Main Article Content

Abstract

A digital instructional game with embedded multimedia was believed not limited to allowing the learner to visualize chemistry concepts while playing but enable them to collect relevant information that connects the understanding of the other. The subject was described as a core science area with multiple macroscopic, submicroscopic, and symbolic representations. Thus, the study intended to investigate the effectiveness of the instructional game in enhancing students' cognitive development in learning chemical symbols and periodicity of elements. An instructional tool called "Symperiod Board Game) The study was designed and developed, containing 20 test items distributed in three different levels in order of complexity from simple to complex. The between-group experimental research design was adopted for this study in which 20 Form IV students distributed into four groups was selected. The alpha value 0.830 of the Pearson correlation coefficient determines the strength of the instrument's reliability, hence used for data collection. The data obtained were analyzed using descriptive statistics, and the results indicated that the cognitive development of the respondents' increases as students play the instructional game from level 1 to 3. Thus, the study reveals that a learner cannot understand a concept if he/she does not first remember it; similarly, he/she cannot apply knowledge and concepts if he/she does not understand them. It is imperative to conclude that the poor performance of students in chemistry can be associated with the quality of instruction provided by the teacher during classroom instructions.

Keywords

The instructional game Cognitive development Chemistry

Article Details

How to Cite
Aliyu, H., Raman, Y., & Talib, C. A. (2021). Enhancing Cognitive Development in Learning Chemical Symbol and Periodicity through Instructional Game. International Journal of Asian Education, 2(3), 285–295. https://doi.org/10.46966/ijae.v2i3.115

References

  1. Aliyu, H., Talib, C. A., Aliyu, F., Maimun, A., Malik, A., & Ali, A. (2020). Predominant Chemical Substances Causing Environmental Degradation as a Result of Climate Change : A Systematic Review. Solid State Technology, 63(1s), 704–720.
  2. Bernholt, S., & Parchmann, I. (2011). Assessing the complexity of students’ knowledge in chemistry. Chemistry Education Research and Practice, 12(2), 167–173. https://doi.org/10.1039/c1rp90021h
  3. Bradley, J. (2014). THE CHEMIST ’ S TRIANGLE AND A GENERAL SYSTEMIC APPROACH TO TEACHING , LEARNING AND RESEARCH IN CHEMISTRY EDUCATION. AJCE, 4(2), 64–79.
  4. Bugaje, B. M. (2013). Qualitative Chemistry Education: The Role of the Teacher. Journal of Applied Chemistry (IOSR-JAC), 4(5), 10–14. https://doi.org/10.1080/00094056.1949.10726229
  5. Chiu, M., & Wu, H. (2009). The Roles of Multimedia in the Teaching and Learning of the Triplet Relationship in Chemistry. In Multiple representations in chemical education (pp. 251–283). Springer. https://doi.org/10.1007/978-1-4020-8872-8
  6. Divjak, B., & Tomic, D. (2011). The impact of game-based learning on the achievement of learning goals and motivation for learning mathematics—a literature review. Journal of Information Organization Science, 35(1), 15–30.
  7. Edomwonyi-otu, L., & Avaa, A. (2011). The Challenge of Effective Teaching of Chemistry: A Case Study. Leonardo Electronic Journal of Practices and Technologies, 10(18), 1–8.
  8. Egenfeldt-Nielsen, S. (2006). Overview of research on the educational use of video games. Digital Kompetanse, 1(3), 184–213.
  9. Gee, J. P. (2007). What video games have to teach us about learning and literacy (Revised and updated edition). Palgrave Macmillan.
  10. Gilbert, J. K., & Treagust, D. F. (2009). Towards a Coherent Model for Macro , Submicro and Symbolic Representations in Chemical Education. 333–350. https://doi.org/10.1007/978-1-4020-8872-8
  11. Hanna, W. (2007). The New Bloom’s Taxonomy: Implications for Music Education. Arts Education Policy Review, 108(4), 7–16. https://doi.org/10.3200/AEPR.108.4.7-16
  12. Hays, R. T. (2005). Training Systems Division. Distribution.
  13. Johnstone, A. (1982). Macro- and micro-chemistry. School Science Review, 64, 377–379.
  14. Kraiger, K., Ford, J. K., & Salas, E. (1993). Application of cognitive, skill-based, and affective theories of learning outcomes to new methods of training evaluation. Journal of Applied Psychology, 78(2), 311–328. https://doi.org/10.1037/0021-9010.78.2.311
  15. Li, M.-C., & Tsai, C.-C. (2013). Game-Based Learning in Science Education : A Review of Relevant Research. Journal of Science Education and Technology, 22, 877–898. https://doi.org/10.1007/s10956-013-9436-x
  16. Martina Eya, N. (2016). Investigating the Contents of the Senior Secondary School Chemistry Curriculum that can Inculcate Entrepreneurial Skills among Students in Nigeria. International Journal for Cross-Disciplinary Subjects in Education, 6(2), 2195–2201. https://doi.org/10.20533/ijcdse.2042.6364.2015.0303
  17. Mayer, R.E, & Johnson, C. . (2010). Adding instructional features that promote learning in a game-like environment. Journal of Education and Computer Resources, 42(3), 241–265.
  18. Mayer, Richard E. (2005). Cognitive Theory of Multimedia Learning. The Cambridge Handbook of Multimedia Learning, 31–48. https://doi.org/10.1207/s15326985ep4102_2
  19. Munzenmaier, C., & Rubin, N. (2013). Bloom’s Taxonomy: What’s Old Is New Again. Perspectives, 1–47. http://www.elearningguild.com/research/archives/index.cfm?id=164&action=viewonly&utm_campaign=research-blm13&utm_medium=email&utm_source=elg-insider
  20. Overton, T., Potter, N., & Leng, C. (2013). A study of approaches to solving open-ended problems in chemistry. Chemistry Education Research and Practice, 14(4), 468–475. https://doi.org/10.1039/c3rp00028a
  21. Plass, J. L., O’Keefe, P. A., Biles, M. L., Frye, J., & Homer, B. D. (2014). Motivational and Cognitive Impact of Badges in Games for Learning. Aera 2014.
  22. Sanchez, J. M. P. (2017). Integrated Macro-Micro-Symbolic Approach in Teaching Secondary Chemistry. Kimika, 28(2), 22–29. https://doi.org/10.26534/kimika.v28i2.22-29
  23. Smith, D. K. (2011). From crazy chemists to engaged learners through education. Nature Chemistry, 3(9), 681–684. https://doi.org/10.1038/nchem.1091
  24. Stieff, M., & Wilensky, U. (2003). Connected Chemistry—Incorporating Interactive Simulations into the Chemistry Classroom. Journal of Science Education and Technology, 3(12), 285–302. https://doi.org/10.1023/A
  25. Talanquer, V. (2011). Macro , Submicro , and Symbolic: The many faces of the chemistry “ triplet .” August 2013, 37–41. https://doi.org/10.1080/09500690903386435
  26. Talib, C. A., Aliyu, H., Maimum, A., Malik, A., Siang, K. H., & Ali, M. (2018). Interactive Courseware as an effective strategy to overcome misconceptions in Acid-base Chemistry. 2018 IEEE 10th International Conference on Engineering Education (ICEED), 240–245.
  27. Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd
  28. Ullman, D. (1997). The mechanical design process. McGraw-Hill International.
  29. Vogel, J. ., Vogel, D. ., Cannon-Bowers, J., Bowers, G. ., Muse, K., & Wright, M. (2006). Computer gaming and interactive simulations for learning: a meta-analysis. Journal of Education Computer Resources, 34(3), 229–243.
  30. Wilson, K. A., Bedwell, W. L., Lazzara, E. H., Salas, E., Burke, C. S., Estock, J. L., Orvis, K. L., & Conkey, C. (2009). Relationships Between Game Attributes and Learning Outcomes. Simulation & Gaming, 40(2), 217–266. https://doi.org/10.1177/1046878108321866