Using Kolb's Experiential Learning Theory to Improve Student Learning in Theory Course

Abstract

Abstract : Data structures and Algorithms (DSA) is a mandatory course for all discipline students to get placement in IT companies and to participate in competitive examinations including GATE and TANCET for their higher studies in a computer science discipline. DSA course focuses on how to organize, manage and store data in an efficient manner, which facilitates to access data easily and at a faster rate. Different types of data structures, its functionality and its applicability are discussed in this course. At the end of the course, students will have the capability to identify the suitable data structure for a problem. Due to its importance and complexity, pressure will be created on faculty members, who are handling this course. From the perspective of the student, some students understand the concept but lack knowledge of how to apply it. The majority of students struggle to comprehend the data structure and are perplexed by it. Recent work focuses on how faculty members play a major role in active learning like developing models to explain the concept, conducting activities like role play, think-pair share, flipped classrooms and so on. In this work, a study was conducted in the course DSA which focused on reflective practice led by David Kolb's experiential learning theory. An experiment was conducted during Academic Year 2021-22 (Odd) in the course 18CS340 – Data Structures and Algorithms for a set of 54 students. It is inferred that the student gained a higher or deeper knowledge level in this course and is confident to identify appropriate data structures for real world problems. By engaging in reflective practice, faculty members can think around and reflect on their experiences, learn from them, make changes, and enhance their learning and instructional skills. Keywords : Activity-based learning, Data Structures and Algorithms, Kolb's experiential learning, Reflective practice, Self-Learning.