The landscape of higher education is being transformed by the integration of digital technologies, with online learning environments playing a central role in academic delivery. Within this paradigm, student engagement is critical to ensuring academic success. Intelligent Agents (IA) within Learning Management Systems (LMS) offer a groundbreaking approach to addressing engagement challenges by automating personalized reminders and fostering timely participation in essential academic activities such as Lecturer Evaluations (LE). This study investigates the impact of IA, presenting preliminary findings from data collected across 164 modules at Tshwane University of Technology (TUT) during four semesters in 2023 and 2024.

Preliminary results indicate a 112% improvement in LE response rates in modules with correctly configured IA compared to those with no or incorrectly configured IA. IA reminders were deployed at daily, weekly, and monthly intervals, with the most significant engagement improvements observed during daily runs over six weeks. Anonymized LMS data, including IA logs and response patterns, were analyzed to identify how configuration accuracy and timing influence participation. The findings underscore the transformative potential of well-designed IA interventions in enhancing engagement.

The research addresses the following key questions:
1. How do Intelligent Agents within LMS influence student engagement and response patterns in Lecturer Evaluations?
2. What configurations and scheduling strategies maximize the effectiveness of IA in promoting participation?
3. Can the principles of IA-driven engagement extend to broader LMS activities, enhancing their utility?

This research builds upon foundational studies by Fredricks et al. (2004) and Popenici & Kerr (2017), and aligns with contemporary findings such as Bälter (2023), which emphasize the efficacy of personalized, automated interventions. The study incorporates longitudinal data from 2023 and 2024 to provide a comprehensive perspective on IA effectiveness over time.

By developing an “IA Engagement Framework,” this research offers actionable strategies for educators and policymakers to optimize LMS functionalities, fostering inclusive and effective learning environments. These insights are pivotal as higher education institutions navigate the complexities of digital transformation and strive to ensure equitable access and student success.

Keywords: Intelligent Agents, Learning Management Systems, student engagement, lecturer evaluations, online education, Automated Interventions, personalized learning, Adaptive Learning Strategies, Educational Technology.