International Journal of Academic Research in Business and Social Sciences

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Development of ChemDataLog Module and Determination of Its Content Validity and Reliability

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ChemDataLog Module is developed to elevate chemistry achievement among preparatory course science students. ASSURE learning model was chosen for the researchers to design chemistry practical that aided by Microcomputer Based Laboratory (MBL). 5E Model of Inquiry Based Learning (IBL) was the learning strategy applied in using the module during chemistry practical class. A need assessment has been conducted among 170 Year Two students and seven Chemistry teachers of that preparatory course. Findings from the need assessment revealed that Organic Chemistry, Chemical Bonding, and Acid and Base were amongst three most difficult chemistry topics to learn perceived by the students. Meanwhile Organic Chemistry, Acid and Base, and Chemical Bonding were amongst three most difficult topics from teachers’ perspectives. Besides, Electrochemistry, Acid and Base, and Thermochemistry were amongst three suitable topics to incorporate MBL from teachers’ opinions. Therefore, Acid and Base, and Thermochemistry topics were selected for this module. This module comprised of six practical units. The content of this module was validated by six chemistry experts while the appropriateness of the language used was validated by two language experts. Feedbacks from the experts showed that they have a high agreement on the module’s content validity. Meanwhile, the reliability of the module was determined from the questionnaires given to 64 students who used the module. Findings demonstrated that ChemDataLog Module has a high module reliability. This module is ready to be used as a learning instruction in elevating chemistry achievement among preparatory course science students.
Adlim, S., Soewarno, S., Ali, H., Ibrahim, A., Umar, H., & Ismail, K. (2014). Assessing chemistry-learning competencies of students in isolated rural senior high schools by using the national examination: A case study of Simeulue Island, Indonesia. International Journal of Science and Mathematics Education, 12, 817-839.

Bybee, R. W., Taylor, J. A., Gardner, A., Van Scotter, P., Powell, J., Westbrook, A., & Landes, N. (2006). The BSCS 5E instructional model: Origins and effectiveness. Colorado Springs, CO: Biological Sciences Curriculum Studies.

Chairam, S., Ubon, N.K. & Coll, R.K. (2015). Exploring Secondary Students' Understanding of Chemical Kinetics through Inquiry-Based Learning Activities. Eurasia Journal of Mathematics, Science & Technology Education, 11(5), 937-956.

Cetin-Dindra, A. & Gebanb, O. (2016). Conceptual understanding of acids and bases concepts and motivation to learn chemistry. The Journal of Educational Research, 1–13.

Demircioglu, G., A. Ayas & H. Demircioglu, 2005. Conceptual change achieved through a new teaching program on acids and bases. Chemistry Education Research and Practice, 6: 36-51.

Demircioglu, G. & Cagatay, G. (2014). The effect of laboratory activities based on 5E model of constructivist approach on 9th grade students’ understanding of solution chemistry, Procedia - Social and Behavioral Sciences, 116, 3120 – 3124.

Gilbert, J. K.; Treagust, D. (2009). Multiple representations in chemical education: Dordrecht, The Netherlands: Springer.

Gunhaart, A., & Srisawasdi, N. (2012). Effect of integrated computer-based laboratory environment on students' physics conceptual learning of sound wave properties. Procedia-Social and Behavioral Sciences, 46, 5750-5755.

Fraenkel, J.R. & Wallen, N.E. (1996). How to Design and Evaluate Research in Education. 3rd Edition. New York: Mc Graw Hill, Inc.
Hofstein, A., & Lunetta, V. N. (2004). The laboratory in science education: Foundation for the 21st century. Science Education, 88, 28-54.

Ibrahim. D. (2010). A Data Logger for Teaching Data Capturing and Analysis to Engineering Students. Computer Application Engineering Education, 18, 397- 405.

Jansoon, N., Coll, R. K. & Samsook, E. (2009). Understanding mental models of dilution in
Thai students. International Journal of Environmental & Science Education, 4, 147–168.

Johnstone, A. H. (2006). Chemical Education Research in Glasgow in perspective. Chemistry Education Research and Practice, 7(2), 49-63.

Kale, B. (2015). Smart phone based real time wireless data logger system. International Journal of Multidisciplinary Research and Development, 2(6), 258-261.

Kan, S-Y, Cha, J. & Chia, P.W. (2015). A Case Study on Using Uncritical Inference Test to Promote Malaysian College Students’ Deeper Thinking in Organic Chemistry. Journal of the Korean Chemical Society, 59(2), 1-8.

Karsli, F. & Ayas, A. (2014). Developing a Laboratory Activity by Using 5E Learning Model on Student Learning of Factors Affecting the Reaction Rate and Improving Scientific Process Skills. Procedia - Social and Behavioral Sciences, 143, 663 – 668.

Kerlinger, E.N. (1986). Foundation of Behavioral Research. New York: Holt, Rinehart and Wiston.

Laudonia, I. & Eilks, I., (2018). Reflections on a Three-Year-Long Teacher-Centered, Participatory Action Research Experience on Teaching Chemical Bonding in a Swiss Vocational School. Educ. Sci., 8, 141.

Liu, H., C., Andre, T. & Greenbowe, T. (2008). The Impact of Learner’s Prior Knowledge on Their Use of Chemistry Computer Simulations: A Case Study, Journal of Science Education and Technology, 17(5), 466-482.

Liu, C.Y, Wu. C.J., Wong, W.K., Lien, Y.W., Chao, T.K. (2017). Scientific modelling with mobile devices in high school physics labs. Computers & Education, 105, 44-56.

National Research Council (NRC). (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.

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In-Text Citation: (Turiman, Osman, & Wook, 2018)
To Cite this Article: Turiman, P., Osman, K., & Wook, T. S. M. T. (2018). Development of ChemDataLog Module and Determination of Its Content Validity and Reliability. International Journal of Academic Research in Business and Social Sciences, 8(12), 2265–2277.