| Title | Authors |
| Investigating the Impact of Skill-Related Videos on Online Learning | Ethan Prihar, Aaron Haim, Tracy Shen, Adam Sales, Dongwon Lee, Xintao Wu and Neil Heffernan |
| All a-board: sharing educational data science research with school districts | Nabeel Gillani, Doug Beeferman, Cassandra Overney, Christine Vega-Pourheydarian and Deb Roy |
| Convincing the Expert: Reducing Algorithm Aversion in Administrative Higher Education Decision-making | Lingrui Xu, Zachary A. Pardos and Anirudh Pai |
| M-Powering Teachers: Natural Language Processing Powered Feedback Improves 1:1 Instruction and Student Outcomes | Dorottya Demszky and Jing Liu |
| Exploring Cross-Country Prediction Model Generalizability in MOOCs | Juan Miguel Andres-Bray, Stephen Hutt and Ryan Baker |
| Assessing the Fairness of Course Success Prediction Models in the Face of (Un)equal Demographic Group Distribution | Oscar Deho, Srecko Joksimovic, Lin Liu, Jiuyong Li, Chen Zhan and Jixue Liu |
| Evaluating a Learned Admission-Prediction Model as a Replacement for Standardized Tests in College Admissions | Hansol Lee, Rene Kizilcec and Thorsten Joachims |
| Exploring Students’ Perceptions and Engagement in Hybrid Flexible Courses | Lina Battestilli, Elaine Bohorquez, Sarah Khan and Cigdem Meral |
| Investigating the Experiences of Teaching Assistants in Introductory Computer Science | Emma McDonald, Gisele Arevalo, Sadaf Ahmed, Ildar Akhmetov and Carrie Demmans Epp |
| From answering questions to commenting on the answers of others: An examination of the posting behaviours of high-reputation-score users of Stack Overflow | Thomas Hillman, Alena Seredko, Tanya Osborne and Markus Nivala |
| The Relevance of Ivan Illich’s Learning Webs 50 Years On | Shayan Doroudi and Yusuf Ahmad |
| EliRank: A Code Editing History Based Ranking Model for Early Detection of Students in Need | Jungkook Park and Alice Oh |
| How Learning Experience Designers Make Design Decisions: the Role of Data, the Reliance on Subject Matter Expertise, and the Opportunities for Data-Driven Support | Xiaofei Zhou, Christopher Kok, Rebecca Quintana, Anita Delahay and Xu Wang |
| Teaching at Scale and Back Again: The Impact of Instructors’ Participation in At-Scale Education Initiatives on Traditional Instruction | David Joyner, Ana Rusch, Alex Duncan, Jolanta Wojcik and Diana Popescu |
| How Common are Common Wrong Answers? Exploring Remediation at Scale | Ashish Gurung, Morgan P. Lee, Sami Baral, Kirk P. Vanacore, Andrew A. McReynolds, Hilary Kreisberg, Cristina Heffernan, Aaron Haim, Nathan Smearsoll, Adam C. Sales and Neil T. Heffernan |
| Supporting Online Collaborative Work at Scale: A Mixed-Methods Study of a Learning Analytics Tool | Xavier Ochoa, Vanessa Echeverria, Gladys Carrillo, Vanessa Heredia Jimenez, Benito Auria and Katherine Chiluiza |
| High-Resolution Course Feedback: Timely Feedback for Course Instructors | Yunsung Kim and Chris Piech |
| How to Open Science: Analyzing the Open Science Statement Compliance of the Learning @ Scale Conference | Aaron Haim, Robert Gyurcsan, Chris Baxter, Stacy Shaw and Neil Heffernan |
| LENS: Predictive diagnostics for flexible and efficient assessments | S. Thomas Christie, Hayden Johnson, Carson Cook, Garron Gianopulos and Anna Rafferty |
| Interactive TA Training with GPT-based Students | Julia M. Markel, Steven G. Opferman, James A. Landay and Chris Piech |
| How teachers influence student adoption and effectiveness of a recommendation system for Algebra | Walter Leite, Amber Hatch, Huan Kuang, Catherine Cavanaugh and Wanli Xing |
| Isolating the impact of gamification: Application of fully latent principle stratification analysis to estimate the effects of gamification for persistent learners | Kirk Vanacore, Adam Sales, Allison Liu and Erin Ottmar |
| Crowdsourcing the Evaluation of Educational Multiple-Choice Questions: An Analysis of Item-Writing Flaws and Bloom’s Taxonomy | Steven Moore, Huy Nguyen, Ellen Fang and John Stamper |
Conference Theme: Learning Futures @ Scale
The widespread move to online learning during the last few years due to the global pandemic has opened up new opportunities and challenges for the Learning at Scale (L@S) community. These opportunities and challenges relate not only to the educational technologies used but also to the social, organizational and contextual aspects of supporting learners and educators in these dynamic and, nowadays, often multicultural learning environments. How the future of learning at scale will look needs careful consideration from several points of view, including a focus on technological, social, organizational, cultural, and responsible aspects of learning and teaching. The theme of this year’s conference is the learning futures that the L@S community aims to develop and support in the coming decades. This year, contributions of special interest examine the design and deployment of large-scale systems for the future of learning at scale. We are especially welcoming works targeting not only learners but also educators, educational institutions and other stakeholders involved in designing, using and evaluating large-scale learning systems. Moreover, we welcome qualitative and mixed-methods contributions, as well as studies that are not at scale themselves but about scaled learning phenomena/environments. Finally, we are also welcoming submissions focusing on the role of culture and cultural values in implementing and evaluating large-scale systems.