Elnetthra Folly Eldy

Artificial intelligence (AI) is revolutionizing education by enabling personalized learning tailored to individual student needs, especially in STEM fields. Tools like adaptive learning platforms and intelligent tutoring systems enhance engagement, understanding, and academic success through real-time feedback and targeted interventions. However, challenges such as unequal access to technology, data privacy concerns, and teacher readiness must be addressed. Examining case studies and ethical considerations highlights both opportunities and hurdles in AI integration. Collaborative efforts among educators, policymakers, and technologists are vital to ensure equitable access, robust infrastructure, and effective implementation, preparing all students for a technology-driven future.

Artificial intelligence (AI) is revolutionizing education by enabling personalized learning tailored to individual student needs, especially in STEM fields. Tools like adaptive learning platforms and intelligent tutoring systems enhance engagement, understanding, and academic success through real-time feedback and targeted interventions. However, challenges such as unequal access to technology, data privacy concerns, and teacher readiness must be addressed. Examining case studies and ethical considerations highlights both opportunities and hurdles in AI integration. Collaborative efforts among educators, policymakers, and technologists are vital to ensure equitable access, robust infrastructure, and effective implementation, preparing all students for a technology-driven future.

Online learning has been crucial since COVID-19, yet its effectiveness, particularly in physics education, remains debated. Understanding students’ motivation and problem-solving abilities in online environments is critical. This paper examined and presented the gender difference in motivation and problem-solving skills using an integrated online problem-based learning (iON-PBL) in a physics course. Developed using analysis, design, development, implementation, and evaluation (ADDIE) mode, iON-PBL module of physics guided students through problem-solving activities over 13 weeks. A post-test–delayed post-test design was used to assess retention of motivation and problem-solving skills. The study involved 116 pre-university students from Universiti Malaysia Sabah (88 females, 28 males). Motivation was measured using the motivated strategies for learning questionnaire (MSLQ) (four components), and problem-solving skills were assessed with the problem-solving inventory (PSI) (three components). Data analysis was conducted using SPSS version 28. Findings showed a significant gender difference in the ‘cognitive strategy’ component of motivation at the post-test, favoring female students. However, this difference was not sustained in the delayed post-test. In contrast, no gender difference was found in problem-solving at the post-test, but females scored significantly higher in ‘personal control’ in the delayed post-test. These findings suggest that female students are more likely to maintain cognitive strategies and personal control in online learning. Educators should consider targeted strategies to support male students’ motivation and problem-solving development in virtual environments to foster gender equity. Educators should consider targeted strategies to support male students’ motivation and problem-solving development in virtual environments to foster gender equity.