating at different levels. The three factors are instructional strategies, gender, and mental ability.
Variables of the Study
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The independent variable for the quasi experimental design is treatment/ instructional strategy operating
at 3 levels. – Enhanced inquiry, inquiry instructional strategy and lecture method.
Gender at 2 levels: male and female.
Dependent variable is engagement (at 3 dimensions namely cognitive, emotional and behavioral)
Area of Study
Area of study included all the Senior Secondary Schools in Lagos State.
Population of the Study
All biology students that are in SS2 in the Senior Secondary Schools in Lagos State are the target
population. The study specifically involved all SS II Biology Students both male and female in four schools.
The three schools that were selected are co-educational schools because gender effect was investigated
in this study.
Sample and Sampling Technique
Multi stage sampling technique was used. For this study, two stages of multistage sampling technique
were used which are random and stratified sampling techniques. Three schools were therefore selected
for the study. Intact classes in these schools were used for all the streams.
Research Instruments
The instruments that were used for data collection:
(1) Classroom Engagement Inventory (CEI)
(2) Students Mental ability Test (SMAT)
Validity and Reliability of SMAT
Experts in the field, English teachers carried out face and content validation.
Its reliability was carried out using Guttmann Split half method. Its reliability coefficient was 0.70.
Validity and Reliability of CEI
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The validity of the CEI was examined by correlation factor scores from five-factor confirmatory factory
analysis model with variables that research and theory predict would be linked to classroom engagement.
The reliability coefficient for the three dimensions of engagement namely behavioural, cognitive and
emotional are 0.78, 0.76 and 0.74 respectively.
Data Collection
The schools were visited for familiarization. Permission to conduct the study was obtained from the
principal of the school also the consent of the teachers was sought. The use of treatment was
implemented over a period of 8 weeks for SS 2 Biology Students in the treatment groups. During class,
the students used their personal science journal; they were also involved in group discussion. The students
also observed the pictures given to them during their classes. Prior to the intervention, the students were
given a student’s mental ability test to determine if there will be an influence of students’ mental ability
on their engagement dimensions. Classroom engagement inventory was also given to each student after
the intervention period to determine the effect of each strategy on their engagement in class. The data
collected using these instruments was therefore analyzed.
Data Analysis
Inferential analysis was used. The descriptive data was analyzed using means, tables and charts. The
inferential statistics tool was MANCOVA precisely for testing the hypotheses which was rejected at a
probability value less than or equal to 0.05 (5% alpha level). Pairwise comparison Post-hoc test was also
used.
Analysis of Research Hypothesis
The following hypotheses guiding this study are tested:
Research Hypothesis 1: There is no significant main effect of treatment (enhanced inquiry instructional
strategy, inquiry instructional strategy and lecture method) on students’ engagement (behavioral,
cognitive and emotional)
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Table 1a: Summary of Multivariate Analysis of Covariance (MANCOVA) of Teaching Methods
(Treatment) of Students on Engagements
Source Dependent
Variable
Type III Sum of
Squares
Df Mean
Square
F Sig. Partial Eta Squared
Corrected
Model
PostEmotional 3.642 7 .520 1.305 .249 .041
PostCognitive 50.325 7 7.189 12.530 .000 .294
PostBehaviour 11.675 7 1.668 5.274 .000 .149
Intercept PostEmotional 19.196 1 19.196 48.134 .000 .186
PostCognitive 84.931 1 84.931 148.029 .000 .412
PostBehaviour 34.512 1 34.512 109.125 .000 .341
PreEmotional PostEmotional 1.905 1 1.905 4.778 .030 .022
PostCognitive .223 1 .223 .389 .533 .002
PostBehaviour .155 1 .155 .491 .484 .002
PreCognitive PostEmotional .660 1 .660 1.654 .200 .008
PostCognitive .505 1 .505 .881 .349 .004
PostBehaviour .058 1 .058 .182 .670 .001
PreBehaviour PostEmotional .001 1 .001 .001 .970 .000
PostCognitive .336 1 .336 .586 .445 .003
PostBehaviour .022 1 .022 .070 .791 .000
PostCognitive .033 1 .033 .058 .810 .000
PostBehaviour .171 1 .171 .540 .463 .003
Treatment PostEmotional .966 3 .322 .807 .491 .011
PostCognitive 40.634 3 13.545 23.607 .000* .251
PostBehaviour 8.309 3 2.770 8.758 .000* .111
Error PostEmotional 84.148 211 .399
PostCognitive 121.060 211 .574
PostBehaviour 66.732 211 .316
Total PostEmotional 2792.003 219
PostCognitive 8568.926 219
PostBehaviour 4461.826 219
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Corrected Total PostEmotional 87.790 218
PostCognitive 171.385 218
PostBehaviour 78.407 218
* Main effect is significant at 5% level.
The test for significant main effect of treatment on students’ engagements and in Biology is determined
using multivariate analysis of covariance (MANCOVA).The result reveals a significant main effect of
treatment on students’ cognitive engagement, behaviour in Biology at F-value = 23.607 (p<0.05), 8.758
(p<0.05) respectively. Therefore, the hypothesis is rejected. Hence, there is significant main effect of
treatment on students’ engagement (cognitive and behaviour) in Biology. But treatment has no significant
main effect on students’ emotional engagement at F-value = 0.807. The most significant treatment effect
is determined using parameter estimation.
Table 1b: Parameter Estimates of MANCOVA for Engagements
Dependent Variable Parameter B Std. Error t Sig. 95% Confidence Interval Partial Eta Squared
Lower Bound Upper Bound
PostEmotional Intercept 3.177 .435 7.302 .000 2.319 4.035 .202
PreEmotional .185 .085 2.186 .030 .018 .352 .022
PreCognitive -.082 .064 -1.286 .200 -.208 .044 .008
PreBehaviour .003 .078 .038 .970 -.150 .156 .000
[Treatment=1] -.112 .134 -.834 .405 -.377 .153 .003
[Treatment=2] .008 .139 .061 .951 -.265 .282 .000
[Treatment=3] 0a . . . . . .
PostCognitive Intercept 5.832 .522 11.176 .000 4.804 6.861 .372
PreEmotional .063 .102 .624 .533 -.137 .264 .002
PreCognitive -.072 .077 -.938 .349 -.223 .079 .004
PreBehaviour -.071 .093 -.765 .445 -.255 .112 .003
[Treatment=1] 1.096 .161 6.798 .000* .778 1.414 .180
[Treatment=2] 1.311 .166 7.891 .000* .983 1.639 .228
[Treatment=3] 0a . . . . . .
PostBehaviour Intercept 3.869 .387 9.987 .000 3.106 4.633 .321
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PreEmotional .053 .076 .701 .484 -.096 .202 .002
PreCognitive -.024 .057 -.427 .670 -.136 .088 .001
PreBehaviour .018 .069 .265 .791 -.118 .155 .000
[Treatment=1] .496 .115 4.327 .000* .270 .723 .081
[Treatment=2] .446 .120 3.728 .000* .210 .682 .062
[Treatment=3] 0a . . . . . .
a. This parameter is set to zero because it is the reference.
The parameter estimated results reveal for cognitive engagement that Treatment 2 (enhanced inquiry)
has the most significant main effect on students’ cognitive engagement at t = 7.891 (p<0.05), followed by
Treatment 1 (Inquiry) at t = 6.798 (p<0.05) Further, enhanced inquiry, inquiry methods are 0.228, 0.180
times more likely to influence cognitive engagement than lecture method (control), respectively. Also, a
unit increase in enhanced inquiry, inquiry will increase students’ cognitive engagement by 1.311, 1.096
respectively. For behavioural engagement; enhanced inquiry has the most significant main effect on
students’ behaviour at t = 4.723 (p<0.05), followed by inquiry at t = 3.728 (p<0.05). Further, enhanced
inquiry treatment method, and inquiry are 0.096, and 0.062 times more likely to affect behavioural
engagement than lecture method (control) respectively. Also, a unit increase in enhanced inquiry, and
inquiry will increase students’ behaviour by 0.583 and 0.446 respectively.
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Research Hypothesis 2: There is no significant main effect of gender on students’ engagement in
Biology.
Table 2: Summary of Multivariate Analysis of Covariance (MANCOVA) of Gender of Students
on Engagements
Source Dependent
Variable
Type III Sum of
Squares
Df Mean
Square
F Sig. Partial Eta Squared
Corrected
Model
Post Emotional 3.911a 5 .782 1.982 .083 .044
Post Cognitive 7.002b 5 1.400 1.856 .103 .042
Post Behaviour 1.899c 5 .380 1.062 .383 .024
Intercept Post Emotional 34.471 1 34.471 87.341 .000 .291
Post Cognitive 63.610 1 63.610 84.298 .000 .284
Post Behaviour 33.158 1 33.158 92.695 .000 .303
PreEmotional Post Emotional .328 1 .328 .832 .363 .004
Post Cognitive .017 1 .017 .023 .879 .000
Post Behaviour .104 1 .104 .290 .591 .001
PreCognitive Post Emotional 1.099 1 1.099 2.784 .097 .013
Post Cognitive 1.799 1 1.799 2.384 .124 .011
Post Behaviour .139 1 .139 .389 .533 .002
PreBehaviour Post Emotional .002 1 .002 .004 .947 .000
Post Cognitive 1.035 1 1.035 1.372 .243 .006
Post Behaviour .023 1 .023 .063 .801 .000
Gender Post Emotional .006 1 .006 .015 .904 .000
Post Cognitive .038 1 .038 .051 .822 .000
Post Behaviour .177 1 .177 .493 .483 .002
Error Post Emotional 84.065 213 .395
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Post Cognitive 160.728 213 .755
Post Behaviour 76.193 213 .358
Total Post Emotional 2773.807 219
Post Cognitive 8569.854 219
Post Behaviour 4457.128 219
Corrected Total Post Emotional 87.976 218
Post Cognitive 167.730 218
Post Behaviour 78.092 218
The test for significant main effect of gender on students’ engagements in Biology is determined using
multivariate analysis of covariance (MANCOVA).The summary of MANCOVA results indicated that gender
had no significant main effect on students’ emotional engagement, cognitive engagement, behaviour in
Biology concepts at F-value = 0.015, 0.051, 0.493 respectively. Therefore, the hypothesis is not rejected.
Hence, there is no significant main effect of gender on students’ engagement in Biology. Consequently,
there is no gender preference on students’ engagement (emotional, cognitive and behavior) in Biology
Research Hypothesis 3: There is no significant main effect of mental ability on students’ engagement in
Biology.
Table 3a: Summary of Multivariate Analysis of Covariance (MANCOVA) of Mental Ability of
Students on Engagements
Source Dependent
Variable
Type III Sum of
Squares
Df Mean
Square
F Sig. Partial Eta Squared
Corrected Model Post Emotional 3.915a 6 .652 1.646 .136 .044
Post Cognitive 9.265b 6 1.544 2.066 .059 .055
Post Behaviour 2.992c 6 .499 1.408 .213 .038
Intercept Post Emotional 34.043 1 34.043 85.855 .000 .288
Post Cognitive 57.828 1 57.828 77.365 .000 .267
Post Behaviour 29.399 1 29.399 82.991 .000 .281
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PreEmotional Post Emotional .329 1 .329 .829 .364 .004
Post Cognitive .018 1 .018 .024 .877 .000
Post Behaviour .004 1 .004 .012 .913 .000
PreCognitive Post Emotional 1.169 1 1.169 2.947 .087 .014
Post Cognitive 2.443 1 2.443 3.268 .072 .015
Post Behaviour .409 1 .409 1.155 .284 .005
PreBehaviour Post Emotional .003 1 .003 .009 .926 .000
Post Cognitive .570 1 .570 .762 .384 .004
Post Behaviour .000 1 .000 .001 .976 .000
PreAchievement Post Emotional 2.252 1 2.252 5.680 .018 .026
Post Cognitive 3.740 1 3.740 5.004 .026 .023
Post Behaviour 1.247 1 1.247 3.519 .062 .016
Mentalability Post Emotional .009 2 .005 .012 .988 .000
Post Cognitive 2.301 2 1.151 4.539 .017* .014
Post Behaviour 1.269 2 .635 4.792 .009* .017
Error Post Emotional 84.061 212 .397
Post Cognitive 158.465 212 .747
Post Behaviour 75.100 212 .354
Total Post Emotional 2773.807 219
Post Cognitive 8569.854 219
Post Behaviour 4457.128 219
Corrected Total Post Emotional 87.976 218
Post Cognitive 167.730 218
Post Behaviour 78.092 218
* Main effect is significant at 5% level.
The test for significant main effect of mental ability on students’ engagements in Biology is determined
using multivariate analysis of covariance (MANCOVA).The summary of MANCOVA results indicated that
mental ability had no significant main effect on students’ emotional engagement in Biology concepts at
F-value = 0.012. Therefore, the hypothesis is not rejected. Hence, there is no significant main effect of
mental ability on students’ emotional engagement in Biology. However, mental ability had significant
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main effects on students’ cognitive engagement, behaviour in Biology classes at F-value = 4.539 (p<0.05),
4.792 (p<0.05) a respectively. Hence, the hypothesis is rejected. Therefore, there are significant
differences in cognitive engagement, behavior based on mental ability of the students. Invariably,
students with high mental ability are 0.014 (1.4%), 0.017 (1.7%) times more likely to have higher cognitive
engagement, behaviour in biology classes, respectively. Further analysis is carried out using parameter
estimates.
Table 3b: Parameter Estimates of MANCOVA for Engagement
Dependent Variable Parameter B Std. Error T Sig. 95% Confidence Interval Partial Eta Squared
Lower Bound Upper Bound
Post Emotional Intercept 4.028 .467 8.619 .000 3.107 4.949 .259
PreEmotional -.079 .087 -.911 .364 -.250 .092 .004
PreCognitive -.104 .060 -1.717 .087 -.223 .015 .014
PreBehaviour .007 .077 .093 .926 -.145 .160 .000
[Mentalability=1] .023 .160 .143 .887 -.293 .339 .000
[Mentalability=2] .023 .152 .151 .880 -.276 .322 .000
[Mentalability=3] 0a . . . . . .
Post Cognitive Intercept 5.060 .642 7.886 .000 3.795 6.325 .227
PreEmotional -.018 .119 -.154 .877 -.254 .217 .000
PreCognitive .150 .083 1.808 .072 -.014 .314 .015
PreBehaviour -.093 .106 -.873 .384 -.302 .117 .004
[Mentalability=1] -.270 .220 -1.226 .222 -.164 .703 .007
[Mentalability=2] -.359 .208 -1.723 .046 -.052 .769 .014
[Mentalability=3] 0a . . . . . .
Post Behaviour Intercept 3.592 .442 8.131 .000 2.721 4.462 .238
PreEmotional .009 .082 .109 .913 -.153 .171 .000
PreCognitive .061 .057 1.075 .284 -.051 .174 .005
PreBehaviour .002 .073 .030 .976 -.142 .146 .000
[Mentalability=1] -.226 .151 -1.493 .137 -.072 .524 .010
[Mentalability=2] -.271 .143 -1.890 .040 -.012 .553 .017
[Mentalability=3] 0a . . . . . .
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a. This parameter is set to zero because it is the reference.
The results reveal that students’ with low and average mental ability have negative effect on cognitive
engagement, behavior engagement at t = -1.226 and -1.723(p<0.05), t = -1.493 and -1.890 (p<0.05),
respectively. Therefore, students’ with high mental ability have the most significant main effect on
cognitive engagement, behaviour engagement since a unit increase in low and average mental ability will
decrease students’ cognitive and behavior engagement by -0.270 and -0.359,-0.226 and -0.271,
respectively. The results are further supported using pairwise comparison of main effects.
Table 3c: Pairwise Comparisons of MANCOVA for Engagements and Achievement
Dependent
Variable
(I) Mental
Ability
(J) Mental
Ability
Mean Difference
(I-J)
Std.
Error
Sig. 95% Confidence Interval for
Difference
Lower Bound Upper Bound
Post Emotional Low Medium -5.256E-5 .093 1.000 -.184 .184
Low High .023 .160 .887 -.293 .339
Medium High .023 .152 .880 -.276 .322
Post Cognitive Low Medium -.089 .128 .488 -.342 .164
Low High -.270* .220 .222 -.164 .703
Medium High -.359* .208 .086 -.052 .769
Post Behaviour Low Medium -.045 .088 .612 -.219 .129
Low High -.226* .151 .137 -.072 .524
Medium High -.271* .143 .060 -.012 .553
*. The mean difference is significant at the .05 level. Based on estimated marginal means.
African Journal of Pure and Applied Science Education Volume 18, Number 1, pp 1 – 20, July 2020 www.ajopase.com; [email protected] ISSN 11187670
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Multiple comparisons: Least Significant Difference.
The pairwise comparison results indicate that students’ with high mental ability have the most cognitive
and behaviour engagements since there is significance mean difference compare to students’ with either
low or average mental ability.
Discussion of findings
Effect of Treatment on Students Engagement (Cognitive, Behavioural and Emotional)
In the data analysis, it was shown that there was significant effect of treatment on students’ cognitive and
behavioural engagement while there was no significant effect of treatment on students’ emotional
engagement. This is in consonance with the findings of Smallhorn et al (2015) who found that inquiry-
based learning has great impact on student’s engagement (cognitive and behavioural) in that students
showed high level of satisfaction which indicates their behavior and critical thinking skills which indicates
cognitive engagement was developed.
Kennedy et al. (2018) in their research found that inquiry method allows students to be more engaged,
focused and on task, discover, draw conclusions and report their findings, reasoning and problem-solving
abilities indicating the positive effect of inquiry on students cognitive and behavioural engagement.
Wheatley (2018) investigated effect of inquiry based learning on students’ engagement and found that
there is an increase in scores on content questions indicating a positive impact on students’ cognitive
engagement. It was also found that there was a positive shift in students strongly agreeing with being
more on task, enjoying the lesson and becoming more curious. Being more on task points to behavioural
engagement while enjoying the lesson becoming more curious point to emotional engagement. The
findings support the findings of this research. However, the present study does not find any effect of
inquiry on students’ emotional engagement thereby negating the result in the aspect of emotional
engagement.
Effect of Gender on Students Engagement in Biology
Table 4.72a showed the effect of gender on students’ engagement in Biology. It was found that gender
had no significant effect on students’ emotional cognitive and behavioural engagement. This result is in
African Journal of Pure and Applied Science Education Volume 18, Number 1, pp 1 – 20, July 2020 www.ajopase.com; [email protected] ISSN 11187670
Fasuyi, O. A AJOPASE, Vol. 18, No. 1, July 2020
agreement with the work of Kulitu (2014) who found that there was no statistically significant difference
between male and female students in academic engagement. However, it disagrees with the study of
Ronel (2016) who found that boys showed a more maladaptive profile in terms of engagement.
The result of this present study is not in agreement with the work of Ahmad & Rosnainis (2017). They
found that girls were significantly better than boys in affecting cognitive and behavioural engagement.
However, the work of Ruslin (2014) is in support of Ahmad et al (2017) in that they also found that female
students have higher level of engagement when compared to boys.
In addition, Pagar (2016) found in her study titled the effect of gender and perceived control on student
engagement that gender has no significant effect on student engagement. This finding is in agreement
with the present study. Inspite this, Sofie et al (2015) found that boys were less engaged than girls.
Invariably, girls were more engaged than boys in their study this report is not in agreement with the
present study.
Effects of Mental ability on Students Engagement in Biology
The analysis of result in this study indicates that mental ability had no significant main effect on students’
emotional engagement. However, it had a significant reflect on students’ cognitive and behavior
engagement in Biology. The area of emotional engagement negates the study of Mariam & Intan (2012)
who found that mental ability levels may affect emotional engagement of those with low mental ability
levels. However, the area of cognitive engagement is in agreement with the present study in that they
found that cognitive engagement could be determined through the level of mental ability.
In addition, the study by Roger et al (2015) indicated that intellectual engagement (cognitive engagement)
was significantly associated with level of cognitive performance (mental ability). This study is in
consonance with the present study in that mental ability had a significant effect on students’ cognitive
engagement
Recommendations
Based on the findings of this study, the following recommendation are expedient:
Teachers should embrace enhanced inquiry instructional strategy in order to enhance students’
engagement in learning of Biology.
African Journal of Pure and Applied Science Education Volume 18, Number 1, pp 1 – 20, July 2020 www.ajopase.com; [email protected] ISSN 11187670
Fasuyi, O. A AJOPASE, Vol. 18, No. 1, July 2020
Gender did not affect the engagement of student therefore both female and male students should be
treated equally by the teachers with no preference for one.
Students should be encouraged to use personal science journal as this will assist them in monitoring
their own ideas/knowledge about the concept taught which would finally influence their engagement
in biology classes
Ministries of Education at both Federal and state levels and other stakeholder should organize
continuous seminars/workshops for teachers where they can be trained/re-trained on how to assist
the student to learn better by being engaged in class.
In developing instructional plan, teachers should put into consideration the different activities that
will take place in the class and the group discussion that will be set up during the teaching. The teacher
should make sure that each group consists of students with low, medium and high mental abilities.
Also, gender should be evenly distributed in each group that is no group should be dominated by
either male or female.
References
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Conner, J. & Pope, D. 2013).Not just robo students: why full engagement matters and how schools can promote it journal of youth and adolescence, 42(9), 1426-1442.
Crumpton, H. E & Gregory, A. (2011). I’m not learning: The role of academic relevancy for law-achieving students. Journals of Educational Research., 104(1), 42-53.
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Kutitu, M. (2014).The difference between male and female students’ Self efficacy, academic engagement and academic achievement in biology among grade ten students in South Wollo Zone schools in Ethiopia.Mediterranean Journal of Social Sciences. Doi:10.5901/mjss.2014.v5n23p804.
Mariam, A. & Intan A. (2012). Students of low academic achievement – their personality, mental abilities and academic performance: International Journal of humanities and social science, 2(23), 220-225.
Ronel,K. (2016). Gender difference, in motivation, engagement and achievement are related to students perception of peer-but not of parent or teachers attitudes towards school. Learning and individual differences. www-researchgate.net.Doi:10.1016/j.indif.2016.10.006.
Roger, T., Michael, N., Davies, S. &Whalleyli (2018). BMJ 2018;363doi:https://doi.org/10.1136/binj.k4925 (published10Dec.2018). Wheatley, K. (2018). Inquiry based learning: Effects on student engagement. Honors project 417 http://scholarworksbgsu.edu/honoursprojects/417.
Sofie, L., Debira, R., Ferre, L. &Barki, D. (2015). The gender gap in student engagement: The role of teachers’ autonomy supports, structure and involvement. British Journal of Educational Pshychology, 85(4). Do teachers matter? Students perception of classroom interactions and student engagement, Scandinavian Journal of Educational Research. Published online 11 February, 2019 https://doi,DoIorg/10.108/00303831 2011. 1577254
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