The Effect of Instruction Based on Cognitive Load theory on Academic Achievement, Perceived Cognitive Load and Motivation to Learning in Science Courses
Subject Areas : Educational Psychology
Ali Abdi
1
(
استادیار و هیئت علمی گروه علوم تربیتی دانشگاه پیام نور
)
Maryam Rostami
2
(
دانشجوی دکتری
)
Keywords: Cognitive Load Theory, motivation towards science course, perceived cognitive load,
Abstract :
The purpose of this study was to investigate the effect of instruction based on cognitive load theory on academic achievement, perceived cognitive load and motivation to learning in science courses. The method of research was a quasi-experimental with non-equivalent groups, which includes pre and post-test design with the control group. A total of 58 sixth grade students from two different classes were involved in the study (experimental group N=28 and control group N=23). They were selected through available sampling. The experimental group were trained through the science course syllabus based on cognitive load effects (Worked Example Effect and Completion Problem Effect, Attention Split Effect, Modality Effect, Redundancy effect) and the control group through traditional and common teaching methods for six weeks. For collecting the data, a teacher-made achievement test on sciences which consisted of 20 multiple choice questions and a motivation toward sciences questionnaire were applied. Also, at the end of each unit, the Subjective Rating Scale (SRS) was used to measure the students’ cognitive load. Both descriptive and inferential statistical (ANCOVA) techniques were used for analyzing the data. The results showed that instruction designed by CLT principles was effective for teaching sciences. Also, the findings showed that students in the experimental group developed more positive motivation towards science after the treatment.
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Akbas A., & KAN A. (2007) Affective Factors that Influence Chemistry Achievement (Motivation and Anxiety) and the Power of These Factors to Predict Chemistry Achievement-II, Journal of Turkish Science Education, 4(1), 10-19
Atkinson, R., Renkl, A., & Merrill, M. (2003). Transitioning from studying examples to solving problems: Effects of self-explanation prompts and fading worked-out steps. Journal of Educational Psychology, 95(4), 774-783.
Ayres, P., & Paas, F. (2012). Cognitive load theory: New directions and challenges. Applied Cognitive Psychology, 26, 827– 832. DOI: http://dx.doi.org/10.1002/ acp.2882
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Clark, R. C., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco: Pfeiffer.
Clarke, T., Ayres, P., & Sweller, J. (2005). The impact of sequencing and prior knowledge on learning mathematics through spreadsheet applications. Educational Technology Research and Development, 53(3), 15-24.
Cowan, N. (2005). Working memory capacity: Psychology,PressNew York.
De Jong, T. (2010). Cognitive Load Theory, Educational Research and Instructional Designs: Some Food for More Thought. Instructional Science,38, 105-134.
Erb, M. (1996). Increasing students’ responsibility for their learning through multiple intelligence activities and cooperative learning. [Unpublished master’s thesis]. Saint Xavier University, IL.
Glover, J. M., & Bruning, R. H. (1990). Educational psychology: Principles and Application. Boston: Little, Brown.
Glynn, S. M., Taasoobshirazi, G., & Brickman, P. (2008). Science Motivation Questionnaire: Construct Validation with Nonscience Majors. Journal of Research in Science Teaching. Published online in Wiley InterScience (www.interscience.wiley.com).
Haj Hosseini. M., & Akhavan, M. (2007). The relationship between learning strategies and academic achievement in math, physics, science, and humanities. Educational and Psychological Research University of Isfahan. 3(2), 73-90 [In Persian].
Jalani, N. H., & Chee sern, L. (2014). Effects of example-problem based learning on transfer performance in Circuit Theory. Journal of Technical Education and Training, 6(2), 28–37.
Jalani, N. H., & Chee sern, L. (2015). The Example-Problem-Based Learning Model: Applying Cognitive Load Theory. Procedia- Social and Behavioral Sciences, 195, 872-880
Kalyuga, S. (2011). Cognitive load theory: how many types of load does it really need? Educational Psychology Review, 23, 1–19. DOI: http://dx.doi.org
Karimi, A., Bakhshalizadhe, S., & Kabiri, M. (2012). Report on the most important results of TIMSS & PIRLS 2011, comparing it with Iranian students' performance in the previous period. Research and Educational Administration. Institute of Education Studies. DOI: http:\\www.rie.ir [In Persian].
Kiamanesh, A. R. (2006). The role of students’ characteristics and family background in Iranian students’ mathematics achievement. Contexts of learning mathematics and sciences, lessons learned from TIMSS. London & New York Routhedge.
Kiamanesh, A., & Noori, R. (1999). The results of the third international study TIMSS: primary school science. Tehran: Publish Education Research Institute [In Persian].
Kuldas, S., Satyen, L., Ismail, H, N., & Hashim. (2014). Greater Cognitive Effort for Better Learning: Tailoring an Instructional Design for Learners with Different Levels of Knowledge and Motivation. Psychological Belgic, 54(4), 350-373, DOI:http://dx.doi.org/10.5334/pb.aw
Leahy, W., Chandler, P., & Sweller, J. (2003). When auditory presentations should and should not be a component of multimedia instruction. Applied Cognitive Psychology, 17(4), 401-418.
Lee, A. & Boyle, P. (2008) Quality assurance for learning and teaching: A systemic perspective. Ideas on Teaching, 6, 82–94
Lee, O., & Brophy, J. (1996). Motivational patterns observed in sixth-grade science classrooms. Journal of Research in Science Teaching, 33(3), 585–610.
Angell, C., Kjaernsli, M., & Lie, S. (2000). Exploring student responses on free-response scienceitems in TIMSS: Learning from others, international comparisons ineducation. Book Chapter, Publishers: Science and Technology Education Library. 8, 159-187.
Mayer, R. E. (Ed.) (2005). The Cambridge Handbook of Multimedia Learning. Cambridge: Cambridge University Press
McLaren, B, M., van Gog, T., Ganoe, C., Karabinos, M., Yaron, D. (2016). The efficiency of worked examples compared to erroneous examples, tutored problem solving, and problem solving in computer-based learning environments. Computers in Human Behavior, 55, 87-99
Mosaramezani, S., Kanani, E., & Velayati, E. (2013). Investigating the control of cognitive load imposed on memory on the learning and retention of English grammar. New Thoughts on Education, 9(1), 105-132 [In Persian].
Mousavi, S., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319-334.
Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38, 1–4.
Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32(1), 1-8.
Paas, F., Tuovinen, J. E., Van Merriënboer, J. J. G., & Darabi, A. A. (2005). A motivational perspective on the relation between mental effort and performance: Optimizing learner involvement in instruction. Educational Technology Research and Development, 53, 25–34. DOI: http://dx.doi.org
Paas, F., van Gog, T., & Sweller, J. (2010). Cognitive load theory: New conceptualizations, specifications, and integrated research perspectives. Educational Psychology Review, 22(2), 115-121.
PIRLS & TIMSS International Study Center (2009). The most significant findings of TIMSS & PIRLS (Karim, A). Available on the website of the National Center for TIMSS & PIRLS studies [In Persian].
Redman, BK. (1997) The Practice of Patient Education. (8th ed.). USA: Mosby.
Renkl, A., & Atkinson, R. (2003). Structuring the transition from example study to problem solving in cognitive skill acquisition: A cognitive load perspective. Educational Psychologist, 38(1), 15-22.
Roets, A., & Van Hiel, A. (2011). Impaired performance as a source of reduced energy investment in judgement under stressors. Journal of Cognitive Psychology, 23, 625–632.
Saif, Ali Akbar (2011), Educational Psychology, (8th ed.), Davran Publication, Tehran [In Persian].
Salari. M., Amirtimori. M. H., Zaree. Z. A. (2016). The effectiveness four-component instructional design model on the external cognitive load and problem solving skills in physics courses. Quarterly Journal of New Thoughts in Education, 12 (1),117- 142 [In Persian].
Sarmadi, M.R., Saif, M.H., Talebi, S., Abedi, S. (2010). To investigate the factors associated with third-grade highschool students’ academic achievement, based on the results of the TIMSSR and present path analysis model to assess the impact of each factor on academic achievement. Journal of Modern Educational Approaches, 5(1), 1-30 [In Persian].
Schnotz, W. (2010). Reanalyzing the expertise reversal effect. Instructional Science, 38, 315–323.
Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19(4), 469-508.
Schnotz, W., Fries, S., & Horz, H. (2009). Motivational aspects of cognitive load theory. In M. Wosnitza, S. A. Karabenick, A. Efklides, & P. Nenniger (Eds.), Contemporary motivation research: From global to local perspectives(pp. 69–96). New York.
Senko, C., Hulleman, C. S., & Harackiewicz, J. M. (2011). Achievement goaltheory at the crossroads: Old controversies, current challenges, and new directions. Educational Psychologist, 46, 1, 26–47.
Sweller, J. (1999). From cognitive architecture to instructional design. Paper presented at the Inaugural Seminar of Professor J.G. van Merrie¨nboer, Heerlen, The Netherlands.
Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science, 32, 9-31.
Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123-138.
Sweller, J., Van Merriënboer, J., & Paas, F. (2004). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-296.
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Tabbers, H. K., Martens, R. L., & Merriënboer, J. J. G. (2004). Multimedia instructions and cognitive load theory: Effects of modality and cueing. British Journal of Educational Psychology, 74(1), 71-81.
Takir, A., & Aksu, M., (2012). The Effect of an Instruction Designed by Cognitive Load Theory Principles on 7th Grade Students’ Achievement in Algebra Topics and Cognitive Load. Journal of Creative Education. (3) 2, 232-240.
Tarmizi, R. A., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80(4), 400-424.
Tella, A. (2007). The Impact of Motivation on Student’s Academic Achievement and Learning Outcomes in Mathematics among Secondary School Students in Nigeria; Eurasia Journal of Mathematics, Science & Technology Education, 3(2), 149-156.
Tuan, h. l., chin, c. c., shieh, s. h. (2006). The development of a questionnaire to measure students’ motivation towards science learning. International Journal of Science Education, 27(6), 639–654.
Van Merriënboer, J., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147-177.
Van Merrinbur, J., & Ayres, P. (2005). Research On Cognitive Load Theory and Its Design Implication for E-Learning. Educational Technology Research and Developmen (ETR & D.), 53(3).5-13.
Vollmeyer, R., & Rheinberg, F. (2000). Does motivation affect performance via persistence? Learning and Instruction, 10, 293-309.
Zare M., Sarikhani R., & Mehraban J. (2015). Investigation the impact of educational multimedia designed on the principles of cognitive load on learning and retention in teaching biology. Journal of Analytical Cognitive Psychology, 6(22), 61-68 [In Persian].
Zare M. (2014). Investigation extraneous cognitive load multimedia instruction methods based on the model of Instructional Design Merrill. [Unpublished Master Thesis]. Allameh Tabatabei University. [In Persian].
Zare, H., Sarmadi, M. R., Fardanesh. H., Feizi. A., & Mahboobi, T. (2012). Effectiveness of Instructional Design Principles Applied to Learning and Retention in Multimedia Learning Environments. Biennial Journal of Management and Planning in Educational Systems, 5(8), 9-27 [In Persian].
Zhu, X., & Simon, H. A. (1987). Learning mathematics from examples and by doing. Cognition and Instruction, 4(3), 137-166.
_||_Akbas A., & KAN A. (2007) Affective Factors that Influence Chemistry Achievement (Motivation and Anxiety) and the Power of These Factors to Predict Chemistry Achievement-II, Journal of Turkish Science Education, 4(1), 10-19
Atkinson, R., Renkl, A., & Merrill, M. (2003). Transitioning from studying examples to solving problems: Effects of self-explanation prompts and fading worked-out steps. Journal of Educational Psychology, 95(4), 774-783.
Ayres, P., & Paas, F. (2012). Cognitive load theory: New directions and challenges. Applied Cognitive Psychology, 26, 827– 832. DOI: http://dx.doi.org/10.1002/ acp.2882
Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293-332.
Clark, R. C., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco: Pfeiffer.
Clarke, T., Ayres, P., & Sweller, J. (2005). The impact of sequencing and prior knowledge on learning mathematics through spreadsheet applications. Educational Technology Research and Development, 53(3), 15-24.
Cowan, N. (2005). Working memory capacity: Psychology,PressNew York.
De Jong, T. (2010). Cognitive Load Theory, Educational Research and Instructional Designs: Some Food for More Thought. Instructional Science,38, 105-134.
Erb, M. (1996). Increasing students’ responsibility for their learning through multiple intelligence activities and cooperative learning. [Unpublished master’s thesis]. Saint Xavier University, IL.
Glover, J. M., & Bruning, R. H. (1990). Educational psychology: Principles and Application. Boston: Little, Brown.
Glynn, S. M., Taasoobshirazi, G., & Brickman, P. (2008). Science Motivation Questionnaire: Construct Validation with Nonscience Majors. Journal of Research in Science Teaching. Published online in Wiley InterScience (www.interscience.wiley.com).
Haj Hosseini. M., & Akhavan, M. (2007). The relationship between learning strategies and academic achievement in math, physics, science, and humanities. Educational and Psychological Research University of Isfahan. 3(2), 73-90 [In Persian].
Jalani, N. H., & Chee sern, L. (2014). Effects of example-problem based learning on transfer performance in Circuit Theory. Journal of Technical Education and Training, 6(2), 28–37.
Jalani, N. H., & Chee sern, L. (2015). The Example-Problem-Based Learning Model: Applying Cognitive Load Theory. Procedia- Social and Behavioral Sciences, 195, 872-880
Kalyuga, S. (2011). Cognitive load theory: how many types of load does it really need? Educational Psychology Review, 23, 1–19. DOI: http://dx.doi.org
Karimi, A., Bakhshalizadhe, S., & Kabiri, M. (2012). Report on the most important results of TIMSS & PIRLS 2011, comparing it with Iranian students' performance in the previous period. Research and Educational Administration. Institute of Education Studies. DOI: http:\\www.rie.ir [In Persian].
Kiamanesh, A. R. (2006). The role of students’ characteristics and family background in Iranian students’ mathematics achievement. Contexts of learning mathematics and sciences, lessons learned from TIMSS. London & New York Routhedge.
Kiamanesh, A., & Noori, R. (1999). The results of the third international study TIMSS: primary school science. Tehran: Publish Education Research Institute [In Persian].
Kuldas, S., Satyen, L., Ismail, H, N., & Hashim. (2014). Greater Cognitive Effort for Better Learning: Tailoring an Instructional Design for Learners with Different Levels of Knowledge and Motivation. Psychological Belgic, 54(4), 350-373, DOI:http://dx.doi.org/10.5334/pb.aw
Leahy, W., Chandler, P., & Sweller, J. (2003). When auditory presentations should and should not be a component of multimedia instruction. Applied Cognitive Psychology, 17(4), 401-418.
Lee, A. & Boyle, P. (2008) Quality assurance for learning and teaching: A systemic perspective. Ideas on Teaching, 6, 82–94
Lee, O., & Brophy, J. (1996). Motivational patterns observed in sixth-grade science classrooms. Journal of Research in Science Teaching, 33(3), 585–610.
Angell, C., Kjaernsli, M., & Lie, S. (2000). Exploring student responses on free-response scienceitems in TIMSS: Learning from others, international comparisons ineducation. Book Chapter, Publishers: Science and Technology Education Library. 8, 159-187.
Mayer, R. E. (Ed.) (2005). The Cambridge Handbook of Multimedia Learning. Cambridge: Cambridge University Press
McLaren, B, M., van Gog, T., Ganoe, C., Karabinos, M., Yaron, D. (2016). The efficiency of worked examples compared to erroneous examples, tutored problem solving, and problem solving in computer-based learning environments. Computers in Human Behavior, 55, 87-99
Mosaramezani, S., Kanani, E., & Velayati, E. (2013). Investigating the control of cognitive load imposed on memory on the learning and retention of English grammar. New Thoughts on Education, 9(1), 105-132 [In Persian].
Mousavi, S., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319-334.
Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38, 1–4.
Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32(1), 1-8.
Paas, F., Tuovinen, J. E., Van Merriënboer, J. J. G., & Darabi, A. A. (2005). A motivational perspective on the relation between mental effort and performance: Optimizing learner involvement in instruction. Educational Technology Research and Development, 53, 25–34. DOI: http://dx.doi.org
Paas, F., van Gog, T., & Sweller, J. (2010). Cognitive load theory: New conceptualizations, specifications, and integrated research perspectives. Educational Psychology Review, 22(2), 115-121.
PIRLS & TIMSS International Study Center (2009). The most significant findings of TIMSS & PIRLS (Karim, A). Available on the website of the National Center for TIMSS & PIRLS studies [In Persian].
Redman, BK. (1997) The Practice of Patient Education. (8th ed.). USA: Mosby.
Renkl, A., & Atkinson, R. (2003). Structuring the transition from example study to problem solving in cognitive skill acquisition: A cognitive load perspective. Educational Psychologist, 38(1), 15-22.
Roets, A., & Van Hiel, A. (2011). Impaired performance as a source of reduced energy investment in judgement under stressors. Journal of Cognitive Psychology, 23, 625–632.
Saif, Ali Akbar (2011), Educational Psychology, (8th ed.), Davran Publication, Tehran [In Persian].
Salari. M., Amirtimori. M. H., Zaree. Z. A. (2016). The effectiveness four-component instructional design model on the external cognitive load and problem solving skills in physics courses. Quarterly Journal of New Thoughts in Education, 12 (1),117- 142 [In Persian].
Sarmadi, M.R., Saif, M.H., Talebi, S., Abedi, S. (2010). To investigate the factors associated with third-grade highschool students’ academic achievement, based on the results of the TIMSSR and present path analysis model to assess the impact of each factor on academic achievement. Journal of Modern Educational Approaches, 5(1), 1-30 [In Persian].
Schnotz, W. (2010). Reanalyzing the expertise reversal effect. Instructional Science, 38, 315–323.
Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19(4), 469-508.
Schnotz, W., Fries, S., & Horz, H. (2009). Motivational aspects of cognitive load theory. In M. Wosnitza, S. A. Karabenick, A. Efklides, & P. Nenniger (Eds.), Contemporary motivation research: From global to local perspectives(pp. 69–96). New York.
Senko, C., Hulleman, C. S., & Harackiewicz, J. M. (2011). Achievement goaltheory at the crossroads: Old controversies, current challenges, and new directions. Educational Psychologist, 46, 1, 26–47.
Sweller, J. (1999). From cognitive architecture to instructional design. Paper presented at the Inaugural Seminar of Professor J.G. van Merrie¨nboer, Heerlen, The Netherlands.
Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science, 32, 9-31.
Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123-138.
Sweller, J., Van Merriënboer, J., & Paas, F. (2004). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-296.
Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185–233.
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. Publisher Springer, New York.
Sweller, J., Van Merrienboer, J. J. G., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251-296.
Tabbers, H. K., Martens, R. L., & Merriënboer, J. J. G. (2004). Multimedia instructions and cognitive load theory: Effects of modality and cueing. British Journal of Educational Psychology, 74(1), 71-81.
Takir, A., & Aksu, M., (2012). The Effect of an Instruction Designed by Cognitive Load Theory Principles on 7th Grade Students’ Achievement in Algebra Topics and Cognitive Load. Journal of Creative Education. (3) 2, 232-240.
Tarmizi, R. A., & Sweller, J. (1988). Guidance during mathematical problem solving. Journal of Educational Psychology, 80(4), 400-424.
Tella, A. (2007). The Impact of Motivation on Student’s Academic Achievement and Learning Outcomes in Mathematics among Secondary School Students in Nigeria; Eurasia Journal of Mathematics, Science & Technology Education, 3(2), 149-156.
Tuan, h. l., chin, c. c., shieh, s. h. (2006). The development of a questionnaire to measure students’ motivation towards science learning. International Journal of Science Education, 27(6), 639–654.
Van Merriënboer, J., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147-177.
Van Merrinbur, J., & Ayres, P. (2005). Research On Cognitive Load Theory and Its Design Implication for E-Learning. Educational Technology Research and Developmen (ETR & D.), 53(3).5-13.
Vollmeyer, R., & Rheinberg, F. (2000). Does motivation affect performance via persistence? Learning and Instruction, 10, 293-309.
Zare M., Sarikhani R., & Mehraban J. (2015). Investigation the impact of educational multimedia designed on the principles of cognitive load on learning and retention in teaching biology. Journal of Analytical Cognitive Psychology, 6(22), 61-68 [In Persian].
Zare M. (2014). Investigation extraneous cognitive load multimedia instruction methods based on the model of Instructional Design Merrill. [Unpublished Master Thesis]. Allameh Tabatabei University. [In Persian].
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