July 17 (Wednesday)

July 18 (Thursday)

July 19 (Friday)

July 20 (Saturday)

Poster Session #1 (Thursday July 18):

Work-in-progress (presented as posters)

• Collaborate and Listen: International Research Collaboration at Learning @ Scale
  Alex Duncan (Georgia Institute of Technology ), Travis Tang (Georgia Institute of Technology ), Yinghong Huang (Georgia Institute of Technology ), Jeanette Luu (Georgia Institute of Technology ), Nirali Thakkar (Georgia Institute of Technology ) and David Joyner (Georgia Institute of Technology )
• Automatic Feedback Generation on K-12 Students’ Data Science Education by Prompting Cloud-based Large Language Models
  Sze Ching Evelyn Fung (Diocesan Girls’ School), Man Fai Wong (City University of Hong Kong) and Chee Wei Tan (Nanyang Technological University)
• Transforming CS Education with DevOps: Streamlined Assignment Validation and Delivery @ Scale
  Gururaj Deshpande (Georgia Institute of Technology), Shravan Cheekati (Georgia Institute of Technology), Shail Patel (Georgia Institute of Technology), Pranav Raj (Georgia Institute of Technology), Madhuri Singh (Georgia Institute of Technology), Mark Pindur (Georgia Institute of Technology), Nouf Al Soghyar (Georgia Institute of Technology), Bryan Zhao (Georgia Institute of Technology), Parisa Babolhavaeji (Georgia Institute of Technology), Mohammad Taher (Georgia Institute of Technology), Krish Nathan (Georgia Institute of Technology), Will Spaeth (Georgia Institute of Technology) and Max M Roozbahani (Georgia Institute of Technology)
• Videos for Parents and Child Performance
  Fiona Lee (University of Pennsylvania), Ryan Baker (University of Pennsylvania), Pradip Tomar (Humanitus Learning Sciences and Consulting Services), Krishna Kumari (Humanitus Learning Sciences and Consulting Services), Qimu Liang (University of Pennsylvania) and Zhanlan Wei (Columbia University)
• Do Virtual Teaching Assistants Enhance Teaching Presence?
  Robert Lindgren (Georgia Institute of Technology), Sandeep Kakar (Georgia Institute of Technology), Pratyusha Maiti (Georgia Institute of Technology), Karan Taneja (Georgia Institute of Technology) and Ashok Goel (Georgia Institute of Technology)
• Exploring Disparities in Student and Practitioner Perceptions of Skill Proficiency with SE Gap Awareness
  Sean Gruber (Virginia Tech), Grace Govan (Virginia Tech) and Chris Brown (Virginia Tech)
• Using Cipherbot: An Exploratory Analysis of Student Interaction with an LLM-Based Educational Chatbot
  Joni Salminen (University of Vaasa), Soon-Gyo Jung (Hamad Bin Khalifa University), Johanne Medina (Hamad Bin Khalifa University), Kholoud Aldous (Hamad Bin Khalifa University), Jinan Azem (Hamad Bin Khalifa University), Waleed Akhtar (Hamad Bin Khalifa University) and Bernard Jansen (Hamad Bin Khalifa University)
• Optimizing Mentor-student Communication Using LLM-Based Automated Labeling Information States
  Yuanzhe Jin (Northwestern University) and Jiali Yu (Zhejiang University)
• Intelligent Tutors for Adult Learning at Scale: A Narrative Review
  Utkarsh Nattamai Subramanian Rajkumar (Georgia Institute of Technology), Sibley Lyndgaard (Georgia Institute of Technology) and Ruth Kanfer (Georgia Institute of Technology)
• Three Paradoxes to Reconcile to Promote Safe, Fair, and Trustworthy AI in Education
  Rachel Slama (Georgia Institute of Technology), Amalia Christina Toutziaridi (Georgia Institute of Technology) and Justin Reich (Georgia Institute of Technology)
• Can Large Language Models Make the Grade? An Empirical Study Evaluating LLMs Ability To Mark Short Answer Questions in K-12 Education
  Owen Henkel (University of Oxford), Olivia Hills (Jacobs Foundation), Adam Boxer (Carousel Learning), Bill Roberts (Legible Labs) and Zach Levonian (Digital Harbor Foundation)
• Towards Educator-Driven Tutor Authoring: Generative AI Approaches for Creating Intelligent Tutor Interfaces
  Tommaso Calò (Politecnico Di Torino) and Christopher MacLellan (Georgia Institute of Technology)
• Scaling Up Mastery Learning with Generative AI: Exploring How Generative AI can assist in the Generation and Evaluation of Mastery Quiz Questions
  Stephen Hutt (University of Denver) and Grayson Hieb (University of Denver)
• Is GPT-4 Alone Sufficient for Automated Essay Scoring?
  Seungju Kim (Korea National University of Education) and Myounggeun Jo (Hoseo University)
• Leveraging Past Assignments to Determine If Students Are Using ChatGPT for Their Essays
  Yuhui Zhao (Georgia Institute of Technology), Chunhao Zou, Rohit Sridhar (Georgia Institute of Technology), Christopher Cui (Georgia Institute of Technology) and Thad Starner (Georgia Institute of Technology)
• Analyzing Students’ Information Behavior in Generative AI-Supported Small Group Discussions
  Xiuyu Chen (The University of Hong Kong) and Shihui Feng (The University of Hong Kong)
• Examinator v4.0 : Cheating Detection in Online Take-Home Exams
  Christopher Cui (Georgia Institute of Technology), Jui-Tse Hung (Georgia Institute of Technology), Vaibhav Malhotra (Georgia Institute of Technology), Hardik Goel (Georgia Institute of Technology), Raghav Apoorv (Georgia Institute of Technology) and Thad Starner (Georgia Institute of Technology)
• Comparing Feedback from Large Language Models and Instructors: Teaching Computer Science at Scale
  Ha Nguyen (Utah State University), Nate Stott (Utah State University) and Vicki Allan (Utah State University)
• Socratic Mind: Scalable Oral Assessment Powered By AI
  Jui-Tse Hung (Georgia Institute of Technology), Christopher Cui (Georgia Institute of Technology), Diana Popescu (Georgia Institute of Technology), Saurabh Chatterjee (Georgia Institute of Technology) and Thad Starner (Georgia Institute of Technology)
• Teacher-AI Collaboration in Content Recommendation for Digital Personalised Learning among Pre-primary Learners in Kenya
  Chen Sun (University of Manchester), Louis Major (University of Manchester), Rebecca Daltry (Jigsaw), Nariman Moustafa (Open Development & Education ) and Aidan Friedberg (EIDU)
• DevCoach: Supporting Students in Learning the Software Development Life Cycle at Scale with Generative Agents
  Tianjia Wang (Virginia Tech), Ramaraja Ramanujan (Virginia Tech), Yi Lu (Virginia Tech), Chenyu Mao (Virginia Tech), Yan Chen (Virginia Tech) and Chris Brown (Virginia Tech)
• Examining the Use of an AI-Powered Teacher Orchestration Tool at Scale
  Emma Brunskill (Stanford University), Kole Norberg (Carnegie Learning), Stephen Fancsali (Carnegie Learning) and Steve Ritter (Carnegie Learning)
• Classifying Tutor Discursive Moves at Scale in Mathematics Classrooms with Large Language Models
  Baptiste Moreau-Pernet (Digital Harbor Foundation), Yu Tian (Digital Harbor Foundation), Sandra Sawaya (University of Colorado, Boulder), Peter Foltz (University of Colorado, Boulder), Jie Cao (University of Colorado, Boulder), Brent Milne (Saga Education) and S. Thomas Christie (Digital Harbor Foundation)
• Propagating Large Language Models Programming Feedback
  Charles Koutcheme (Aalto University) and Arto Hellas (Aalto University)
• Positive Affective Feedback Mechanisms in an Online Mathematics Learning Platform
  Hai Li (University of Florida), Wanli Xing (University of Florida), Chenglu Li (University of Utah), Wangda Zhu (University of Florida) and Neil Heffernan (Worcester Polytechnic Institute)
• Forums, Feedback, and Two Kinds of AI: A Selective History of Learning @ Scale
  Alex Duncan (Georgia Institute of Technology), Travis Tang (Georgia Institute of Technology), Yinghong Huang (Georgia Institute of Technology), Jeanette Luu (Georgia Institute of Technology), Nirali Thakkar (Georgia Institute of Technology) and David Joyner (Georgia Institute of Technology)
• Are Students Reading? How Formative Practice Impacts Student Reading Behaviors in Etextbooks
  Nick Brown (VitalSource), Rachel Van Campenhout (VitalSource), Michelle Clark (VitalSource) and Benny Johnson (VitalSource)
• Comparing Expert and ChatGPT-authored Guidance Prompts
  Allison Bradford (UC Berkeley), Weiying Li (UC Berkeley), Libby Gerard (UC Berkeley) and Marcia Linn (UC Berkeley)
• Nemobot: Crafting Strategic Gaming LLM Agents for K-12 AI Education
  Yuchen Wang (Nanyang Technological University), Shangxin Guo (City University of Hong Kong), Lin Ling (City University of Hong Kong) and Chee Wei Tan (Nanyang Technological University )

Demonstrations (presented as posters with a table for interactivity)

• Ruffle&Riley: From Lesson Text to Conversational Tutoring
  Robin Schmucker (Carnegie Mellon University), Meng Xia (Texas A&M University), Amos Azaria (Ariel University) and Tom Mitchell (Carnegie Mellon University)
• MuFIN: A Framework for Automating Multimodal Feedback Generation using Generative Artificial Intelligence
  Jionghao Lin (Carnegie Mellon University), Eason Chen (Carnegie Mellon University), Ashish Gurung (Carnegie Mellon University) and Kenneth Koedinger (Carnegie Mellon University)
• HAROR: A System for Highlighting and Rephrasing Open-Ended Responses
  Jionghao Lin (Carnegie Mellon University) and Kenneth Koedinger (Carnegie Mellon University)

Poster Session #2 (Friday July 19):

Work-in-progress (presented as posters)

• Roles of Joining Time, Technology Use, and Social Interaction in Sustaining Student Participation in an Online Mathematics Discussion Board
  Bailing Lyu (The Pennsylvania State University), Chenglu Li (University of Utah), Hai Li (University of Florida) and Wanli Xing (University of Florida)
• Context-Embedded Knowledge Tracing and Latent Concept Detection in a Reading Game
  Katerina Christhilf (Learning Engineering Institute), Jiachen Gong (Learning Engineering Institute) and Danielle S. McNamara (Learning Engineering Institute)
• Technology-Based Instructional Strategies Show Promise in Improving Self-Regulated Learning Skills at Broad-Access Postsecondary Institutions
  Renzhe Yu (Columbia University), Hui Yang (SRI International), Xiaoying Lin (Teachers College), Chengyuan Yao (Teachers College), Paul Burkander (SRI International), Krystal Thomas (SRI International) and Jessica Mislevy (SRI International)
• Scaling Generated Feedback for Novice Teachers by Sustaining Teacher Educators’ Expertise: A Design to Train LLMs with Teacher Educator Endorsement of Generated Feedback
  Erin Barno (Boston University), Mariano Albaladejo-González (University of Murcia) and Justin Reich (MIT)
• Reframing Authority: A Computational Measure of Power-Affirming Feedback on Student Writing
  Mei Tan (Stanford University), Christopher Mah (Stanford University) and Dorottya Demszky (Stanford University)
• Enhancing Tutoring Effectiveness Through Automated Feedback: Preliminary Findings from a Pilot Randomized Controlled Trial on SAT Tutoring
  Joy Yun (Stanford University), Yann Hicke (Cornell University), Mariah Olson (Schoolhouse.world) and Dorottya Demszky (Stanford University)
• A Proposed Model of Learners’ Acceptance and Trust of Pedagogical Conversational AI
  Griffin Pitts (University of Florida), Viktoria Marcus (University of Florida) and Sanaz Motamedi (University of Florida)
• Enhancing Knowledge Tracing Efficacy with Expert-defined Graphs: A case study in Introductory Physics classes
  Zhenting Yan (Tongji University) and Rui Zhang (Tongji University)
• Short answer scoring with GPT-4
  Lan Jiang (University of Illinois Urbana-Champaign) and Nigel Bosch (University of Illinois Urbana-Champaign)
• Examining Student Engagement in Online Learning Platforms for Promoting Exam Readiness and Success in Undergraduate Nursing Education
  Mamta Shah (Elsevier, Inc.), Ryan Baker (University of Pennsylvania), Peter Granville (University of Pennsylvania) and Kimberly Sharp (Mississippi College)
• Teacher-informed expansion of an idea detection model for a Knowledge Integration assessment
  Weiying Li (University of California, Berkeley), Yuying Liao (ETS), Kenneth Steimel (University of California, Berkeley), Allison Bradford (University of California, Berkeley), Libby Gerard (University of California, Berkeley) and Marcia Linn (University of California, Berkeley)
• Beyond Repetition: The Role of Varied Questioning and Feedback in Knowledge Generalization
  Gautam Yadav (Carnegie Mellon University), Paulo F. Carvalho (Carnegie Mellon University), Elizabeth A. McLaughlin (Carnegie Mellon University) and Kenneth Koedinger (Carnegie Mellon University)
• Lessons Learned from a Research-to-Practice Scale-Up of an Adaptive Middle School Math Learning Platform
  Mingyu Feng (WestEd), Natalie Brezack (WestEd), Megan Schneider (WestEd), Kelly Collins (WestEd), Wynnie Chan (WestEd) and Melissa Lee (WestEd)
• SimPal: Towards a Meta-Conversational Framework to Understand Teacher’s Instructional Goals for K-12 Physics
  Effat Farhana (Vanderbilt University), Souvika Sarkar (Auburn University), Ralph Knipper (Auburn University), Indrani Dey (University of Wisconsin-Madison), Hari Narayanan (Auburn University), Sadhana Puntambekar (University of Wisconsin-Madison) and Shubhra Kanti Karmaker (Auburn University)
• Interplay Among Students’ Technical, Social, and Content-Related Participation Patterns in an Online Mathematical Discussion Board
  Bailing Lyu (The Pennsylvania State University), Chenglu Li (University of Utah), Hai Li (University of Florida) and Wanli Xing (University of Florida)
• Using Large Language Models to Diagnose Math Problem-solving Skills at Scale
  Hyoungwook Jin (Korea Advanced Institute of Science and Technology), Yoonsu Kim (Korea Advanced Institute of Science and Technology), Yeon Su Park (Korea Advanced Institute of Science and Technology), Bekzat Tilekbay (Korea Advanced Institute of Science and Technology), Jinho Son (Algorithm LABS) and Juho Kim (Korea Advanced Institute of Science and Technology)
• Scaling High-Leverage Curriculum Scaffolding in Middle-School Mathematics
  Rizwaan Malik (Stanford University), Dorna Abdi (Stanford University), Rose Wang (Stanford University) and Dora Demszky (Stanford University)
• Learning and AI Evaluation of Tutors Responding to Students Engaging in Negative Self-Talk
  Danielle R Thomas (Carnegie Mellon University), Jionghao Lin (Carnegie Mellon University), Shambhavi Bhushan (Carnegie Mellon University), Ralph Abboud (Oxford University), Erin Gatz (Carnegie Mellon University), Shivang Gupta (Carnegie Mellon University) and Kenneth Koedinger (Carnegie Mellon University)
• ChatGPT’s Performance on Problem Sets in an At-Scale Introductory Computer Science Course
  Diana Popescu (Georgia Institute of Technology) and David Joyner (Georgia Institute of Technology)
• HTN-Based Tutors: A New Intelligent Tutoring Framework Based on Hierarchical Task Networks
  Momin Siddiqui (Georgia Institute of Technology), Adit Gupta (Drexel University), Jennifer Reddig (Georgia Institute of Technology) and Christopher Maclellan (Georgia Institute of Technology)
• Open, Collaborative, and AI-Augmented Peer Assessment: Student Participation, Performance, and Perceptions
  Chaohua Ou (Georgia Institute of Technology), Ploy Thajchayapong (Georgia Institute of Technology) and David Joyner (Georgia Institute of Technology)
• Transformative Approach to Fairness and Transparency in Classroom Participation Assessment
  Michelle Banawan (Asian Institute of Management), Elias John Kukas (Asian Institute of Management), Adonna Tan (Asian Institute of Management), John Richard Tano (Asian Institute of Management) and Ramil Villegas (Asian Institute of Management)
• Who, What, and Where: Plotting Ten Years of Learning @ Scale Research
  Alex Duncan (Georgia Institute of Technology), Travis Tang (Georgia Institute of Technology), Yinghong Huang (Georgia Institute of Technology), Jeanette Luu (Georgia Institute of Technology), Nirali Thakkar (Georgia Institute of Technology) and David Joyner (Georgia Institute of Technology)
• Building Reading Comprehension and Knowledge with iSTART
  Micah Watanabe (Arizona State University), Megan Imundo (Arizona State University), Katerina Christhilf (Arizona State University), Tracy Arner (Arizona State University) and Danielle McNamara (Arizona State University)
• Learning Representations for Math Strategies using BERT
  Abisha Thapa Magar (University of Memphis), Steve Fancsali (Carnegie Learning), Vasile Rus (University of Memphis), April Murphy (Carnegie Learning), Steve Ritter (Carnegie Learning) and Deepak Venugopal (University of Memphis)
• Answer Watermarking: Using Answer Generation Assistance Tools to Find Evidence of Cheating
  Christopher Cui (Georgia Institute of Technology), Jui-Tse Hung (Georgia Institute of Technology), Pranav Sharma (Georgia Institute of Technology), Saurabh Chatterjee (Georgia Institute of Technology) and Thad Starner (Georgia Institute of Technology)
• Large-Scale and Versatile Deployment of Biology Cloud Labs in Schools through Teacher Driven Curricula Design
  Ingmar Riedel-Kruse (University of Arizona), Engin Bumbacher (EPFL), Paulo Blikstein (Columbia University) and Tahrina Ahmed (Cadence Design Systems)
• Generation and Assessment of Multiple-Choice Questions from Video Transcripts using Large Language Models
  Taimoor Arif (University of Michigan), Sumit Asthana (University of Michigan) and Kevyn Collins-Thompson (University of Michigan)
• Varying Impacts: The Role of Student Self-Evaluation in Navigating Learning Analytics
  Qiujie Li (Nanyang Technological University), Xuehan Zhou (Peking University), Di Xu (University of California Irvine), Rachel Baker (University of Pennsylvania) and Amanda Holton (University of California, Irvine)

Demonstrations (presented as posters with a table for interactivity)

• GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation
  Eason Chen (Carnegie Mellon University), Jia-En Lee (Carnegie Mellon University), Jionghao Lin (Carnegie Mellon University) and Kenneth Koedinger (Carnegie Mellon University)
• Demonstration of CFlow: Supporting Semantic Flow Analysis of Students’ Code in Programming Problems at Scale
  Ashley Zhang (University of Michigan), Xiaohang Tang (Virginia Tech), Steve Oney (University of Michigan) and Yan Chen (Virginia Tech)
• VizCode: A Practical Real-time Tool for In-Class Computer Programming Tutoring
  Yinuo Yang (University of Michigan) and Steve Oney (University of Michigan)