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TeachNow: Enabling Teachers to Provide Spontaneous, Realtime 1:1 Help in Massive Online Courses (2404.11918v1)

Published 18 Apr 2024 in cs.CY

Abstract: One-on-one help from a teacher is highly impactful for students, yet extremely challenging to support in massive online courses (MOOCs). In this work, we present TeachNow: a novel system that lets volunteer teachers from anywhere in the world instantly provide 1:1 help sessions to students in MOOCs, without any scheduling or coordination overhead. TeachNow works by quickly finding an online student to help and putting them in a collaborative working session with the teacher. The spontaneous, on-demand nature of TeachNow gives teachers the flexibility to help whenever their schedule allows. We share our experiences deploying TeachNow as an experimental feature in a six week online CS1 course with 9,000 students and 600 volunteer teachers. Even as an optional activity, TeachNow was used by teachers to provide over 12,300 minutes of 1:1 help to 375 unique students. Through a carefully designed randomised control trial, we show that TeachNow sessions increased student course retention rate by almost 15%. Moreover, the flexibility of our system captured valuable volunteer time that would otherwise go to waste. Lastly, TeachNow was rated by teachers as one of the most enjoyable and impactful aspects of their involvement in the course. We believe TeachNow is an important step towards providing more human-centered support in massive online courses.

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References (36)
  1. A new paradigm for intelligent tutoring systems: Example-tracing tutors. International Journal of Artificial Intelligence in Education 19, 2 (2009), 105–154.
  2. Azad Ali and David T Smith. 2015. Comparing Social Isolation Effects on Students Attrition in Online Versus Face-to-Face Courses in Computer Literacy. Issues in Informing Science and Information Technology 12 (2015), 011–020. https://doi.org/10.28945/2258
  3. Strategies to Engage Online Students and Reduce Attrition Rates. Journal of Educators Online 4, 2 (July 2007).
  4. Kwamena Appiah-Kubi and Duncan Rowland. 2016. PEER Support In MOOCs: The Role Of Social Presence. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale (Edinburgh, Scotland, UK) (L@S ’16). Association for Computing Machinery, New York, NY, USA, 237–240. https://doi.org/10.1145/2876034.2893423
  5. Benjamin S. Bloom. 1984. The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring. Educational Researcher 13, 6 (1984), 4–16. https://doi.org/10.3102/0013189X013006004 arXiv:https://doi.org/10.3102/0013189X013006004
  6. Mark Carter. 2009. Visible learning: A synthesis of over 800 meta-analyses relating to achievement.
  7. ProjectLens: Supporting Project-Based Collaborative Learning on MOOCs. In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale (Cambridge, Massachusetts, USA) (L@S ’17). Association for Computing Machinery, New York, NY, USA, 253–256. https://doi.org/10.1145/3051457.3053998
  8. Isaac Chuang and Andrew Ho. 2016. HarvardX and MITx: Four Years of Open Online Courses – Fall 2012-Summer 2016. (Dec 2016). Available at SSRN: https://ssrn.com/abstract=2889436 or http://dx.doi.org/10.2139/ssrn.2889436.
  9. Carol S. Dweck and Nicholas Dickon Reppucci. 1973. Learned helplessness and reinforcement responsibility in children. Journal of Personality and Social Psychology 25 (1973), 109–116. https://api.semanticscholar.org/CorpusID:42092746
  10. Academic Tenacity: Mindsets and Skills that Promote Long-Term Learning. Bill & Melinda Gates Foundation (2014).
  11. Design of a smart MOOC trust model: Towards a dynamic peer recommendation to foster collaboration and Learner’s engagement. International Journal of Emerging Technologies in Learning (Online) 17, 5 (2022), 36.
  12. The role of deliberate practice in the acquisition of expert performance. Psychological review 100, 3 (1993), 363.
  13. Scaling Introductory Courses Using Undergraduate Teaching Assistants. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (Seattle, Washington, USA) (SIGCSE ’17). Association for Computing Machinery, New York, NY, USA, 657–658. https://doi.org/10.1145/3017680.3017694
  14. Arthur C Graesser. 2016. Conversations with AutoTutor help students learn. International Journal of Artificial Intelligence in Education 26 (2016), 124–132.
  15. ElectronixTutor: an intelligent tutoring system with multiple learning resources for electronics. International journal of STEM education 5 (2018), 1–21.
  16. Philip J. Guo. 2013. Online Python Tutor: Embeddable Web-Based Program Visualization for Cs Education. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education (Denver, Colorado, USA) (SIGCSE ’13). Association for Computing Machinery, New York, NY, USA, 579–584. https://doi.org/10.1145/2445196.2445368
  17. Philip J. Guo. 2015. Codeopticon: Real-Time, One-To-Many Human Tutoring for Computer Programming. In Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology (Charlotte, NC, USA) (UIST ’15). Association for Computing Machinery, New York, NY, USA, 599–608. https://doi.org/10.1145/2807442.2807469
  18. Neil T Heffernan and Cristina Lindquist Heffernan. 2014. The ASSISTments ecosystem: Building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching. International Journal of Artificial Intelligence in Education 24 (2014), 470–497.
  19. Rebecca A Hines and Cynthia E Pearl. 2004. Increasing interaction in web-based instruction: Using synchronous chats and asynchronous discussions. Rural special education Quarterly 23, 2 (2004), 33–36.
  20. PyodideU: Unlocking Python Entirely in a Browser for CS1. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 (¡conf-loc¿, ¡city¿Portland¡/city¿, ¡state¿OR¡/state¿, ¡country¿USA¡/country¿, ¡/conf-loc¿) (SIGCSE 2024). Association for Computing Machinery, New York, NY, USA, 583–589. https://doi.org/10.1145/3626252.3630913
  21. Peer and Self Assessment in Massive Online Classes. ACM Trans. Comput.-Hum. Interact. 20, 6, Article 33 (dec 2013), 31 pages. https://doi.org/10.1145/2505057
  22. PeerStudio: Rapid Peer Feedback Emphasizes Revision and Improves Performance. In Proceedings of the Second (2015) ACM Conference on Learning @ Scale (Vancouver, BC, Canada) (L@S ’15). Association for Computing Machinery, New York, NY, USA, 75–84. https://doi.org/10.1145/2724660.2724670
  23. A peer assessment method to provide feedback, consistent grading and reduce students’ burden in massive teaching settings. Computers and Education 126 (2018), 283–295. https://doi.org/10.1016/j.compedu.2018.07.016
  24. Learners Teaching Novices: An Uplifting Alternative Assessment. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 (Portland, OR, USA) (SIGCSE 2024). Association for Computing Machinery, New York, NY, USA, 785–791. https://doi.org/10.1145/3626252.3630887
  25. Loneliness, student engagement, and academic achievement during emergency remote teaching during COVID-19: the role of the God locus of control. Humanities and Social Sciences Communications 9 (2022), 305. https://doi.org/10.1057/s41599-022-01328-9
  26. SKOPE-IT (Shareable Knowledge Objects as Portable Intelligent Tutors): overlaying natural language tutoring on an adaptive learning system for mathematics. International journal of STEM education 5 (2018), 1–20.
  27. Guru: designing a conversational expert intelligent tutoring system. In Cross-disciplinary advances in applied natural language processing: Issues and approaches. IGI Global, 156–171.
  28. Code in place: Online section leading for scalable human-centered learning. In Proceedings of the 52nd acm technical symposium on computer science education. 973–979.
  29. The Effective Use of Undergraduates to Staff Large Introductory CS Courses. In Proceedings of the Nineteenth SIGCSE Technical Symposium on Computer Science Education (Atlanta, Georgia, USA) (SIGCSE ’88). Association for Computing Machinery, New York, NY, USA, 22–25. https://doi.org/10.1145/52964.52971
  30. Recommendations for the generalized intelligent framework for tutoring based on the development of the deeptutor tutoring service. In AIED 2013 Workshops Proceedings, Vol. 7. Citeseer, 116.
  31. Creating collaborative groups in a MOOC: A homogeneous engagement grouping approach. Behaviour & Information Technology 38, 11 (2019), 1107–1121.
  32. Experiences of online learning: students’ perspective. Nurse Education Today 25, 2 (2005), 140–147. https://doi.org/10.1016/j.nedt.2004.11.004
  33. Hoi K. Suen. 2014. Peer assessment for massive open online courses (MOOCs). The International Review of Research in Open and Distributed Learning 15, 3 (Jun. 2014). https://doi.org/10.19173/irrodl.v15i3.1680
  34. Aru Ukenova and Gulmira Bekmanova. 2023. A review of intelligent interactive learning methods. Frontiers in Computer Science 5 (2023). https://doi.org/10.3389/fcomp.2023.1141649 Section: Digital Education.
  35. Neal A Whitman and Jonathan D Fife. 1988. Peer Teaching: To Teach Is To Learn Twice. ASHE-ERIC Higher Education Report No. 4, 1988. ERIC.
  36. Smart MOOC integrated with intelligent tutoring: A system architecture and framework model proposal. Computers and Education: Artificial Intelligence 3 (2022), 100092. https://doi.org/10.1016/j.caeai.2022.100092

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