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Peer-Reviewed Publications in Academic Journals
2019
Price, T.W., Y. Dong, R. Zhi, B. Paaßen, N. Lytle, V. Cateté, T. Barnes. “A Comparison of the Quality of Data-driven Programming Hint Generation Algorithms.” International Journal of Artificial Intelligence in Education. 2019. [Paper]
2018
Paaßen, B., B. Hammer, T. W. Price, T. Barnes, S. Gross and N. Pinkwart. “The Continuous Hint Factory – Providing Hints in Continuous and Infinite Spaces.” Journal of Educational Data Mining. 2018. [Paper]
Peer-Reviewed Publications in Conference Proceedings
2021
S. Marwan, Y. Shi, I. Menezes, M. Chi, T. Barnes, T. W. Price, “Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming”. Proceedings of the International Conference on Educational Data Mining (EDM) 2021. (Acceptance Rate 22.0%, 22/100 Full Papers, Best Full Paper Award). [Paper | Video Presentation]
Y. Mao, Y. Shi, S. Marwan, T. Price, T. Barnes and M. Chi, “Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks”. Proceedings of the International Conference on Educational Data Mining (EDM) 2021. (Acceptance Rate 22.0%, 22/100 Full Papers). [Paper | Slides]
Y. Shi*, Y. Mao*, T. Barnes, M. Chi and T. W. Price, “More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code”. Proceedings of the International Conference on Educational Data Mining (EDM) 2021. (Combined Acceptance Rate 27.2%, 44/162 Short Papers). [Paper | Slides]
Y. Dong, S. Marwan, P. Shabrina, T. Barnes and T. W. Price, “Using Student Trace Logs To Determine Meaningful Progress and Struggle During Programming Problem Solving”. Proceedings of the International Conference on Educational Data Mining (EDM) 2021. (Combined Acceptance Rate 27.2%, 44/162 Short Papers). [Paper |Slides]
W. Wang, C. Zhang, A. Stahlbauer, G. Fraser, T. W. Price, “SnapCheck: Automated Testing for Snap! Programs“. ITiCSE’21 – Proceedings of the 2021 ACM Conference on Innovation and Technology in Computer Science Education, to appear. (31% acceptance rate; 84/275 full papers.). [talk | slides | paper]
W. Wang, A. Kwatra, J. Skripchuk, N. Gomes, A. Milliken, C. Martens, T. Barnes, T. W. Price, “Novices’ Learning Barriers When Using Code Examples in Open-Ended Programming”. ITiCSE’21 – Proceedings of the 2021 ACM Conference on Innovation and Technology in Computer Science Education, to appear. (31% acceptance rate; 84/275 full papers.). [paper]
Y. Shi, K. Shah, W. Wang, S. Marwan, P. Penmetsa, T. W. Price, “Toward Semi-Automatic Misconception Discovery Using Code Embeddings”. International Conference on Learning Analytics and Knowledge (LAK), 2021. (Acceptance Rate 29.3%, 29/99 Short Papers) [Paper | Slides].
A. Milliken, W. Wang, V. Cateté, S. Martin, N. Gomes, Y. Dong, R. Harred, A. Isvik, T. Barnes, T. W. Price, C. Martens. “PlanIT! A new integrated tool to help novices design for open-ended projects”. SIGCSE Technical Symposium, 2021. [paper].
G.Gao, S.Marwan, and T.W. Price. “Early Performance Prediction using Interpretable Patterns in Programming Process Data”. SIGCSE Technical Symposium, 2021. [paper].
2020
S.Marwan, G. Gao, S. Fisk, T.W. Price, and T. Barnes. “Adaptive Immediate Feedback Can Improve Novice Programming Engagement and Intention to Persist in Computer Science”. In the sixteenth annual ACM International Computing Education Research (ICER), 2020. (22.7% acceptance rate; 27/119 full papers). [Paper | Video Presentation]
T.W. Price, S. Marwan, M. Winters, J.J. Williams, “An Evaluation of Data-driven Programming Hints in a Classroom Setting.” International Conference on Artificial Intelligence in Education (AIED). 2020. (short paper) [Paper | Poster | Video Presentation]
Y. Mao, S. Marwan, T.W. Price, T. Barnes, M. Chi, “What Time is It? Student Modeling Needs to Know.” Proceedings of the International Conference on Educational Data Mining (EDM) 2020. (30.6% acceptance rate; 30/98 papers) [Paper]
S. Marwan, A. Dombe, T.W. Price, “Unproductive Help-seeking in Programming: What it is and How to Address it” ITiCSE’20 – Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. (27.6% acceptance rate; 72/261 full papers) [Paper | Slides | Video Presentation]
T.W. Price et al. “ProgSnap2: A Flexible Format for Programming Process Data.” Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. (27.6% acceptance rate; 72/261 full papers) [Paper | Video Presentation]
W. Wang, Y. Rao, R. Zhi, S. Marwan, G. Gao, T.W. Price, “Step Tutor: Supporting Students through Step-by-Step Example-Based Feedback.” Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education. (27.6% acceptance rate; 72/261 full papers) [Paper | Video Presentation | Slides]
T.W. Price, J.J. Williams, J. Solyst, S. Marwan, “Engaging Students with Instructor Solutions in Online Programming Homework.” Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 2020. (24.3% acceptance rate; 760/3126 papers) [Paper]
W. Wang, R. Zhi, A. Milliken, N. Lytle, T.W. Price, “Crescendo: Engaging Students to Self-Paced Programming Practices.” ACM Special Interest Group on Computer Science Education (SIGCSE). 2020. (31.4% acceptance rate; 171/544 papers) [Paper | Video Presentation | Slides]
2019
S. Marwan, J. J. Williams, T.W. Price. “An Evaluation of the Impact of Automated Programming Hints on Performance and Learning.” International Computing Education Research Conference (ICER). 2019. (20.4% acceptance rate; 28/137 full papers)[Paper].
R. Zhi, M. Chi, T. Barnes, T.W. Price. “Evaluating the Effectiveness of Parsons Problems for Block-based Programming.” International Computing Education Research Conference (ICER). 2019. (20.4% acceptance rate; 28/137 full papers) [Paper | Slides]
R. Zhi, S. Marwan, Y. Dong, N. Lytle, T.W. Price, T. Barnes. “Toward Data-Driven Example Feedback for Novice Programming.” Proceedings of the International Conference on Educational Data Mining (EDM). 2019. (22.5% acceptance rate for full papers) [Paper | Slides]
Mao, Y., R. Zhi, F. Khoshnevisan, T.W. Price, T. Barnes, M. Chi. ” One minute is enough: Early Prediction of Student Success and Event-level Difficulty during a Novice Programming Task.” Proceedings of the International Conference on Educational Data Mining (EDM). 2019. (22.5% acceptance rate for full papers) [Paper]
S. Marwan, N. Lytle, J. J. Williams, T. W. Price. “The Impact of Adding Textual Explanations to Next-step Hints in a Novice Programming Environment”. Proceedings of the 24th Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE). 2019. (28% acceptance rate; 67/243 full papers) [Paper] [Slides]
R. Zhi, T. W. Price, S. Marwan, A. Milliken, T. Barnes and M. Chi. “Exploring the Impact of Worked Examples in a Novice Programming Environment.” ACM Special Interest Group on Computer Science Education (SIGCSE). 2019. (32% acceptance rate; 169/526 full papers) [Paper | Slides]
Dong, Y., S. Marwan, V. Cateté, T. Barnes and T. W. Price. “Defining Tinkering Behavior in Open-ended Block-based Programming Assignments.” ACM Special Interest Group on Computer Science Education (SIGCSE). 2019. (32% acceptance rate; 169/526 full papers) [Paper | Slides]
2018
Price, T. W., R. Zhi, Y. Dong, N. Lytle and T. Barnes. “The Impact of Data Quantity and Source on the Quality of Data-driven Hints for Programming.” International Conference on Artificial Intelligence in Education. 2018. (25% acceptance rate; 46/186 full papers) [Paper | Slides]
Zhi, R., N. Lytle, T. W. Price.”Exploring Instructional Support in an Educational Game for K-12 Computing Education.” ACM Special Interest Group on Computer Science Education (SIGCSE). 2018. (35% acceptance rate; 161/459 full papers) [Paper | Slides]
2017
Price, T. W., Z. Liu, V. Cateté and T. Barnes. “Factors Influencing Students’ Help-Seeking Behavior while Programming with Human and Computer Tutors.” International Computing Education Research (ICER) Conference. 2017. (27% acceptance rate; 29/108 full papers) [Paper | Slides]
Price, T. W., R. Zhi and T. Barnes. “Hint Generation Under Uncertainty: The Effect of Hint Quality on Help-Seeking Behavior.” International Conference on Artificial Intelligence in Education. 2017. (30% acceptance rate; 36/121 full papers) [Paper | Slides]
Price, T. W., R. Zhi and T. Barnes. “Evaluation of a Data-driven Feedback Algorithm for Open-ended Programming.” International Conference on Educational Data Mining. 2017. (42% acceptance rate; 32 short papers) [Paper | Slides]
Price, T. W., Y. Dong and D. Lipovac. “iSnap: Towards Intelligent Tutoring in Novice Programming Environments.” ACM Special Interest Group on Computer Science Education (SIGCSE). 2017. (Exemplary CS Education Paper Award; 30% acceptance rate; 105/350 full papers) [Paper | Slides]
2016
Price, T. W., N.C.C. Brown, D. Lipovac, T. Barnes and M. Kölling. “Evaluation of a Frame-based Programming Editor.” International Computing Education Research (ICER) Conference. 2016. (25.5% acceptance rate; 26/102 full papers) [Paper | Slides]
Price, T. W., Dong, T. and Barnes, T. “Generating Data-driven Hints for Open-ended Programming.” International Conference on Educational Data Mining. 2016. (Exemplary Paper Award; 27.5% acceptance rate; 30/105 full papers) [Paper | Slides]
Price, T. W., V. Cateté, J. Albert, T. Barnes and D. Garcia. “Lessons Learned from “BJC” CS Principles Professional Development.” ACM Special Interest Group on Computer Science Education (SIGCSE). 2016. (35.4% acceptance rate; 105/297 full papers) [Paper | Slides]
2015
Price, T. W., J. Albert, V. Cateté and T. Barnes. “BJC in Action: Comparison of Student Perceptions of a Computer Science Principles Course.” Research in Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT) Conference. 2015. (44.4% acceptance rate; 8/18 short papers) [Paper | Slides]
Price, T. W. and T. Barnes. “Comparing Textual and Block Interfaces in a Novice Programming Environment.” International Computing Education Research Conference (ICER). 2015. (26% acceptance rate; 25/96 full papers) [Paper | Slides]
Peer-Reviewed Publications in Workshops
2021
W. Wang, G. Fraser, T. Barnes, C. Martens, T. Price, “Execution-Trace-Based Feature Engineering To Enable Formative Feedback on Visual, Interactive Programs”. CSEDM Workshop @ EDM’21 [talk | slides | paper]
P. Penmetsa, Y. Shi, T. Price, “Identifying Struggling Students in Novice Programming Course with Knowledge Tracing.” Work-In-Progress Track, CSEDM Workshop @ EDM’21
2020
Wang, W., Rao, Y., Shi, Y., Milliken, A., Martens, C., Barnes, T. and Price, T. W., ‘’Comparing Feature Engineering Approaches to PredictComplex Programming Behaviors.“ Educational Data Mining in Computer Science Education (CSEDM) Workshop @ EDM’20 (short paper) [Paper| Video Presentation |Slides]
Marwan, S., Price, T. W., Chi, M., and Barnes, T., “Immediate Data-Driven Positive Feedback Increases Engagement on Programming Homework for Novices.” Educational Data Mining in Computer Science Education (CSEDM) Workshop @ EDM’20 (short paper) [Paper|Poster]
Shabrina, P., Marwan, S., Chi, M., Price, T. W., and Barnes, T., “The Impact of Data-driven Positive Programming Feedback: When it Helps, What Happens when it Goes Wrong, and How Students Respond” Educational Data Mining in Computer Science Education (CSEDM) Workshop @ EDM’20 (24% acceptance rate; 4/17 full papers) [Paper | Presentation]
2019
Price, T. W., D. Hovemeyer, K. Rivers, A. C. Bart, A. Petersen, B. A. Becker and J. Lefever. “ProgSnap2: A Flexible Format for Programming Process Data.” 2nd Educational Data Mining in Computer Science Education (CSEDM) Workshop at the International Conference on Learning Analytics and Knowledge (LAK). 2019, forthcoming. [Paper]
Price, T. W., J. J. Williams, S. Marwan. “A Comparison of Two Designs for Automated Programming Hints.” 2nd Educational Data Mining in Computer Science Education (CSEDM) Workshop at the International Conference on Learning Analytics and Knowledge (LAK). 2019. [Paper]
2018
Zhi, R., T. W. Price, N. Lytle, Y. Dong and T. Barnes. “Reducing the State Space of Programming Problems through Data-Driven Feature Detection.” Educational Data Mining in Computer Science Education (CSEDM) Workshop at the International Conference on Educational Data Mining (EDM). 2018. [Paper | Slides]
2017
Price, T. W. and T. Barnes. “Position Paper: Block-based Programming Should Offer Intelligent Support for Learners.” Blocks and Beyond Workshop at the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 2017. [Paper | Slides]
Extended Abstracts and Posters
2020
S.Marwan “Investigating Best Practices in the Design of Automated Feedback to Improve Students’ Performance and Learning”. In Proceedings of the 2020 ACM Conference on International Computing Education Research (ICER ’20). [DC | Poster]
2018
Price, T. W. “iSnap: Automatic Hints and Feedback for Block-based Programming.” ACM Special Interest Group on Computer Science Education (SIGCSE). 2018.
2017
Price, T. W. and T. Barnes. “Showpiece: iSnap Demonstration.” IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 2017. [Abstract]
2016
Price, T. W. and T. Barnes. “Data-driven Support for Novice Programmers.” UP CS Ed Research Workshop at the International Computing Education Research (ICER) Conference. 2016. [Abstract | Slides]
PhD Dissertations, Committee Chair
2019
Zhi, R. “Design and Evaluation of Instructional Supports for Novice Programming Environments.” NCSU PhD Dissertation. 2019.[Dissertation]