Pedagogical Innovation of an Emotional-Responsive Agent to Improve PPG Student Engagement in Synchronous LMS

Dani Irawan; Citra Kurniawan; Municha Zainul

doi:10.51574/jrip.v5i3.4001

Authors

Dani Irawan Automotive Education Study Program, Faculty of Engineering, Universitas Negeri Malang, Indonesia https://orcid.org/0000-0002-8120-8860
Citra Kurniawan Educational Technolog Study Program, Faculty of Education, Universitas Negeri Malang, Indonesia https://orcid.org/0000-0001-7927-3500
Municha Zainul Teacher Professional Education Study Program, Graduate School, Universitas Negeri Malang, Indonesia

Keywords:

Emotionally Responsive Agent, Student Engagement, Learning Management System, Artificial Intelligence in Education

Abstract

The rapid digital transformation in higher education has accelerated the adoption of Learning Management Systems (LMS) as a primary platform for online learning, including in the Teacher Professional Education (PPG) program at Universitas Negeri Malang. However, synchronous LMS implementation still suffers from low student engagement, particularly in vocational fields such as automotive education which demand procedural knowledge and hands-on practice. Learning interactions tend to be one-way, lack emotional sensitivity, and reduce student participation. This study develops and evaluates an Emotionally Responsive Pedagogical Agent (PAER) to enhance engagement in synchronous LMS learning. PAER is an AI- and NLP-based virtual assistant designed to detect and respond to learners’ emotional states in real time, providing empathetic interaction and instructional support. The research adopts the ADDIE development model, consisting of needs analysis, emotional interaction design, prototype development, implementation in the PPG Automotive class, and evaluation. PAER effectiveness was measured across affective, cognitive, and behavioral engagement. Results show improved engagement: affective (61.3 to 83.4; N-Gain 0.57), cognitive (63.8 to 86.1; N-Gain 0.61), and behavioral (58.2 to 81.6; N-Gain 0.56), with an overall N-Gain of 0.58 (moderate-high category). These results indicate that emotionally adaptive learning agents can significantly improve interaction quality in LMS-based learning and foster more personalized and human-centered learning. This study contributes to the development of emotional AI in education and offers a scalable model for enhancing online pedagogy in vocational teacher training.

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