Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect | Zendy

Kavita Kelkar | Zendy; Dr Jagdish Bakal | Zendy

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Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect

Author(s) -

Kavita Kelkar,

Dr Jagdish Bakal

Publication year - 2020

Publication title -

international journal of recent technology and engineering (ijrte)

Language(s) - English

Resource type - Journals

ISSN - 2277-3878

DOI - 10.35940/ijrte.e6549.018520

Subject(s) - affect (linguistics) , confusion , grasp , computer science , usability , test (biology) , cognition , virtual learning environment , human–computer interaction , cognitive psychology , psychology , artificial intelligence , machine learning , multimedia , communication , paleontology , neuroscience , psychoanalysis , biology , programming language

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%.

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