Real-Time Cognitive Evaluation of Online Learners through Automatically Generated Questions
This addresses engagement issues for online learners and instructors by automating question generation, though it is incremental as it builds on existing text extraction and question generation methods.
The paper tackles the challenge of maintaining online learner engagement by automatically generating wh-questions from video lectures to evaluate lower-level cognitive abilities, providing feedback on responses to free instructors from question design.
With the increased adoption of E-learning platforms, keeping online learners engaged throughout a lesson is challenging. One approach to tackle this challenge is to probe learn-ers periodically by asking questions. The paper presents an approach to generate questions from a given video lecture automatically. The generated questions are aimed to evaluate learners' lower-level cognitive abilities. The approach automatically extracts text from video lectures to generates wh-kinds of questions. When learners respond with an answer, the proposed approach further evaluates the response and provides feedback. Besides enhancing learner's engagement, this approach's main benefits are that it frees instructors from design-ing questions to check the comprehension of a topic. Thus, instructors can spend this time productively on other activities.