Journal of Engineering Education Transformations

Abstract

With the increasing rise in competitiveness and the rate at which technologies are growing, Engineering Education is facing challenge in equipping its students with the potential to deal with real life, complex problems and providing innovative solution for them. Educators report that the teaching process requires new pedagogical approach in fostering its students the skills required by the new globalized world. It is envisaged that engineering education needs shift in Teaching Learning Process (TLP) from Teacher-Centric approach to Learner- Centric environment. The traditional teaching approach may not provide students with the required skills and life-long learning. The student is not able to retain knowledge after exams. Due to the advancement in technology and exposure to the Internet, students are having many sources of information and learning centers. Due to this, students are drifted from the lecture-based teaching learning process towards the technology driven education. To meet the requirements of rapid changes and developments in technology, the biggest challenge is to use of knowledge into the recent teaching learning process, to produce professional engineers, who are globally accepted, skillful and industry ready. Today’s demand to implement innovative teaching methodologies and initiatives towards student professional development with a holistic approach.

Experiential learning (EL) or Learning by doing will begin a modern perspective towards teaching-learning process. The National Education Policy (NEP) 2020 emphasis more on experiential learning to help students to apply their knowledge in real world situation. This paper emphases on how EL helps to improve engineering student’s academic performance and overall development with global acceptance through hands-on laboratory experiments based on design and development (DnD), Professional Skill (PS), Project Based Learning (PBL) and Multidisciplinary Projects.

Student’s survey was conducted, and Prediction model is designed to measure the outcome of these activities. This paper attempts to get a hands-on experience of concepts which will enable students to think out-of-box and become a competent engineer. Experimental results showed that Logistic Regression performs better than Support Vector Machine to predict the outcome of Experiential Learning. Logistic Regression provides 83.87 % of Accuracy, 83.33 % of Precision and 95.23 % of Recall.

Keywords: Teaching Learning Process, Experiential learning, Project Based Learning, Professional Skill, Multidisciplinary Projects.