Continuous Evaluation of Video Lectures from Real-Time Difficulty Self-Report

Online Learning & MOOC PlatformsIntelligent Tutoring Systems & Learning AnalyticsK-12 TeachersUniversity Professors & ResearchersOnline Course Designers

With the increased reach and impact of video lectures, it is crucial to understand how they are experienced. Whereas previous studies typically present questionnaires at the end of the lecture, they fail to capture students' experience in enough granularity. In this paper we propose recording the lecture difficulty in real-time with a physical slider, enabling continuous and fine-grained analysis of the learning experience. We evaluated our approach in a study with 100 participants viewing two variants of two short lectures. We demonstrate that our approach helps us paint a more complete picture of the learning experience. Our analysis has design implications for instructors, providing them with a method that helps them compare their expectations with students' beliefs about the lectures and to better understand the specific effects of different instructional design decisions.

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https://hci.top/en/papers/chi/7805/2019

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Source
CHI
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Year
2019
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5 authors
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Subtopics
Online Learning & MOOC Platforms, Intelligent Tutoring Systems & Learning Analytics
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K-12 Teachers, University Professors & Researchers, Online Course Designers
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Abstract only
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