Establishing the Practicability of Organic Reaction Teaching Model in Minimizing Student’s Common Errors to Improve Academic Performance
Abstract
Background: Systematic collection of scientific evidence on the applicability an usability of model and its components is an important aspect of design and development research.
Purpose: The aim of this study is to determine external validity of the organic reaction teaching model in terms of its practicability and potentiality in enhancing students’ performance scores.
Method: A field testing method was conducted across five matriculation colleges in Malaysia by five (5) experts’ chemistry lectures who implemented a lesson plan developed based on the model’s constructs and then responded to an open ended questionnaire to express their views on the practicability of the model. 40 matriculation Students that participated in the field testing were also evaluated to determine the potentiality of the model on their performance in organic reactions. Four main themes having of many codes and quotations were identified.
Results: The analysis of the results indicates that the model is compatible, clear and flexible for teaching organic reactions. Moreover, the model components have the potential of miximizing students’ academic performance in organic reaction with an overall score of 84.4 % in the organic chemistry tests. Thus, the model was found practicable for teaching and have the potential to minimized students’ common errors in organic reaction mechanisms.
Conclusions: The findings of this study may similarly work as a reference model in developing modules and measuring instruments to reduce errors in other procedural concepts in chemistry and other science-related subjects.
-
Page Number : 71-81
-
Published Date : 2023-01-25
-
Keywords
Teaching model, Organic reaction mechanism, Practicability, Potentiality, Field Testing
-
DOI Number
10.15415/iie.2022.102008
-
Authors
Abdulmalik Sabitu, Othman Talib and Norizah Abdul Rahaman
References
- Abdurrahman Alkhaldi, I. A., Talib, O. B., Kamarudin, N. B., & Ab Jalil, H. (2020). Covid-19 and the Need for the use of Digital Game-based Learning for Teaching Mathematics at the Saudi Elementary Schools. Compusoft, 9(12), 3953-3959.
- Abdullah, M. R. T. L., Siraj, S., Asra, & Hussin, Z. (2014). Interpretive Structural Modeling of Mlearning Curriculum Implementation Model of English Language Communication Skills for Undergraduates. Turkish Online Journal of Educational Technology, 13(1), 151–161.
- Ahmed, G., & Artosh, M. (2016). Development of a Higher Order Thinking Teaching Model for Basic Education Students in Science. In Thsesis Doctor of Philosophy. University Malaya, Malaysia.
- Akaygun, S. (2016). Is the Oxygen Atom Static or Dynamic? The Effect of Generating Animations on Students’ Mental Models of Atomic Structure. Chemistry Education Research and Practice, 17(4), 788- 807. https://doi.org/10.1039/C6RP00067C
- Ali, W. (2020). Online and Remote Learning in Higher Education Institutes: A necessity in light of COVID-19 Pandemic. Higher Education Studies, 10(3), 16-25. https://doi.org/10.5539/hes.v10n3p16
- Altschuld, J. W., & Hines, C. V. (1982). Factors Affecting the Validity of Field Tests in Education. Educational Evaluation and Policy Analysis, 4(3), 331–339. https://doi.org/10.3102/01623737004003331
- Andrews, D. H., & Goodson, L. A. (1980). A Comparative Analysis of Models of Instructional Design. Journal of instructional development, 3(4), 2-16. https://doi.org/10.1007/BF02904348
- Azraai, O. (2016). Modeling Relationships of Matriculation Students’ Affective and Cognitive Factors and Achievement in Organic Chemistry. In Universitas Putra Malaysia. University Putra Malaysia
- Dick, W., Carey, L., & Carey, J. O. (2001). The systematic design of instruction. 6th. New York: Longmann.
- Dutt, A., Tan, M., Alagumalai, S., & Nair, R. (2019). Development and Validation of the Ability in Behavior Assessment and Interventions for Teachers Using Delphi Technique and Rasch Analysis. Journal of Autism and Developmental Disorders, 49(5), 1976–1987. https://doi.org/10.1007/s10803-019-03887-4
- Deldjoo, Y., Anelli, V. W., Zamani, H., Bellogin, A., & Di Noia, T. (2021). A flexible Framework for Evaluating User and Item Fairness in Recommender Systems. User Modeling and User-Adapted Interaction, 1-55. https://doi.org/10.1007/s11257-020-09285-1
- Dejene, W. (2019). The Practice of Modularized Curriculum in Higher Education Institution: Active Learning and Continuous Assessment in Focus. Cogent Education, 6(1), 201-221. https://doi.org/10.1080/2331186X.2019.1611052
- Djoko Dwiyogo, W. & LigyaRadjah, C. (2020). Effectiveness, Efficiency and Instruction Appeal of Blended Learning Model. International Association of OnlineEngineering. Retrieved October 12, 2021 from https://www.learntechlib.org/p/217970/.
- Englander, M. (2016). The Interview: Data collection in Descriptive Phenomenological Human Scientific Research. Journal of Phenomenological Psychology, 47(1), 13–35. https://doi.org/10.1163/156916212X632943
- Gilbert, J. K., Boulter, C. J., & Elmer, R. (2000). Positioning Models in Science Education and in Design and Technology Education. Developing Models in Science Education (pp. 3-17). Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0876-1
- Gustafson, K. L., & Branch, R. M. (2002). What is Instructional Design. Trends and Issues in Instructional Design and Technology, 2, 10-16.
- Kristiono, I. D., Dwiyogo, W. D., & Hariadi, I. (2019). Sports Nutrition Science Learning Based on Blended Learning in Physical Education, Health, and Recreation Students. Journal of Education:Theory, Research, and Development, 4 (2), 235-241.
- Lim, J. E., Wong, W. T., Teh, T. A., Lim, S. H., Allen Jr, J. C., Quah, J. H. M., & Tan, N. C. (2021). A Fully-Immersive and Automated Virtual Reality System to Assess the Six Domains of Cognition: Protocol for a Feasibility Study. Frontiers in Aging Neuroscience, 482. https://doi.org/10.3389/fnagi.2020.604670
- Mama, M., & Hennessy, S. (2013). Developing a Typology of Teacher Beliefs and Practices Concerning Classroom Use of ICT. Computers & Education, 68, 380-387. https://doi.org/10.1016/j.compedu.2013.05.022
- Muqsith, A., Zaharah, Farazila, A., Yusof, H., & Mohd Ridhuan, J. (2017). Nominal Group Technique (NGT) And Its Application To The Construction Of Ethical Elements and Values (Morals) Based on Inquiry Activities in Polytechnics and Community Colleges. Journal of Social Sciences and Humanities, 2(1), 125-145
- Nworgu, C., & Oluwuo, S. O. (2019). Time Resource Management and Teachers’ Task Performance in Public Senior Secondary Schools in Rivers State. International Journal of Education and Evaluation, 5(6), 36-48.
- Ragan, T. J., Smith, P. L., & Curda, L. K. (2008). Outcome- Referenced, Conditions-Based Theories and Models. Handbook of research on educational communications and technology, 3, 383-399.
- Ridhuan, M. B. M. J. (2016). Development of Skives Training Curriculum Model for Work -Based Learning Engineering Study Program. In Thsesis Doctor of Philosophy. University Malaya, Malaysia.
- Tobin, K., & Gallagher, J. J. (1987). What happens in high school science Classrooms? Journal of Curriculum studies, 19(6), 549-560. https://doi.org/10.1080/0022027870190606
- Tracey, M. W., & Richey, R. C. (2007). ID Model Construction and Validation: A Multiple Intelligences Case. Educational Technology Research and Development, 55(4), 369-390. https://doi.org/10.1007/s11423-006-9015-4
- Umoren, G., & Ogong, A. S. (2007). Prior presentation of Behavioral Objectives and Students’ Achievement in Biology. Educational Research and Reviews, 2(2), 022-025
- Uzunboylu, H., & Kosucu, E. (2017). Comparison and Evaluation of Seels& Glasgow and Addie Instructional Design Model. Ponte, 73(6), 98-112. https://doi.org/10.21506/j.ponte.2017.6.37
- Wong, K. K. H., & Day, J. R. (2009). A comparative study of problem-based and lecture-based learning in junior secondary school science. Research in Science Education, 39(5), 625-642. https://doi.org/10.1007/s11165-008-9096-7