HyperMOOC: Augmenting MOOC Videos with Concept-based Embedded Visualizations

TL;DR

HyperMOOC tackles the challenge of maintaining knowledge context in MOOC videos by embedding concept-based visualizations directly into the video through a concept-driven design space and a three-stage Play–Focused–Paused interaction. The system combines a bottom-up data-processing pipeline with multi-glyph visualizations and hyperlink-based navigation to support simultaneous explanatory and exploratory learning. A user study (n=36) and expert interviews demonstrate that FULL HyperMOOC improves learning outcomes and reduces cognitive load compared to raw videos, though effectiveness is moderated by learner background and information density. The approach advances design principles for cognitive-guided, embedded educational visualizations and offers a generalizable framework for enhancing information-dense video tutorials across domains.

Abstract

Massive Open Online Courses (MOOCs) have become increasingly popular worldwide. However, learners primarily rely on watching videos, easily losing knowledge context and reducing learning effectiveness. We propose HyperMOOC, a novel approach augmenting MOOC videos with concept-based embedded visualizations to help learners maintain knowledge context. Informed by expert interviews and literature review, HyperMOOC employs multi-glyph designs for different knowledge types and multi-stage interactions for deeper understanding. Using a timeline-based radial visualization, learners can grasp cognitive paths of concepts and navigate courses through hyperlink-based interactions. We evaluated HyperMOOC through a user study with 36 MOOC learners and interviews with two instructors. Results demonstrate that HyperMOOC enhances learners' learning effect and efficiency on MOOCs, with participants showing higher satisfaction and improved course understanding compared to traditional video-based learning approaches.

Figures (10)

• Figure 1: Left: An original MOOC video. Middle: HyperMOOC utilizes deep learning models to extract data from the original video, allowing learners to deepen their course understanding through direct interactions with elements in the video, facilitated by a concept-based design space, multi-glyph embedded visualizations, and hyperlink-based interactions. Right: The multi-stage augmented video highlights course organization and concept relationships.
• Figure 2: Literature review result, including the number of literature on a) research filed, b) analytical task, c) employed data, and d) content of interest.
• Figure 3: The design of Play (a,b,c) and Focused (d) stage of HyperMOOC, Alex is currently viewing the original content of concept "Percentages" in "Preparation" stage.
• Figure 4: HyperMOOC interaction workflow includes 1) Play - Follow the instructor's learning path. 2) Focused - Get concept explanation, and 3) Paused - Deepen the course understanding. Paused stage user interface, a) slides and course overview, b) video player, including (b1) concept relationships and (b2) demonstration materials, and c) video preview. Alex is currently delving into the concept of "Percentages" and how it relates to others.
• Figure 5: The data processing pipeline for augmenting MOOC videos. HyperMOOC adopts a bottom-up approach to (a) extract slides and audio from raw videos, then further distills these into (b) element-level, (c) event-level, and (d) conclusion-level representations through deep learning models.