comparative analysis of two instructional strategies

Comparative Analysis of Two Instructional Strategies and Their Impacts on Selected University

Engineering Students Performances in Particle Technology

Kevon R. McAnuff & Simon M. Yalams University of Technology

Kingston, Jamaica

Abstract This study examined the effects of active learning and traditional lecturing on the academic performance of Particle Technology students in order to identify the more effective teaching strategy. Two active learning models, namely, cooperative and collaborative learning were used. The population of the study consisted of thirty-eight third year students enrolled in the Bachelor of Engineering in Chemical Engineering program in one of the universities in one of the Caribbean Island. The post-test only control group experimental design was employed for the study while the instruments used to collect data were midterm tests and a final examination. The data collected was subjected to an independent t-test analysis ( = 0.05), using the SPSS statistical software application. The findings indicated that students taught with traditional lecturing performed significantly better (mean P = 0.01) than those taught using active learning strategies. Males and female participants taught with traditional lecturing also performed better than their counterparts taught with active learning. Based on the findings of the study, it was recommended that students be better sensitized about new teaching strategies being implemented, Particle Technology teachers recognize the value of traditional lecturing, appropriate measures be implemented to achieve comparable attendance among study groups and future studies should focus on understanding the characteristics of female students which results in them exhibiting enhanced learning compared to their male counterparts.

Keywords-comparative;engineering; instructional; strategies; performances; particle technology

I. INTRODUCTION Active learning strategies are viewed by many as a

fundamental change from traditional teaching methods. As such it has received substantial attention over the past several years. However, there remains some uncertainty as to the necessity for these methods in engineering education since students are already active through practical homework assignments and laboratory experiments. Beside, many engineering educators lack the interest to examine the educational literature for answers and consequently do not always appreciate the difference between the common forms of active learning. There are also drawbacks for engineering faculty expecting to select a few articles to see the effectiveness of active learning strategies. Readers must take care to understand the subject of the study as well at the

authors methods of data collection and interpretation. However, the subject of the study might not necessarily be obvious as a result of the broad range of methods which are presented as active learning. This process cannot be eliminated but its complexity can be greatly reduced if one focuses on the fundamental aspects of common active learning methods. According to [1], in order to assess what works, care must be taken in interpreting data, various learning outcomes must be considered and reported improvement should be properly quantified. While the use of statistics assist in the presentation of learning outcomes, it does not eliminate the need for interpretation when evaluating for significance. Educators should not expect that simply adopting a particular educational method will result in similar learning outcomes to those reported in educational studies as the practical limitations of these studies must also be considered. This approach is supported by [1] who opined that educational studies only tell us what worked, on average, and specifically for the populations examined. Nevertheless, according to [2], if the data supporting a particular learning model is extensive and a teachers students also resemble the test population, there is a greater possibility that similar results will be obtained. Alternatively, educators should also view the findings presented in literature as a means to identify the variables involved in educational studies.

Teaching models which incorporate active learning strategies continue to receive widespread support from modern literature on classroom instructional modes which suggest that these strategies result in more meaningful learning when compared to traditional, passive lectures with regards to retention of material, motivating students and developing thinking skills [3]. This was supported by [4] who went further to state that active learning also improved students performance, as measured by traditional tests, and also created positive students attitudes towards the learning process. Moreover, the multiple learning styles included in active learning strategies conform to educational models based on theories of learning and motivation. However, not all of these supports for active learning are compelling. For example, [5] conceded that the measured improvements of learner-centered over instructor-centered instructional strategy on students learning in two online courses were small, and concluded that

978-1-4673-6109-5 /13/$31.00 2013 IEEE Technische Universitt Berlin, Berlin, Germany, March 13-15, 20132013 IEEE Global Engineering Education Conference (EDUCON)

Page 952

the principles lack substantial evidence with respect to empirical support for active learning. Nonetheless, active learning models continue to receive huge support from educational literature. Still, given the range of instructional methods presented as active learning, what is being endorsed by the literature is not always apparent and therefore it can be quite confusing interpreting the findings of educational studies. Consequently, active learning should be thought of as an approach and not as a method and so the various methods are best assessed independently.

Active learning can be achieved by introducing students activity into the traditional lecture sessions. Reference [2] highlighted the use of one such approach called the concept tests method in their Unified Engineering class. This involved incorporating brief multiple-choice conceptual questions into lectures to test students knowledge of the material. Additionally, the lecturer only introduced new material when a majority of the class did well on a question. On the other hand, students were placed in small groups to work out the answer to the question when the concept tests revealed conceptual problems or misunderstandings. When students were asked to compare the active learning techniques to the traditional lecture format, their responses reflected an overall positive attitude towards the active learning techniques. Specifically, some students commented on the effect of the active learning techniques on improving their learning and understanding of the content, and in stimulating their thinking and classroom participation. Another important component of active learning highlighted by [4] is the type of activity, as this influences how much material students retained. Essentially, students should be thoughtfully engaged and activities designed around important learning outcomes. There is little doubt as to the significance of students engagement as there is substantial evidence to support its effectiveness on a wide range of learning outcomes.

1) Collaborative Learning Model Collaborative learning may be used to describe any

instructional method in which students work together in small groups to accomplish a common task. Consequently, this model can be viewed as encompassing all group-based instructional methods, including cooperative learning [7]. Reference [4] however, stated that some authors indeed distinguish between collaborative and cooperative learning as having distinct historical developments and different philosophical roots. Interpretation aside, it is important to understand that the principal element of collaborative learning is students interactions and not solely learning. There is strong agreement among the findings of various educational studies probing the question of how collaboration influences learning outcomes. In a review of 168 studies, [8] found that cooperation improved learning outcomes relative to individual work across the board. Similar results were found by [9] who looked at 37 studies of students in science, mathematics, engineering and technology. In a related study investigating the effect of incorporating small, medium and large amounts of group work on achievement, [9] sought to determine if the benefits of group work improve with frequency. The positive effect sizes associated with low, medium and high amount of

time in groups were found to be 0.52, 0.73 and 0.53, respectively. Interestingly, the highest benefit was found for medium time in groups and not for large time in groups. On the contrary, evaluating the effects of frequency of group work on promoting positive students attitudes revealed that more time spent in groups did however produce the highest effect. The effect sizes reported were 0.37, 0.26, and 0.77 for low, medium and high amount of time in groups respectively. These attitudinal results must however be interpreted with caution as the authors admitted that they were based on a relatively small number of studies.

2) Cooperative Learning Model According to [4], this model can be defined as a

structured form of group work where students pursue common goals while being assessed individually. The cooperative learning model proposed by [1] is the most common found in the engineering literature [1]. This model is characterized by five specific tenets, namely, face-to-face promotive interaction, mutual interdependence, appropriate practice of interpersonal skills, individual accountability, and regular self-assessment of team functioning. The principal feature among the different cooperative learning models highlighted by [7] is a focus on cooperative incentives as oppose to competition to promote learning. Increased higher-order thinking skills and improved students performance are among the benefits of cooperative group learning outline in the findings of much of the educational research. Cooperation has also been credited with fostering self-esteem, promoting interpersonal relationships and improving social support. Still, the rather stringent criteria and time needed for successful learning causes many instructors to hesitate when considering the use of cooperative learning models. The fact that cooperative learning models create a setting which promotes interpersonal skills and effective teamwork would also interest engineering faculty. In addition, engineering program accreditation bodies such as the Accreditation Board for Engineering and Technology (ABET) call for engineering students to acquire these skills [6]. The lack of team skills displayed by engineeering students was also noted as a frequent concern among employers. Therefore, the development of these skills in engineering students could also lead to better integration in the industry. Furthermore, it would be quite difficult to put forth an argument that individual work such as that taking place in traditional lecture classes helps to build team skills given that practice is a precondition of learning any skill. It is not always easy to ascertain whether cooperative learning effectively develops interpersonal skills as how one defines and measures team skills must be taken into consideration. Even so, strong arguments are put forward by [8] to support the view that cooperative learning is indeed effective in this area. Additionally, when cooperative learning groups are used, they recommend that students be explicitly trained in the skills required to be effective team members. Since traditional instruction focuses on individual learning and typically does not include explicit instruction in teamwork, it is fair to assume that it would be less effective than the opportunity to practice interpersonal skills while getting explicit instructions in these skills. Empirical evidence to support this conclusion was provided by [10] who studied the effects of competitive


Page 953

and cooperative learning strategies on academic performance of Nigerian students in mathematics. Furthermore, the authors went on to state that cooperative strategies resulted in a greater increase in social skills when compared to competitive or individual situations. These findings are in agreement with a study conducted by [11] which reported an increase in students interpersonal skills necessary for effective teamwork as a result of employing cooperative learning strategies.

In one of the Islands in the Caribbean, many of our educational institutions employ passive learning through traditional lecturing and as a result active learning strategies are sparsely used. In contrast, many researchers support the use of active learning which they have found to increase retention, foster team building and develop higher level thinking skills [3]. The main problem that the study sought to investigate was which of these learning strategies will bring about better performances from the students enrolled in the Particle Technology module. The study was guided by the following questions: 1.) Which of the two instructional approaches (active learning and traditional lecturing strategy) used for teaching Particle Technology students yields better students academic performance? 2.) Do Particle Technology students significantly differ in their academic performances based on the two methods of teaching (active learning and traditional lecturing strategy) used? and 3.) Do Particle Technology students taught with active learning strategies and traditional lecturing significantly differ in their academic performances based on gender?

II. METHODOLOGY The experimental design adopted for this study was

the Post-test Only Control Group Design. This design was chosen because of its strength against single-group and multiple-group threats to internal validity [12]. Typically, a pre-test is used to assess whether the groups are comparable at the beginning of the program. However, since random assignment was used in the formation of the groups, it then could be assumed that the two groups are probabilistically equivalent initially and therefore the pre-test was not required. In this design, the primary focus of the researchers was determining whether the two groups are different after the program. The groups performance on three assessments were measured and then compared by testing for the differences between the means using a two-tailed independent t-test with a 95% confidence interval ( = 0.05). This t-test was done using the SPSS statistical analysis software and the t-value (t), degrees of freedom (df) and p-value (Sig. (2-tailed)) reported. The t-value is the ratio of the difference between the mean of both groups and the standard error of the difference. The degree of freedom is calculated by adding the two sample sizes then subtracting two when equal variance can be assumed. If equal variance cannot be assumed it is then calculated using the Satterthwaite formula. The p-value is the two-tailed probability obtained from the t distribution which gives the probability of observing a t-value of equal or greater absolute value under the null hypothesis. The null hypothesis being that there is no significant difference between the mean score of both groups.

1) Participants The study was conducted in the chemical engineering

program at a popular university in one of the Islands in the Caribbean. The participants in this study were 38 third-year students (16 females and 22 males between the ages of 21 and 24). These students were enrolled in the compulsory Particle Technology module. Particle Technology is a three (3) credit module designed to give students a clear understanding of the characteristics of particles and how these characteristics determine such prosperities as its density and conductivity, the surface per unit volume and the interaction between particles and fluids. The module also focuses on some physical unit operations involving particle enlargement, reduction, separation and blending as well as the design and analysis of several equipment involved in these processes. The module consisted of a two hours lecture session in addition to two one-hour tutorial sessions per week. The lecture sessions were attended by all students while the class was divided into two groups, A and B, with each group attending a single tutorial session per week.

2) Instruments The instruments used to assess students performance

were two midterm tests and a final examination. The first midterm tests was given at the end of the second unit and assessed major concepts covered in units one and two while the second midterm test was given at the end of the fourth unit and assessed major concepts covered in units three and four. Both tests had duration of two hours and comprised of three problems in the form of short answer and restricted essay items in which the students had to carry out numerous calculations. At the completion of the module, students were given a summative assessment in the form of a comprehensive final examination, which was used to test students overall understanding of the major concepts covered in the module. The examination comprised one short answer item and three restricted essay items and required students to perform various calculations. Students were required to answer all questions within the allotted duration of two hours. A formula sheet was also provided. In order to determine whether the research instruments truly measure that which they were intended to measure or how truthful the research results are, the instruments were assessed for face and content validity. The content validity was done using a method advocated by [13] for gauging agreement among raters or judges regarding how essential a particular item is. This formula yields values, which range from +1 to -1. The content validity ratio for individual test items ranged from 0.2 to 1.0 and 0.47 to 0.87 for the overall test instruments. This indicates that the instruments had sound content validity as positive ratios mean that more than half of the expert raters rated the knowledge being measured by the items as being essential. In order to assess the reliability of the instruments, the inter-rater method was used. The reliability of individual test items ranged from 0.6 to 1.0 on a scale of 0.0 to 1.0. This indicates that the research instruments had good reliability, as there was at least 60% agreement between the expert raters. The reliability for the overall test instruments were even higher ranging from 0.73 to 0.93.


Page 954

3) Procedure Firstly, the third year chemical engineering class

which consists of 38 students was initially randomly divided into two groups of equal size, groups A and B. Therefore, there was no sampling error as the entire population was used for this study based on the small size of the groups. However, due to absenteeism of some participants in both groups, the group sizes had to be revised to capture those who actually took part in the study. That is, those who were present for at least half of the sessions. In the final analysis Group A was reduced to 17 members while Group B reduced to 14 members. Both groups had two hours of joint lecture and one hour of separate tutorial sessions each week. It is in these tutorial sessions that the variation in instructional strategies was employed. Group A was used as the traditional lecturing group while Group B was the active learning group. In the traditional lecturing sessions, there were no active learning exercises or cooperative/collaborative group activities. PowerPoint slides presentation was used to deliver lessons and one of the researchers solved all examples on the whiteboard. Socratic questions were asked during lecture and volunteer answers solicited. Conversely, in the active learning sessions for group B, active learning strategies in the form of cooperative and collaborative exercises were employed. Students worked together on problems in a small group setting until all members of the group understood the problem and completed it. The main class activities used included the jigsaw method, think-pair-share, round robin, brainstorming and debates to name a few. In order to assess students performance two midterm tests and a comprehensive final examination were administered. The first midterm test was given at the end of the second unit and the other at the end of the fourth unit while the final examination, which covered the entire module content, was given at the end of the module.

III. RESULTS

a) Research question 1: Which of the two instructional approaches (active learning and traditional lecturing strategy) used for teaching Particle Technology students yields better students academic performance?

To answer this question, the mean of participants score on each instrument was calculated for each group and then compared. Fig. 1 presents a comparison between the mean score of group A and group B participants on each of the instruments.

As can be seen in Fig. 1, the results indicate that students taught with traditional lecturing (group A) yielded better academic performances than those taught with active learning strategies (group B) on all the instruments. The largest difference between the mean performance of each group was observed in test 2 (20.9 percentage points) while the difference in the mean performance of both groups in test 1 and the final examination were approximately equal (18.1 percentage points on test 1 compared to 18.4 percentage points on the final examination).

Fig. 1. Mean scores for group A and group B participants on each test instrument.

b) Research question 2: Do Particle Technology students significantly differ in their academic performances based on the two methods of teaching (active learning and traditional lecturing strategy) used?

To answer this question, participants performances on the various test instruments were subjected to an independent t-test analysis to establish whether the difference between the performances of participants taught with traditional lecturing (group A) and those taught with active learning strategies (group B) was significant. This analysis was carried out using the SPSS software applications with a confidence interval of 95% ( = 0.5).

As can be seen in Table 1, there was a significant difference in the scores for group A and group B participants on all three assessments, with group A participants recording higher scores than those in group B. These results suggest that active learning strategies do not have a positive effect on participants performance. Specifically, the results suggest that when traditional lecturing is used, participants performance improved.

TABLE 1: T-TEST ANALYSIS OF PARTICIPANTS SCORE ON EACH ASSESSMENT

Ass

essm

ent

Gro

up

N

Mea

n

Std.

Dev

.

t df

Sig.

(2

-tai

led)

A 17 56.12 17.87 Test 1

B 14 38.04 18.58 2.75 29 0.010

A 17 82.82 11.77 Test 2

B 14 61.93 19.84 3.47 20.25 0.002

A 17 66.24 14.42 Final Exam B 11 47.82 19.31 2.89 26 0.008


Page 955

c) Research question 3: Do Particle Technology students taught with active learning strategies and traditional lecturing significantly differ in their academic performances based on gender?

In order to establish whether the observed differences between the mean performances of male and female participants taught with traditional lecturing (group A) and those taught with active learning strategies (group B) was significant, the data was subjected to an independent t-test analysis using the SPSS software application with a confidence interval of 95% ( = 0.5).

Table 2 presents the results of the statistical analysis conducted on the mean scores of female participants in groups A and group B on each assessment. As can be seen, there was a significant difference between the scores of group A and group B female participants on midterm Test 1 and the Final Examination. These results suggest that female participants taught with traditional learning performed significantly better than their counterparts taught with active learning strategies. However, for midterm Test 2, there was no significant difference between the scores for group A (M=89.43, SD=8.87) and group B (M=75.50, SD=18.35) female participants; t (11) = 1.789, p = 0.101. This suggests that there is no significant difference between the performance of female participants taught with traditional learning and those taught with active learning strategies.

Table 3 presents the results of the statistical analysis conducted on the mean scores of male participants in groups A and B on each assessment. As can be seen, there was a significant difference in the scores for group A and group B male participants on all three assessments with group A participants recording higher scores than those in group B. These results suggest that active learning strategies do not have a positive effect on male participants performance. Specifically, the results of the analysis suggest that male participants taught with traditional learning performed significantly better than their counterparts taught with active learning strategies.

TABLE 2: T-TEST ANALYSIS OF FEMALE PARTICIPANTS SCORE ON EACH ASSESSMENT

Ass

essm

ent

Gro

up

N

Mea

n

Std.

Dev

.

t df

Sig.

(2

-tai

led)

A 7 70.29 12.98 Test 1

B 6 46.33 21.66 2.465 11 0.031

A 7 89.43 8.87 Test 2

B 6 75.50 18.35 1.789 11 0.101

A 7 69.86 12.56 Final Exam B 6 54.00 13.16

2.220 11 0.048

TABLE 3: T-TEST ANALYSIS OF MALE PARTICIPANTS SCORE ON EACH ASSESSMENT

Ass

essm

ent

Gro

up

N

Mea

n

Std.

Dev

.

t df

Sig.

(2

-tai

led)

A 10 46.20 13.78 Test 1

B 8 31.82 14.24 2.169 16 0.045

A 10 78.20 11.67 Test 2

B 8 51.75 14.64 4.273 16 0.001

A 10 63.70 15.72 Final Exam

B 5 40.00 24.29 2.266 13 0.041

IV. DISCUSSION From the results, it can be seen that the test

instruments showed a high level of content validity and reliability. This can be attributed to the fact that all instruments were constructed to be in close agreement with the module outline. Therefore, individual test items were designed to assess one or more specific objectives to determine if the participants have satisfied the desired learning outcomes. The statistical analysis conducted on both mid-semester examinations as well as the final examination found p values ranging from 0.001 to 0.01 which indicates that there was a significant difference between the mean of both groups. In all three instances, the mean for Group A (ranging from 56.12 to 82.82) was found to be higher than that of Group B (ranging from 38.04 to 61.93). These findings indicate that participants taught with traditional instructional strategies performed better than those taught with active learning strategies. Since these assessments were announced well in advance, participants had sufficient time to build on the concepts they were introduced to in the various sessions. Therefore, the results could be interpreted to suggest that participants in the active learning group (Group B) did not sufficiently grasp the basic concepts being conveyed and therefore could not make significant addition to their knowledge base. These findings disagreed with that of [6] who examined the performance of over 90 students in five chemical engineering courses and found significantly improved performance for students in classes with extensive use of active and cooperative learning techniques as opposed to students taught using the traditional approach. The active learning group outperformed the control group on several measures among which are retention and graduation in chemical engineering. Additionally, a significantly larger number of the graduates in this group opted to pursue further study in chemical engineering. It must be noted however, that [6] conducted a longitudinal study, which spanned the entire period of the participants course of study. This would have given the participants the opportunity to fully develop an appreciation for the active learning strategies. This argument is supported by [8], who provided strong arguments to suggest that training participants to be effective team member will increase the probability of success when using cooperative learning groups.


Page 956

The data analysis also revealed that male and female participants taught with traditional lecturing (group A) performed better than their counterparts taught with active learning strategies (group B). Female students taught with traditional lecturing achieved up to 24.0 percentage point higher academic performance when compared to their female counterparts taught with active learning strategies. Similarly, male participants taught with traditional lecturing achieved up to 26.4 percentage point higher academic performance when compared to their male counterparts taught with active learning strategies. These findings are in contradiction to that conducted by [5] which examined the impact of instructor-centered versus learner-centered instructional strategy on students learning in two online courses and found no significant difference across treatment groups. The lower academic performance witnessed among participants taught with active learning strategies could be due to the fact that this was the first time they have been involved with the use of active learning strategies on such an extensive basis. Reference [9] conducted a study in which the effect of utilizing large, medium and small amounts of group work on achievement was investigated and found positive effect sizes associated with large, medium and small amount of time in groups to be 0.53, 0.73 and 0.52, respectively. Interestingly, the highest achievement was not found for large time in groups but for medium time in groups. This suggests that the use of extensive group work will not necessarily result in higher performance. Rather a balance between group and individual work should be sought. One possibility is the fact that, too much group work can lead to some members not being given a chance to process the material in their own time (self-discovery) but rather being told the solutions by other members. This could then lead to some members of the group not being able to properly develop their critical thinking capabilities. In addition, the participants were being exposed, almost exclusively, to traditional instructional methods over their previous two years at the university. Even during the period of this study, participants were enrolled in other module in which instructors also used traditional methods. Since these methods allow participants to remain passive, they could view active learning strategies in a negative light by requiring them to do more work. This could also explain the lower level of attendance recorded for the active learning group (Group B) when compared to the group exposed to traditional methods (Group A). Additionally, the introduction of different active learning strategies could also have resulted in some of the participants being more fascinated and grossly involved with the social interaction aspects so much that they lost tract of the main objectives of the lesson, thus achieving lower academic performances.

Another important factor, which could greatly influence the performance of the participants, is their average class attendance. As was presented in the results, the average attendance for participants taught with traditional learning strategies (Group A) was found to be 66% while that observed for the participants taught with active learning strategies (Group B) was 58%. Therefore, the consistently higher scores recorded by Group A participants (male and female) when compared to their counterparts in group B could be attributed to their higher rate of class attendance which resulted in them

having a longer contact time with one of the researchers who in this case was the lecturer directly involved with the module. This low average attendance observed for participants in this study can also be linked to the universitys policy, which regards students as adult learners capable of making responsible decision, and therefore does not mandate students to attend class.

While these results contradicts many of the studies conducted as seen in the review of the literature for instance, [1] cautioned that educational studies only tell us what worked, on average, and specifically for the populations examined. Educators should not expect that simply adopting a particular educational method will result in similar learning outcomes to those reported in educational studies as the practical limitations of these studies and the complex nature of the learning process must also be considered. This complexity of interpreting research finding was highlighted by [5] who measured small improvements of discussion over lecture in his study but still conceded that the principles lacked substantial evidence with respect to empirical support for active learning.

V. CONCLUSION AND RECOMMENDATIONS Although the increasing body of educational research

seems to suggest that active learning strategies prove to be more effective than traditional lecturing methods, whether that premise holds for teaching engineering modules is yet to be determined. In this study, active learning strategies were evaluated with a view to determine if they were, indeed, more effective than traditional lecturing in improving students academic performance in an engineering module and, if so, to what extent. The research findings revealed that there is a significant difference between the academic performances of Particle Technology students based on the two methods of teaching (active learning and traditional lecturing strategy) used, which favors traditional lecturing. The revelation persisted even when students academic performances were compared based on gender. Interestingly though, male and female Particle Technology students taught with traditional lecturing approach significantly differ in their academic performances while male and female students taught with active learning strategies did not differ significantly in their academic performances. Thus, the findings of this study provide empirical evidence contrary to common beliefs about the greater effectiveness of active learning strategies compared with traditional lecturing in developing students engineering skills.

Based on the findings of this study, the following recommendations were made:

1. Students should be sensitized as to the nature of active learning strategies as well as possible benefits in order to alleviate concerns of additional workload and limited supports.

2. Particle Technology teachers should not rely completely on active learning strategies but rather recognize the value of traditional lecturing as an effective learning strategy in order to improve students performances.


Page 957

3. Future studies should be conducted with appropriate measures in place to achieve comparable attendance among the students in both study groups. This would convincingly remove any potential confounding effects associated to attendance, and would reaffirm or refute this finding.

4. Again, because this approach has not been tried on other engineering modules other than Particle Technology, doing so is highly recommended especially on varied population and sample size in order to authenticate further this finding.

5. Further research in this area is also warranted which should focus on understanding the characteristics of female students that possibly resulted in them exhibiting enhanced learning under both models when compared to their male counterparts.

6. The study also recommends that a replication of this experiment be done in other occupational education areas such as Technical and Vocational Education modules which share certain characteristics with engineering in order to confirm or refute these findings.

VI. REFERENCES [1] M. Prince, Does active learning work? A review of the research.

Journal of Engineering Education , vol. 93, no.3, pp. 223-231, 2004. [2] S. R. Hall, I.Waitz, D. R. Brodeur, D. H. Soderholm, & R.Nasr,

Adoption of active learning in a lecture-based engineering class. 32nd ASEE/IEEE Frontiers in Education Conference. Boston:MA, 2002.

[3] L. B. Nilson, Teaching at its best: A research-based resource for college instructors 2nd ed., San Francisco, CA: Anker Publishing Company, Inc. 2003.

[4] A. R. Mohamed, Effects of active learning variants on student performance and learning perceptions. International Journal for the Scholarship of Teaching and Learning , vol. 2, no.2, pp. 1-14, 2008.

[5] R. Sweat-Guy, & C. Wishart, A longitudinal analysis of the effects of instructional strategies on student performance in traditional and e-learning formats. Issues in Informing Science and Information Technology , vol. 5, pp. 149-163, 2008.

[6] R. M. Felder, A longitudinal study of engineering student performance and retention V: Comparisons with traditionally-taught students. Journal of Engineering Education , vol. 87, pp. 469-480, 1998.

[7] R. M. Felder, & R. Brent, Effective strategies for cooperative learning. The Journal of Cooperation and Collaboration in College Teaching , vol. 10, pp. 69-75, 2001.

[8] D. Johnson, R. Johnson, & K. Smith, Cooperative learning returns to college: What evidence is there that it works? Change, vol. 30, pp. 2635, 1998.

[9] L. Springer, M. Stanne, & S. Donovan, Effects of small-group learning on undergraduates in Science, Mathematics, Engineering and Technology: A meta-analysis. Review of Educational Research, vol. 69, no.1, pp. 2152, 1999.

[10] E. B. Kolawole, Effects of competitive and cooperative learning strategies on academic performance of Nigerian students in mathematics. Educational Research and Review, vol. 3, pp. 033-037, 2008.

[11] P. T. Terenzini, A. F. Cabrera, C. L. Colbeck, J. M. Parente, & S. A. Bjorklund, Collaborative learning vs. lecture/discussion: Students reported learning gains. Journal of Engineering Education , pp. 123-130, 2001.

[12] W. Trochim, The research methods knowledge base, 2nd ed., Cincinnati, OH: Atomic Dog Publishing, 2000.

[13] C. H. Lawshe, A quantitative approach to content validity. Personnel Psychology, vol. 28, pp. 563-575, 1975.


Page 958

Contribution1350_b