The Role of Adaptive Personalized Technologies in the Learning Process

The integration of artificial intelligence (AI) in mathematics education, focusing on its implications in the 4<sup>th</sup> Industrial Revolution (4IR) era. Through a comprehensive analysis of 10 relevant studies in Scopus and Google Scholar from 2015 to 2023, this review identifies the research methods, research instruments, participants, and AI tools used in mathematics education. Some key ideas include using AI-driven personalized learning and enhanced mathematics instruction, real-time assessment and feedback, curriculum development, and empowering educators, which were highlighted. The study aligns with the preferred reporting items for systematic reviews and meta-analysis. Based on the analysis, most studies reviewed utilized qualitative research methods. The study indicates that questionnaires were mainly used to gather data from students and teachers who were the most significant participants in the reviewed papers. Further results revealed that ChatGPT were the primary AI tool used in mathematics education, among other AI tools, as identified in this review. Additionally, this review discusses the transformative potential of AI in addressing educational disparities and preparing learners for the demands of 4IR.

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Designing Adaptive Learning Space by Integrating Technology to a Sustainable Classroom

Hotar,

Baran,

Tokuç

et al. 2024

Advances in Educational Technologies and Instructional Design

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It is imperative to consider what adaptive and innovative learning spaces should include if higher education institutions want their students to be open to learning, creative thinkers and digitally literate. This chapter of the book starts with a review of sustainable learning spaces and continues with the introduction of technological developments (AI, IoT, Hybrid Education, VR, etc.) that transform traditional learning spaces into innovative spaces that better meet the needs of learners in terms of pedagogy, interaction, progress, measurement and assessment. Finally, the meta-classroom model, developed as a result of a project by authors from different disciplines such as educational technology, architecture, computer science, etc., is presented as an adaptive learning space model for higher education. This model prioritises diverse learning needs, takes into account the thermal comfort and indoor air quality of stakeholders in the classroom, enables lifelong learning and encourages learners' creative thinking and problem-solving skills in a collaborative learning environment.

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The Role of Adaptive Personalized Technologies in the Learning Process

Cited by 3 publications

References 22 publications

Application of Reinforcement Learning Algorithm in Personalized Music Teaching

Application of Reinforcement Learning Algorithm in Personalized Music Teaching

A systematic review of artificial intelligence in mathematics education: The emergence of 4IR

Designing Adaptive Learning Space by Integrating Technology to a Sustainable Classroom

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