Scholarlink

<p>Artificial intelligence (AI) and learning analytics are transforming higher education by enabling data-driven personalization, adaptive assessment, and informed instructional decision-making. Conventional learning management systems (LMSs) primarily support content delivery but lack mechanisms for providing actionable insights to educators or personalized guidance to learners. To address these limitations, this study introduces an AI-Supported Learning Analytics Platform that integrates three key functions: (i) personalized learner support through intelligent matching and recommendations, (ii) automated quiz generation and evaluation using large language models, and (iii) conversational assistance for real-time interaction. The platform not only enhances student engagement but also collects interaction and performance data, which are trans- formed into analytics for educators to inform course design and pedagogical strategies. A mixed-method research design, combining system development with quasi-experimental evaluation, was employed in a higher education context. Findings indicate that students using the proposed platform achieved higher academic performance, greater engagement, and improved satisfaction compared to those using traditional LMSs. Moreover, the analytics generated provided educators with valuable feedback for evidence-based decision-making. This study contributes to the field of educational technology by (1) demonstrating how AI- driven personalization, assessment, and conversational support can be embedded in higher education platforms, (2) highlighting the role of learning analytics in supporting both student learning and educator decision-making, and (3) offering a framework for integrating AI-supported analytics into institutional teaching and learning practices. The results affirm the potential of AI-enhanced systems to strengthen both learner experiences and institutional decision-making in higher education.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Design and Implementation of an AI Integrated Educational Assistant for Learning

  • 期刊论文

  • 发表日期：

    2026年5月20日

查看全文
  • Karthikeyan Jothikumar,
  • Gomathi Velusamy,
  • A. J. Meenakshi,
  • S. Aruna Varshini,
  • S. Anisha

摘要

Artificial intelligence (AI) and learning analytics are transforming higher education by enabling data-driven personalization, adaptive assessment, and informed instructional decision-making. Conventional learning management systems (LMSs) primarily support content delivery but lack mechanisms for providing actionable insights to educators or personalized guidance to learners. To address these limitations, this study introduces an AI-Supported Learning Analytics Platform that integrates three key functions: (i) personalized learner support through intelligent matching and recommendations, (ii) automated quiz generation and evaluation using large language models, and (iii) conversational assistance for real-time interaction. The platform not only enhances student engagement but also collects interaction and performance data, which are trans- formed into analytics for educators to inform course design and pedagogical strategies. A mixed-method research design, combining system development with quasi-experimental evaluation, was employed in a higher education context. Findings indicate that students using the proposed platform achieved higher academic performance, greater engagement, and improved satisfaction compared to those using traditional LMSs. Moreover, the analytics generated provided educators with valuable feedback for evidence-based decision-making. This study contributes to the field of educational technology by (1) demonstrating how AI- driven personalization, assessment, and conversational support can be embedded in higher education platforms, (2) highlighting the role of learning analytics in supporting both student learning and educator decision-making, and (3) offering a framework for integrating AI-supported analytics into institutional teaching and learning practices. The results affirm the potential of AI-enhanced systems to strengthen both learner experiences and institutional decision-making in higher education.