July 17 (Wednesday)

Joint Reception with Educational Data Mining

Georgia Tech Hotel & Conference
800 Spring St NW
Atlanta, GA 30308

6-9pm

 

July 18 (Thursday)

Breakfast 8-9am

Keynote: Chris Dede 

Designing a Model for Massive Digital Lifelong Learning

9-10:15am
Break 10:15-10:45am

Paper Session #1: Generative AI to Support Teaching and Learning

AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and Guardrails Sankalan

Sankalan Pal Chowdhury (ETH Zurich), Vilém Zouhar (ETH Zurich) and Mrinmaya Sachan (ETH Zurich)

Generative Students: Using LLM-Simulated Student Profiles to Support Question Item Evaluation

Xinyi Lu (University of Michigan) and Xu Wang (University of Michigan)

Simulating Climate Change Discussion with Large Language Models: Considerations for Science Communication at Scale

Ha Nguyen (Utah State University), Victoria Nguyen (University of California, Irvine), Saríah López-Fierro (Utah State University), Sara Ludovise (Orange County Department of Education) and Rossella Santagata (University of California, Irvine)

Prompting for Comprehension: Exploring the Intersection of Explain in Plain English Questions and Prompt Writing

David Smith (University of Illinois Urbana-Champaign), Paul Denny (University of Auckland) and Max Fowler (University of Illinois Urbana-Champaign)

10:45-12:15pm

Lunch

Global Learning Center Atrium

Sponsored by Vocareum, Gold-Level Learning @ Scale Sponsor

12:15-1:15pm
Poster Session #1  1:15-2:15pm

Paper Session #2: LLMs for Programming Education

CodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming *

Xinying Hou (University of Michigan), Zihan Wu (University of Michigan), Xu Wang (University of Michigan) and Barbara Ericson (University of Michigan)

Evaluating the Effectiveness of LLMs in Introductory Computer Science Education: A Semester-Long Field Study

Wenhan Lyu (William & Mary), Yimeng Wang (William & Mary), Tingting Rachel Chung (William & Mary), Yifan Sun (William & Mary) and Yixuan Zhang (William & Mary)

Plagiarism in the Age of Generative AI: Cheating Method Change and Learning Loss in an Intro to CS Course

Binglin Chen (University of Illinois at Urbana-Champaign), Colleen Lewis (University of Illinois at Urbana-Champaign), Matthew West (University of Illinois at Urbana-Champaign) and Craig Zilles (University of Illinois at Urbana-Champaign)

Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms

Harsh Kumar (University of Toronto), Ruiwei Xiao (Carnegie Mellon University), Benjamin Lawson (University of Toronto), Ilya Musabirov (University of Toronto), Jiakai Shi (University of Toronto), Xinyuan Wang (University of Toronto), Huayin Luo (University of Toronto), Joseph Williams (University of Toronto), Anna Rafferty (Carleton College), John Stamper (Carnegie Mellon University) and Michael Liut (University of Toronto Mississauga)

2:15-3:45pm
Break 3:45-4:15pm

Paper Session #3: Creating Learning Content at Scale

Edgeworth: Efficient and Scalable Authoring of Visual Thinking Activities *

Wode Ni (Carnegie Mellon University), Sam Estep (Carnegie Mellon University), Hwei-Shin Harriman (Carnegie Mellon University), Kenneth Koedinger (Carnegie Mellon University) and Joshua Sunshine (Carnegie Mellon University)

Automated Quality Assessment of Multimodal Mathematical Stories Generated by Generative Artificial Intelligence: Text-Image Coherence and Grade Level Appropriateness

Hai Li (University of Florida), Rui Guo (University of Florida), Chenglu Li (University of Utah) and Wanli Xing (University of Florida)

Automated Generation and Tagging of Knowledge Components From Multiple-Choice Question

Steven Moore (Carnegie Mellon University), Robin Schmucker (Carnegie Mellon University), John Stamper (Carnegie Mellon University) and Tom Mitchell (Carnegie Mellon University)

Multimodal Deep Learning for Classifying Student-Generated Questions in Computer-Supported Collaborative Learning

Han Kyul Kim (University of Southern California), Aleyeh Roknaldin (University of Southern California), Shriniwas Nayak (University of Southern California), Aditya Chavan (University of Southern California) and Stephen C.-Y. Lu (University of Southern California)

4:15-5:45pm

Learning at Scale Reception

The Historic Academy of Medicine
875 W Peachtree St NW
Atlanta, GA 30309

6-9pm

 

July 19 (Friday)

Breakfast 8-9am

Keynote: Nesra Yannier

Bringing AI Tutoring into the Physical World and Scaling to Schools and Museums

9-10:15am
Break 10:15-10:45am

Paper Session #4: Formal Education at Scale: MOOCs and Residential Programs

Ten Years, Ten Trends: The First Decade of an Affordable At-Scale Degree

David Joyner (Georgia Institute of Technology) and Alex Duncan (Georgia Institute of Technology)

From One-Size-Fits-All to Individualisation: Redefining MOOCs through Flexible Learning Paths

Selina Reinhard (Hasso Plattner Institute), Sebastian Serth (Hasso Plattner Institute), Thomas Staubitz (German University of Digital Science) and Christoph Meinel (Hasso Plattner Institute)

Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning

Frederik Baucks (Ruhr-Universität Bochum), Robin Schmucker (Carnegie Mellon University), Conrad Borchers (Carnegie Mellon University), Zachary A. Pardos (University of California, Berkeley) and Laurenz Wiskott (Ruhr-Universität-Bochum)

Combining LLM-Generated and Test-Based Feedback in a MOOC for Programming

Hagit Gabbay (Tel Aviv University) and Anat Cohen (Tel Aviv University)

10:45-12:15pm

Lunch

Global Learning Center Atrium

12:15-1:15pm
Poster Session #2 1:15-2:15pm

Paper Session #5: Technologies to Enhance Participation and Engagement in Computing Education

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)

Handwritten Code Recognition for Pen-and-Paper CS Education

Md Sazzad Islam (Stanford University), Moussa Koulako Bala Doumbouya (Stanford University), Christopher D. Manning (Stanford University) and Chris Piech (Stanford University)

New Coding Assignments and the First Repository Effect on Inter-Semester Plagiarism

Keith Adkins (Georgia Institute of Technology) and David Joyner (Georgia Institute of Technology)

Influence on Judgements of Learning Given Perceived AI Annotations

Warren Li (University of Michigan) and Christopher Brooks (University of Michigan)

2:15-3:45pm
Break 3:45-4:15pm

Paper Session #6: Learning at Scale in a Global Context

“I believe I did not preach into the desert”: Opportunities & Challenges in Scaling Teacher Mentorship through Mobile Technology in Rural Côte d’Ivoire

Tricia Ngoon (Carnegie Mellon University), Vikram Kamath Cannanure (Carnegie Mellon University), Kaja Jasinska (University of Toronto), Sharon Wolf (University of Pennsylvania) and Amy Ogan (Carnegie Mellon University)

STEM Pathways in a Global Context: Are Male and Female Learners Motivated the Same?

Yiwen Lin (University of California, Irvine) and Nia Nixon (University of California, Irvine)

4:15-5pm
Closing Session + Awards Annoucement (* Best Paper Nominations) 5-5:45pm

July 20 (Saturday)

Workshop: Learnersourcing: Student-Generated Content @ Scale

Detailed Schedule: https://sites.google.com/andrew.cmu.edu/learnersourcing

9am-5pm

Workshop: AI-Driven Content Creation: Revolutionizing Educational Materials

Detailed Schedule: https://research.ges.galileo.edu/workshopai/

9am -1pm

Workshop: Scaling Classrooms: A Forum for Practitioners Seeking, Developing and Adapting their Own Tools

Detailed Schedule: https://guru-desh.github.io/practitioners-workshop-2024/

1pm-5pm

Workshop: Fifth Annual Workshop on A/B Testing and Platform-Enabled Learning Research

Detailed Schedule: https://sites.google.com/carnegielearning.com/pele-2024

9am-5pm

 

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)