Abstract
Critical voices on the traditional "one-size-fits-all" education system, which assumes a uniform approach for all students, abound for not meeting individual student learning needs. Expecting teachers to cater to the diverse learning needs of each student is seen impractical and unrealistic. There is a growing demand for personalized student-centered education, aiming to accommodate the unique learning needs, abilities, and interests. Modern educational systems are incorporating innovations like Artificial Intelligence (AI), which not only personalize students’ educational experiences but also make them adaptive. The concept of Personalized Adaptive Learning (PAL), which systematically tailor instruction to individual learners has gained prominence as a key educational reform effort in contemporary systems. As more teachers embrace PAL, it presents an opportunity to explore the relationship between student satisfaction and their level of engagement. In this study conducted in Singapore, PAL was implemented to 1061 students across three subjects – theory-based marketing, calculation-based statistics, and procedural airway bill calculation. The analysis is done by using factor analysis, Kruskal-Wallis test, Friedman test and Kendall tau correlation coefficient. The results revealed significant differences in the ratings of the three subjects between different constructs (lesson content, personalization and mobile devices) except for the system user interface construct. Moreover, there was a significant difference between all constructs among the students. Interestingly, the level of engagement is significant for three constructs: system user interface, lesson content and personalization. These findings provide insights into the factors that are likely significant antecedents for planning, designing and implementing PAL to enhance student satisfaction.
Author Information
Li Fern Tan, Temasek Polytechnic, Singapore
Poh Nguk Lau, Temasek Polytechnic, Singapore
Steven C.K. Ng, Temasek Polytechnic, Singapore
Paper Information
Conference: ACE2023
Stream: Learning Experiences
This paper is part of the ACE2023 Conference Proceedings (View)
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To cite this article:
Tan L., Lau P., & Ng S. (2024) Measuring the Effects of Student Satisfaction and the Engagement Level of Personalized Adaptive Learning Using an AI-Enabled Learning Pathway Tool ISSN: 2186-5892 The Asian Conference on Education 2023: Official Conference Proceedings https://doi.org/10.22492/issn.2186-5892.2024.103
To link to this article: https://doi.org/10.22492/issn.2186-5892.2024.103
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