Effecting an Adaptive Learning System on Academic Achievement as Regulations for Measuring Pharmacist Qualifications to Licensure of Pharmaceutical Management Students
Abstract
Background and Aims: On March 15, 1994, China began implementing the qualification system for practicing pharmacists. Pharmaceutical management and regulations course is a compulsory course for students majoring in pharmacy. It is also one of the mandatory subjects for the licensed pharmacist qualification examination. The objective of this study is to (1) compare students' academic achievements before and after learning through an adaptive learning system. (2) To compare students' academic achievements after learning through an adaptive learning system with the criterion set at 70 percent. And (3) To assess the student's satisfaction with the adaptive learning system.
Methodology: This study used a cluster sampling method with 30 students as the sample. The research tools are: (1) Course lesson plan, (2) Academic achievements test paper, (3) Student satisfaction questionnaire. Conduct pre-test and post-test on the sample using academic performance papers, and analyze the mean, standard deviation, and single sample t-test of the data using SPSS.
Result: After using the adaptive learning system: (1) Students' academic achievements were significantly higher than before use, with a statistically significant difference of 0.05; (2) The student's academic achievements are above the 70% standard, and the difference is statistically significant at 0.05; and (3) Improved student satisfaction.
Conclusion: Through adaptive learning system classroom practice, learning efficiency has been improved and the personalized learning needs of students have been met. Helps to improve academic achievements among students and win their popularity.
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References
Brusilovsky, P. (1996). Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted Interaction, 6(3), 87-129.
Chen, J. (2021). Master's thesis on the construction and system design of an adaptive learning framework for online education. Northeastern Normal University. Retrieved from: https://link.cnki.net/doi/10.27011/d.cnki.gdbsu.2021.000260doi:10.27011/d.cnki.gdbsu.2021.000260.
CQLP. (2023) Certification Center for licensed Pharmacists of NMPA Test trends. Retrieved from: http://www.cqlp.org/info/infoxlb.aspx?page=1&infox=1000310001.
Cronbach, L.J. (1951). Coefficient Alpha and the Internal Structure of Tests. Psychometrika, 16, 297-334. https://doi.org/10.1007/BF02310555
De Bra, P., Houben, G-J., & Wu, H. (1999). AHAM: a Dexter-based reference model for adaptive hypermedia. In Proceedings of the tenth ACM Conference on Hypertext and hypermedia: returning to our diverse roots: returning to our diverse roots (pp. 147-156). https://doi.org/10.1145/294469.294508
Dziuban, C., Howlin, C., Moskal, P., Johnson, C., Parker, L., & Campbell, M. (2018). Adaptive Learning: A Stabilizing Influence Across Disciplines and Universities. Online Learning. 22 (3). Doi: 10.24059/olj.v22i3.1465.
Hu, W., & Chen, Y. (2018). Adaptive Learning: A New Push for Personalized Learning in the Era of Big Data. China's Education Informatization, 21, 42-47 Doi: CNKI:SUN:JYXX.0.2018-21-011
Li, G., et al. (2020). Application Research of Adaptive Learning Systems in English Learning for Adult Undergraduate Bachelor's Degree. Modern Educational Technology, 3, 59-65
Li, Z., et al. (2018). Research on Educational Artificial Intelligence in the Context of Artificial Intelligence Applications. Modern Educational Technology, 9, 19-25
Ministry of Education of China. (2018). Notice of the Ministry of Education on Issuing the Action Plan for Artificial Intelligence Innovation in Higher Education Institutions. Ministry of Education of the People's Republic of China. http://www.moe.gov.cn/srcsite/A16/s7062/201804/t20180410_332722.html
National Medical Products Administration. (2020). Notice of the State Food and Drug Administration on Regulating the Use of Licensed Pharmacists in Drug Retail Enterprises. Chinese government portal. Retrieved from: https://www.gov.cn/zhengce/zhengceku/2020-11/21/content_5563176.htm
Richardson, M.W., & Kuder, G.F. (1939). The calculation of test reliability coefficients based on the method of rational equivalence. Journal of Educational Psychology, 30(9), 681–687. https://doi.org/10.1037/h0054933
Somyurek, S. (2015). The New Trends in Adaptive Educational Hypermedia Systems. International Review of Research in Open & Distributed Learning, 16(1), 221-241.
State Council of China. (2017). Notice of the State Council on Issuing the Development Plan for the New Generation of Artificial Intelligence. Chinese government portal. Retrieved from:https://www.gov.cn/zhengce/zhengceku/2017-07/20/content_5211996.htm
Ye, X. (2019). Research on the Knewton Adaptive Learning Platform in the United States. Master's Thesis, Southwest University https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD201902&filename=1019913792.nh
Zhou, Q., & Wen, X. (2020). From Adaptation to Intelligent Adaptation: A New Path to Personalized Learning in the Age of Artificial Intelligence. Modern Education Management, 9, 89-96. doi: 10.16697/j.1674-5485.2020.09.012