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TSConnect: An Enhanced MOOC Platform for Bridging Communication Gaps Between Instructors and Students in Light of the Curse of Knowledge

Qianyu Liu, Xinran Li, Xiaocong Du, Quan Li

TL;DR

The paper targets the curse of knowledge as a barrier to effective MOOC-based learning. It introduces TSConnect, a bias-aware platform that combines a dynamic knowledge graph with multiple feedback channels to connect instructors, students, and AI. Through formative studies and a between-subjects user study (n=30), TSConnect improves the quality and quantity of student feedback and helps instructors diagnose root causes of learning obstacles, albeit with higher workload and cognitive demands. The work demonstrates potential for data-driven iterative improvement of teaching practices and suggests pathways for bias-aware, student-centered MOOC design with broader applicability beyond traditional online courses.

Abstract

Knowledge dissemination in educational settings is profoundly influenced by the curse of knowledge, a cognitive bias that causes experts to underestimate the challenges faced by learners due to their own in-depth understanding of the subject. This bias can hinder effective knowledge transfer and pedagogical effectiveness, and may be exacerbated by inadequate instructor-student communication. To encourage more effective feedback and promote empathy, we introduce TSConnect, a bias-aware, adaptable interactive MOOC (Massive Open Online Course) learning system, informed by a need-finding survey involving 129 students and 6 instructors. TSConnect integrates instructors, students, and Artificial Intelligence (AI) into a cohesive platform, facilitating diverse and targeted communication channels while addressing previously overlooked information needs. A notable feature is its dynamic knowledge graph, which enhances learning support and fosters a more interconnected educational experience. We conducted a between-subjects user study with 30 students comparing TSConnect to a baseline system. Results indicate that TSConnect significantly encourages students to provide more feedback to instructors. Additionally, interviews with 4 instructors reveal insights into how they interpret and respond to this feedback, potentially leading to improvements in teaching strategies and the development of broader pedagogical skills.

TSConnect: An Enhanced MOOC Platform for Bridging Communication Gaps Between Instructors and Students in Light of the Curse of Knowledge

TL;DR

The paper targets the curse of knowledge as a barrier to effective MOOC-based learning. It introduces TSConnect, a bias-aware platform that combines a dynamic knowledge graph with multiple feedback channels to connect instructors, students, and AI. Through formative studies and a between-subjects user study (n=30), TSConnect improves the quality and quantity of student feedback and helps instructors diagnose root causes of learning obstacles, albeit with higher workload and cognitive demands. The work demonstrates potential for data-driven iterative improvement of teaching practices and suggests pathways for bias-aware, student-centered MOOC design with broader applicability beyond traditional online courses.

Abstract

Knowledge dissemination in educational settings is profoundly influenced by the curse of knowledge, a cognitive bias that causes experts to underestimate the challenges faced by learners due to their own in-depth understanding of the subject. This bias can hinder effective knowledge transfer and pedagogical effectiveness, and may be exacerbated by inadequate instructor-student communication. To encourage more effective feedback and promote empathy, we introduce TSConnect, a bias-aware, adaptable interactive MOOC (Massive Open Online Course) learning system, informed by a need-finding survey involving 129 students and 6 instructors. TSConnect integrates instructors, students, and Artificial Intelligence (AI) into a cohesive platform, facilitating diverse and targeted communication channels while addressing previously overlooked information needs. A notable feature is its dynamic knowledge graph, which enhances learning support and fosters a more interconnected educational experience. We conducted a between-subjects user study with 30 students comparing TSConnect to a baseline system. Results indicate that TSConnect significantly encourages students to provide more feedback to instructors. Additionally, interviews with 4 instructors reveal insights into how they interpret and respond to this feedback, potentially leading to improvements in teaching strategies and the development of broader pedagogical skills.

Paper Structure

This paper contains 64 sections, 10 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. The Curse of Knowledge
  4. Technology-Enhanced Learning and Educational Recommendation Systems
  5. Teacher Education and Teaching Skills
  6. Formative Study
  7. Survey Study of Students
  8. Survey Protocol
  9. Respondents
  10. Semi-structured Interview of instructors
  11. Interview Protocol
  12. Participants
  13. Findings
  14. [Finding 1] The Necessity of instructors' proactive assessment of learning status
  15. [Finding 2] Learning challenges affect the willingness to communicate with instructors
  16. ...and 49 more sections

Figures (10)

  • Figure 1: The system architecture includes a central backend engine and dual frontend interfaces: a student end for pseudonym video viewing and feedback, and a teacher end for retrospective analysis insights.
  • Figure 2: The backend pipeline for dependency graph construction
  • Figure 3: Student end interface of TSConnect, featuring: A) the Course Video Player, B) the Comment Section, C) the Network View for displaying prerequisite dependency relationships, and D) Knowledge View for self-evaluation.
  • Figure 4: Instructor end interface of TSConnect, featuring: A) the Course Video Player, B) the VideoData View, C) the Comment Section, and D) the Network View for displaying prerequisite dependency relationships.
  • Figure 5: The Tooltip mode of the VideoData View. Upon mouse hover over the view, the system displays detailed feedback statistics while simultaneously highlighting the corresponding chapter title for the given temporal point.
  • ...and 5 more figures