EXPLORING CHEMISTRY TEACHERS’ AWARENESS AND APPLICATION OF COGNITIVE LOAD THEORY IN SENIOR HIGH SCHOOLS
DOI:
https://doi.org/10.64712/imjre.v3i2.603Keywords:
cognitive load theory, working memory, chemistry teachers, perceptionsAbstract
Chemistry teaching and learning are often regarded as difficult. Several studies have explored the causes of this difficulty and demonstrated that students struggle with chemistry because of the high cognitive demands it places on them, combined with their limited working memory capacity to process such information. These studies also suggest that chemistry can be made easier for learners when instructors consider the cognitive load theory in their instructional design. According to the cognitive load theory, humans' working memory has limited capacity; therefore, for effective learning to take place, the amount of information provided should not exceed this capacity. The theory offers opportunities for chemistry instructors to develop effective instructions that reduce learners' cognitive load, thereby improving learning outcomes. This study examined senior high school chemistry teachers’ perceptions of the cognitive load theory. A descriptive cross-sectional survey method was used to gather data from 94 senior high school chemistry teachers in the Cape Coast Metropolis, selected via a census. A questionnaire was adapted as the main tool for data collection. Descriptive statistics were utilised to analyse the responses. The findings revealed that 76.3% of senior high school chemistry teachers had low familiarity with and application of the cognitive load theory. It is therefore recommended that professional development programmes related to the cognitive load theory be implemented to improve teachers’ understanding and application of the concept.References
Adaboh, S. (2016). Using the cognitive load theory to assist in the design of instruction for the university lecture room: Some key lessons. Asian Journal of Educational Research, 4(4), 53–59. https://www.researchgate.net/publication/314096362
Adu-Gyamfi, K., Ampiah, G. J., & Agyei, D. D. (2015). High school chemistry students’ alternative conceptions of H2O, OH-, and H+ in balancing redox reactions. International Journal of Development and Sustainability, 4(6), 744–758. https://doi.org/10.5281/zenodo.1471731
Almeida, B., Santos, M., & Justi, R. (2023). Aspects and abilities of science literacy in the context of nature of science teaching. Science & Education, 32(3), 567-587. https://doi.org/10.1007/s11191-022-00324-4
Amoako, S. K., Oppong, K., Tabi, J. A., & Ossei-Anto, T. A. (2022). Factors affecting trainees’ performance in organic chemistry in colleges of education in Ghana. European Journal of Education and Pedagogy, 3(6), 97–102. https://doi.org/10.24018/ejedu.2022.3.6.403
Anim-Eduful, B., & Adu-Gyamfi, K. (2022). Factors influencing high school chemistry teachers’ and students’ teaching and learning of organic qualitative analysis: A qualitative study. European Journal of Education Studies, 9(7), 194–219. https://doi.org/10.46827/ejes.v9i7.4378
Asghar, A., Huang, Y.S., Elliot, K., & Skelling, Y. (2019). Exploring secondary students’ alternative conceptions about engineering design technology. Journal of Education Science, 9(45), 1-18. https://doi.org/10.3390/educsci9010045
Asma, H., & Dallel, S. (2020). Cognitive load theory and its relation to instructional design: Perspectives of some Algerian university teachers of English. Arab World English Journal (AWEJ), 11(4), 111–127. https://dx.doi.org/10.24093/awej/vol11no4.8
Bertoglio, K. (2024). Load reduction leadership: A Novel school improvement framework based on cognitive load theory, early findings (Poster 18). AERA 2024. https://doi.org/10.3102/ip.24.2108341
Bokosmaty, S., Sweller, J., & Kalyuga, S. (2015). Learning geometry problem solving by studying worked examples. American Educational Research Journal, 52(2), 307-333. https://doi.org/10.3102/0002831214549450
De Jong T (2010) Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science 38(2): 105–134. https://doi.org/10.1007/s11251-009-9110-0
Elford, D., Lancaster, S. J., & Jones, G. A. (2022). Exploring the effect of augmented reality on cognitive load, attitude, spatial ability, and stereo-chemical perception. Journal of Science Education and Technology, 31(3), 322–339. https://doi.org/10.1007/s10956-022-09957-0
Fallatah, R. (2021). Curriculum Development in Saudi Arabia: Saudi Primary EFL Teachers’ Perspectives of the Challenges of Implementing CLT into the English Curriculum in State Schools [Doctoral thesis, University of Exeter].
Gafoor, K. A., & Shilna, V. (2012). Creating better classroom practices for reducing cognitive load in school chemistry learning: Initial thoughts. 1–10.
Ishtiaq, M. (2019). Book Review Creswell, J. W. (2014). Research Design: Qualitative, Quantitative and Mixed Methods Approaches (4th ed.). Thousand Oaks, CA: Sage. English Language Teaching, 12(5), 40. https://doi.org/10.5539/elt.v12n5p40
Joseph, A. (2011). Grade 12 learners’ conceptual understanding of chemical representations. [Master’s thesis, University of Johannesburg (South Africa)].
Khurshid, F., O’Connor, E., Thompson, R., & Hegazi, I. (2023). Pedagogical interventions and their influences on university-level students learning pharmacology-a realist review. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1190672
Kibga, E. S., Gakuba, E., & Sentongo, J. (2021). Developing students’ curiosity through chemistry hands-on activities: a case of selected community secondary schools in Dar es Salaam, Tanzania. Eurasia Journal of Mathematics, Science and Technology Education, 17(5), em1962. https://doi.org/10.29333/ejmste/10856
Leahy, W., & Sweller, J. (2011). Cognitive load theory, modality of presentation and the transient information effect. Applied Cognitive Psychology, 25, 943–951. https://doi.org/10.1002/acp.1787
Leslie, K. C., Low, R., Jin, P., & Sweller, J. (2012). Redundancy and expertise reversal effects when using educational technology to learn primary school science. Educational Technology Research and Development, 60(1), 1–13. https://doi.org/10.1007/sl 1423-01 1-9199-0
Mayer, R. E. (2024). The past, present, and future of the cognitive theory of multimedia learning. Educational Psychology Review, 36(1), 8. https://doi.org/10.1007/s10648-023-09842-1
Milenkovi?, D. D., Segedinac, M. D., & Hrin, T. N. (2014). Increasing high school students’ chemistry performance and reducing cognitive load through an instructional strategy based on the interaction of multiple levels of knowledge representation. Journal of Chemical Education, 9(91), 1409–1416. https://doi.org/10.1021/ed400805p
Musonda, M. (2021). Chemistry topics perceived as difficult to learn by secondary school pupils of Kasama, Luwingu, Mbala and Mungwi districts of Northern Province of Zambia. Multidisciplinary Journal of Language and Social Sciences Education, 4(2), 25-29.
Nartey, E., & Hanson, R. (2021). The perceptions of senior high school students and teachers about organic chemistry: A Ghanaian perspective. Science Education International, 32(4), 331–342. https://doi.org/10.33828/sei.v32.i4.8
Nyachwaya, J. M., & Gillaspie, M. (2015). Features of representations in general chemistry textbooks: A peek through the lens of the cognitive load theory. The Royal Society of Chemistry, 17, 58–71. https://doi.org/10.1039/c5rp00140d
Owusu-Agyeman, Y., & Amoakohene, G. (2020). Transnational education delivery in Ghana: examining the benefits, challenges and future prospects. Policy Reviews in Higher Education, 4(2), 135–163. https://doi.org/10.1080/23322969.2020.1774408
Reid, N. (2021). The Johnstone triangle: The key to understanding chemistry. Royal Society of Chemistry. https://doi.org/10.1039/9781839163661
Roodenrys, K., Agostinho, S., Roodenrys, S., & Chandler, P. (2012). Managing one’s own cognitive load when evidence of split attention is present. 26, 878–886. https://doi.org/10.1002/acp.2889
Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in science education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
Tsaparlis, G. (2021). Introduction? The Many Types and Kinds of Chemistry Problems. In Problems and Problem Solving in Chemistry Education: Analysing Data, looking for Patterns and Making Deductions (pp. 1-14). The Royal Society of Chemistry. https://doi.org/10.1039/9781839163586-00001
Shibli, D., & West, R. (2018). Cognitive load theory and its application in the classroom. Journal of the Chartered College of Teaching, 2(1), 1-12.
Sibomana, A., Karegeya, C., & Sentongo, J. (2021). Factors affecting secondary school students’ academic achievements in chemistry. International Journal of Learning, Teaching and Educational Research, 20(12), 114-126. https://doi.org/10.26803/ijlter.20.12.7
Skulmowski, A. and Xu, K. M. (2021). Understanding cognitive load in digital and online learning: a new perspective on extraneous cognitive load. Educational Psychology Review, 34(1), 171-196. https://doi.org/10.1007/s10648-021-09624-7
Sripradith, R. (2023). Getting to the (power) point: unleashing the impact of assertion-evidence design in powerpoint for enhancing students’ English grammatical competence and retention. Shanlax International Journal of Education, 11(4), 45-57. https://doi.org/10.34293/education.v11i4.6375
Sweller, J. (2019). Cognitive load theory and educational technology. Educational Communications and Technology, 68, 1–16. https://doi.org/10.1007/s11423-019-09701-3
Sweller, J. (2023). The development of cognitive load theory: replication crises and incorporation of other theories can lead to theory expansion. Educational Psychology Review, 35(4), 95. https://doi.org/10.1007/s10648-023-09817-2
Sweller, J. (2024). Cognitive load theory and the curriculum. Research Handbook on Curriculum and Education, 155–166. https://doi.org/10.4337/9781802208542.00017
Sweller, J. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68(1), 1-16. https://doi.org/10.1007/s11423-019-09701-3
Szulewski, A., Howes, D., van Merriënboer, J. J., & Sweller, J. (2021). From theory to practice: the application of cognitive load theory to the practice of medicine. Academic Medicine, 96(1), 24-30. https://doi.org/10.1097/acm.0000000000003524
Upahi, J. E., & Ramnarain, U. (2020). Examining the Connection between Students' Working Memory and Their Abilities to Solve Open-Ended Chemistry Problems. Journal of Baltic Science Education, 19(1), 142-156. https://doi.org/10.33225/jbse/20.19.142
Uzun, K. (2022). Cognitive load theory and its educational implications. In K. Thamizhmaran, M. S. Bhatti & B. A. Yilmaz (Eds.), 6th international congress on life, social, and health sciences in a changing world (pp. 1–8). BZT Academy Publishing House.
Weis, S. E., Firker, A., & Hennig, J. (2007). Associations between the second to fourth digit ratio and career interests. Personality and Individual Differences, 43(3), 485–493. https://doi.org/10.1016/j.paid.2006.12.017