Classification of Students’ Misconceptions in Individualised Learning Environments (C-SMILE): An Innovative Assessment Tool for Engineering Education Settings N. P. Subheesh Dept. of HSS IIT Madras Chennai, Tamilnadu, India npsubheesh@gmail.com Meka Varsha Dept. of CSE SRM University AP Andhra Pradesh, India meka_varsha@srmap.edu.in Sobin C. C. Dept. of CSE SRM University AP Andhra Pradesh, India sobincc@gmail.com Jahfar Ali LTRC IIIT Hyderabad Telangana, India jahfar2004@gmail.com Abstract— The COVID-19 pandemic has reformed the teaching-learning processes in engineering education across the globe. Virtual classrooms substituted physical classrooms with the widespread use of online meeting platforms. The proliferation of virtual classrooms not only paved the way for accelerated digital transformation but also brought back some elementary issues in engineering education. Many engineering students face difficulties in comprehending the fundamental concepts in their courses during virtual learning. As real-world engineering solutions depend on conceptual clarity, misconceptions of basic engineering principles need to be taken seriously. If not identified, analysed and corrected with constructive feedback, misconceptions on various engineering topics can create challenging obstacles in learning. Against this backdrop, this research study introduces a novel solution titled Classification of Students Misconceptions in Individualised Learning Environment (C-SMILE). The primary objective of the C-SMILE system is to examine the usefulness of personalised automated feedback to students to enhance their conceptual understanding by pinpointing their misconceptions. Besides, we propose a method by which students’ misconceptions can be effectively classified for every instructional objective in every engineering course using machine learning techniques. Our pilot-study results show that the proposed C-SMILE system can precisely classify students’ misconceptions in engineering education settings. Keywords— Automated Feedback, C-SMILE, Formative Assessment, Individualised Learning, Misconceptions I. INTRODUCTION The emergence of the COVID-19 pandemic in December 2020 has made enormous changes in the higher education settings across the globe [1-3]. The traditional physical classroom education systems were abruptly switched to the online education systems. Although several universities used digital education using learning management systems earlier, the rapid shift brought many difficulties for both teachers and students [4]. Many of the students face problems in understanding the basic engineering concepts through online learning. Teachers are also facing issues in assessing and taking remedial action for students’ misconceptions of course contents in the post-COVID era. According to Rapanta et al. and Dwivedi et al. [5-6], the COVID-19 pandemic has severe repercussions on students’ learning and the educational assessment system. An emergent solution to tackle this situation is creating automated individualised learning environments that incorporate effective assessment and feedback practices. Online assessment tools play a vital role, particularly in post-COVID online education settings. The extent of attainment of the primary purposes of assessment determines the quality of online education. The most significant purpose of assessment is to identify students’ strengths and weaknesses in learning course contents. Assessment can enhance students’ learning by providing individualised qualitative feedback [7]. Another purpose of assessment is to assure higher education stakeholders that the students have achieved the required knowledge and skills for employment. As the quality of assessment tools are affected due to the inherent limitations of online learning, these purposes are not adequately met. There is a critical necessity to develop novel assessment tools customised for the post-COVID virtual classrooms, especially for engineering education. Among different assessment types, formative assessment is the one that directly helps students to improve their learning. It is the continuous assessment process conducted throughout the course with the intention to enhance the learning. Rather than assigning marks and grades, it focuses on the learning process. It gives a perception to the teachers about how much students have comprehended course contents. If students’ learning is not proper, corrective actions can be undertaken using the qualitative feedback mechanism. Many researchers [7-12] have extensively used formative assessments with innovative modifications. In particular, there are only a very few studies on identifying students’ misconceptions for providing corrective feedback to them. Such assessment approaches are crucial in online learning. Generating automated feedback for every misconception can work wonders in the online learning process. In 2016, Bhagat et al. [7] developed an innovative formative assessment system entitled i-SMILE (Identification Page 795 2022 IEEE Global Engineering Education Conference (EDUCON) | 978-1-6654-4434-7/22/$31.00 ©2022 IEEE | DOI: 10.1109/EDUCON52537.2022.9766572 Authorized licensed use limited to: National Institute of Technology Patna. Downloaded on October 11,2022 at 08:01:58 UTC from IEEE Xplore. Restrictions apply.