2026, 3(Special Issue 1), 89-96, 10.70372/jeltp.v3.sp1.13, None
In the Industry 4.0 era, the challenges to be overcome by engineering education are twofold: covering increasingly complex theoretical concepts and developing practical, hands-on skills. Analog and Digital communication courses are characterized by abstract mathematical foundations and intricate…
2026, 3(Special Issue 1), 83-88, 10.70372/jeltp.v3.sp1.12, None
This practice adds a fast, suitable AI layer to micro-teaching such that teaching, assessment, and feedback happen in the same class cycle. After a short lesson, students complete a five-item Google Form: four concept questions (multiple choice or short answer) plus a 1–5 self-rating on at…
2026, 3(Special Issue 1), 78-82, 10.70372/jeltp.v3.sp1.11, None
This paper presents an innovative teaching–learning practice that integrates Artificial Intelligence (AI)-generated animated video quizzing with traditional learning pedagogies to improve engagement in theoretical courses of Electrical Engineering. Using InVideo, an AI-powered video creati…
2026, 3(Special Issue 1), 69-77, 10.70372/jeltp.v3.sp1.10, None
In outcome-oriented higher education, feedback from students is essential to ensure the teaching–learning (T-L) quality and continual improvement. The majority of Higher Education Institutions (HEIs) still rely on manual analysis, despite the fact that feedback can often be collected onlin…
2026, 3(Special Issue 1), 57-68, 10.70372/jeltp.v3.sp1.9, None
Traditional pedagogy is increasingly being transcended by Heutagogy as Education 5.0 moves toward experiential, learner-driven frameworks. In alignment with this shift, the present study explores the effectiveness of AI-enhanced, vodcast-based learning in undergraduate engineering education. Res…
2026, 3(Special Issue 1), 41-56, 10.70372/jeltp.v3.sp1.8, None
This paper presents an innovative pedagogical practice titled "Teach the AI - Vidyarthi Vijaya" that reverses traditional classroom dynamics by positioning students as teachers to an AI-powered chatbot. Implemented in an MBA Digital Marketing course with 12 students, this initiative em…
2026, 3(Special Issue 1), 32-40, 10.70372/jeltp.v3.sp1.7, None
Course Delivery is a detailed lesson plan about how the entire course will be delivered in that term or semester including the outcomes expected, learning interventions planned and assessments to measure the achievement of outcomes. Student performance and student engagement in the course taught…
2026, 3(Special Issue 1), 24-31, 10.70372/jeltp.v3.sp1.6, None
English language learning is essential for engineering graduates, yet traditional instructional approaches often result in passive participation and reduced motivation. This study presents a project-based gamification model implemented through a 30-hour elective course, where engineering student…
2026, 3(Special Issue 1), 19-23, 10.70372/jeltp.v3.sp1.5, None
In education, classroom engagement tools have become essential for teachers to connect with Gen-Z students. In this digital era dominated by Artificial Intelligence (AI), classroom engagement tools have revolutionized education by transforming lessons into vibrant, participatory experiences that…
2026, 3(Special Issue 1), 15-18, 10.70372/jeltp.v3.sp1.3, None
The integration of Artificial Intelligence (AI) in higher education has transformed the preparation, delivery, and accessibility of instructional materials. Traditionally, faculty members spend significant time creating lecture notes, assessments, bilingual content, and visual materials. With AI…
2026, 3(Special Issue 1), 7-14, 10.70372/jeltp.v3.sp1.2, None
Gamified, data-driven learning models are evolving engineering education into a dimensional, facilitating improved motivation, analytics, and contextualization. This research study presents the implementation of a machine learning-abled gamified model for the Computer Organization and Architectu…
2026, 3(Special Issue 1), 1-6, 10.70372/jeltp.v3.sp1.1, None
KARE–Teaching Learning Centre has operationalized a human-centric, tool-agnostic microteaching assisted by Artificial intelligence (MT–AI) model that breaks core topics into 10–15 minute micro-segments, couples AI-assisted preparation with visual pedagogy, and closes each loop …