Conference paper 2024

STEM Explorations: A REACT Model Module

2024 IEEE 13th International Conference on Engineering Education: Dissemination and Advancement of Engineering Education using Artificial Intelligence, ICEED 2024
Conference
Abstract

Mathematics as one of the elements in STEM is challenging and tedious themes for students. Algebra, a key subject, is the most misunderstood chapter. This study developed a mathematics teaching and learning module for vocational college students using the REACT methodology. This quantitative investigation uses Vocational College math experts and students to confirm the findings. A rater reliability-checked form and structured interview were employed. The study included three vocational mathematics experts, ten first-year vocational college students for the first semester interview phase, and three mathematics experts for dependability data verification. Thematic analysis was performed on raw interview data. The REACT model identified 20 usability aspects of the algebra topic learning module, according to teacher responders. The Cohen Kappa Index approval coefficient averaged 0.9, suggesting high dependability. Five of the 18 items in the study were approved by expert teachers due to inter-rater reliability. According to student responses, the module comprises 30 components. Cohen Kappa Index approval coefficients average 0.82, showing high reliability. After inter-rater reliability, 26 items with 5 constructions were approved. The findings of this study have an impact on the modules used for teaching and studying mathematics in vocational colleges. These classes enhance students' understanding, proficiency, and attitudes towards mathematics. © 2024 IEEE.

Keywords

Author Keywords

mathematics REACT Model STEM Module

Index Keywords

Teaching Teachers' Apprentices Students Vocational colleges STEM (science, technology, engineering and mathematics) College students Algebra Cohen's kappas Interrater reliability Kappa index Learning modules Model module REACT model STEM module
Author Affiliations
Faculty of Technical and Vocational Education, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia
Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
Funding & Acknowledgements
Universiti Tun Hussein Onn Malaysia, UTHM
This research was supported by Universiti Tun Hussein Onn Malaysia (UTHM) through International Grant funded by Association of the Universities of Asia and the Pacific (AUAP) (vot W034) and Tier 1 (vot Q531).
Association of Arab Universities, AArU
Grant: W034, Q531
This research was supported by Universiti Tun Hussein Onn Malaysia (UTHM) through International Grant funded by Association of the Universities of Asia and the Pacific (AUAP) (vot W034) and Tier 1 (vot Q531).
Association of Arab Universities, AArU
This research was supported by Universiti Tun Hussein Onn Malaysia (UTHM) through International Grant funded by Association of the Universities of Asia and the Pacific (AUAP) (vot W034) and Tier 1 (vot Q531).
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