Links
Full Publication List
Italicized author names indicate mentored students. An asterisk (*) indicates equal contribution.
Journal Articles
Borchers, C., Zhang, J., Fleischer, H., Schanze, S., Aleven, V., & Baker, R. S. (accepted). Large Language Models Generalize SRL Prediction to New Languages Within But Not Between Domains. Journal of Educational Data Mining.
Borchers, C., Wang, Y., Hodge, E., & Rosenberg, J. M. (in-press). Decoding Sentiment Signals: Lessons from the Political Reception of the Common Core and Next Generation Science Standards. Educational Researcher. [pdf]
Borchers, C. & Pardos, Z. A. (in-press). Course Load Analytics Interventions on Higher Education Course Selection: Experimental Evidence. Journal of Learning Analytics.
Borchers, C., Xu, Y., & Pardos, Z. A. (2025). Workload Overload? Late Enrollment Leads to Course Dropout. Journal of Educational Data Mining. https://doi.org/10.5281/zenodo.14907388 [github]
Borchers, C., Darriet, C., Rosenberg, J., & Lopez, F. (2025). Dual Intent in Dual-language Programs: Internet Data Mining of School District Communications. TechTrends. https://doi.org/10.1007/s11528-025-01049-1 [data] [github]
Borchers, C., Fleischer, H., Yaron, D. J., McLaren, B. M., Scheiter, K., Aleven, V., & Schanze, S. (2025). Problem-Solving Strategies in Stoichiometry Across Two Intelligent Tutoring Systems: A Cross-National Study. Journal of Science Education and Technology. https://doi.org/10.1007/s10956-024-10197-7
Zhang, L., Lin, J., Sabatini, J., Borchers, C., Weitekamp, D., Cao, M., Hollander, J., Hu, X., & Graesser, A. C. (2025). Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI. IEEE Transactions on Learning Technologies. https://doi.org/10.1109/TLT.2025.3526582
Pritchard, C., Borchers, C., Rosenberg, J. M., Fox, A. K., & Stegenga, S. M. (2024). The datafication of student information on X (Twitter). Computers and Education Open, 7, 100197. https://doi.org/10.1016/j.caeo.2024.100197 [pdf]
Borchers, C.*, Rosenberg, J.*, & Swartzentruber, R. M.* (2023). Facebook Post Data: A Primer for Educational Research. Educational Technology Research and Development. https://doi.org/10.1007/s11423-023-10269-2 [pdf]
Borchers, C.*, Eder, T. F.*, Richter, J., Keutel, C., Huettig, F., & Scheiter, K. (2023). A Time Slice Analysis of Dentistry Students’ Visual Search Strategies and Pupil Dilation during Diagnosing Radiographs. Plos One, 18(6), e0283376. https://doi.org/10.1371/journal.pone.0283376
Pardos, Z. A., Borchers, C., & Yu, R. (2023). Credit hours is not enough: Explaining undergraduate perceptions of course workload using LMS records. The Internet and Higher Education. https://doi.org/10.1016/j.iheduc.2022.100882 [pdf] [github]
Rosenberg, J., Borchers, C., Burchfield, M., Anderson, D., Stegenga, S., & Fischer, C. (2022). How educational institutions reveal students’ personally identifiable information on Facebook. Learning, Media and Technology. https://doi.org/10.1080/17439884.2022.2140672
Rosenberg, J., Borchers, C., Stegenga, S., Burchfield, M., Anderson, D., & Fischer, C. (2022). Posts About Students on Facebook: A Data Ethics Perspective. Educational Researcher. https://doi.org/10.3102/0013189X221120538
Rosenberg, J., Burchfield, M., Borchers, C., Gibbons, B., Anderson, D., & Fischer, C. (2021). Social media and students’ privacy: What schools and districts should know. Phi Delta Kappan, 103(2), 49-53. https://doi.org/10.1177/00317217211051145
Rosenberg, J., Borchers, C., Dyer, E., Anderson, D. & Fischer, C. (2021). Understanding Public Sentiment About Educational Reforms: The Next Generation Science Standards on Twitter. AERA Open, 7(1), 1-17. https://doi.org/10.1177/23328584211024261 [github]
Conference Proceedings
Simon, S., Tajik, E., Borchers, C., Shahrokhian, B., Sankaranarayanan, S., Balzan, F., Strauss, S., Viswanathan, S. A., Atas, A. H., Carapina, M., Liang, L., & Celik, B. (in-press). Comparing Human and LLM-Generated Inductive Thematic Analyses: Assessing Agreement in Coding Consistency and Interpretative Accuracy. In Proceedings of the 26th International Conference on Artificial Intelligence in Education (AIED 2025). Palermo, Italy.
Borchers, C., Houk, A., Aleven, V., & Koedinger, K. R. (in-press). Engagement and Learning Benefits of Goal Setting with Rewards in Human-AI Tutoring. In Proceedings of the 26th International Conference on Artificial Intelligence in Education (AIED 2025). Palermo, Italy.
Borchers, C., Nguyen, H. T., Carvalho, P. F., Koedinger, K. R., & Aleven, V. (in-press). Involving Parents and Caregivers in Intelligent Tutoring Systems: A Design Probe Study. In Proceedings of the 26th International Conference on Artificial Intelligence in Education (AIED 2025). Palermo, Italy.
Borchers, C. & Shou, T. (in-press). Can Large Language Models Match Tutoring System Adaptivity? A Benchmarking Study. In Proceedings of the 26th International Conference on Artificial Intelligence in Education (AIED 2025). Palermo, Italy. [pdf] [github]
Borchers, C., Peng, C., Lyu, Q., Carvalho, P. F., Koedinger, K. R., & Aleven, V. (in-press). Student Perceptions of Adaptive Goal Setting Recommendations: A Design Prototyping Study. In Proceedings of the 26th International Conference on Artificial Intelligence in Education (AIED 2025). Palermo, Italy.
Thomas, D. R., Borchers, C., Bhushan, S., Kakarla, S., Houk, A., Abboud, R., Gatz, E., Gupta, S., & Koedinger, K. R. (in-press). Improving Open-Response Assessment with LearnLM. In Proceedings of the 26th International Conference on Artificial Intelligence in Education (AIED 2025). Palermo, Italy. [github] [data]
Gurung, A., Lin, J., Huang, Z., Borchers, C., Baker, R. S., Aleven, V., & Koedinger, K. R. (in-press). Starting Seatwork Earlier as a Valid Measure of Student Engagement. In Proceedings of the 18th International Conference on Educational Data Mining (EDM 2025). Palermo, Italy.
Borchers, C. (in-press). Toward Sufficient Statistical Power in Algorithmic Bias Assessment: A Test for ABROCA. In Proceedings of the 18th International Conference on Educational Data Mining (EDM 2025). Palermo, Italy. [pdf] [github]
Butler, R., Borchers, C., Asher, M., Lee, Y., Karnataki, S., Dangi, S., Athreya, S., Stamper, J., Ogan, A., & Carvalho, P. (in-press). Does the Doer Effect Generalize to Non-WEIRD Populations? Toward Analytics in Radio and Phone-Based Learning. In LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), March 03–07, 2025, Dublin, Ireland. ACM, New York, NY, USA. https://doi.org/10.1145/3706468.3706505 [pdf]
Venugopalan, D., Yan, Z., Borchers, C., Lin, J., & Aleven, V. (in-press). Combining Large Language Models with Tutoring System Intelligence: A Case Study in Caregiver Homework Support. In LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), March 03–07, 2025, Dublin, Ireland. ACM, New York, NY, USA. https://doi.org/10.1145/3706468.3706516 [pdf] [github]
Thomas, D. R., Borchers, C., Kakarla, S., Lin, J., Bhushan, S., Guo, B., Gatz, E., & Koedinger, K. R. (in-press). Do Tutors Learn from Equity Training and Can Generative AI Assess It? In LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), March 03–07, 2025, Dublin, Ireland. ACM, New York, NY, USA. https://doi.org/10.1145/3706468.3706531 [pdf] [github]
Borchers, C.*, Ooge, J.*, Peng, C., & Aleven, V. (in-press). How Learner Control and Explainable Learning Analytics on Skill Mastery Shape Student Desires to Finish and Avoid Loss in Tutored Practice. In LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), March 03–07, 2025, Dublin, Ireland. ACM, New York, NY, USA. https://doi.org/10.1145/3706468.3706484 [pdf] [github]
Thomas, D. R., Borchers, C., Kakarla, S., Lin, J., Bhushan, S., Guo, B., Gatz, E., & Koedinger, K. R. (in-press). Does Multiple Choice Have a Future in the Age of Generative AI? A Posttest-only RCT. In LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), March 03–07, 2025, Dublin, Ireland. ACM, New York, NY, USA. https://doi.org/10.1145/3706468.3706530 [pdf] [github]
Švábenský, V.,Borchers, C., Cloude, E. B., & Shimada, A. (in-press). Evaluating the Impact of Data Augmentation on Predictive Model Performance. In LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), March 03–07, 2025, Dublin, Ireland. ACM, New York, NY, USA. https://doi.org/10.1145/3706468.3706485 [pdf] [zenodo]
Borchers, C. & Baker, R. S. (in-press). ABROCA Distributions For Algorithmic Bias Assessment: Considerations Around Interpretation. In LAK25: The 15th International Learning Analytics and Knowledge Conference (LAK 2025), March 03–07, 2025, Dublin, Ireland. ACM, New York, NY, USA. https://doi.org/10.1145/3706468.3706498 [pdf] [github]
Zhang, J.*, Borchers, C.*, & Barany, A. (2024). Studying the Interplay of Self-Regulated Learning Cycles and Scaffolding Through Ordered Network Analysis Across Three Tutoring Systems. Proceedings of the International Conference on Quantitative Ethnography. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-76335-9_17 [pdf] BEST STUDENT PAPER AWARD
Yang, K. B.*, Borchers, C.*, Falhs, A.-C., Echeverria, V., Karumbaiah, S., Rummel, N., & Aleven, V. (2024). Leveraging Multimodal Classroom Data for Teacher Reflection: Teachers’ Preferences, Practices, and Privacy Considerations. In Proceedings of the 19th European Conference on Technology Enhanced Learning, EC-TEL 2024, Krems, Austria. [pdf]
Baucks, F.*, Schmucker, R.*, Borchers, C., Pardos, Z. A., & Wiskott, L. (2024). Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning. Proceedings of the Tenth (2024) ACM Conference on Learning@Scale (L@S). Atlanta, GA, USA. https://doi.org/10.1145/3657604.3662028 [pdf] [github]
Borchers, C., Xu, Y., & Pardos, Z. A. (2024). Are You an Early Dropper or Late Shopper? Mining Enrollment Transaction Data to Study Procrastination in Higher Education. Proceedings of the 17th International Conference on Educational Data Mining (EDM). Atlanta, GA, USA. [pdf] [github] BEST SHORT PAPER AWARD
Zhang, J., Borchers, C., Aleven, V., & Baker, R. S. (2024). Using Large Language Models to Detect Self-Regulated Learning in Think-Aloud Protocols. Proceedings of the 17th International Conference on Educational Data Mining (EDM). Atlanta, GA, USA. [pdf] [data1] [data2]
Borchers, C., Yang, K., Lin, J., Rummel, N., Koedinger, K. R., & Aleven, V. (2024). Combining Dialog Acts and Skill Modeling: What Chat Interactions Enhance Learning Rates During AI-Supported Peer Tutoring? Proceedings of the 17th International Conference on Educational Data Mining (EDM). Atlanta, GA, USA. [pdf] [github] [data1] [data2] [data3] BEST STUDENT PAPER AWARD
Borchers, C., Liu, X., Lee, H. H., & Zhang, J. (2024). Ethical AIED and AIED Ethics: Toward Synergy Between AIED Research and Ethical Frameworks. Proceedings of 25th International Conference on Artificial Intelligence in Education (AIED) — BlueSky Track. Recife, Brazil. [pdf]
Zhang, L., Lin, J., Borchers, C., Sabatini, J., Hollander, J., Cao, M., & Hu, X. (2024). Predicting Learning Performance with Large Language Models: A Study in Adult Literacy. Proceedings of the 26th International Conference On Human-Computer Interaction (HCII). Washington, DC, USA. [pdf] BEST PAPER AWARD
Peng, C., Borchers, C., & Aleven, V. (2024). Designing Homework Support Tools for Middle School Mathematics Using Intelligent Tutoring Systems. Proceedings of the 2024 Annual Meeting of the International Society of the Learning Sciences (ISLS). Buffalo, NY, USA. [pdf]
Nguyen, H. T., Borchers, C., Xia, M., & Aleven, V. (2024). Designing Tools for Caregiver Involvement in Intelligent Tutoring Systems for Middle School Mathematics. Proceedings of the 2024 Annual Meeting of the International Society of the Learning Sciences (ISLS). Buffalo, NY, USA. [pdf]
Borchers, C., Wang, Y., Karumbaiah, S., Ashiq, M., Shaffer, D. W., & Aleven, V. (2024). Revealing Networks: Understanding Effective Teacher Practices in AI-Supported Classrooms using Transmodal Ordered Network Analysis. Proceedings of the 14th International Learning Analytics and Knowledge Conference (LAK). Kyoto, Japan. ACM. https://doi.org/10.1145/3636555.3636892 [pdf] [github] [data]
Borchers, C., Zhang, J., Baker, R. S., & Aleven, V. (2024). Using Think-Aloud Data to Understand Relations between Self-Regulation Cycle Characteristics and Student Performance in Intelligent Tutoring Systems. Proceedings of the 14th International Learning Analytics and Knowledge Conference (LAK). Kyoto, Japan. ACM. https://doi.org/10.1145/3636555.3636911 [pdf] [github] [data]
Borchers, C., Carvalho, P. F., Xia, M., Liu, P., Koedinger, K. R., & Aleven, V. (2023). What Makes Problem-Solving Practice Effective? Comparing Paper and AI Tutoring. In Proceedings of the 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal. [pdf]
Karumbaiah, S., Borchers, C., Shou, T., Falhs, A.-C., Liu, C., Nagashima, T., Rummel, N., & Aleven, V. (2023). A Spatiotemporal Analysis of Teacher Practices in Supporting Student Learning and Engagement in an AI-enabled Classroom. In Proceedings of the 24th International Conference on Artificial Intelligence in Education (AIED). Tokyo, Japan. [pdf][github]
Shou, T., Borchers, C., Karumbaiah, S., & Aleven, V. (2023). Optimizing Parameters for Accurate Position Data Mining in Diverse Classrooms Layouts. In Proceedings of the 16th International Conference on Educational Data Mining (EDM). Bengaluru, India. [pdf] [github]
Borchers, C., Klein, L., Johnson, H., & Fischer, C. (2023). Timing Matters: Inferring Educational Twitter Community Switching from Membership Characteristics. In Proceedings of the 16th International Conference on Educational Data Mining (EDM). Bengaluru, India. [pdf] [github]
Karumbaiah, S.*, Borchers, C.*, Falhs, A.-C.*, Holstein, K., Rummel, N., & Aleven, V. (2023). Teacher Noticing and Student Learning in Human-AI Partnered Classrooms: A Multimodal Analysis. In Proceedings of the 2023 Annual Meeting of the International Society of the Learning Sciences (ISLS). Montréal, Canada. [pdf]
Borchers, C., & Pardos, Z. A. (2023). Insights into undergraduate pathways using course load analytics. In Proceedings of the 14th International Learning Analytics and Knowledge Conference (LAK). ACM. https://doi.org/10.1145/3576050.3576081 [pdf] [github] BEST FULL PAPER HONORABLE MENTION
Borchers, C., Rosenberg, J., Gibbons, B., Burchfield, M., & Fischer, C. (2021). To Scale or Not to Scale: Comparing Popular Sentiment Analysis Dictionaries on Educational Twitter Data. Proceedings of the 14th International Conference on Educational Data Mining (EDM). Paris, France. [video presentation] [pdf]
Burchfield, M., Rosenberg, J., Borchers, C., Thomas, T., Gibbons, B., & Fischer, C. (2021). Are Violations of Student Privacy “Quick and Easy”? Investigating the Privacy of Students’ Images and Names in the Context of K-12 Educational Institution’s Posts on Facebook. Proceedings of the 14th International Conference on Educational Data Mining (EDM). Paris, France. [pdf] BEST POSTER AWARD
Workshop Publications
Sankaranarayanan, S., Borchers, C., Simon, S., Tajik, E., Atas, A. H., Celik, B., Balzan, F., & Shahrokhian, B. (2025). Automating Thematic Analysis with Multi-Agent LLM Systems. From Data to Discovery: LLMs for Qualitative Analysis in Education (ACM LAK25 Workshop). [pdf]
Borchers, C., Thomas, D. R., Lin, J., Abboud, R., & Koedinger, K. R. (2025). Augmenting Human-Annotated Training Data with Large Language Model Generation and Distillation in Open-Response Assessment. Proceedings of the Second Workshop on Generative AI for Learning Analytics (GenAI-LA) at LAK25. [pdf]
Kakarla, S., Borchers, C., Thomas, D. R., Bhushan, S., & Koedinger, K. R. (2025). Comparing Few-Shot Prompting of GPT-4 LLMs with BERT Classifiers for Open-Response Assessment in Tutor Equity Training. Proceedings of the Innovation and Responsibility in AI-Supported Education (iRAISE) Workshop at AAAI25. [pdf]
Aleven, V., Borchers, C., Huang, Y., Nagashima, T., McLaren, B., Carvalho, P., Popescu, O., Sewall, J., & Koedinger, K. (2024). An Integrated Platform for Studying Learning with Intelligent Tutoring Systems: CTAT+TutorShop. Proceedings of the Fifth Annual Workshop on Learning@Scale 2024: A/B Testing and Platform-Enabled Learning Research. [pdf]
Zhang, L., Lin, J., Borchers, C., Cao, M., & Hu, X. (2024). 3DG: A Framework for Using Generative AI for Handling Sparse Learner Performance Data From Intelligent Tutoring Systems. Proceedings of the First Workshop on Generative AI for Learning Analytics (GenAI-LA) at LAK24. [pdf]
Han, Z. F., Lin, J., Gurung, A., Thomas, D. R., Chen, E., Borchers, C., Gupta, S., & Koedinger, K. R. (2024). Improving Assessment of Tutoring Practices using Retrieval-Augmented Generation. Proceedings of the AAAI2024 Workshop on AI for Education - Bridging Innovation and Responsibility. [pdf]
Borchers, C.*, Gala, D. S.*, Gilburt, B.*, Oravkin, E., Bounsi, W., Asano, Y. M., & Kirk, H. R. (2022). Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements. Proceedings of the 4th Workshop on Gender Bias in Natural Language Processing (NAACL). [pdf] [github]
Conference Demo Publications
Rao, J., Borchers, C., & Lin, J. (2024). Coursera-REC: Explainable MOOCs Course Recommendation using RAG-facilitated LLMs. 25th International Conference on Artificial Intelligence in Education (AIED) [pdf] [video] BEST INTERACTIVE EVENT NOMINATION
Conference Presentations
Rosenberg, J. M., Pritchard, C., Borchers, C., Burchfield, M., Fischer, C., Fox, A. K., & Stegenga, S. (2024, March). Data ethics in the open: Navigating student information risks in educational social media. Presentation at the Data Science & Social Research, 4th International Conference. https://dssr2024.unina.it/index.html
Gold, G., Borchers, C., & Carvalho P. F. (2024, March). Students’ Academic Performance and Goal Orientation Relate to Initial Knowledge but Not Learning Rate. Poster presented at the 14th International Learning Analytics and Knowledge Conference (LAK), Kyoto, Japan.
Fischer, C., Morina, F., Borchers, C., & Klein, L. (2023, August). Online Communities of Practice on Twitter: A Case Study of the German Educational Twittersphere. Paper to be presented at the 20th Biennial EARLI Conference, Thessaloniki, Greece.
Borchers, C., & Braesemann, F.. Correlation networks predict success of digital technologies (2022, November). Paper to be presented at the the 11th International Conference on Complex Networks and their Applications, Palermo, Italy.
Fischer, C., Morina, F., Borchers, C., Klein, L., & Eich, M. (2022, April). Informal Professional Development in Online Communities of Practice at Scale: Mapping Nationwide Educational Twitterspheres. Paper to be presented at the 2022 Annual Meeting of the American Educational Research Association, San Diego, CA.
Borchers, C., Eder, T., & Scheiter, K. (2021, September). How Effective is Reflective search? A Time Slice Analysis of Dentistry Students’ Visual Search Strategies and Pupil Dilation during Diagnosing Radiographs. 2nd Workshop on Mental Effort, Virtual Conference.
Rosenberg, J., Borchers, C., Gibbons, B., Dyer, E., Anderson, D., & Fischer, C. (2021, April). Don’t worry, be happy? A sentiment analysis of the #NGSSchat Twitter community. Paper at the 2021 annual meeting of the American Educational Research Association, Virtual Conference.
Fischer, C., Morina, F., Borchers, C., & Klein, L. (2021, March). Using Big Data to Support Educational Change: Twitter as a Platform for Informal Professional Development. Paper presented at the 2021 annual meeting of the Leibniz Education Research Network, Hannover, Germany.
Student Conferences, White Papers, and Blog Posts
Borchers, C. (2020). Die Replikationskrise in der Psychologie – Reflexionen und Implikationen für die Erziehungswissenschaft in. Dynamiken des Pädagogischen Perspektiven auf Studium, Theorie und Praxis. Budrich. [Shop]
Borchers, C., Rosenberg, J., & Fischer, C. (2020). An Examination of the #NGSSchat Storify Database. [pdf]
Borchers, C., Ferdinand, J., & Fischer, C. (2020). Inquiry-based Learning: Forschendes Lernen im Unterricht. [Inquiry-based learning in classroom instruction]. [Blog Post]