Collin Lynch

Hoq, M., Shi, Y., Leinonen, J., Babalola, D., Lynch, C., Price, T., & Akram, B. (2024). Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models. PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1, pp. 526–532. https://doi.org/10.1145/3626252.3630826

Oliveira, G. S., Gao, Z., Heckman, S., & Lynch, C. (2024). Exploring Novice Programmer Testing Behavior: A First Step to Define Coding Struggle. PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1, pp. 1251–1257. https://doi.org/10.1145/3626252.3630851

Ma, Y., Celepkolu, M., Boyer, K. E., Wiebe, E., Lynch, C. F., & Israel, M. (2023). How Noisy is Too Noisy? The Impact of Data Noise on Multimodal Recognition of Confusion and Conflict During Collaborative Learning. PROCEEDINGS OF THE 25TH INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, ICMI 2023, pp. 326–335. https://doi.org/10.1145/3577190.3614127

Vandenberg, J., Lynch, C., Boyer, K. E., & Wiebe, E. (2022, March 11). "I remember how to do it": exploring upper elementary students' collaborative regulation while pair programming using epistemic network analysis. COMPUTER SCIENCE EDUCATION, Vol. 3. https://doi.org/10.1080/08993408.2022.2044672

Erickson, B., Heckman, S., & Lynch, C. F. (2022). Characterizing Student Development Progress: Validating Student Adherence to Project Milestones. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 15–21. https://doi.org/10.1145/3478431.3499373

Gitinabard, N., Heckman, S., Barnes, T., & Lynch, C. (2022). Designing a Dashboard for Student Teamwork Analysis. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 446–452. https://doi.org/10.1145/3478431.3499377

Gaweda, A. M., & Lynch, C. F. (2022). Exploration of theWeek-by-Week ICAP Transitions by Students. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 2, pp. 1088–1088. https://doi.org/10.1145/3478432.3499068

Ma, Y., Ruiz, J. M., Brown, T. D., Diaz, K.-A., Gaweda, A. M., Celepkolu, M., … Wiebe, E. (2022). It's Challenging but Doable: Lessons Learned from a Remote Collaborative Coding Camp for Elementary Students. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 342–348. https://doi.org/10.1145/3478431.3499327

Zakaria, Z., Vandenberg, J., Tsan, J., Boulden, D. C., Lynch, C. F., Boyer, K. E., & Wiebe, E. N. (2022). Two-Computer Pair Programming: Exploring a Feedback Intervention to improve Collaborative Talk in Elementary Students. COMPUTER SCIENCE EDUCATION, 32(1), 3–29. https://doi.org/10.1080/08993408.2021.1877987

Gao, Z., Heckman, S., & Lynch, C. (2022). Who Uses Office Hours? A Comparison of In-Person and Virtual Office Hours Utilization. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 300–306. https://doi.org/10.1145/3478431.3499334

Akintunde, R. O., Limke, A., Barnes, T., Heckman, S., & Lynch, C. (2021). PEDI - Piazza Explorer Dashboard for Intervention. 2021 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING (VL/HCC 2021). https://doi.org/10.1109/VL/HCC51201.2021.9576443

Vandenberg, J., Zakaria, Z., Tsan, J., Iwanski, A., Lynch, C., Boyer, K. E., & Wiebe, E. (2021, August 7). Prompting collaborative and exploratory discourse: An epistemic network analysis study. INTERNATIONAL JOURNAL OF COMPUTER-SUPPORTED COLLABORATIVE LEARNING, Vol. 8. https://doi.org/10.1007/s11412-021-09349-3

Ma, Y., Wiggins, J. B., Celepkolu, M., Boyer, K. E., Lynch, C., & Wiebe, E. (2021). The Challenge of Noisy Classrooms: Speaker Detection During Elementary Students' Collaborative Dialogue. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 268–281. https://doi.org/10.1007/978-3-030-78292-4_22

Vandenberg, J., Tsan, J., Boulden, D., Zakaria, Z., Lynch, C., Boyer, K. E., & Wiebe, E. (2020). Elementary Students' Understanding of CS Terms. ACM TRANSACTIONS ON COMPUTING EDUCATION, 20(3). https://doi.org/10.1145/3386364

Shabrina, P., Akintunde, R. O., Maniktala, M., Barnes, T., Lynch, C., & Rutherford, T. (2020). Peeking through the Classroom Window : A Detailed Data-Driven Analysis on the Usage of a Curriculum Integrated Math Game in Authentic Classrooms. LAK20: THE TENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, pp. 625–634. https://doi.org/10.1145/3375462.3375525

Peddycord-Liu, Z., Catete, V., Vandenberg, J., Barnes, T., Lynch, C. F., & Rutherford, T. (2019). A Field Study of Teachers Using a Curriculum-integrated Digital Game. CHI 2019: PROCEEDINGS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS. https://doi.org/10.1145/3290605.3300658

Weldon, R. A., Jr., Mueller, J. M., Lynch, C., Schuster, P., Hedges, S., Awe, C., … Mattingly, J. (2019). High-precision characterization of the neutron light output of stilbene along the directions of maximum and minimum response. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 927, 313–319. https://doi.org/10.1016/j.nima.2018.10.075

Gitinabard, N., Xu, Y., Heckman, S., Barnes, T., & Lynch, C. F. (2019). How Widely Can Prediction Models Be Generalized? Performance Prediction in Blended Courses. IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 12(2), 184–197. https://doi.org/10.1109/TLT.2019.2911832

Tsan, J., Rodriguez, F. J., Boyer, K. E., & Lynch, C. (2018). "I Think We Should...": Analyzing Elementary Students' Collaborative Processes for Giving and Taking Suggestions. SIGCSE'18: PROCEEDINGS OF THE 49TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, pp. 622–627. https://doi.org/10.1145/3159450.3159507

Shen, S., Mostafavi, B., Lynch, C., Barnes, T., & Chi, M. (2018). Empirically Evaluating the Effectiveness of POMDP vs. MDP Towards the Pedagogical Strategies Induction. In Lecture Notes in Computer Science (pp. 327–331). https://doi.org/10.1007/978-3-319-93846-2_61

Peddycord-Liu, Z., Harred, R., Karamarkovich, S., Barnes, T., Lynch, C., & Rutherford, T. (2018). Learning Curve Analysis in a Large-Scale, Drill-and-Practice Serious Math Game: Where Is Learning Support Needed? In Lecture Notes in Computer Science (pp. 436–449). https://doi.org/10.1007/978-3-319-93843-1_32

Crossley, S. A., Sirbu, M.-D., Dascalu, M., Barnes, T., Lynch, C. F., & McNamara, D. S. (2018). Modeling Math Success Using Cohesion Network Analysis. In Lecture Notes in Computer Science (pp. 63–67). https://doi.org/10.1007/978-3-319-93846-2_12

Tsan, J., Lynch, C. F., & Boyer, K. E. (2018). “Alright, what do we need?”: A study of young coders’ collaborative dialogue. International Journal of Child-Computer Interaction, 17, 61–71. https://doi.org/10.1016/J.IJCCI.2018.03.001

Tsan, J., Rodriguez, F. J., Boyer, K. E., & Lynch, C. (2017). Let's work together: Improving block-based environments by supporting synchronous collaboration. 2017 IEEE Blocks and Beyond Workshop (B&B), 53–56. https://doi.org/10.1109/blocks.2017.8120411

Lynch, C. F. (2017). Who prophets from big data in education? New insights and new challenges. THEORY AND RESEARCH IN EDUCATION, 15(3), 249–271. https://doi.org/10.1177/1477878517738448

Lynch, C. F., Xue, L. T., & Chi, M. (2016). Evolving augmented graph grammars for argument analysis. Proceedings of the 2016 Genetic and Evolutionary Computation Conference (GECCO'16 Companion), 65–66. https://doi.org/10.1145/2908961.2908994

Mostafavi, B., Zhou, G., Lynch, C., Chi, M., & Barnes, T. (2015). Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor. In Lecture Notes in Computer Science (pp. 726–729). https://doi.org/10.1007/978-3-319-19773-9_102

Mostafavi, B., Zhou, G. J., Lynch, C., Chi, M., & Barnes, T. (2015). Data-driven worked examples improve retention and completion in a logic tutor. Artificial intelligence in education, aied 2015, 9112, 726–729.

Lynch, C. F., Ashley, K. D., & Chi, M. (2014). Can Diagrams Predict Essay Grades? In Intelligent Tutoring Systems (pp. 260–265). https://doi.org/10.1007/978-3-319-07221-0_32

Ashley, K., Lynch, C., Pinkwart, N., & Aleven, V. (2009). Toward Modeling and Teaching Legal Case-Based Adaptation with Expert Examples. In Case-Based Reasoning Research and Development (pp. 45–59). https://doi.org/10.1007/978-3-642-02998-1_5

Pinkwart, N., Lynch, C., Ashley, K., & Aleven, V. (2008). Re-evaluating LARGO in the Classroom: Are Diagrams Better Than Text for Teaching Argumentation Skills? In Intelligent Tutoring Systems (pp. 90–100). https://doi.org/10.1007/978-3-540-69132-7_14

Pinkwart, N., Aleven, V., Ashley, K., & Lynch, C. (2006). Toward Legal Argument Instruction with Graph Grammars and Collaborative Filtering Techniques. In Intelligent Tutoring Systems (pp. 227–236). https://doi.org/10.1007/11774303_23

VanLehn, K., Bhembe, D., Chi, M., Lynch, C., Schulze, K., Shelby, R., … Wintersgill, M. (2004). Implicit Versus Explicit Learning of Strategies in a Non-procedural Cognitive Skill. In Intelligent Tutoring Systems (pp. 521–530). https://doi.org/10.1007/978-3-540-30139-4_49