Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect
Kavita M Kelkar1, Jagdish Bakal2
1Kavita Kelkar*, Research Scholar, Department of Computer Engineering, Sardar Patel Institute of Technology; Faculty,K J Somaiya College of Engineering, University of Mumbai, India.
2Dr Jagdish Bakal, Principal, S S Jondhale College of Engineering, University of Mumbai, India.

Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4034-4039 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6549018520/2020©BEIESP | DOI: 10.35940/ijrte.E6549.018520

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Abstract: Virtual learning systems are expected to be adaptive to the grasp exhibited by the learner. Learner affects like confusion and confidence are displayed by the learner through behavioural cues. Identifying affect in a non-intrusive, sensor-free and scalable setting is preferable. Using interaction based behavioural log features; methodology for determining learner affect is presented. The MCQ test questions in the system are based on Bloom’s Taxonomy Cognitive levels. The system records interactions of the learner. The regression analysis result on the dataset shows accuracy of confusion detection above 70%.
Keywords: Cognitive Levels, Virtual Learning System, Learning Affect, MCQ Test, Interaction Patterns. Abbreviation: MCQ: Multiple Choice Questions.
Scope of the Article: Online learning Systems.