Cognitive Evaluation of Examinees by Dynamic Question Set Generation based on Bloom’s Taxonomy

Abstract

Educational data mining (EDM) is an emerging topic in recent years steered by data mining and machine learning techniques to enhance students’ overall learning experience and academic progress. In recent years EDM techniques are frequently used to improve assessment systems but the evaluation procedure is majorly marks driven. Developing an evaluation system to distinguish candidates, based on their ability to answer cognitively difficult questions is a challenging task. In this study, a unique methodology is proposed to dynamically rank the candidates to develop an outcome-based online examination system that will properly evaluate a candidate’s cognitive competencies. The questions are segmented into different cognitive groups based on classical Bloom’s educational taxonomy. The Jenks Natural Breaks Optimization technique is used here to segment the questions and as a result, distinct question clusters based on different cognitive levels are obtained. Students are evaluated with different questions from these cognitive groups and ranking is done for individual candidates considering both the marks of the questions and his/her ability to solve questions from different difficulty levels.

KEYWORDS:

• Bloom’s taxonomy
• Cognitive level
• Clustering
• Educational data mining
• Jenks Natural Breaks Optimization
• Machine learning
• Ranking

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Anjan Dutta

Anjan Dutta completed his Bachelor of Technology in information technology from Regional Computer Centre Institute of Information Technology, Kolkata, India and Master of Technology in information technology from Calcutta University, Kolkata, India. Currently, he is working as a lecturer in computer science and technology, Raja Ranjit Kishore Govt. Polytechnic, Jhargram, India. He is pursuing PhD at Jadavpur University, Kolkata, India. His research area includes data mining, big data and machine learning. Corresponding author. Email: [email protected]

Punyasha Chatterjee

Punyasha Chatterjee received the BTech, MTech and PhD degrees in information technology from the University of Calcutta, Kolkata, India, in 2003, 2005 and 2018, respectively. She has been an assistant professor in the School of Mobile Computing and Communication, Jadavpur University, Kolkata, India, since 2012. Her area of interest includes adhoc networks, wireless sensor networks, internet of things and pervasive computing. She is a Senior Member of IEEE and a Member of ACM. Email: [email protected]

Nilanjan Dey

Nilanjan Day was born in Kolkata, India, in 1984. He received his BTech degree in information technology from West Bengal University of Technology in 2005, MTech in information technology in 2011 from the same University and PhD in digital image processing in 2015 from Jadavpur University, India. In 2011, he was appointed as an assistant professor in the Department of Information Technology at JIS College of Engineering, Kalyani, India followed by Bengal College of Engineering College, Durgapur, India in 2014. He is now employed as an associate professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. His research topic is signal processing, machine learning and information security. Email: [email protected]

Pablo Moreno-Ger

Pablo Moreno-Ger was born in Madrid, Spain, in 1981. He received a degree in computer engineering from Universidad Complutense de Madrid, in 2004, and PhD in computer science from the Department of Software Engineering and Artificial Intelligence, Universidad Complutense de Madrid, in 2007. He is currently the director of the School of Engineering and Technology, UNIR. He was with the Universidad Complutense de Madrid, where he was a Member of the e-UCM Research Group. He was also the vice dean for Innovation with the School of Computer Engineering, Universidad Complutense de Madrid. He has a strong research record in technology enhanced learning, AI, machine learning and learning analytics. He has published more than 150 academic articles in these topics. He holds the IBM Chair on Data Science in Education at UNIR. Email: [email protected]

Soumya Sen

Soumya Sen received PhD in computer science & engineering from the University of Calcutta in 2016. He received the MTech in computer science & engineering in 2007 and MSc in computer and information science in 2005 also from University of Calcutta. He joined the A K Choudhury School of Information Technology at the University of Calcutta in 2009. He has around 80 research publications in international journals and conferences. He has 3 international patents and also published 2 books. He is a TPC member of many conferences across the world and serves as a reviewer for international journals. He is a member of IEEE and ACM. His current research interests are data warehouse & OLAP tools, data mining and distributed database. Email: [email protected]