An Affective-Cognitive Teaching and Learning Approach for Enhanced Behavioural Engagements among Engineering Students

Abstract

Promoting students’ engagement has been of great interest to engineering educators as it is associated with better teaching and learning effectiveness. However, students’ engagement is a multifaceted construct comprising the cognitive, affective, and behavioural aspect of engagements which makes it difficult to get a holistic measure of it. Thus, the behavioural engagement alone is often measured as it enables the researcher to investigate outcomes ‘in-action’ and evaluate the individuals’ ability at high-order thinking. The aim of this study is to explore the effect of an integrated affective-cognitive teaching and learning approach on behavioural engagements.

The study utilized the quasi-experimental design method with pre- and post-test. The experimental group (n = 36) was taught a course on mechanics of material using the integrated approach while the control group (n = 34) was taught the same course using the conventional method. The results indicate that the integrated affective-cognitive learning approach promotes some types of positive behavioural engagement while suppressing other types of negative engagements. Thus, it was concluded that the integrated teaching and learning approach is effective in promoting positive behavioural engagements among engineering students.

Keywords:

• Integrated teaching
• learning approach
• behavioural engagement
• affective-cognitive teaching

Introduction

The essence of a teaching process is to facilitate learning (Cazden 2001) and promoting students’ engagement has long being recognized as a precursor to learning. Student engagement is concerned with the interaction between, time, and effort invested by students. The teacher plays a fundamental role in motivating the students which leads to engagement. The term engagement refers to students’ feelings, experiences and participation in academic and non-academic activities (Appleton et al. 2008). Student’s engagement is influenced by personal factors such as age, gender, race, and self-efficacy; social factors such as familial and peer and other social influences. Engagement is an essential element in the learning process because learning requires engagement for mastery attainment and knowledge acquisition (Shi 2010).

Students’ engagement is a multifaceted construct comprising the cognitive, the affective, and the behavioural dimensions (Fredricks et al. 2004, Wang & Holcombe 2010). Three identified dimensions have their roots in the work of Bloom on learning taxonomy (Trowler 2010). Students’ engagement is also a part of the learning process that refers to a student’s cognitive involvement, active participation, and emotional engagement with specific learning task. Thus, based on the definition; student’s engagement can be further defined as students’ emotional attachment towards the learning process which can be perceived as a motivated behaviour.

Chapman (2003) provides similar definitions of this construct which he defines as one’s eagerness to actively participate in habitual school activities with cognitive, behavioural, and affective indicators of student engagement in specific learning tasks. According to him, cognitive engagement refers to thinking exercise mainly dealt with the use of cognitive strategies such as coding, analysis, interpretation, etc. High level of cognitive engagement requires higher-order thinking such as creativity or connecting a new knowledge to prior knowledge.

Expanding on the definition, Trowler (2010) suggests that in higher level cognitive engagement, students seek to go beyond the basic requirements and would welcome challenges whilst lower-level cognitive engagement involves rote memory. In contrast to cognitive engagement, affective engagement is associated with the emotional reactions such as acceptance, interest, sense of belongingness and attitude towards learning. The emotional reaction refers to a sense of belongingness, a feeling of being accepted by a friend or simply being happy to be at school.

Behavioural engagement, however, is the operationalization of the behavioural aspect that underpins the particular set of behaviour such as devotion and determination (Appleton et al. 2008), learning behaviour and sense of belongingness (Fredricks et al. 2004), and student’s self-regulatory strategies to monitor their learning processes (Chapman 2003). Educators often made use of ‘time-base indices’ which measure the time engaged in assignment completion as behavioural engagement.

Among the three components of the engagement construct, in the current study, a behavioural engagement is measured, as it enables a researcher to investigate outcomes ‘in-action’ and evaluate the individuals’ ability to function in the higher level thinking of the learning domains (Besterfield-Sacre et al. 2007). Behavioural engagement alone is worthy of research since behavioural engagement is associated with academic achievement and motivation (Borman & Overman 2004, Christenson et al. 2008, Dotterer & Lowe 2011).

Two types of behavioural engagement have been identified namely, positive behavioural engagement and negative behavioural engagement as suggested by the literature (Wang & Holcombe 2010). Positive indicators of behavioural engagement can be seen from the willingness of students to participate (Marks 2000), to undertake task management (Martin & Liem 2010) and students’ participation in routine class activities (Chapman 2003, Willms 2003). Negative indicators of behavioural engagement includes cheating on tests, frequent absence from classes, damaging school properties or exhibiting delinquent behaviour (Chapman 2003). Students who positively engaged during classroom activities tend to display lesser distracting and deviant behaviours (Hamre & Pianta 2001, Patrick et al. 2007).

The status of engineering education: the need for the study

Learning is not only associated with cognition; the emotional aspects can also be associated with a learning goal. Looking at the engineering content and learning goal in particular, the educators have emphasized the need to consider the affective needs in engineering education (Strobel et al. 2011). However, current educational pedagogy is lacking in certain areas of engineering education as their focus is more on the acquisition of knowledge which is the cognitive dimension of learning instead of valuing the acquired knowledge which is the affective dimension of learning. Therefore, engineering is often perceived as object-oriented rather than people-oriented (Malcom 2008, Strobel et al. 2011).

Thus, providing effective engineering education is important. Subsequently, there is no consensus on how to integrate affects into the teaching and learning activities that are highly dominated by cognitive considerations (Lashari et al. 2012). The interactions between teaching and learning should promote a balance between pursuit of cognitive and affective goals, where each goal is pursued as both a means and an end of education in such a way that neither should be seen as subservient to the other.

Purpose of the study

The purpose of the study is to determine the effect of an integrated affective-cognitive teaching and learning approach on behavioural engagements among engineering students. The study reported here is part of a larger study looking into the effect of the approach on academic achievement. It focuses merely on the observational schedules via behavioural engagement. The use of observational schedules allowed the researchers to capture behavioural aspects of engagement as it unfolded during the classroom, but that the use of self-report measures would allow to target aspects of engagement that were not measured here for the purposes of future studies. Though, the use of self-report measures to assess self-efficacy, locus of control, and attitude are also aligned with the affective and cognitive components of engagement. The self-report questionnaires mentioned earlier were used in the pre-test as well as the post-test. In the pre-test they are used to form baseline information about the sample. In the post-test they are used to assess changes if any. The focus of this article is on the behavioural engagement through out the intervention which was measured using observational schedule. The use of observational schedules provides an opportunity to capture behavioural aspects of engagement.

Four objectives are formulated as follows:

1. To determine if there are any differences in the positive behavioural engagement between the experimental and the control group.

2. To determine if there are any differences in the negative behavioural engagement between the experimental and the control group.

3. To determine the dominant types of positive behavioural engagement among groups.

4. To determine the dominant types of negative behavioural engagement among groups.

Research methods

Research design

The research made use of the non-equivalent quasi-experimental design method (Table 1). The non-equivalent quasi-experimental design method was similar to the experimental design method but it lacks random assignment (Shaughnessy et al. 2002). Participants did not have an equal chance of being either in the control or the experimental groups. Researcher can control the nature of treatment, neither subject tends not to be randomly assigned or randomly selected, nor do they not necessarily constitute equivalent groups of all characteristics. However, randomization was not desirable in this study because putting the students with unfamiliar faces or conditions may affect the outcome of the study that is, the internal validity (Alias & Hafir 2009).

Table 1 Research design.

	Pre-test	Intervention	Post-test
Experimental group	01	X	01
Control group	02	—	02

Note: 01, pre-test on experimental and control group; 02, post-test on experimental group; X, intervention – use of integrated affective-cognitive learning approach; —, no intervention – does not use integrated-cognitive learning approach (Adapted from Alias & Tukiran 2010).

Thus, the quasi-experimental design method has the next greatest potential for establishing support for causality. Although it is relatively easier to conduct compared to the true experimental design method, it may pose a threat to external validity (Shaughnessy et al. 2002). In order to avoid external invalidity, the solution is to ensure that the groups chosen are similar to the general target population. As in terms of teaching and learning culture, educational resources, and teaching staff, students are given equal opportunities. Therefore, it is expected that there is not much difference regarding students’ educational background (Alias & Hafir 2009). The study duration was eight weeks which is sufficient for the purpose of the study (Shaughnessy et al. 2002). The description on the sequence of the research design is given in Table 1.

Pre-test and post-test are self-report measures namely self-efficacy, locus of control and attitude. The affective-cognitive learning approach is used as intervention. Self-efficacy is a belief of a student to accomplish a specific task. It is a motivational construct that creating the internal urge for students to learn. Locus of control refers to a person’s belief on the controlling events that causes an outcome. A person may tend to believe that the outcomes are beyond his control and outcomes are the results of fate or destiny-external locus of control or within his/her control – internal locus of control. Attitudes are beliefs and opinion towards particular object, situation or event. The independent variable was teaching method (using or not using integrated affective-cognitive learning) and dependent variable was academic achievement which was measured by the means of the scores of cumulative grade point average (CGPA).

Sample

The samples for the study were two intact classes of students from an engineering foundation programme in a Malaysian University. The experimental group consisted of 36 students and the control group consisted of 34 students with an age range between 18 to 24 years old. The two samples were taught by the same lecturer which avoids the teacher’s personality and teaching style from confounding the results (Alias & Tukiran 2010).

Data gathering instruments

Participant observation schedule and video recording – frequently used approaches in the education setting – were employed for data gathering. Participant observation is one of the types of data collection methods that refers to the systematic attempt to discover the knowledge of a group that is accustomed to making decisions regarding future lessons and to making learning effective. Observation is a selective activity that usually dictates what is of value to concentrate upon. In a naturalistic setting (e.g. classroom), an observer cannot observe everything. Therefore, a researcher needs to target the behaviour(s) prior to observation and make a checklist of the types of behaviour they feel to be significant for the study (Turner 2000). The method provides a rich description and valuable outcomes regarding what is actually happening in the classroom. In addition, classroom observation is an effective way to transcribe the process of teaching and learning being investigated. The common ethical issue to participant observation is ‘invasion of privacy’. However, the obtained information is kept confidential and will be used only for educational purposes.

Three observational schedules were conducted which was a mini time-series interpretation that has been used for the time-on task investigations. An assistant was trained to assist in data collection to improve accuracy of the data. Prior to the actual data collection, an hour long training session was carried out to obtain deeper understanding of the coded items. All the three observations were conducted by the two observers. One observer sat in front while the other sat at the back with the stop watch, observation checklist and blank pages for recording the observations. For these observations the two hour class time was divided into multiple 10 minute sessions.

At the end of each session, the researchers discussed their coding as suggested by Atweh et al. (1992). According to Atweh et al. (1992), the use of codes allows a researcher to record the behaviour of a student on a seating plan of the whole class. It is a beneficial way to record the behaviour amongst novices in such a way that information about behaviour occurrence is not lost but recorded. For example, in the current study ‘interacting with the classmates’ refers to peer learning and students’ inattentive and distracted behaviour during lecture time refers to ‘disruptive behaviour’.

The observation checklists were divided into two categories namely positive behavioural engagement and negative behavioural engagement. The checklist for positive behavioural engagement includes asking questions voluntarily, responding voluntarily, responding only when the teacher poses questions, interacting with classmates, writing down notes, giving opinions freely, and submitting class assignment on time. The negative behavioural engagement includes yawning/sleeping in the class, wasting time when a teacher allots class assignments, disruptive behaviour, wasting time (headphone, stationary, etc.), looking outside, daydreaming, and looking at watch. A standard checklist was utilized to record the earlier-mentioned aspects. However wasting time (headphone, stationary, etc.) and looking at watch was added after the trail as shown in Table 2.

Table 2 Indicators of behavioural engagements.

Positive behavioural engagement
1	Asking questions voluntarily
2	Responding voluntarily
3	Responding only when the teacher poses questions
4	Interacting with classmates
5	Writing down notes
6	Giving opinions freely
7	Submitting class assignments on time
Negative behavioural engagement
1	Yawning/sleeping in the class
2	Wasting time when a teacher allots a class assignment
3	Disruptive behaviour
4	Wasting time (headphone, candy, stationary, face)
5	Looking outside
6	Daydreaming
7	Looking at watch

Source: Chapman 2003, Lee 2008, Alias & Tukiran 2010.

Research procedure

Clearance to conduct the study was obtained from the Dean of the centre for Diploma Studies (where the study was conducted) prior to the data collection process which is in accordance with the existing research practices of the University. The study is then deemed to be ethically accepted from the point of view of the University.

Pre-survey on self-efficacy, locus of control and attitude was given to both classes on the same day. The intervention is the integrated affective-cognitive teaching and learning approach. During the intervention the experimental group was taught using the integrated affective-cognitive teaching and learning approach while the control group used the method that was normally used by the lecturer which is the lecture and demonstration method.

After it was determined that the experimental group had benefited from the intervention, the same method was used for the control group as well so that the control group could benefit equally from the involvement in the study.

The new integrated learning approach is formulated on the theoretical foundation from four major schools of thought namely behaviourism, cognitivism, socio-culturalism, and constructivism. Their technique such as reinforcing appropriate behaviour, immediate feedback, motivational video, persuasive technique, cognitive construction, magnification and minimization, arbitrary inferences, modelling, peer learning, group processing were used where appropriate.

Students in both classes had the same instructor, syllabus, course materials and printed notes. The subject taught to students was mechanics of material (mechanics of rigid body). The sole difference between the two groups was the teaching and learning technique where the experimental group was taught using the integrated affective-cognitive learning approach. The typical lesson structure for both groups is illustrated in Appendix A. At the end of the semester, students were prescribed the post-tests which are the same as the pre-test.

However, the pre-test results and the post-test results are not reported in this paper. This paper will only focus on the effect of the intervention on the teaching and learning process, i.e. the learning engagements.

Results and discussion

Before presenting the results obtained from observation, a check on the group is presented first with respect to academic ability based on CGPA, self-efficacy, attitudes and locus of control.

Equivalence in self-efficacy, locus of control, attitude and academic ability

The group equivalence was tested at the 5% level of significance using the independent equal variance t-test method to determine the difference in self-efficacy, locus of control, attitude and academic achievement between the two groups. The equal variance t-test was used as the Levene’s test indicates equal variance as shown in Table 3 (p > 0.05).

Table 3 t-Test result on mean difference of self-efficacy, locus of control, attitude and academic achievement between groups.

	Levene’s test for equal variance	t-Test for equality of means
	F	P	t	df	P (two-tailed)
Locus of control	2.77	0.100	2.84	68	0.006
Self-efficacy	0.530	0.469	1.02	68	0.309
Attitude	1.23	0.271	0.70	68	0.484
Academic achievement (CGPA)	1.93	0.169	1.18	66	0.242

Table 3 (t = 1.026, df = 68, p = 0.305) indicates no significant difference on the self-efficacy scores which means students of both groups are equal with respect to their self-efficacy level. In-addition no significant difference on the scores on attitude is also revealed (t = −7.04, df = 68, p = 0.484) indicates that both groups are equal with respect to their attitude at the initial stage of the study. Moreover, the t-test results in Table 3 also show that there is no statistically significant difference between the two groups on academic competence (t = −1.180, df = 66, p = 0.242) indicates that the p-values is greater than 0.05. Thus, the groups are assumed to be equivalent with respect to their academic competence at the initial stage of the study.

However, a significant difference on locus of control (t = 2.842, df = 68, p = 0.006) is found among groups. The p-value is greater than 0.05 for self-efficacy, attitude, and academic achievement which indicates that there is no significance. Thus, it can be concluded that both groups are similar at the start of the study and whatever differences that are observed later on can be attributed to the effect of the proposed approach.

The different types of behaviours and the related frequencies are shown in Table 4. Based on Table 4, it is observed that the two groups behave differently. The experimental group exhibit better frequencies of positive behavioural engagement and less frequencies of negative behavioural engagement compared to the control group. The most prominent positive behavioural engagement indicators were responding when the teacher poses questions, interacting with classmates and submitting class assignments on time. The frequency of positive behavioural engagements over the three observations on interacting with classmates increased ranging from 20, 29 to 34, respectively. In fact, most types of positive behavioural engagement are relatively lower for the control group.

Table 4 Types and frequencies of behaviours.

	Observation 1	Observation 2	Observation 3
Behavioural indicators	G 1	G 2	G 1	G 2	G 1	G 2
Positive behavioural engagement
Asking questions voluntarily	5	17	9	6	1	2
Responding voluntarily	9	11	6	7	3	3
Responding when the teacher poses questions	7	25	34	36	11	25
Interacting with classmates	8	20	16	29	13	34
Writing down notes	34	36	34	36	31	36
Giving opinions freely	5	2	1	2	0	0
Submitting class assignments on time	17	25	12	36	33	36
Negative behavioural engagement
Yawning/sleeping in the class	21	12	56	25	40	20
Wasting time when a teacher allots a class assignments	3	0	20	16	9	1
Disruptive behavior	11	7	44	28	15	3
Wasting time (headphone, stationary, etc.)	5	7	5	5	6	4
Looking outside	4	2	5	0	1	3
Daydreaming	13	4	11	8	9	0
Looking at watch	7	1	5	0	1	1

Note: G1, control group; G2, experimental group.

Persistently high frequencies in most types of positive behavioural engagements are indications of students’ positive attitude towards the subject and their sense of belongingness with their class fellows (Lee 2008). Thus, the higher incidences of positive behavioural engagement for the experimental group were interpreted as the positive impact of the integrated affective-cognitive learning approach on the learning process. The higher responses towards teachers questions in the experimental group indicates better teacher–student relations in this group which leads to more active participation in the classroom activities.

As far as negative behavioural engagement is concerned; the prominent indicators were yawning/sleeping in the class, wasting time when a teacher allots a class assignment, disruptive behaviour, day dreaming and looking at watch. The frequencies in the control group in general were high over the three observations whereas the frequency in the experimental group was relatively low. This sort of negative indictor shows students disengagement in task and learning (Overton & Sullivan 2008). This observation is interpreted as a failure of the conventional method to support student engagement.

The findings of the present study are enlightening as they indicate that appropriate teaching and learning approaches can be designed to promote positive behavioural engagements. Promoting greater positive behavioural engagement is important as higher engagement is more evident among motivated and academically resilient students (Borman & Overman 2004, Christenson et al. 2008, Lee 2008, Dotterer & Lowe 2011). Furthermore, students who positively engage during classroom activities tend to reduce their likelihood of exhibiting distracting and deviant behaviour (Hamre & Pianta 2001, Patrick et al. 2007).

The results indicate that the use of the integrated affective-cognitive learning approach keeps the student motivated and engaged in the instructional process. It is also expected that the supportive learning environment created through the approach encourages learning responsibilities, develops a positive attitude towards the subject because it is not just what is taught, but how the material is taught is worthwhile, which influences the learning (Bransford 2000).

Conclusion

The study sets out to determine if specifically designed interventions that cater to the cognitive and affective learning needs would promote positive behavioural engagements and reduce negative behavioural engagements among engineering students in a foundation course. The study has established the worthiness of the intervention; the integrated affective-cognitive learning approach in promoting positive behavioural engagement among engineering students based on the observational data. Lowering of negative engagement was also observed among students undergoing the integrated approach which further supports positive impact of the approach. Higher positive engagement and lower negative engagement indicate positive attitude towards learning in general. Since, learning in past studies has been found to be not only associated with cognition but also with emotions, therefore, the integrated approach which supports positive emotion as indicated by the positive behavioural engagements is expected to enhance the students learning experience in making teaching more efficient and learning more effective. In brief, the approach appears to be effective in promoting behavioural engagements that are conducive to learning. Future studies could look at the mediating effect of positive behavioural engagement on academic achievement.

Acknowledgement

The authors would like to express their gratitude to the Ministry of Higher Education for supporting the research project under the Fundamental Research Grant Scheme (FRGS) Vot 0757.

Appendix A

Table A1 Typical lesson structure.

Experimental group (Integrated affective-cognitive learning approach)	Control group (Non-integrated affective-cognitive learning approach)
SET INDUCTION
Lecturer gave motivational talk to prepare students emotional association with learning; afterwards teacher informed students about learning objectives	Lecturer informed students about learning objectives
LECTURE
One-way lecture
• Lecturer gave a short lecture.	• Lecturer gave a short note lecture.
• Students took the notes	• Students took the notes.
Interactive lecture
• Given everyday life examples and students are encouraged to give other examples on the related topics with discussion of pros and cons that embodies their impact on lives. [Student–teacher interaction that promotes feeling of empathy (affects) to encourage cognitive learning.]	• Given everyday life examples and lecturer encouraged students to give examples on the related topics. [Student–teacher interaction focuses on cognitive learning.]
DISCUSSION AND FEEDBACK
• Lecturer acknowledged students contribution and gave feedback in the form of positive reinforcement to motivate students continuing efforts in the learning. [Affective dimension of learning is emphasized in addition to cognitive emphasis.]	• Lecturer acknowledged students contribution and gave feedback. [Sole emphasis is on cognitive dimension of the learning.]
PRACTICE BY STUDENTS
• Students done exercises	• Students done exercises
CLOSURE
• A summary of what has been learnt; reflection by students; lecturer highlighted students strengths and potentials giving positive feedback to promote improvement, comments of self worth and contribution of engineers in every field of life.	• A summary of what has been learnt and what to be learnt; explanation on next assignments.
• Students were given assignments.