Sarah Heckman

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

Reckinger, S., Hummel, J., & Heckman, S. (2024). Traditional vs. Flexible Modalities in a Data Structures Class. PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1, pp. 1112–1118. https://doi.org/10.1145/3626252.3630952

McGill, M. M., Heckman, S., Liut, M., Sanusi, I. T., & Szabo, C. (2024, March 14). Unlocking Excellence in Educational Research: Guidelines for High-Quality Research that Promotes Learning for All. https://doi.org/10.1145/3626253.3633402

Gao, Z., Gaweda, A., Lynch, C., Heckman, S., Babalola, D., & Oliveira, G. S. (2024, March 14). Using Survival Analysis to Model Students' Patience in Online Office Hour Queues. https://doi.org/10.1145/3626253.3635517

Gransbury, I., McGill, M. M., Thompson, A., Heckman, S., Rosato, J., & Delyser, L. A. (2023, August 7). A Framework of Factors that Influence Academic Achievement in Computer Science within Capacity, Access, Participation and Experience. https://doi.org/10.1145/3568812.3603481

Bai, G. R., Sthapit, S., Heckman, S., Price, T. W., & Stolee, K. T. (2023). An Experience Report on Introducing Explicit Strategies into Testing Checklists for Advanced Beginners. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL 1, pp. 194–200. https://doi.org/10.1145/3587102.3588781

Bai, G. R., Sthapit, S., Heckman, S., Price, T. W., & Stolee, K. T. (2023). An Experience Report on Introducing Explicit Strategies into Testing Checklists for Advanced Beginners.

Gitinabard, N., Gao, Z., Heckman, S., Barnes, T., Lynch, C. F., & others. (2023). Analysis of Student Pair Teamwork Using GitHub Activities. Journal of Educational Data Mining, 15(1), 32–62.

Zahn, M., Gransbury, I., Heckman, S., & Battestilli, L. (2023). Assessment of Self-Identified Learning Struggles in CS2 Programming Assignments. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL 1, pp. 264–270. https://doi.org/10.1145/3587102.3588786

McGill, M. M., Heckman, S., Chytas, C., Diaz, L., Liut, M., Kazakova, V., … Szabo, C. (2023). Building Recommendations for Conducting Equity-Focused, High Quality K-12 Computer Science Education Research. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL. 2, pp. 565–566. https://doi.org/10.1145/3587103.3594207

McGill, M. M., Thompson, A., Gransbury, I., Heckman, S., Rosato, J., & DeLyser, L. A. (2023). Building upon the CAPE Framework for Broader Understanding of Capacity in K-12 CS Education. PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 1, SIGCSE 2023, pp. 577–582. https://doi.org/10.1145/3545945.3569799

McGill, M. M., Heckman, S., Chytas, C., Liut, M., Kazakova, V., Sanusi, I. T., … Szabo, C. (2023). Conducting Sound, Equity-Enabling Computing Education Research. PROCEEDINGS OF THE 2023 WORKING GROUP REPORTS ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE-WGR 2023. https://doi.org/10.1145/3623762.3633495

Presler-Marshall, K., Heckman, S., & Stolee, K. T. (2023). Improving Grading Outcomes in Software Engineering Projects Through Automated Contributions Summaries. 2023 IEEE/ACM 45TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING-SOFTWARE ENGINEERING EDUCATION AND TRAINING, ICSE-SEET, pp. 259–270. https://doi.org/10.1109/ICSE-SEET58685.2023.00030

Gao, Z., Lynch, C., & Heckman, S. (2023). Too long to wait and not much to do: Modeling student behaviors while waiting for help in online office hours. Proceedings of the 7th Educational Data Mining in Computer Science Education (CSEDM) Workshop.

Heckman, S., Carver, J. C., Sherriff, M., & Al-zubidy, A. (2022). A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature. ACM Transactions on Computing Education. https://doi.org/10.1145/3470652

Battestilli, L., Zahn, M., & Heckman, S. (2022). Academic Help Seeking Patterns in Introductory Computer Science Courses. 2022 ASEE Annual Conference & Exposition.

Heckman, S., & Minnes, M. (2022). Academic Middle Management: Undergraduate Leadership in Computing Programs. Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2, 1184–1184.

Gao, Z., Erickson, B., Xu, Y., Lynch, C., Heckman, S., & Barnes, T. (2022). Admitting you have a problem is the first step: Modeling when and why students seek help in programming assignments. Proceedings of the 15th International Conference on Educational Data Mining, A. Mitrovic and N. Bosch, Eds. International Educational Data Mining Society, Durham, United Kingdom, 508–514.

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

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-Volume 1, 15–21.

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

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-Volume 1, 446–452.

Mannekote, A., Celepkolu, M., Galdo, A. C., Boyer, K. E., Israel, M., Heckman, S., & Stephens-Martinez, K. (2022). Don't Just Paste Your Stacktrace: Shaping Discussion Forums in Introductory CS Courses. Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2, 1164–1164.

Presler-Marshall, K., Heckman, S., & Stolee, K. T. (2022). Identifying Struggling Teams in Software Engineering Courses ThroughWeekly Surveys. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 126–132. https://doi.org/10.1145/3478431.3499367

Presler-Marshall, K., Heckman, S., & Stolee, K. T. (2022). Identifying struggling teams in software engineering courses through weekly surveys. Proceedings of the 53rd ACM Technical Symposium on Computer Science Education-Volume 1, 126–132.

Zahn, M., & Heckman, S. (2022). Observations on Student Help-Seeking Behaviors in Introductory Computer Science Courses. Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2, 1380–1380. https://doi.org/10.1145/3545947.3576325

Carver, J. C., Heckman, S., & Sherriff, M. (2022). Training Computing Educators to Become Computing Education Researchers. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 724–730. https://doi.org/10.1145/3478431.3499297

Carver, J. C., Heckman, S., & Sherriff, M. (2022). Training computing educators to become computing education researchers. Proceedings of the 53rd ACM Technical Symposium on Computer Science Education-Volume 1, 724–730.

Presler-Marshall, K., Heckman, S., & Stolee, K. T. (2022). What Makes Team [s] Work? A Study of Team Characteristics in Software Engineering Projects. Proceedings of the 2022 ACM Conference on International Computing Education Research-Volume 1, 177–188.

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

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-Volume 1, 300–306.

Gao, Z., Erickson, B., Xu, Y., Lynch, C., Heckman, S., Barnes, T., & others. (2022). You asked, now what? Modeling Students' Help-Seeking and Coding actions from Request to Resolution. Journal of Educational Data Mining, 14(3), 109–131.

Heckman, S., Carver, J. C., Sherriff, M., & Al-Zubidy, A. (2021). A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature. ACM Transactions on Computing Education (TOCE), 22(1), 1–46.

Gao, Z., Lynch, C., Heckman, S., & Barnes, T. (2021). Automatically Classifying Student Help Requests: A Multi-Year Analysis. International Educational Data Mining Society.

Basu, D., Heckman, S., & Maher, M. L. (2021). Online Vs Face-to-face Web-development Course: Course Strategies, Learning, and Engagement. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, 1191–1197.

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

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), 1–4.

Presler-Marshall, K., Heckman, S., & Stolee, K. T. (2021). SQLRepair: Identifying and Repairing Mistakes in Student-Authored SQL Queries. 2021 IEEE/ACM 43RD INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: JOINT TRACK ON SOFTWARE ENGINEERING EDUCATION AND TRAINING (ICSE-JSEET 2021), pp. 199–210. https://doi.org/10.1109/ICSE-SEET52601.2021.00030

Presler-Marshall, K., Heckman, S., & Stolee, K. T. (2021). SQLRepair: Identifying and Repairing Mistakes in Student-Authored SQL Queries. 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET), 199–210.

Heckman, S., Schmidt, J. Y., & King, J. (2020). Integrating Testing Throughout the CS Curriculum. 2020 IEEE 13TH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION WORKSHOPS (ICSTW), pp. 441–444. https://doi.org/10.1109/ICSTW50294.2020.00079

Heckman, S., Schmidt, J. Y., & King, J. (2020). Integrating Testing Throughout the CS Curriculum. 2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 441–444.

Gitinabard, N., Okoilu, R., Xu, Y., Heckman, S., Barnes, T., & Lynch, C. (2020). Student Teamwork on Programming Projects: What can GitHub logs show us? ArXiv Preprint ArXiv:2008.11262.

Heckman, S., Fain, B., & Pérez-Quiñones, M. (2019). Building and expanding a successful undergraduate research program. Journal of Computing Sciences in Colleges, 35(4), 18–19.

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

Hawthorne, E. K., Pérez-Quiñones, M. A., Heckman, S., & Zhang, J. (2019). SIGCSE technical symposium 2019 report. ACM SIGCSE Bulletin, 51(2), 2–4.

Zhang, J., Sherriff, M., Heckman, S., Cutter, P., & Monge, A. (2019). SIGCSE technical symposium 2020 call for submissions. ACM SIGCSE Bulletin, 51(3), 2–3.

Presler-Marshall, K., Horton, E., Heckman, S., & Stolee, K. (2019). Wait, Wait. No, Tell Me. Analyzing Selenium Configuration Effects on Test Flakiness. 2019 IEEE/ACM 14th International Workshop on Automation of Software Test (AST), 7–13.

Gitinabard, N., Heckman, S., Barnes, T., & Lynch, C. F. (2019). What will you do next? A sequence analysis on the student transitions between online platforms in blended courses. ArXiv Preprint ArXiv:1905.00928.

Heckman, S., Stolee, K. T., & Parnin, C. (2018). 10+ years of teaching software engineering with itrust: the good, the bad, and the ugly. Proceedings of the 40th International Conference on Software Engineering: Software Engineering Education and Training, 1–4.

Heckman, S., Stolee, K. T., & Parnin, C. (2018). 10+Years of Teaching Software Engineering with iTrust: the Good, the Bad, and the Ugly. 2018 IEEE/ACM 40TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING EDUCATION AND TRAINING (ICSE-SEET), pp. 1–4. https://doi.org/10.1145/3183377.3183393

Sherriff, M., & Heckman, S. (2018). Capstones and large projects in computing education. ACM Transactions on Computing Education (TOCE), Vol. 18, pp. 1–4. ACM New York, NY, USA.

Carver, J. C., Heckman, S., & Sherriff, M. (2018). Designing Empirical Education Research Studies (DEERS): Creating an Answerable Research Question. SIGCSE'18: PROCEEDINGS OF THE 49TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, pp. 1051–1051. https://doi.org/10.1145/3159450.3162350

Carver, J. C., Heckman, S., & Sherriff, M. (2018). Designing Empirical Education Research Studies (DEERS): Creating an Answerable Research Question. Proceedings of the 49th ACM Technical Symposium on Computer Science Education, 1051–1051.

Heckman, S., & King, J. (2018). Developing Software Engineering Skills using Real Tools for Automated Grading. SIGCSE'18: PROCEEDINGS OF THE 49TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, pp. 794–799. https://doi.org/10.1145/3159450.3159595

Heckman, S., & King, J. (2018). Developing Software Engineering Skills using Real Tools for Automated Grading. Proceedings of the 49th ACM Technical Symposium on Computer Science Education, 794–799.

Sheshadri, A., Gitinabard, N., Lynch, C. F., Barnes, T., & Heckman, S. (2018). Predicting student performance based on online study habits: a study of blended courses. the 11th International Conference on Educational Data Mining (EDM 2018), 87–96.

Heckman, S., Zhang, J., Peérez-Quiñones, M. A., & Hawthorne, E. K. (2018). SIGCSE 2019 paper length change. ACM SIGCSE Bulletin, 50(2), 4–4.

Heckman, S., Zhang, J., Pérez-Quiñones, M. A., & Hawthorne, E. K. (2018). What is a SIGCSE symposium paper? ACM SIGCSE Bulletin, 50(3), 3–3.

Gitinabard, N., Xue, L., Lynch, C. F., Heckman, S., & Barnes, T. (2017). A Social Network Analysis on Blended Courses. ArXiv Preprint ArXiv:1709.10215.

Bahler, D., Battestilli, L., DeMaria, M., Healey, C., Heckman, S., Heil, M., … others. (2017). Conversations (oral history interviews) with members of North Carolina State University Computer Science Department by Carol Lee and Carolyn Miller.

Vellukunnel, M., Buffum, P., Boyer, K. E., Forbes, J., Heckman, S., & Mayer-Patel, K. (2017). Deconstructing the Discussion Forum: Student Questions and Computer Science Learning. Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 603–608.

Heckman, S., Carver, J. C., & Sherriff, M. (2017). Designing Empirical Education Research Studies (DEERS): Creating an Answerable Research Question. Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 737–737.

Gitinabard, N., Lynch, C. F., Heckman, S., & Barnes, T. (2017). Identifying Student Communities in Blended Courses. ArXiv Preprint ArXiv:1710.04129.

Smith, A. J., Boyer, K. E., Forbes, J., Heckman, S., & Mayer-Patel, K. (2017). My Digital Hand: A Tool for Scaling Up One-to-One Peer Teaching in Support of Computer Science Learning. Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 549–554.

Al-Zubidy, A., Carver, J. C., Heckman, S., & Sherriff, M. (2016). A (Updated) Review of Empiricism at the SIGCSE Technical Symposium. Proceedings of the 47th ACM Technical Symposium on Computing Science Education, 120–125.

Johnson, B., Pandita, R., Smith, J., Ford, D., Elder, S., Murphy-Hill, E., … Sadowski, C. (2016). A Cross-Tool Study on Program Analysis Tool Notification Communication.

Johnson, B., Pandita, R., Smith, J., Ford, D., Elder, S., Murphy-Hill, E., … Sadowski, C. (2016). A cross-tool communication study on program analysis tool notifications. Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, 73–84.

Heckman, S., & King, J. (2016). Teaching Software Engineering Skills in CS1. 5: Incorporating Real-world Practices and Tools. Proceedings of the 47th ACM Technical Symposium on Computing Science Education, 696–697.

Heckman, S. S. (2015). An Empirical Study of In-Class Laboratories on Student Learning of Linear Data Structures. Proceedings of the eleventh annual International Conference on International Computing Education Research, 217–225.

Heckman, S., King, J., & Winters, M. (2015). Automating Software Engineering Best Practices Using an Open Source Continuous Integration Framework. Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 677–677.

Johnson, B., Pandita, R., Murphy-Hill, E., & Heckman, S. (2015). Bespoke Tools: Adapted to the Concepts Developers Know. 2015 10TH JOINT MEETING OF THE EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND THE ACM SIGSOFT SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE 2015) PROCEEDINGS, pp. 878–881. https://doi.org/10.1145/2786805.2803197

Johnson, B., Pandita, R., Murphy-Hill, E., & Heckman, S. (2015). Bespoke tools: adapted to the concepts developers know. Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, 878–881.

Anderson, P. V., Heckman, S., Vouk, M., Wright, D., Carter, M., Burge, J. E., & Gannod, G. C. (2015). CS/SE Instructors Can Improve Student Writing without Reducing Class Time Devoted to Technical Content: Experimental Results. 2015 IEEE/ACM 37TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, VOL 2, pp. 455–464. https://doi.org/10.1109/icse.2015.178

Anderson, P. V., Heckman, S., Vouk, M., Wright, D., Carter, M., Burge, J. E., & Gannod, G. C. (2015). CS/SE instructors can improve student writing without reducing class time devoted to technical content: experimental results. 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, 2, 455–464.

Sherriff, M., & Heckman, S. (2015). Empirical Research in CS Education. Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 701–701.

Heckman, S., & Williams, L. (2013). A comparative evaluation of static analysis actionable alert identification techniques. Proceedings of the 9th International Conference on Predictive Models in Software Engineering, 1–10.

Carter, M., Fornaro, R., Heckman, S. S., & Heil, M. (2012). Developing a learning progression that integrates communication in an undergraduate CD/SE curriculum. North Carolina State University. Dept. of Computer Science.

Heckman, S., & Williams, L. (2011). A systematic literature review of actionable alert identification techniques for automated static code analysis. Information and Software Technology, 53(4), 363–387.

Heckman, S., Horton, T. B., & Sherriff, M. (2011). Teaching second-level Java and software engineering with Android. 2011 24th IEEE-CS Conference on Software Engineering Education and Training (CSEET), 540–542. https://doi.org/10.1109/cseet.2011.5876144

Heckman, S. (2010). Software testing (CS1 & CS2). NC State University, August, 6.

Heckman, S., & Williams, L. (2009). A model building process for identifying actionable static analysis alerts. 2009 International Conference on Software Testing Verification and Validation, 161–170.

Heckman, S. S. (2009). A systematic model building process for predicting actionable static analysis alerts. North Carolina State University.

Heckman, S. S., & Williams, L. A. (2008). A measurement framework of alert characteristics for false positive mitigation models. North Carolina State University. Dept. of Computer Science.

Heckman, S., & Williams, L. (2008). On establishing a benchmark for evaluating static analysis alert prioritization and classification techniques. Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement, 41–50.

Heckman, S. S. (2007). Adaptive probabilistic model for ranking code-based static analysis alerts. 29th International Conference on Software Engineering (ICSE'07 Companion), 89–90.

Heckman, S. S. (2007). Adaptively ranking alerts generated from automated static analysis. XRDS: Crossroads, The ACM Magazine for Students, 14(1), 1–11.

Sherriff, M., Heckman, S. S., Lake, M., & Williams, L. (2007). Identifying fault-prone files using static analysis alerts through singular value decomposition. Proceedings of the 2007 conference of the center for advanced studies on Collaborative research, 276–279.

Sherriff, M. S., Heckman, S. S., Lake, J. M., & Williams, L. A. (2007). Using groupings of static analysis alerts to identify files likely to contain field failures. The 6th Joint Meeting on European software engineering conference and the ACM SIGSOFT symposium on the foundations of software engineering: companion papers, 565–568.

Heckman, S., & Williams, L. (2006). Automated adaptive ranking and filtering of static analysis alerts. Proc of the Fast abstract at the International Symposium on Software Reliability Engineering (ISSRE).

Heckman, S., & Gehringer, E. F. Google Forms as an Enhanced Classroom Response System.