effects of enhanced inquiry and inquiry instructional

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




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




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




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




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




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




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)




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




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




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.




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


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




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



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


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




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



Corrected Total Post Emotional 87.976 218



* 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




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


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


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





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


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.




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




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.




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

Ahmad, A. Ardy, Y. & Rosnainis, M. (2017). Differences in students’ mathematics engagement between gender and between rural and urban schools, AIP Conference Proceedings 1795; 020025 (2017) https://doi.org/10.1063//.4972169.

Aquarena Wetlands Project glossary of terms. Texas State University at San Marcos. Anchored from the original on 2004-06-08.

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.

Fredricks. J. A., Blumanfeld, P. C & Paris A. H. (2004). School engagement: Potential of the concept, state of evidence. American Educational Research Association.Retrieved from htrp: search.ebsc ohost.com.

Green, J., Liem, G. A.D., Martin, A. J., Colmar, S., Marsh, H.W. &Mclnernay, D. 920120. Academic motivation, self-concept, engagement, and performance in high school: Key processes from a longitudinal perspective. Journal of Adolescence, 35(5), 1111-1122.

Kennedy Ameyan-Baab, Charles Anuah Yin, Anhafo, rlymphpey D. Assem (2018). Investigating the effect of enquiry based learning approach in science on junior high school 2 students in Paradise International School. International Journal of Scientific Research and Management (IJSRM), 6(7), 497-505.

Kuh, Buckley, Bridges, Hayek (2007). Piecing together the student success puzzle: Research,propositions & recommendations. ASHE Higher Education Report. Vol 32, No5, San Francisco: Jossey-Bass.s




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

Wheatley, K. (2018). Inquiry based learning: Effects on student engagement. Honors project 417 http://scholarworksbgsu.edu/honoursprojects/417.


http://scholarworksbgsu.edu/honoursprojects/417

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