The Effect of Interactive Computer Animation and Simulation on Students’ Achievement and Motivation in Learning Electrochemistry

N. J. Ahmad, N. Yakob, M. A. H. Bunyamin, N. Winarno, W. H. Akmal

Abstract

Electrochemistry is difficult to learn due to its abstract concepts involving macroscopic, microscopic, and symbolic representation levels. Studies have shown that students can visualize and improve their understanding of chemistry by using interactive computer animation and simulation. This study reports the effect of interactive computer animation and simulation module named “Interactive Electrolysis of Aqueous Solution” (IEAS) developed to aid students in learning electrolysis. A pre and post-test control quasi-experimental design was carried out to investigate the effects of the IEAS on students’ achievement and motivation in electrochemistry topics. This study involved 62 16-years-old male students from two different secondary schools. Pre and post electrochemistry achievement tests (EAT) and pre and post- Instructional Material Motivation Surveys (IMMS) were used. For EAT, using one-way ANOVA, it shows that there was a significant difference in the post-test mean score in this study on the understanding of the electrolysis concept between students in the treatment and control groups [F (1, 60) = 5.15, p <0.05]. The qualitative results also provided evidence that the students in the treatment group had a better conceptual understanding than the control group, especially at the microscopic representation level. For the IMMS test, there was a significant difference between the treatment and control groups in terms of the mean score of the post motivation IMMS test where p <0.05 in chemistry learning [F (1,59) = 266.89, p <0.05].  Thus, it can be concluded that IEAS has an impact on enhancing the students’ understanding of the electrolysis concept, and the students are more motivated to learn electrochemistry.

Keywords

animation; chemistry; electrochemistry; simulation

Full Text:

PDF

References

Acar, B., & Tarhan, L. (2007). Effect of cooperative learning strategies on students’ understanding of concepts in electrochemistry. International Journal of Science and Mathematics Education, 5(2), 349-373.

Ahmad, N. J., & Lah, Y. C. (2013). A designed teaching sequence as a tool to improve students’ conceptual understanding of the conductivity in the electrolytic cell. Asian Social Science, 9(2), 298.

Ahmad, N. J., Ishak, N. A., & Bunyamin, M. A. H. (2019). Learning Demand and Classroom Discourse Design Tools to Improve Students’ Conceptual Understanding of the Nature of Electrolytes. Asia Pacific Journal of Educators and Education, 34, 187-218.

Akpoghol, T. V., Ezeudu, F. O., Adzape, J. N., & Otor, E. E. (2016). Effects of Lecture Method Supplemented with Music and Computer Animation on Senior Secondary School Students’ Academic Achievement in Electrochemistry. Journal of Education and Practice, 7(4), 75-86.

Al-Balushi, S. M., Al-Musawi, A. S., Ambusaidi, A. K., & Al-Hajri, F. H. (2017). The effectiveness of interacting with scientific animations in chemistry using mobile devices on grade 12 students’ spatial ability and scientific reasoning skills. Journal of Science Education and Technology, 26(1), 70-81.

Barak, M., Ashkar, T., & Dori, Y. J. (2011). Learning science via animated movies: Its effect on students’ thinking and motivation. Computers & Education, 56(3), 839-846.

Bolliger, D. U., Mills, D., White, J., & Kohyama, M. (2015). Japanese students’ perceptions of digital game use for English-language learning in higher education. Journal of Educational Computing Research, 53(3), 384-408.

Bong, A. Y. L., & Lee, T. T. (2016, June). Form four students’ misconceptions in electrolysis of molten compounds and aqueous solutions. In Asia-Pacific Forum on Science Learning & Teaching (Vol. 17, No. 1).

Buty, C., Tiberghien, A., & Le Maréchal, J. (2004). Learning hypotheses and an associated tool to design and to analyse teaching-learning sequence. International Journal of Science Education, 26(5), 579-604.

Campbell, D. T., Stanley, J. C., & Gage, N. L. (1963). Experimental and quasi-experimental designs for research (No. 04; Q175, C3.). Boston: Houghton Mifflin.

Chandrasegaran, A. L., Treagust, D. F., & Mocerino, M. (2007). The development of a two-tier multiple-choice diagnostic instrument for evaluating secondary school students’ ability to describe and explain chemical reactions using multiple levels of representation. Chemistry Education Research and Practice, 8(3), 293-307.

Chen, M. P., & Liao, B. C. (2015, July). Augmented reality laboratory for high school electrochemistry course. In 2015 IEEE 15th International Conference on Advanced Learning Technologies (pp. 132-136). IEEE.

Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design and analysis issues for field settings. Boston, MA: Houghton Mifflin Company.

Deci, E. L., & Ryan, R. M. (1991). A motivational approach to self: Integration in personality.

Dempsey, J. V., & Johnson, R. B. (1998). The development of an ARCS gaming scale. Journal of Instructional Psychology, 25(4), 215.

Doymus, K., Karacop, A., & Simsek, U. (2010). Effects of jigsaw and animation techniques on students’ understanding of concepts and subjects in electrochemistry. Educational Technology Research and Development, 58(6), 671-691.

Eilks, I., Witteck, T., & Pietzner, V. (2012). The role and potential dangers of visualisation when learning about sub-microscopic explanations in chemistry education. ceps Journal, 2(1), 125-145.

Garnett, P. J., & Treagust, D. F. (1992). Conceptual difficulties experienced by senior high school students of electrochemistry: Electric circuits and oxidation‐reduction equations. Journal of Research in Science Teaching, 29(2), 121-142.

Gay, L. R., Mills, G. E., & Airasian, P. W. (2011). Educational research: Competencies for analysis and applications. Pearson Higher Ed.

Green, M., & Sulbaran, T. (2006, October). Motivation assessment instrument for virtual reality scheduling simulator. In E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 45-50). Association for the Advancement of Computing in Education (AACE).

Hamza, K. M., & Wickman, P. O. (2008). Describing and analyzing learning in action: An empirical study of the importance of misconceptions in learning science. Science Education, 92(1), 141-164.

Iksan, Z. H., & Daniel, E. (2015). Emerging Model of Questioning through the Process of Teaching and Learning Electrochemistry. International Education Studies, 8(10), 137-149.

Johnstone, A. H. (1993). The development of chemistry teaching: A changing response to changing demand. Journal of Chemical Education, 70(9), 701–705.

Józsa, K., & Morgan, G. A. (2017). Reversed items in Likert scales: Filtering out invalid responders. Journal of Psychological and Educational Research, 25(1), 7-25.

Karamustafaoğlu, S., & Mamlok-Naaman, R. (2015). Understanding electrochemistry concepts using the predict-observe-explain strategy. Eurasia Journal of Mathematics, Science and Technology Education, 11(5), 923-936.

Karsli, F. & Çalik, M. (2012). Can freshman science student teachers’ alternative conceptions of ‘electrochemical cells’ be fully diminished?. Asian Journal of Chemistry, 24(2), 485-491.

Keller, J. M. (1983). Motivational design of instruction. Instructional design theories and models: An overview of their current status, 1(1983), 383-434.

Keller, J. M. (2008). First principles of motivation to learn and e3‐learning. Distance education, 29(2), 175-185.

Land, S. M. (2000). Cognitive requirements for learning with open-ended learning environments. Educational Technology Research and Development, 48(3), 61-78.

Lee, T. T., & Arshad, M. Y. (2008). Kefahaman pelajar tingkatan empat mengenai Elektrokimia (Doctoral dissertation, Universiti Teknologi Malaysia).

Madar, A. R., & Hashim, M. N. (2011). Effectiveness of using graphic animation courseware for students with different cognitive styles and spatial visual abilities. Journal of Technical Education and Training, 3(1).

Mumba, F., Banda, A., & Chabalengula, V. M. (2018). Junior high school pre-service science teachers’ familiarity, conceptual understanding and interest in electrochemistry. African Journal of Research in Mathematics, Science and Technology Education, 22(2), 149-161.

O’Neal, L. J., Gibson, P., & Cotten, S. R. (2017). Elementary school teachers’ beliefs about the role of technology in 21st-century teaching and learning. Computers in the Schools, 34(3), 192-206.

Osman, K., & Lee, T. T. (2012). Interactive multimedia module with pedagogical agent in Electrochemistry. Interactive Multimedia, 29-48.

Osman, K., & Lee, T. T. (2014). Impact of interactive multimedia module with pedagogical agents on students understanding and motivation in the learning of electrochemistry. International Journal of Science and Mathematics Education, 12(2), 395-421.

Özmen, H. (2011). Effect of animation enhanced conceptual change texts on 6th grade students› understanding of the particulate nature of matter and transformation during phase changes. Computers & Education, 57(1), 1114-1126.

Prihastyanti, N., Rokhim, D. A., Subandi, S., & Sigit, D. (2020). Development Of Contextual Teaching And Learning (Ctl) Based Learning Materials To Facilitate Students In Improving Critical Thinking Ability In Redox And Electro Chemical Topics. Jurnal Pembelajaran Sains, 4(2), 67-73.

Rahayu, S., Treagust, D. F., Chandrasegaran, A. L., Kita, M., & Ibnu, S. (2011). Assessment of electrochemical concepts: a comparative study involving senior high-school students in Indonesia and Japan. Research in Science & Technological Education, 29(2), 169-188.

Reigeluth, C. M. (Ed.). (2018). Instructional theories in action: Lessons illustrating selected theories and models. Routledge.

Rodgers, D. L., & Withrow-Thorton, B.J. (2005). The effect of instructional media on learner motivation. International Journal of Instructional Media 32(4), 333.

Rodrigues, S., Smith, A. & Ainley, M. (2001). Video clips and animation in chemistry CDROMS: Student interest and preference. Australian Science Teachers Journal, 47(2), 9-15.

Rosen, Y. (2009). The effects of an animation-based online learning environment on transfer of knowledge and on motivation for science and technology learning. Journal of Educational Computing Research, 40(4), 451-467.

Sandi-Urena, S., Cooper, M., & Stevens, R. (2012). Effect of cooperative problem-based lab instruction on metacognition and problem-solving skills. Journal of chemical education, 89(6), 700-706.

Sanger, M. J., & Greenbowe, T. J. (1997a). Common student misconceptions in Electrochemistry: Galvanic, electrolytic, and concentration cells. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 34(4), 377-398.

Sanger, M. J., & Greenbowe, T. J. (1997b). Students’ misconceptions in electrochemistry regarding current flow in electrolyte solutions and the salt bridge. Journal of chemical education, 74(7), 819.

Sanger, M. J., & Greenbowe, T. J. (2000). Addressing student misconceptions concerning electron flow in aqueous solutions with instruction including computer animations and conceptual change strategies. International Journal of science education, 22(5), 521-537.

Seels, B., & Glasgow, Z. (1998). Making instructional design decisions. Merrill.

Sesen, B. A., & Tarhan, L. (2013). Inquiry-based laboratory activities in electrochemistry: High School Students’ Achievements and Attitudes. Research in Science Education, 43(1), 413-435.

Song, S. H., & Keller, J. M. (2001). Effectiveness of motivationally adaptive computer-assisted instruction on the dynamic aspects of motivation. Educational technology research and development, 49(2), 5-22.

Supasorn, S. (2015). Grade 12 students’ conceptual understanding and mental models of galvanic cells before and after learning by using small-scale experiments in conjunction with a model kit. Chemistry Education Research and Practice, 16(2), 393-407.

Surif, J., Ibrahim, N. H., Alwi, A. M., Loganathan, P., & Serman, N. S. (2019, December). Effect of Inductive Teaching Method To Improve Science Process Skills In Electrochemistry. In 2019 IEEE International Conference on Engineering, Technology and Education (TALE) (pp. 1-5). IEEE.

Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International journal of medical education, 2, 53.

Widodo, W. (2017). Development Of Integrated Electrochemistry Teaching Material Based Contextual For Vocational High School In Machine Engineering Departement. Jurnal Pena Sains, 4(2), 80-87.

Wolters, C. A., & Rosenthal, H. (2000). The relation between students’ motivational beliefs and their use of motivational regulation strategies. International journal of educational research, 33(7-8), 801-820.

Yustina, Y., Halim, L., & Mahadi, I. (2020). The Effect of ‘Fish Diversity’ Book in Kampar District on the Learning Motivation and Obstacles of Kampar High School Students through Online Learning during the COVID-19 Period. Journal of Innovation in Educational and Cultural Research, 1(1), 7-14.

Refbacks

  • There are currently no refbacks.