The Effectiveness of an Interactive Multimedia Courseware with Cooperative Mastery Approach in Enhancing Higher Order Thinking Skills in Learning Cellular Respiration

Available online at www.sciencedirect.com

ScienceDirect Procedia - Social and Behavioral Sciences 176 (2015) 977 – 984

IETC 2014

The effectiveness of an interactive multimedia courseware with cooperative mastery approach in enhancing higher order thinking skills in learning cellular respiration Fazzlijan Mohamed Adnan Khana, Mona Masooda,* a,b

Centre for Instructional Technology and Multimedia, Universiti Sains Malaysia, Pulau Pinang, Malaysia

Abstract The main objective of this study is to integrate mastery and cooperative learning approaches together with an interactive multimedia to enhance students’ high order thinking skills in the learning of Cellular Respiration. A multimedia interactive courseware was developed and applied in three different strategies, namely the Multimedia-assisted Mastery Learning (MML), Multimedia-assisted Cooperative Learning (MCL) and Multimedia-assisted Cooperative Mastery Learning (MCML). The MML used a self-learning approach while MCL and MCML involve learning in groups. This study involved a quasi-experimental design whereby the domain scores of analysing, evaluating and synthesizing were the three dependent variables. The independent variable was the interactive multimedia courseware with the three approaches. Eighty-four, 88 and 90 preuniversity students went through the MML, MCL, and MCML respectively. The MANCOVA was applied to analyse the performance scores of each of the three higher order thinking skills based on the three approaches with the implemented courseware. The result revealed that the MML and MCML students performed significantly better in the creating domain score compared to MCL. Overall, the findings of this study suggest that the multimedia interactive courseware with the combination of mastery and cooperative learning approaches brings a positive effect in the learning of Cellular Respiration. © byby Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license © 2015 2015The TheAuthors. Authors.Published Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Sakarya University. Peer-review under responsibility of the Sakarya University. Keywords: multimedia learning, learning biology, multimedia-assisted learning, mastery learning, cooperative learning

* Mona Masood. Tel.: +6012-423-2559; fax: +604-657-6749. E-mail address: [email protected]

1877-0428 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the Sakarya University. doi:10.1016/j.sbspro.2015.01.567

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1. Introduction Biology education involves studying living organisms and how they interact with each other and their physical environment. Rice (2013) reported that biology was an abstract area which existed in unorganized structures and, therefore, it often results in students’ learning difficulties. Complex processes and the use of technical terms made it difficult to learn some topics such as cellular respiration (Patro, 2008; Rice, 2013). This subject contains many abstract concepts that are difficult to understand. As such students must be able to conceptualise and construct abstract concepts in biology in order to understand and make sense of them. Many students’ demonstrate common misconceptions concerning biology, including their understanding of topics such as cellular respiration, photosynthesis, ecology, genetic, classification and the human circulatory system (Tekkaya, 2002). Furthermore complex processes and the use of technical terms such as in the topic of cellular respiration, make them difficult to learn (Patro, 2008). Hence, it is important to design a high quality instructional system to enhance the teaching and learning of difficult and abstract topics as part of the subject of biology. Cooperative learning and mastery learning are two of the most used learning strategies which focus on different aspects of the teaching and learning processes. Since both strategies require the assessment of student learning to be criterion referenced, learning becomes non-competitive. Both strategies emphasize the teacher’s role as a facilitator by working with students closely to accomplish students’ learning goals. At the same time, these strategies are flexible in their applications. One the other hand, cooperative learning and mastery learning have been found to yield positive results in many studies (Grant, Fazarro, & Steinke, 2014; Guskey, 1997; Kulik, Kulik & BangertDrowns, 1990). Although each has its own characteristics, the aim of this study is to incorporate these two strategies to produce and enhance an effective learning environment. As suggested by Guskey (1990), the sum of its part (mastery learning and cooperative learning) creates a greater whole (cooperative mastery learning). Hence in this study, the researcher tries to embed the three learning strategies in a multimedia interactive courseware and seek the effectiveness in the learning of cellular respiration (Fig. 1). Multimedia Learning Environment x Represent Various of Mode x Interactivity x Dynamic of Media x Feedback x Keep and Retrieve Data

x x x x

Multimedia-assisted Mastery Learning (MML) Quality of instruction All have opportunity to learn successfully Ability to learn from mistake Courage and endurance

Multimedia-assisted Cooperative Learning (MCL) INTEGRATION x Positive MML + MCL = interdependence x Face-to-face promotive Multimedia-assisted interaction Cooperative Mastery x Individual Learning accountability (MCML) x Social skills x Group processing

Systematic design of instruction and active learning and will lead to : x Increase in learning engagement x Sufficient learning time x Identity own and peers weakness and for improvement Improvement of High Order Thinking Skill Achievement

Fig. 1. The Features of the MML, MCL and MCML Approaches in Multimedia Learning Environment

Fazzlijan Mohamed Adnan Khan and Mona Masood / Procedia - Social and Behavioral Sciences 176 (2015) 977 – 984

The cooperative structures could meet various needs of students by positive interdependence, positive interaction, accountability, social skills and group processing through three main processes. First, they gathered students in teams in where interpersonal interaction and cooperation were rewarded. Second, they provided the teacher with opportunities to concentrate on diversity in composing teams. Lastly, they allowed students from diverse backgrounds to contribute in a unique and individual way. In team activities, students are fully engaged to help each other by clarifying misunderstandings and correcting learning errors to achieve criterion-referenced standard. More importantly, students should be presented with the well-designed mastery learning instruction within a cooperative learning situation (Guskey, 1990; Zimmerman & DiBenedetto, 2008). Therefore, cooperative learning will be well coupled with mastery learning in where students in cooperative learning groups are guided through well-designed instruction. 2. Research objectives This research is mainly intended to integrate mastery and cooperative learning approaches in an interactive multimedia learning environment. The innovation used aimed to improve students’ biology achievement score for high order thinking skills in Revised Bloom’s Taxonomy, specifically on the topic of cellular respiration. The combination of all elements in mastery and cooperative learning within the interactive multimedia environment would offer a comprehensive learning experience needed for an effective and efficient teaching and learning of biology concepts. In this study an interactive multimedia courseware was systematically designed in three different approaches namely the Multimedia-assisted Mastery Learning (MML), Multimedia-assisted Cooperative Learning (MCL) and Multimedia-assisted Cooperative Mastery Learning (MCML). Students in the three learning approaches used the same instructional materials. The MML used a self-learning approach while both the MCL and MCML learned in groups. The mastery learning elements were embedded inside the MML and MCML courseware while the MCL omitted the mastery learning elements. The effects of the three learning approaches on achievement score of higher order thinking skill were investigated. Specifically the research question is: • Do students who receive MML, MCL and MCML strategies differ in terms of their achievement score for analyzing, synthesis and creating domain? 3. Research hypothesis Based on the research question, the hypotheses were therefore presumed as follows: H0 : There are no significant differences in the achievement score of Bloom’s high order thinking skills domain among students in the MML, MCL and MCML strategies H01: There are no significant differences in the achievement score of analyzing domain among students in the MML, MCL and MCML strategies H02: There are no significant differences in the achievement score of evaluating domain among students in the MML, MCL and MCML strategies H03: There are no significant differences in the achievement score of creating domain among students in the MML, MCL and MCML strategies

4. Methods In this section, the population, sampling and the multimedia interactive courseware are elaborated. 4.1 Subject This study adopted a quasi-experimental design. The sample of this study consists of Pre University students from three Matriculation Colleges in Malaysia. Their ages ranged from 18 to 19 years old. A total of 262 Matriculation Biology students participated in the research. Eighty-four students were assigned in the MML group, 88 students were in MCL group and 90 were in MCML group.

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4.2 Multimedia interactive courseware context The methodologies of mastery learning and cooperative learning were chosen because decades of research indicated both to be successful methodologies when employed with elementary, secondary, and undergraduate students (Guskey, 1997). Evidence indicated that both the cooperative learning and mastery learning gave positive results for cognitive outcomes (Guskey, 1997; Mevarech & Susak, 1993). The approach to design the interactive multimedia courseware was based on Bloom’s proposed mastery learning strategy, Mayer’s Cognitive Theory of Multimedia Learning, Alessi and Trollip’s instructional systems design, and Gagné’s nine conditions of learning. The content of the Cellular Respiration in the courseware embraced the Bloom’s revised taxonomy. Fig. 2 shows an example of the integration of the Cellular Respiration content within the cognitive domain respectively. High Order Thinking Skill

CREATING EVALUATING

Relation between fermentation process and muscle fatigue condition Compare amount of ATP produce in active and inactive cell.

ANALYZING

Differentiate between aerobic and anaerobic respiration

APPLICATION

Calculate the amount of ATP produce in muscle cell

UNDERSTANDING

Explain the stages of glycolysis

REMEMBERING

Name the enzyme involved and location of cellular respiration

Low Order Thinking Skill

Fig. 2. Example of Cellular Respiration Content Related to the Revised Bloom’s Taxonomy Domain The researcher developed the multimedia interactive courseware entitled "Cellular Respiration" by using Adobe Flash CS4 as the main authoring tool. A series of templates were created through rapid prototyping. The courseware was designed with mastery learning elements, which was used in the MML and MCML strategies. Conversely, during the MCL approach the mastery learning elements in the courseware were hidden and deactivated. Before conducting the experiments, the courseware was field-tested. These field tests served as an evaluation in which the courseware was revised through formative evaluations (beta and alpha test) and pilot test. Table 1 shows the comparison between the components in MML, MCL and MCML. Meanwhile Fig. 3 illustrates the flow chart of the courseware.

Fazzlijan Mohamed Adnan Khan and Mona Masood / Procedia - Social and Behavioral Sciences 176 (2015) 977 – 984

Table 1. Comparison Between Components in MML, MCL & MCML

Group Learning

Instructional Module

Formative Test A

Score ≥ 80

Corrective Activity

Formative Test B

Enrichment Activity

Summative Test

Score Feedback

MML

9

8

9

9

9

9

9

9

9

9

8

MCL

8

9

9

9

x

x

x

x

9

9

9

MCML

8

9

9

9

9

9

9

9

9

9

9

Strategy

Group Reward

Self Learning

Component

Fig. 3. Flow chart of Multimedia Interactive Courseware

5. Result and discussion As seen in Table 2, the descriptive statistic shows that the achievement mean score of the creating domain (Pre Test – Post Test) for students who used the MML (M=10.94) and MCML (M=10.67) was higher than the achievement mean score for the students using MCL (M= 9.06).

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Table 2. Descriptive statistics on achievement score of analyzing, evaluating and creating domain for MML, MCL and MCML Strategy Total Achievement Score of Analyzing Domain Achievement Score of Evaluating Domain Achievement Score of Creating Domain

MML

MCL

MCML

n

84

88

90

262

M

4.14

4.08

3.98

4.06

SD

1.20

1.17

1.19

1.87

n

84

88

90

262

M

4.36

4.35

4.43

4.48

SD n

1.38 84

1.50 88

1.37 90

1.41 262

M

10.94

9.06

10.67

10.21

SD

1.88

2.19

2.12

2.23

A multiple analysis of covariate (MANCOVA) was performed to investigate students’ achievement score (posttest) of the higher order thinking skills in the Revised Bloom’s Taxonomy. Three dependent variables were used (1) achievement score of the analysing domain, (2) achievement score of the evaluating domain, and (3) achievement score of the creating domain. The independent variable was the multimedia interactive courseware. Students’ achievement score of the analysing domain, the evaluating domain, and the creating domain on the pretest that was administered were used as the covariate in this analysis. Preliminary assumption testing was conducted to check for normality, linearity, univariate and multivariate outliers, homogeneity of variancecovariance matrices and multicollinerity, with no serious violations noted. The results of the MANOVA test (Table 2) showed that the Wilk’s lambda of 0.89 was significant, F = 5.02, p <0.05. Thus, hypothesis one (H01) , which stated that the population means on achievement score of Bloom’s higher order thinking skill domain variables (i.e., analyzing, evaluating and creating domain) were the same for the three groups, was rejected. Table 3. Multivariate test of the effect of learning strategies on the achievement score of Bloom’s high order thinking skill domain Effect Strategy

Value

F

Hypothesis df

Error df

p

Partial Eta Squared

Pillai’s Trace

.09

3.02

8

514

.00

.05

Wilks’ Lambda

.89

5.02

6

508

.00

.06

Hotelling’s Trace

.09

3.04

8

510

.00

.05

Roy’s Largest Root

.08

4.90

4

257

.00

.07

When the results for the dependent variables were considered separately (Table 4), using a Bonferroni adjusted level of .017, the mean score of the analyzing domain was not significant, F = 0.49, p > 0.025. Likewise, the results for the mean score of the evaluating domain was not significant, F= 0.15, p > 0.025. Both results showed that there were no significant differences of the analyzing and evaluating domain scores among the groups. Therefore, H01 and H02 were accepted. The only difference to reach statistical significance, was the mean score of creating domain, F = 14.48, p > 0.025. The result showed that there were significant differences of the creating domain score among the groups. Therefore, H03 was rejected.

Fazzlijan Mohamed Adnan Khan and Mona Masood / Procedia - Social and Behavioral Sciences 176 (2015) 977 – 984

Table 4. Test of Between Subjects Effects Source

Dependent Variable

Strategy

Analyzing Mean Score Evaluating Mean Score Creating Mean Score

Type III Sum of Squares 1.39 .61 123.72

Error

Analyzing Mean Score Evaluating Mean Score Creating Mean Score

362.11 510.39 1094.71

df

Mean Square

2 2 2

.69 .303 61.86

256 256 256

1.42 1.99 4.28

F

p

Partial Eta Squared

.49 .15 14.48

.61 .86 .00

.004 .001 .10

An inspection of the creating domain mean difference in Table 5 indicated that two groups differ significantly, (1) Group MML and MCL (p=.00, p<.05) and (2) Group MCML and MCL (p=.00, p<.05). The MML and MCML groups did not show any significant difference (p=.90, p>.05). Table 5. Comparison Mean Difference of Creating Domain for MML, MCL and MCML groups Mean

95% Confidence Interval

Difference (I) Strategy (J) Strategy

(I-J)

Std Error

pa-Value

Low Bound

Upper Bound

1 MML

1.67*

.34

.00

.91

2.82

3 MCML

.23

.32

.90

-.59

1.11

1 MML

-1.67*

.34

.00

-2.82

-.91

3 MCML

-1.44*

.33

.00

-2.37

-.84

1 MML

-.23

.32

.90

-1.11

.59

2 MCL

1.44*

.33

.00

.836

2.38

2 MCL

3 MCML

2 MCL

In summary, although mastery learning, MML (conducted systematically) was the most vital instructional method to make students succeed, it was better when supported by cooperative learning. This finding suggested that the advantages in cooperative learning were not obviously shown in the achievement scores without mastery learning, (MCL). This study showed that mastery learning plays a primary role and when incorporated with cooperative learning, the students will learn more in the cooperative environment. Some students may be weak in the socialization and interaction skills and may need guidelines when using the mastery learning approach. Likewise, some students need peer guidance during the learning process to achieve the higher order thinking skill. The slower learners need confidence in their ability to reach higher mastery standard. Based on that reason, students are not motivated to correct their learning problems in order to attain mastery. Through the use of cooperative learning, students can be provided with high quality corrective activities, assisted through their peers immediately following any formative test without waiting for the teachers’ help. Thus, students are highly engaged in their learning and are able to diagnose their weaknesses to solve higher order thinking problem. The students also learned the skill of seeking out help cooperatively and confidently. Also, learning in teams accelerates important incentives that will strengthen motivation and reduce anxiety. Furthermore, the use of student learning teams serves not only correctives but enrichment purposes as well.

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6. Conclusion In conclusion, this study demonstrates that that the MML and MCML strategies are superior compared to the MCL strategy to enhance higher order thinking skills especially for the creating domain. The findings of this study propose an easy but powerful approach through the use of a multimedia integrated learning courseware with a series of high quality instructions in mastery learning and cooperative mastery learning. Students that used MML and MCML are more capable to developing potential solution to solve high order thinking skill problem. We hope the results of this study can encourage more sciences teachers to incorporate cooperative mastery learning to enhance higher order thinking instruction. References Alessi, S. & Trollip, S. (2001). Multimedia for learning. New Jersey: Allyn and Bacon Aryana, M. (2010). Relationship between self-esteem and academic achievement amongst pre-university students. Journal of Applied Sciences, 10(20), 2174–2477. Bloom, B. (1984). The search for methods of group instruction as effective as one-to-one tutoring. Educational Leadership, 41(8), 4-18. Gagné, R. (1985). The conditions of learning and theory of instruction. Fort Worth: Holt, Rinehart and Winston, Inc. Grant, G., Fazarro, D. E. & Steinke, L. (2014). Application of problem based learning and mastery learning to multimedia Education. Online Journal for Workforce Education and Development,7 (1), 1- 17. Guskey, T. (1997). Implementing mastery learning. New York: Wadsworth Guskey, T. (2007). Closing achievement gaps: Revisiting Benjamin S. Bloom’s “Learning for Mastery”. Journal of Advanced Academics, 19(1), 8-31 Guskey, T. R. (1990). Cooperative mastery learning strategies. Outcomes, 9(3), 10-17. Kulik, J., Kulik, C. & Bangert-Drowns, R. (1990). Effectiveness of mastery learning programs: A meta-analysis. Review of Educational Research, 60(2), 265–299. Mayer, R. (2009). Multimedia learning (2nd Ed.). New York: Cambridge University Press. Mevarech, Z. R. & Susak, Z. (1993). Effects of learning with cooperative-mastery method on elementary students. Journal of Educational Research, 86(4), 197-205. Patro, T. (2008). Teaching aerobic cell respiration using the 5Es. The American Biology Teacher, 70 (2), 85-87 Rice, S. C. (2013). Tips and tools using interactive animations to enhance teaching, learning and retention of respiration pathway concepts in face-to-face. Journal of Microbiology and Biology Education, 14(1), 113–115. Tekkaya, C. (2002). Misconceptions as barrier to understanding biology. Journal of Education, 23, 259-266 Zimmerman, B. J., & DiBenedetto, M. K. (2008). Mastery Learning and assessment: Implications for students and teacher in an era of highstakes testing. Psychology in The Schools, 45(3), 206-216