Adaptive gamification in e-learning based on students’ learning styles

ABSTRACT

With the removal of the barriers of time and distance, E-learning platforms have attracted millions of learners, but these platforms are experiencing a significant drop-out ratio. One of the primary reasons for this problem is the lack of motivation among the learners because of the similar learning experience provided to them despite their varying learning styles. Different researchers have introduced gamification as a solution for students’ engagement. The technique has improved engagement levels a bit, but it is not as useful as it was expected to be. One of the primary problems with gamification elements is their inability to induce intrinsic motivation among learners. To target this issue, we have proposed a framework that identifies the learning style of students based on their interactions with the system and provides an adaptive gamification experience according to their identified learning dimensions. The results of the experiments show that the motivation of learners increases by 25%, and the drop-out ratio is reduced by 26%.

KEYWORDS:

• Gamification
• e-learning
• adaptive learning
• motivation
• learning dimensions

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Muhammad Awais Hassan

Dr Muhammad Awais Hassan is assisstant professor at Computer Science and Engineering Department at the University of Engineering and Technology. He is Gold Medalist of Punjab University. He has completed his MS from UET Lahore and currently doing Ph.d from the same university. His research interest includes Natural Language Processing, Semantic Web, Software Arechitecture and Open source Software Development.

Ume Habiba

Miss Ume Habiba is a post Graduate student of computer science at Computer Science and Engineering Department at the University of Engineering and Technology Lahore, Pakistan. Her research interests include gamification, and adaptive learning. She is also working as a research assistant in UET Lahore.

Fiaz Majeed

Dr Fiaz Majeed is an assistant professor at University of Gujrat (UOG). He has completed his Ph.D from UET Lahore. His research interests include information retreival, data warehousing, and data streams.

Muhammad Shoaib

Dr Muhammad Shoaib is a professor at Computer Science and Engineering Department at the University of Engineering and Technology Lahore, Pakistan. He received his MSc in computer science from Islamia University, Pakistan. He has completed his PhD from the University of Engineering and Technology, Pakistan in 2006. His Post Doc. is from Florida Atlantic University, USA, in 2009. His current research interests include information retrieval systems, information systems, software engineering and semantic web.