CoChat
Sign Up
Cited by 17Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive LearningVisual and Cognitive Learning Processes

VIVID: Human-AI Collaborative Authoring of Vicarious Dialogues from Lecture Videos

Open access
Choi, Seulgi, Lee, Hyewon, Lee, Yoonjoo, Kim, Juho·2024·Proceedings of the CHI Conference on Human Factors in Computing Systems
DOI 10.1145/3613904.3642867
Open this paper in CoChat — free account

Abstract

The lengthy monologue-style online lectures cause learners to lose engagement easily. Designing lectures in a “vicarious dialogue” format can foster learners’ cognitive activities more than monologue-style. However, designing online lectures in a dialogue style catered to the diverse needs of learners is laborious for instructors. We conducted a design workshop with eight educational experts and seven instructors to present key guidelines and the potential use of large language models (LLM) to transform a monologue lecture script into pedagogically meaningful dialogue. Applying these design guidelines, we created VIVID which allows instructors to collaborate with LLMs to design, evaluate, and modify pedagogical dialogues. In a within-subjects study with instructors (N=12), we show that VIVID helped instructors select and revise dialogues efficiently, thereby supporting the authoring of quality dialogues. Our findings demonstrate the potential of LLMs to assist instructors with creating high-quality educational dialogues across various learning stages.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/3613904.3642867

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In the Creative context, support for translating often occurs simultaneously with support for generating ideas, creating narratives or creative elements that blend the user's prior text with new ideas from the AI.

    “Support for translating often occurs simultaneously with support for generating ideas, creating narratives or creative elements that blend the user's prior text with new ideas from the AI [22,41].”

    From Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process (2025) · cites this paper as [22]

    Section 4.3 (p. 5) says LLM-generated dialogues can stimulate instructors’ ideation, and Section 5 (p. 6) describes creating dialogues from instructors’ lecture videos. This supports combining existing material with AI-generated dialogue, but the paper does not establish that translation support often occurs alongside idea generation; its transformation is from lecture monologue to dialogue, not between languages. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 30

  1. [1][1] John R Anderson, C Franklin Boyle, and Brian J Reiser. 1985. Intelligent tutoring systems. Science 228, 4698 (1985), 456-462. -
  2. [2][2] Albert Bandura and Richard H Walters. 1977. Social learning theory . Vol. 1. Englewood cliffs Prentice Hall. -
  3. [4][4] Mobina Beheshti, Ata Taspolat, Omer Sami Kaya, and Hamza Fatih Sapanca. 2018. Characteristics of instructional videos. World Journal on Educational Technology: Current Issues 10, 1 (2018), 61-69. -
  4. [5][5] Kristy Boyer, Robert Phillips, Michael Wallis, Mladen Vouk, and James Lester. 2008. Learner characteristics and feedback in tutorial dialogue. In Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications . 53-61. -
  5. [8][8] HDavid Brecht. 2012. Learning from online video lectures. Journal of Information Technology Education. Innovations in Practice 11 (2012), 227. -
  6. [13][13] Michelene TH Chi, Stephanie A Siler, Heisawn Jeong, Takashi Yamauchi, and Robert G Hausmann. 2001. Learning from human tutoring. Cognitive science 25, 4 (2001), 471-533. -
  7. [18][18] Paul Denny, Hassan Khosravi, Arto Hellas, Juho Leinonen, and Sami Sarsa. 2023. Human vs Machine: Comparison of Student-generated and AI-generated Educational Content. arXiv preprint arXiv:2306.10509 (2023). - · arXiv
  8. [20][20] Sidney D'Mello, Blair Lehman, and Natalie Person. 2010. Expert tutors feedback is immediate, direct, and discriminating. In Twenty-Third International FLAIRS Conference . -
  9. [22][22] David M Driscoll, Scotty D Craig, Barry Gholson, Matthew Ventura, Xiangen Hu, and Arthur C Graesser. 2003. Vicarious learning: Effects of overhearing dialog and monologue-like discourse in a virtual tutoring session. Journal of Educational Computing Research 29, 4 (2003), 431-450. -
  10. [24][24] Matthew S Ellman and Michael L Schwartz. 2016. Article commentary: Online learning tools as supplements for basic and clinical science education. Journal of medical education and curricular development 3 (2016), JMECD-S18933. -
  11. [25][25] Ethan Fast, Binbin Chen, Julia Mendelsohn, Jonathan Bassen, and Michael S Bernstein. 2018. Iris: A conversational agent for complex tasks. In Proceedings of the 2018 CHI conference on human factors in computing systems . 1-12. -
  12. [26][26] Mary Forehand. 2010. Bloom's taxonomy. Emerging perspectives on learning, teaching, and technology 41, 4 (2010), 47-56. -
  13. [31][31] Joshua Grossman, Zhiyuan Lin, Hao Sheng, Johnny Tian-Zheng Wei, Joseph J Williams, and Sharad Goel. 2019. MathBot: Transforming online resources for learning math into conversational interactions. AAAI 2019 Story-Enabled Intelligence (2019). -
  14. [40][40] Juho Leinonen, Paul Denny, Stephen MacNeil, Sami Sarsa, Seth Bernstein, Joanne Kim, Andrew Tran, and Arto Hellas. 2023. Comparing code explanations created by students and large language models. arXiv preprint arXiv:2304.03938 (2023). - · arXiv
  15. [46][46] Sue Lyle. 2008. Dialogic teaching: Discussing theoretical contexts and reviewing evidence from classroom practice. Language and education 22, 3 (2008), 222-240. -
  16. [47][47] Wenting Ma, Olusola O Adesope, John C Nesbit, and Qing Liu. 2014. Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of educational psychology 106, 4 (2014), 901. -
  17. [49][49] J Terry Mayes. 2015. Still to learn from vicarious learning. E-learning and digital media 12, 3-4 (2015), 361-371. -
  18. [51][51] David Moher, Alessandro Liberati, Jennifer Tetzlaff, and Douglas Altman. 2009. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement. Br Med J 8 (07 2009), 336-341. https://doi.org/10.1371/ joumal.pmedl000097 -
  19. [53][53] Heli Muhonen, Helena Rasku-Puttonen, Eija Pakarinen, Anna-Maija Poikkeus, and Marja-Kristiina Lerkkanen. 2016. Scaffolding through dialogic teaching in early school classrooms. Teaching and teacher education 55 (2016), 143-154. -
  20. [56][56] Kian Keong Aloysius Ong, Christina Eugene Hart, and Poh Keong Chen. 2016. Promoting higher-order thinking through teacher questioning: a case study of a Singapore science classroom. New Waves-Educational Research and Development Journal 19, 1 (2016), 1-19. -
  21. [58][58] Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, and Ilya Sutskever. 2023. Robust speech recognition via large-scale weak supervision. In International Conference on Machine Learning . PMLR, 28492-28518. -
  22. [59][59] Caroline P Rose, Dumisizwe Bhembe, Stephanie Siler, Ramesh Srivastava, and Kurt VanLehn. 2003. The role of why questions in effective human tutoring. In Proceedings of AIED , Vol. 3. -
  23. [60][60] Sherry Ruan, Liwei Jiang, Justin Xu, Bryce Joe-Kun Tham, Zhengneng Qiu, Yeshuang Zhu, Elizabeth L Murnane, Emma Brunskill, and James A Landay. 2019. Quizbot: A dialogue-based adaptive learning system for factual knowledge. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems . 1-13. -
  24. [62][62] Pragnya Sridhar, Aidan Doyle, Arav Agarwal, Christopher Bogart, Jaromir Savelka, and Majd Sakr. 2023. Harnessing llms in curricular design: Using gpt-4 to support authoring of learning objectives. arXiv preprint arXiv:2306.17459 (2023). - · arXiv
  25. [66][66] Karen Swan. 2003. Learning effectiveness online: What the research tells us. Elements of quality online education, practice and direction 4, 1 (2003), 13-47. -
  26. [67][67] Thitaree Tanprasert, Sidney S Fels, Luanne Sinnamon, and Dongwook Yoon. 2022. Authoring Virtual Peer Interactions for Lecture Videos. In CHI Conference on Human Factors in Computing Systems Extended Abstracts . 1-7. -
  27. [70][70] Kurt VanLehn, Stephanie Siler, Charles Murray, Takashi Yamauchi, and William B Baggett. 2003. Why do only some events cause learning during human tutoring? Cognition and Instruction 21, 3 (2003), 209-249. -
  28. [74][74] Zichao Wang, Andrew S Lan, Weili Nie, Andrew E Waters, Phillip J Grimaldi, and Richard G Baraniuk. 2018. QG-net: a data-driven question generation model for educational content. In Proceedings of the fifth annual ACM conference on learning at scale . 1-10. -
  29. [77][77] Hongbin Ye, Tong Liu, Aijia Zhang, Wei Hua, and Weiqiang Jia. 2023. Cognitive mirage: A review of hallucinations in large language models. arXiv preprint arXiv:2309.06794 (2023). - · arXiv
  30. [78][78] Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, et al. 2023. Siren's song in the AI ocean: a survey on hallucination in large language models. arXiv preprint arXiv:2309.01219 (2023). · arXiv

Cited by

Sorted by citations

Related

Authors
Choi, S., Lee, H., Lee, Y., & Kim, J.
Affiliations
Korea Advanced Institute of Science and Technology (KR)
ORCID
Venue
Proceedings of the CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2024-05-11
Pages
1-26
DOI
10.1145/3613904.3642867
OpenAlex
W4396833634
Cited by
17
References
49
Citations by year
2026: 6 · 2025: 11
FWCI
6.46
Type
conference paper
Language
en
Open access
Licence
Locations
  • CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by-nc-sa)
  • arXiv (Cornell University) (submittedVersion, cc-by-nc-sa)
  • arXiv (Cornell University)
Funders
  • Elice
  • Ministry of Science and Technology
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
Keywords
large language models, human-AI collaboration, instructor support, online lectures, student engagement, pedagogical dialogue

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review