Research Methods in AI-Enhanced Educational Technology and Pedagogy

EasyChair Preprint no. 13892

Abstract

Research methods in AI-enhanced educational technology and pedagogy encompass a diverse array of approaches aimed at understanding the impacts and potentials of AI in education. Scholars and researchers employ quantitative methods to analyze large datasets generated by AI algorithms, examining correlations between student engagement, learning outcomes, and instructional strategies. Qualitative research methods delve into the nuanced experiences and perceptions of educators and learners regarding AI technologies, exploring issues such as trust, privacy concerns, and ethical considerations. Mixed-methods approaches integrate both quantitative and qualitative data to provide comprehensive insights into the multifaceted impacts of AI on educational practices. Moreover, action research methodologies enable educators to collaboratively design, implement, and evaluate AI-enhanced interventions in real-world educational settings, fostering iterative improvements and evidence-based pedagogical innovations. Through rigorous research methods, the field continues to advance understanding and optimize the integration of AI in educational technology to enhance learning outcomes and educational equity.

Keyphrases: AI in Education, EdTech innovations, personalized learning

@Booklet{EasyChair:13892,
  author = {Jane Elsa and Samir Yosef},
  title = {Research Methods in AI-Enhanced Educational Technology and Pedagogy},
  howpublished = {EasyChair Preprint no. 13892},

  year = {EasyChair, 2024}}