Tiffany Barnes

Wang, W., Limke, A., Bobbadi, M., Isvik, A., Catete, V., Barnes, T., & Price, T. W. (2024). Idea Builder: Motivating Idea Generation and Planning for Open-Ended Programming Projects through Storyboarding. PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1, pp. 1402–1408. https://doi.org/10.1145/3626252.3630872

Wyatt, L. G., Fisk, S. R., Thompson, C., Payton, J., Catete, V., Rorrer, A., … McKlin, T. (2024). Multi-Pronged Pedagogical Approaches to Broaden Participation in Computing and Increase Students' Computing Persistence: A Robustness Analysis of the STARS Computing Corps' Impact on Students' Intentions to Persist in Computing. PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1, pp. 1456–1462. https://doi.org/10.1145/3626252.3630895

Wang, W., Rao, Y., Kwatra, A., Milliken, A., Dong, Y., Gomes, N., … Price, T. (2023). A Case Study on When and How Novices Use Code Examples in Open-Ended Programming. PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL 1, pp. 82–88. https://doi.org/10.1145/3587102.3588774

Harred, R., Barnes, T., Fisk, S. R., Akram, B., Price, T. W., & Yoder, S. (2023). Do Intentions to Persist Predict Short-Term Computing Course Enrollments? A Scale Development, Validation, and Reliability Analysis. PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 1, SIGCSE 2023, pp. 1062–1068. https://doi.org/10.1145/3545945.3569875

Tabarsi, B., Reichert, H., Qualls, R., Price, T., & Barnes, T. (2023). Exploring Novices' Struggle and Progress during Programming through Data-Driven Detectors and Think-Aloud Protocols. 2023 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING, VL/HCC, pp. 179–183. https://doi.org/10.1109/VL-HCC57772.2023.00029

Abdelshiheed, M., Barnes, T., & Chi, M. (2023). How and When: The Impact of Metacognitive Knowledge Instruction and Motivation on Transfer Across Intelligent Tutoring Systems. International Journal of Artificial Intelligence in Education, 9. https://doi.org/10.1007/s40593-023-00371-0

Shabrina, P., Mostafavi, B., Abdelshiheed, M., Chi, M., & Barnes, T. (2023). Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning Towards Improved Problem Solving. International Journal of Artificial Intelligence in Education, 8. https://doi.org/10.1007/s40593-023-00338-1

Wang, W., Bacher, J., Isvik, A., Limke, A., Sthapit, S., Shi, Y., … Price, T. (2023). Investigating the Impact of On-Demand Code Examples on Novices' Open-Ended Programming Projects. PROCEEDINGS OF THE 2023 ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH V.1, ICER 2023 V1, pp. 464–475. https://doi.org/10.1145/3568813.3600141

Hostetter, J. W., Abdelshiheed, M., Barnes, T., & Chi, M. (2023). Leveraging Fuzzy Logic Towards More Explainable Reinforcement Learning-Induced Pedagogical Policies on Intelligent Tutoring Systems. Presented at the 2023 IEEE International Conference on Fuzzy Systems (FUZZ). https://doi.org/10.1109/FUZZ52849.2023.10309741

Limke, A., Lytle, N., Mahmoud, S., Lin, M., Hill, M., Catete, V., & Barnes, T. (2023). Participatory Design with Teachers for Block-based Learning with SnapClass. 2023 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING, VL/HCC, pp. 173–178. https://doi.org/10.1109/VL-HCC57772.2023.00028

Gransbury, I., Brock, J., Root, E., Catete, V., Barnes, T., Grover, S., & Ledeczi, A. (2023). Project-Based Software Engineering Curriculum for Secondary Students. PROCEEDINGS OF THE 18TH WIPSCE CONFERENCE IN PRIMARY AND SECONDARY COMPUTING EDUCATION RESEARCH, WIPSCE 2023. https://doi.org/10.1145/3605468.3605501

Hostetter, J. W., Conati, C., Yang, X., Abdelshiheed, M., Barnes, T., & Chi, M. (2023). XAI to Increase the Effectiveness of an Intelligent Pedagogical Agent. Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents. (IVA’23). Presented at the 23rd ACM International Conference on Intelligent Virtual Agents. (IVA’23), Würzburg, Germany. https://doi.org/10.1145/3570945.3607301

Marwan, S., Akram, B., Barnes, T., & Price, T. W. (2022). Adaptive Immediate Feedback for Block-Based Programming: Design and Evaluation. IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 15(3), 406–420. https://doi.org/10.1109/TLT.2022.3180984

Brady, C., Broll, B., Stein, G., Jean, D., Grover, S., Catete, V., … Ledeczi, A. (2022). Block-based abstractions and expansive services to make advanced computing concepts accessible to novices. JOURNAL OF COMPUTER LANGUAGES, 73. https://doi.org/10.1016/j.cola.2022.101156

Jocius, R., O'Byrne, W. I., Albert, J., Joshi, D., Blanton, M., Robinson, R., … Catete, V. (2022, April 18). Building a Virtual Community of Practice: Teacher Learning for Computational Thinking Infusion. TECHTRENDS, Vol. 4. https://doi.org/10.1007/s11528-022-00729-6

Limke, A., Milliken, A., Catete, V., Gransbury, I., Isvik, A., Price, T., … Barnes, T. (2022). Case Studies on the use of Storyboarding by Novice Programmers. PROCEEDINGS OF THE 27TH ACM CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2022, VOL 1, pp. 318–324. https://doi.org/10.1145/3502718.3524749

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

Maniktala, M., Chi, M., & Barnes, T. (2022, August 3). Enhancing a student productivitymodel for adaptive problem-solving assistance. USER MODELING AND USER-ADAPTED INTERACTION. https://doi.org/10.1007/s11257-022-09338-7

Wang, W., Le Meur, A., Bobbadi, M., Akram, B., Barnes, T., Martens, C., & Price, T. (2022). Exploring Design Choices to Support Novices' Example Use During Creative Open-Ended Programming. PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, pp. 619–625. https://doi.org/10.1145/3478431.3499374

Akram, B., Fisk, S., Yoder, S., Hunt, C., Price, T., Battestilli, L., & Barnes, T. (2022). Increasing Students' Persistence in Computer Science through a Lightweight Scalable Intervention. PROCEEDINGS OF THE 27TH ACM CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2022, VOL 1, pp. 526–532. https://doi.org/10.1145/3502718.3524815

Abdelshiheed, M., Hostetter, J. W., Yang, X., Barnes, T., & Chi, M. (2022). Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer. https://doi.org/10.1007/978-3-031-11644-5_47

Ju, S., Yang, Xi, Barnes, T., & Chi, M. (2022). Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning. ARTIFICIAL INTELLIGENCE IN EDUCATION, PT I, Vol. 13355, pp. 440–452. https://doi.org/10.1007/978-3-031-11644-5_36

Ausin, M. S., Maniktala, M., Barnes, T., & Chi, M. (2022, November 28). The Impact of Batch Deep Reinforcement Learning on Student Performance: A Simple Act of Explanation Can Go A Long Way. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION. https://doi.org/10.1007/s40593-022-00312-3

Maniktala, M., Cody, C., Barnes, T., & Chi, M. (2021, March). Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor (September, 10.1007/s40593-020-00213-3, 2020). INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, Vol. 31, pp. 154–155. https://doi.org/10.1007/s40593-020-00232-0

Ju, S., Zhou, G., Abdelshiheed, M., Barnes, T., & Chi, M. (2021). Evaluating Critical Reinforcement Learning Framework in the Field. https://doi.org/10.1007/978-3-030-78292-4_18

Isvik, A., Catete, V., Elmore, E., & Barnes, T. (2021). Examining Equity in Computing-Infused Lessons Made by Novices. IEEE STCBP RESPECT CONFERENCE: 2021 RESEARCH ON EQUITY AND SUSTAINED PARTICIPATION IN ENGINEERING, COMPUTING, AND TECHNOLOGY (RESPECT), pp. 157–161. https://doi.org/10.1109/RESPECT51740.2021.9620700

Milliken, A., Catete, V., Limke, A., Gransbury, I., Chipman, H., Dong, Y., & Barnes, T. (2021). Exploring and Influencing Teacher Grading for Block-based Programs through Rubrics and the GradeSnap Tool. ICER 2021: PROCEEDINGS OF THE 17TH ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH, pp. 101–114. https://doi.org/10.1145/3446871.3469762

Isvik, A., Catete, V., Bell, D., Gransbury, I., & Barnes, T. (2021). Infusing Computing: Moving a Service Oriented Internship Program Online. IEEE STCBP RESPECT CONFERENCE: 2021 RESEARCH ON EQUITY AND SUSTAINED PARTICIPATION IN ENGINEERING, COMPUTING, AND TECHNOLOGY (RESPECT), pp. 199–203. https://doi.org/10.1109/RESPECT51740.2021.9620644

Zhou, G., Azizsoltani, H., Ausin, M. S., Barnes, T., & Chi, M. (2021, August 16). Leveraging Granularity: Hierarchical Reinforcement Learning for Pedagogical Policy Induction. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, Vol. 8. https://doi.org/10.1007/s40593-021-00269-9

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

Broll, B., Ledeczi, A., Stein, G., Jean, D., Brady, C., Grover, S., … Barnes, T. (2021). Removing the Walls Around Visual Educational Programming Environments. 2021 IEEE SYMPOSIUM ON VISUAL LANGUAGES AND HUMAN-CENTRIC COMPUTING (VL/HCC 2021). https://doi.org/10.1109/VL/HCC51201.2021.9576399

Ausin, M. S., Maniktala, M., Barnes, T., & Chi, M. (2021). Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2021), PT I, Vol. 12748, pp. 356–368. https://doi.org/10.1007/978-3-030-78292-4_29

Cody, C., Maniktala, M., Lytle, N., Chi, M., & Barnes, T. (2021, May 21). The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION. https://doi.org/10.1007/s40593-021-00237-3

Dong, Y., Shabrina, P., Marwan, S., & Barnes, T. (2021). You Really Need Help: Exploring Expert Reasons for Intervention During Block-based Programming Assignments. ICER 2021: PROCEEDINGS OF THE 17TH ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH, pp. 334–346. https://doi.org/10.1145/3446871.3469764

Maniktala, M., Cody, C., Barnes, T., & Chi, M. (2020). Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 30(4), 637–667. https://doi.org/10.1007/s40593-020-00213-3

Barnes, T., Payton, J., Washington, N., Stukes, F., Peterfreund, A., & Dunton, S. (2020). Featured Research on Equity and Sustained Participation in Engineering, Computing, and Technology. COMPUTING IN SCIENCE & ENGINEERING, Vol. 22, pp. 4–6. https://doi.org/10.1109/MCSE.2020.3010595

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

Price, T. W., Dong, Y., Zhi, R., Paaßen, B., Lytle, N., Cateté, V., & Barnes, T. (2019). A Comparison of the Quality of Data-Driven Programming Hint Generation Algorithms. International Journal of Artificial Intelligence in Education, 29(3), 368–395. https://doi.org/10.1007/s40593-019-00177-z

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

Lytle, N., Cateté, V., Dong, Y., Boulden, D., Akram, B., Houchins, J., … Wiebe, E. (2019). CEO: A Triangulated Evaluation of a Modeling-Based CT-Infused CS Activity for Non-CS Middle Grade Students. Proceedings of the ACM Conference on Global Computing Education  - CompEd '19, 58–64. https://doi.org/10.1145/3300115.3309527

Dong, Y., Marwan, S., Catete, V., Price, T., & Barnes, T. (2019). Defining Tinkering Behavior in Open-ended Block-based Programming Assignments. Proceedings of the 50th ACM Technical Symposium on Computer Science Education  - SIGCSE '19, 1204–1210. https://doi.org/10.1145/3287324.3287437

Milliken, A., Cody, C., Catete, V., & Barnes, T. (2019). Effective Computer Science Teacher Professional Development. Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education  - ITiCSE '19, 271–277. https://doi.org/10.1145/3304221.3319779

Lytle, N., Floryan, M., & Barnes, T. (2019). Effects of a Pathfinding Program Visualization on Algorithm Development. Proceedings of the 50th ACM Technical Symposium on Computer Science Education - SIGCSE '19. Presented at the the 50th ACM Technical Symposium. https://doi.org/10.1145/3287324.3287391

Zhi, R., Chi, M., Barnes, T., & Price, T. W. (2019). Evaluating the Effectiveness of Parsons Problems for Block-based Programming. Proceedings of the 2019 ACM Conference on International Computing Education Research  - ICER '19, 51–59. https://doi.org/10.1145/3291279.3339419

Zhi, R., Price, T. W., Marwan, S., Milliken, A., Barnes, T., & Chi, M. (2019). Exploring the Impact of Worked Examples in a Novice Programming Environment. Proceedings of the 50th ACM Technical Symposium on Computer Science Education  - SIGCSE '19, 98–104. https://doi.org/10.1145/3287324.3287385

Zhou, G., Azizsoltani, H., Ausin, M. S., Barnes, T., & Chi, M. (2019). Hierarchical Reinforcement Learning for Pedagogical Policy Induction. ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2019), PT I, Vol. 11625, pp. 544–556. https://doi.org/10.1007/978-3-030-23204-7_45

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

Dong, Y., Andrews, A., Cateté, V., Lytle, N., Isvik, A., Barnes, T., … Robinson, R. (2019). Infusing Computing. Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education  - ITiCSE '19, 278–284. https://doi.org/10.1145/3304221.3319772

Jocius, R., Albert, J., Andrews, A., Catete, V., Dong, Y., Joshi, D., … Lytle, N. (2019). Infusing Computing Through Professional Development: Shifts in Content Area Teachers' Understandings of Computational Thinking Integration. Proceedings of Society for Information Technology & Teacher Education International Conference, 302–305. Las Vegas, NV, United States: Association for the Advancement of Computing in Education (AACE).

Mao, Y., Zhi, R., Khoshnevisan, F., Price, T. W., Barnes, T., & Chi, M. (2019). One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks. In C. F. Lynch, A. Merceron, M. Desmarais, & R. Nkambou (Eds.), Proceedings of the 12th International Conference on Educational Data Mining (pp. 119–128).

Dong, Y., Catete, V., Jocius, R., Lytle, N., Barnes, T., Albert, J., … Andrews, A. (2019). PRADA. Proceedings of the 50th ACM Technical Symposium on Computer Science Education - SIGCSE '19, 906–912. https://doi.org/10.1145/3287324.3287431

Washington, N., Barnes, T., Payton, J., Dunton, S., Stukes, F., & Peterfreund, A. (2019). RESPECT 2019: Yes, We Still Need to Talk About Diversity in Computing. COMPUTING IN SCIENCE & ENGINEERING, Vol. 21, pp. 79–83. https://doi.org/10.1109/MCSE.2018.2887008

Zhi, R., Marwan, S., Dong, Y., Lytle, N., Price, T. W., & Barnes, T. (2019). Toward Data-Driven Example Feedback for Novice Programming. Proceedings of the 12th International Conference on Educational Data Mining. Presented at the International Educational Data Mining Society, Montreal, Canada.

Lytle, N., Barnes, T., Cateté, V., Boulden, D., Dong, Y., Houchins, J., … Wiebe, E. (2019). Use, Modify, Create. Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education  - ITiCSE '19, 395–401. https://doi.org/10.1145/3304221.3319786

Cateté, V., Lytle, N., & Barnes, T. (2018). Creation and validation of low-stakes rubrics for K-12 computer science. Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education  - ITiCSE 2018, 63–68. https://doi.org/10.1145/3197091.3197134

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

Sirbu, M.-D., Dascalu, M., Crossley, S. A., McNamara, D. S., Barnes, T., Lynch, C. F., & Trausan-Matu, S. (2018). Exploring Online Course Sociograms Using Cohesion Network Analysis. In Lecture Notes in Computer Science (pp. 337–342). https://doi.org/10.1007/978-3-319-93846-2_63

Catete, V., Lytle, N., Dong, Y., Boulden, D., Akram, B., Houchins, J., … Boyer, K. (2018). Infusing Computational Thinking into Middle Grade Science Classrooms: Lessons Learned. WIPSCE'18: PROCEEDINGS OF THE 13TH WORKSHOP IN PRIMARY AND SECONDARY COMPUTING EDUCATION, pp. 109–114. https://doi.org/10.1145/3265757.3265778

Cody, C., Mostafavi, B., & Barnes, T. (2018). Investigation of the Influence of Hint Type on Problem Solving Behavior in a Logic Proof Tutor. In Lecture Notes in Computer Science (pp. 58–62). https://doi.org/10.1007/978-3-319-93846-2_11

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

Zhi, R., Price, T. W., Lytle, N., Dong, Y., & Barnes, T. (2018). Reducing the State Space of Programming Problems through Data-Driven Feature Detection. Education Data Mining Workshop.

Paaßen, B., Hammer, B., Price, T. W., Barnes, T., Gross, S., & Pinkwart, N. (2018). The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces. Journal of Educational Data Mining, 10(1), 1–35. Retrieved from https://doi.org/10.5281/zenodo.3554697

Price, T. W., Zhi, R., Dong, Y., Lytle, N., & Barnes, T. (2018). The Impact of Data Quantity and Source on the Quality of Data-Driven Hints for Programming. In Lecture Notes in Computer Science (pp. 476–490). https://doi.org/10.1007/978-3-319-93843-1_35

Cateté, V., & Barnes, T. (2017). Application of the Delphi Method in Computer Science Principles Rubric Creation. Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education - ITiCSE '17, Part F128680, 164–169. https://doi.org/10.1145/3059009.3059042

Rowe, E., Asbell-Clarke, J., Baker, R. S., Eagle, M., Hicks, A. G., Barnes, T. M., … Edwards, T. (2017). Assessing implicit science learning in digital games. COMPUTERS IN HUMAN BEHAVIOR, 76, 617–630. https://doi.org/10.1016/j.chb.2017.03.043

Price, T., Zhi, R., & Barnes, T. (2017). Evaluation of a Data-driven Feedback Algorithm for Open-ended Programming. Educational Data Mining (EDM2017). Presented at the International Conference on Educational Data Mining (EDM), Wuhan, China.

Dong, Y., & Barnes, T. (2017). Evaluation of a Template-based Puzzle Generator for an Educational Programming Game. PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON THE FOUNDATIONS OF DIGITAL GAMES (FDG'17). https://doi.org/10.1145/3102071.3106347

Mostafavi, B., & Barnes, T. (2017). Evolution of an Intelligent Deductive Logic Tutor Using Data-Driven Elements. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 27(1), 5–36. https://doi.org/10.1007/s40593-016-0112-1

Price, T. W., Liu, Z., Catete, V., & Barnes, T. (2017). Factors Influencing Students' Help-Seeking Behavior while Programming with Human and Computer Tutors. PROCEEDINGS OF THE 2017 ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH (ICER 17), pp. 127–135. https://doi.org/10.1145/3105726.3106179

Price, T. W., Zhi, R., & Barnes, T. (2017). Hint Generation Under Uncertainty: The Effect of Hint Quality on Help-Seeking Behavior. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2017, Vol. 10331, pp. 311–322. https://doi.org/10.1007/978-3-319-61425-0_26

Price, T., & Barnes, T. (2017). Position paper: Block-based programming should offer intelligent support for learners. 2017 IEEE Blocks and Beyond Workshop (B&B), 65–68. https://doi.org/10.1109/blocks.2017.8120414

Barnes, T., Boyer, K., Hsiao, S. I.-H., Le, N.-T., & Sosnovsky, S. (2017). Preface for the Special Issue on AI-Supported Education in Computer Science. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 27(1), 1–4. https://doi.org/10.1007/s40593-016-0123-y

Liu, Z., Cody, C., Barnes, T., Lynch, C., & Rutherford, T. (2017). The Antecedents of and Associations with Elective Replay in An Educational Game: Is Replay Worth It? Educational Data Mining (EDM2017). Presented at the International Conference on Educational Data Mining (EDM), Wuhan, China.

Liu, Z., Zhi, R., Hicks, A., & Barnes, T. (2017). Understanding problem solving behavior of 6-8 graders in a debugging game. COMPUTER SCIENCE EDUCATION, 27(1), 1–29. https://doi.org/10.1080/08993408.2017.1308651

Peddycord-Liu, Z., Cody, C., Kessler, S., Barnes, T., Lynch, C. F., & Rutherford, T. (2017). Using Serious Game Analytics to Inform Digital Curricular Sequencing. Proceedings of the Annual Symposium on Computer-Human Interaction in Play - CHI PLAY '17. Presented at the the Annual Symposium. https://doi.org/10.1145/3116595.3116620

Price, T., Dong, Y., & Lipovac, D. (2017). iSnap: Towards Intelligent Tutoring in Novice Programming Environments. SIGCSE '17: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 483–488. https://doi.org/10.1145/3017680.3017762

Shen, S. T., Lin, C., Mostafavi, B., Barnes, T., & Chi, M. (2016). An analysis of feature selection and reward function for model-based reinforcement learning. Intelligent tutoring systems, its 2016, 0684, 504–505.

Barnes, T., Payton, J., Thiruvathukal, G. K., Boyer, K. E., & Forbes, J. (2016). Best of RESPECT, Part 1. Computing in Science & Engineering, 18(2), 6–8.

Barnes, T., Payton, J., Thiruvathukal, G. K., Boyer, K. E., & Forbes, J. (2016). Best of RESPECT, Part 2. COMPUTING IN SCIENCE & ENGINEERING, Vol. 18, pp. 11–13. https://doi.org/10.1109/mcse.2016.51

Liu, Z., Mostafavi, B., & Barnes, T. (2016). Combining Worked Examples and Problem Solving in a Data-Driven Logic Tutor. INTELLIGENT TUTORING SYSTEMS, ITS 2016, Vol. 9684, pp. 347–353. https://doi.org/10.1007/978-3-319-39583-8_40

Eagle, M., Mostafavi, B., & Barnes, T. (2016). Data-driven Domain Models for Problem Solving. In R. Sottilare, A. Graesser, X. Hu, A. Olney, B. Nye, & A. Sinatra (Eds.), Design Recommendations for Intelligent Tutoring Systems: Domain Modeling (Vol. 4). Orlando, Florida: Army Research Laboratory.

Mostafavi, B., & Barnes, T. (2016). Data-driven Proficiency Profiling - Proof of Concept. LAK '16 CONFERENCE PROCEEDINGS: THE SIXTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE, pp. 324–328. https://doi.org/10.1145/2883851.2883935

Cateté, V., Snider, E., & Barnes, T. (2016). Developing a Rubric for a Creative CS Principles Lab. Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education - ITiCSE '16, 11-13-July-2016, 290–295. https://doi.org/10.1145/2899415.2899449

Price, T. W., Brown, N. C. C., Lipovac, D., Barnes, T., & Kolling, M. (2016). Evaluation of a Frame-based Programming Editor. PROCEEDINGS OF THE 2016 ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH (ICER'16), pp. 33–42. https://doi.org/10.1145/2960310.2960319

Mostafavi, B., & Barnes, T. (2016). Exploring the Impact of Data-driven Tutoring Methods on Students' Demonstrative Knowledge in Logic Problem Solving Educational Data Mining (EDM2016). Educational Data Mining, 460–465.

Price, T., Dong, Y., & Barnes, T. (2016). Generating Data-driven Hints for Open-ended Programming. Educational Data Mining, 191–198.

Payton, J., & Barnes, T. (2016). Learn about broadening participation. ACM SIGCSE Bulletin, 48(3), 5–5. https://doi.org/10.1145/2993223.2993226

Price, T. W., Cateté, V., Albert, J., Barnes, T., & Garcia, D. D. (2016). Lessons Learned from "BJC" CS Principles Professional Development. Proceedings of the 47th ACM Technical Symposium on Computing Science Education - SIGCSE '16, 467–472. https://doi.org/10.1145/2839509.2844625

Liu, Z., Brown, R., Lynch, C., Barnes, T., Baker, R., Bergner, Y., & Mcnamara, D. (2016). MOOC Learning by Country and Culture; an Exploratory Analysis. Educational Data Mining, EDM2016, 127–134.

Hicks, D., Liu, Z., Eagle, M., & Barnes, T. (2016). Measuring Gameplay Affordances of User-Generated Content in and Educational Game. Presented at the International Conference on Educational Data Mining (EDM), Raleigh, North Carolina.

Payton, J., Barnes, T., Buch, K., Rorrer, A., Zuo, H. F., & Naolu, B. (2016). Promoting computing faculty success through interinstitutional faculty learning communities. 2016 Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT 2016). https://doi.org/10.1109/respect.2016.7836163

Payton, J., Barnes, T., Buch, K., Rorrer, A., Zuo, H., Gosha, K., … Dennis, L. (2016). STARS Computing Corps: Enhancing Engagement of Underrepresented Students and Building Community in Computing. COMPUTING IN SCIENCE & ENGINEERING, 18(3), 44–57. https://doi.org/10.1109/mcse.2016.42

Zhou, G., Lynch, C., Price, T., Barnes, T., & Chi, M. (2016). The Impact of Granularity on the Effectiveness of Students' Pedagogical Decision. Presented at the Annual Meeting of the Cognitive Science Society (CogSci).

Barnes, T., & Thiruvathukal, G. K. (2016, March). The Need for Research in Broadening Participation. COMMUNICATIONS OF THE ACM, Vol. 59, pp. 33–34. https://doi.org/10.1145/2880177

Hicks, D., Eagle, M., Rowe, E., Asbell-Clarke, J., Edwards, T., & Barnes, T. (2016). Using Game Analytics to Evaluate Puzzle Design and Level Progression in a Serious Game. LAK '16 CONFERENCE PROCEEDINGS: THE SIXTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE, pp. 440–448. https://doi.org/10.1145/2883851.2883953

Rowe, E., Asbell-Clarke, J., Hicks, M. E. A., Barnes, T., Brown, R., & Edwards, T. (2016). Validating Game-based Measures of Implicit Science Learning. Educational Data Mining, 490–495.

Hicks, A., Zhi, R., Dong, Y., & Barnes, T. (2015). Applying Deep Gamification Principles to Improve Quality of User-Designed Levels. Presented at the 11th Annual Games+Learning+Society Conference (GLS 15).

Price, T. W., Albert, J., Catete, V., & Barnes, T. (2015). BJC in action: Comparison of student perceptions of a computer science principles course. 2015 Research in Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT), 1–4. https://doi.org/10.1109/respect.2015.7296506

Liu, Z., & Barnes, T. (2015). Building Compiler-Student Friendship. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 844–847. https://doi.org/10.1007/978-3-319-19773-9_129

Price, T. W., & Barnes, T. (2015). Comparing Textual and Block Interfaces in a Novice Programming Environment. Proceedings of the eleventh annual International Conference on International Computing Education Research - ICER '15, 91–99. https://doi.org/10.1145/2787622.2787712

Price, T. W., & Barnes, T. (2015). Creating Data-Driven Feedback for Novices in Goal-Driven Programming Projects. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 856–859. https://doi.org/10.1007/978-3-319-19773-9_132

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., Liu, Z., & Barnes, T. (2015). Data-driven Proficiency Profiling. Educational Data Mining, 335–341.

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.

Eagle, M., & Barnes, T. (2015). Exploring Missing Behaviors with Region-Level Interaction Network Coverage. ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, Vol. 9112, pp. 831–835. https://doi.org/10.1007/978-3-319-19773-9_126

Eagle, M., Hicks, D., Peddycord, B., III, & Barnes, T. (2015). Exploring networks of problem-solving interactions. Proceedings of the Fifth International Conference on Learning Analytics And Knowledge - LAK '15. Presented at the the Fifth International Conference. https://doi.org/10.1145/2723576.2723630

Barnes, T., Payton, J., & Guzdial, M. (2015). Highlights of broadening participation research at RESPECTS '15. SIGCSE Bulletin, 47(4), 3. https://doi.org/10.1145/2856332.2856334

Eagle, M., Hicks, A., & Barnes, T. (2015). Interaction Network Estimation: Predicting the Size and Coverage for Networks of Student-Tutor Transactions. 8th International Conference on Educational Data Mining, 342–349.

Crossley, S. A., McNamara, D. S., Baker, R. S., Wang, Y., Paquette, L., Barnes, T., & Bergner, Y. (2015). Language to Completion: Success in an Educational Data Mining Massive Open Online Class. 8th International Conference on Educational Data Mining, 388–391.

Eagle, M., Rowe, E., Hicks, D., Brown, R., Barnes, T., Asbell-Clarke, J., & Edwards, T. (2015). Measuring Implicit Science Learning with Networks of Player-Game Interactions. Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play - CHI PLAY '15. Presented at the the 2015 Annual Symposium. https://doi.org/10.1145/2793107.2810330

Barnes, T., Castaneda, S., Forbes, J., Gates, A., Guzdial, M., Ladner, R., … Seals, C. (2015). Panel: BPC fireside chat. 2015 Research in Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT). https://doi.org/10.1109/respect.2015.7296491

Barnes, T., Bown, O., Buro, M., Cook, M., Eigenfeldt, A., Munoz-Avila, H., … Zook, A. (2015). Reports of the Workshops Held at the Tenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE). AI MAGAZINE, 36(1), 99–102. https://doi.org/10.1609/aimag.v36i1.2576

Barnes, T. (2015). SIGCSE BP. ACM SIGCSE Bulletin, 47(3), 8–8. https://doi.org/10.1145/2822363.2822369

Kaczmarczyk, L., & Barnes, T. (2015). SIGCSE BP: Enrollments and Diversity at Odds? ACM SIGCSE Bulletin, 47(2), 8. https://doi.org/10.1145/2782744.2782750

Payton, J., Barnes, T., Buch, K., Rorrer, A., & Zuo, H. F. (2015). STARS computing corps: Enhancing engagement of women and underrepresented students in computing. 2015 Research in Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT). https://doi.org/10.1109/respect.2015.7296495

Zhou, G., Price, T., Lynch, C., Barnes, T., & Chi, M. (2015). The Impact of Granularity on Worked Examples and Problem Solving. Presented at the 37th Annual Cognitive Science Society Meeting (CogSci 2015).

Garcia, D., Harvey, B., & Barnes, T. (2015). The beauty and joy of computing. ACM Inroads, 6(4), 71–79. https://doi.org/10.1145/2835184

Payton, J., Barnes, T., Buch, K., Rorrer, A., & Zuo, H. (2015). The effects of integrating service learning into computer science: an inter-institutional longitudinal study. Computer Science Education, 25(3), 311–324. https://doi.org/10.1080/08993408.2015.1086536

Mostafavi, B., Eagle, M., & Barnes, T. (2015). Towards data-driven mastery learning. Proceedings of the Fifth International Conference on Learning Analytics And Knowledge - LAK '15. Presented at the the Fifth International Conference. https://doi.org/10.1145/2723576.2723622

Eagle, M., Rowe, E., Brown, R., Asbell-Clarke, J., Hicks, A., Barnes, T., & Edwards, T. (2015). Visualization of Play: Graph-based analytics for measuring implicit science learning. Presented at the Second ACM SIGCHI annual symposium on Computer-human interaction in play (CHI PLAY).

Nickel, A., Barnes, T., Payton, J., & Wikstrom, E. (2014, April 3). Balancing physical and cognitive challenge: A study of players psychological responses to exergame play. Presented at the Foundations of Digital Games, Fort Lauderdale, FL.

Hicks, A., Peddycord, B., & Barnes, T. (2014). Building games to learn from their players: Generating hints in a serious game. Intelligent tutoring systems, its 2014, 8474, 312–317. https://doi.org/10.1007/978-3-319-07221-0_39

Mostafavi, B., & Barnes, T. (2014). Evaluation of Logic Proof Problem Difficulty Through Student Performance Data. In S. Gutierrez-Santos & O. C (Eds.), EDM 2014 Extended Proceedings: Workshop Proceedings of the 7th International Conference on Educational Data Mining. London, United Kingdom: CEUR-WS.

Eagle, M., Polamreddi, V., Mostafavi, B., & Barnes, T. (2014). Exploration of student's use of rule application references in a propositional logic tutor. Educational Data Mining, 249–252.

Eagle, M., & Barnes, T. (2014). Exploring differences in problem solving with data-driven approach maps. Educational Data Mining, 76–83.

Peters, J., Jauhari, S., & Barnes, T. (2014). Extracting temporal features using BCIpy. Proceedings of the Workshop on Utilizing EEG Input in Intelligent Tutoring Systems. Presented at the Intelligent Tutoring Systems (ITS2014), Honolulu, Hawaii.

Peddycord, B., III, Hicks, A., & Barnes, T. (2014). Generating hints for programming problems using intermediate output. Educational Data Mining, 92–98.

Sheshadri, V., Lynch, C., & Barnes, T. (2014). InVis: An EDM Tool for Graphical Rendering and Analysis of Student Interaction Data. In S. Gutierrez-Santos & O. C. Santos (Eds.), EDM 2014 Extended Proceedings: Workshop Proceedings of the 7th International Conference on Educational Data Mining. London, United Kingdom: CEUR-WS.

Barnes, T., Catete, V., Hicks, A., & Peddycord, B. (2014). Making games and apps in introductory computer science (abstract only). Proceedings of the 45th ACM technical symposium on Computer science education - SIGCSE '14, 739–739. https://doi.org/10.1145/2538862.2539000

Eagle, M., & Barnes, T. (2014). Modeling student dropout in tutoring systems. Intelligent tutoring systems, its 2014, 8474, 676–678. https://doi.org/10.1007/978-3-319-07221-0_104

Hicks, A., Cateté, V., & Barnes, T. (2014, April 3). Part of the game: Changing level creation to identify and filter low quality user-generated levels. Presented at the Foundations of Digital Games (FDG2014), Fort Lauderdale, FL.

Burns, R., Eugene, W., Barnes, T., Chandler, S., Harwell, M., & Omokaro, O. (2014). Reflections from a computational service learning trip to Haiti. The Journal of Computing Sciences in Colleges, 29(3), 43–50. https://doi.org/10.5555/2544322.2544331

Cateté, V., Hicks, A., Barnes, T., & Lynch, C. (2014). Snag'em: Graph Data Mining for a Social Networking Game. In S. Gutierrez-Santos & O. C. Santos (Eds.), EDM 2014 Extended Proceedings: Workshop Proceedings of the 7th International Conference on Educational Data Mining. London, United Kingdom: CEUR-WS.

Eagle, M., & Barnes, T. (2014). Survival analysis on duration data in intelligent tutors. Intelligent tutoring systems, its 2014, 8474, 178–187. https://doi.org/10.1007/978-3-319-07221-0_22

Cateté, V., Wassell, K., & Barnes, T. (2014). Use and development of entertainment technologies in after school STEM program. SIGCSE '14: Proceedings of the 45th ACM technical symposium on Computer science education, 163–168. https://doi.org/10.1145/2538862.2538952

Johnson, M., Eagle, M., Barnes, T., & Stamper, J. (2013). An Algorithm for Reducing the Complexity of Interaction Networks. Educational Data Mining, 248–251.

Eugene, W., Daily, S., Burns, R., & Barnes, T. (2013). Building Technology Fluency: Fostering Agents of Change. Presented at the 120th ASEE Conference (ASEE 2013), Atlanta, GA. https://doi.org/10.18260/1-2--19275

Mostafavi, B., & Barnes, T. (2013). Determining problem selection for a logic proof tutor. Educational Data Mining, 387–389.

Shannon, A., Boyce, A., Gadwal, C., & Barnes, T. (2013). Effective Practices in Game Tutorial Systems. 8th ACM Foundations of Digital Games, 338–345.

Eagle, M., & Barnes, T. (2013). Evaluation of automatically generated hint feedback. Educational Data Mining, 372–374.

Finkelstein, S., Barnes, T., Wartell, Z., & Suma, E. (2013). Evaluation of the Exertion and Motivation Factors of a Virtual Reality Exercise Game for Children with Autism. 2013 1st Workshop on Virtual and Augmented Assistive Technology (VAAT). Presented at the 2013 1st Workshop on Virtual and Augmented Assistive Technology (VAAT), Lake Buena Vista, Florida, USA. https://doi.org/10.1109/VAAT.2013.6786186

Stamper, J., Eagle, M., Barnes, T., & Croy, M. (2013). Experimental Evaluation of Automatic Hint Generation for a Logic Tutor. International Journal of Artificial Intelligence in Education (IJAIED), 22(1-2), 3–17.

Eagle, M., Johnson, M., Barnes, T., & Boyce, A. (2013). Exploring Player Behavior with Visual Analytics. 8th ACM Foundations of Digital Games, 380–383.

Goldin, I. M., Martin, T., Baker, R., Aleven, V., & Barnes, T. (2013). Formative Feedback in Interactive Learning Environments. In Lecture Notes in Computer Science (pp. 946–946). https://doi.org/10.1007/978-3-642-39112-5_158

Johnson, M., Eagle, M., & Barnes, T. (2013). InVis: An Interactive Visualization Tool for Exploring Interaction Networks Educational Data Mining. Proceedings of the 6th International Conference on Educational Data Mining (EDM 2013), 82–89.

Eugene, W., Barnes, T., & Wilson, J. (2013). Math Fluency through Game Design. In Design, User Experience, and Usability. Health, Learning, Playing, Cultural, and Cross-Cultural User Experience (pp. 189–198). https://doi.org/10.1007/978-3-642-39241-2_22

Eagle, M. J., & Barnes, T. (2012). A learning objective focused methodology for the design and evaluation of game-based tutors. Proceedings of the 43rd ACM technical symposium on Computer Science Education - SIGCSE '12. Presented at the the 43rd ACM technical symposium. https://doi.org/10.1145/2157136.2157170

Doran, K., Boyce, A., Hicks, A., Payton, J., & Barnes, T. (2012). Creation of a game-based digital layer for increased museum engagement among digital natives. 2012 Second International Workshop on Games and Software Engineering: Realizing User Engagement with Game Engineering Techniques (GAS). Presented at the 2012 2nd International Workshop on Games and Software Engineering (GAS). https://doi.org/10.1109/gas.2012.6225924

Eagle, M. J., & Barnes, T. (2012). Data-Driven Method for Assessing Skill-Opportunity Recognition in Open Procedural Problem Solving Environments. In Intelligent Tutoring Systems (pp. 615–617). https://doi.org/10.1007/978-3-642-30950-2_88

Eagle, M., Johnson, M., & Barnes, T. (2012). Interaction networks: generating high level hints based on network community clusterings. Proceedings of the 5th International Conference on Educational Data Mining (EDM 2012), 164–167. Chania, Greece.

Nickel, A., Kinsey, H., Haack, H., Pendergrass, M., & Barnes, T. (2012). Interval training with Astrojumper. 2012 IEEE Virtual Reality (VR). Presented at the 2012 IEEE Virtual Reality (VR). https://doi.org/10.1109/vr.2012.6180931

Johnson, M. W., Okimoto, T., & Barnes, T. (2012). Leveraging Game Design to Promote Effective User Behavior of Intelligent Tutoring Systems. In Intelligent Tutoring Systems (pp. 597–599). https://doi.org/10.1007/978-3-642-30950-2_82

Boyce, A., Campbell, A., Pickford, S., Culler, D., & Barnes, T. (2012). Maximizing learning and guiding behavior in free play user generated content environments. Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education - ITiCSE '12. Presented at the the 17th ACM annual conference. https://doi.org/10.1145/2325296.2325303

Doran, K., Boyce, A., Finkelstein, S., & Barnes, T. (2012). Outreach for improved student performance. Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education - ITiCSE '12. Presented at the the 17th ACM annual conference. https://doi.org/10.1145/2325296.2325348

Jin, W., Barnes, T., Stamper, J., Eagle, M. J., Johnson, M. W., & Lehmann, L. (2012). Program Representation for Automatic Hint Generation for a Data-Driven Novice Programming Tutor. In Intelligent Tutoring Systems (pp. 304–309). https://doi.org/10.1007/978-3-642-30950-2_40

Nickel, A., Kinsey, H., Barnes, T., & Wartell, Z. (2012). Supporting an Interval Training Program with the Astrojumper Video Game. Electronic Proceedings of Meaningful Play 2012. Presented at the Meaningful Play 2012, East Lansing, MI, USA. Retrieved from https://meaningfulplay.msu.edu/proceedings2012/mp2012_submission_118.pdf

Powell, E., Brinkman, R., Barnes, T., & Catete, V. (2012). Table tilt. Proceedings of the International Conference on the Foundations of Digital Games - FDG '12, 242–245. https://doi.org/10.1145/2282338.2282386

Lehmann, L., Wilson, D.-M., & Barnes, T. (2012). Using Individualized Feedback and Guided Instruction via a Virtual Human Agent in an Introductory Computer Programming Course. In Intelligent Tutoring Systems (pp. 612–614). https://doi.org/10.1007/978-3-642-30950-2_87

Finkelstein, S. L., Nickel, A., Lipps, Z., Barnes, T., Wartell, Z., & Suma, E. A. (2011). Astrojumper: Motivating Exercise with an Immersive Virtual Reality Exergame. Presence: Teleoperators and Virtual Environments, 20(1), 78–92. https://doi.org/10.1162/pres_a_00036

Mostafavi, B., Barnes, T., & Croy, M. (2011). Automatic Generation of Proof Problems in Deductive Logic. Proceedings of the 4th International Conference on Educational Data Mining (EDM 2011), 289–294. Eindhoven, Netherlands.

Boyce, A., Doran, K., Campbell, A., Pickford, S., Culler, D., & Barnes, T. (2011). BeadLoom Game. Proceedings of the 6th International Conference on Foundations of Digital Games - FDG '11. Presented at the the 6th International Conference. https://doi.org/10.1145/2159365.2159384

Stamper, J., Barnes, T., & Croy, M. (2011). Enhancing the Automatic Generation of Hints with Expert Seeding. International Journal of Artificial Intelligence in Education, 21(1-2), 153–167.

Stamper, J. C., Eagle, M., Barnes, T., & Croy, M. (2011). Experimental Evaluation of Automatic Hint Generation for a Logic Tutor. In Lecture Notes in Computer Science (pp. 345–352). https://doi.org/10.1007/978-3-642-21869-9_45

Boyce, A. K., Campbell, A., Pickford, S., Culler, D., & Barnes, T. (2011). Experimental evaluation of BeadLoom game. Proceedings of the 16th annual joint conference on Innovation and technology in computer science education - ITiCSE '11. Presented at the the 16th annual joint conference. https://doi.org/10.1145/1999747.1999816

Payton, J., Powell, E., Nickel, A., Doran, K., & Barnes, T. (2011). GameChanger. Proceeding of the 1st international workshop on Games and software engineering - GAS '11. Presented at the Proceeding of the 1st international workshop. https://doi.org/10.1145/1984674.1984688

Babu, S. V., Suma, E., Hodges, L. F., & Barnes, T. (2011). Learning Cultural Conversational Protocols with Immersive Interactive Virtual Humans. International Journal of Virtual Reality, 10(4), 25–35. https://doi.org/10.20870/ijvr.2011.10.4.2826

McCrickard, D. S., Townsend, D. M., Winchester, W. W., & Barnes, T. (2011). Leveraging Card-Based Collaborative Activities as Culturally Situated Design Tools. In Communications in Computer and Information Science (pp. 232–236). https://doi.org/10.1007/978-3-642-22098-2_47

Powell, E., Stukes, F., Barnes, T., & Lipford, H. R. (2011). Snag'em: Creating Community Connections through Games. 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing. Presented at the 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust (PASSAT) / 2011 IEEE Third Int'l Conference on Social Computing (SocialCom). https://doi.org/10.1109/passat/socialcom.2011.229

Boyce, A., Doran, K., Campbell, A., Pickford, S., Culler, D., & Barnes, T. (2011). Social user generated content's effect on creativity in educational games. Proceedings of the 8th ACM conference on Creativity and cognition - C&C '11. Presented at the the 8th ACM conference. https://doi.org/10.1145/2069618.2069675

Johnson, M., Eagle, M., Joseph, L., & Barnes, T. (2011). The EDM Vis Tool. Electronic Data Mining, 349–350.

Dahlberg, T., Barnes, T., Buch, K., & Rorrer, A. (2011). The STARS Alliance. ACM Transactions on Computing Education, 11(3), 1–25. https://doi.org/10.1145/2037276.2037282

Dahlberg, T., Barnes, T., Buch, K., & Bean, K. (2010). Applying service learning to computer science: attracting and engaging under-represented students. Computer Science Education, 20(3), 169–180. https://doi.org/10.1080/08993408.2010.492164

Finkelstein, S., Nickel, A., Barnes, T., & Suma, E. A. (2010). Astrojumper: motivating children with autism to exercise using a VR game. Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems - CHI EA '10. Presented at the the 28th of the international conference extended abstracts. https://doi.org/10.1145/1753846.1754124

Barnes, T., & Stamper, J. (2010). Automatic hint generation for logic proof tutoring using historical data. Journal of Educational Technology & Society, 13(1), 3–12.

Boyce, A., & Barnes, T. (2010). BeadLoom Game: using game elements to increase motivation and learning. Proceedings of the Fifth International Conference on the Foundations of Digital Games (FDG '10), 25–31. https://doi.org/10.1145/1822348.1822352

Stamper, J., Barnes, T., & Croy, M. (2010). Enhancing the Automatic Generation of Hints with Expert Seeding. In Intelligent Tutoring Systems (pp. 31–40). https://doi.org/10.1007/978-3-642-13437-1_4

Eagle, M., & Barnes, T. (2010). Intelligent Tutoring Systems, Educational Data Mining, and the Design and Evaluation of Video Games. In Intelligent Tutoring Systems (pp. 215–217). https://doi.org/10.1007/978-3-642-13437-1_23

Chaffin, A., & Barnes, T. (2010). Lessons from a course on serious games research and prototyping. Proceedings of the Fifth International Conference on the Foundations of Digital Games - FDG '10. Presented at the the Fifth International Conference. https://doi.org/10.1145/1822348.1822353

Barnes, T. (2010). Novel Derivation and Application of Skill Matrices. In Handbook of Educational Data Mining (pp. 159–172). https://doi.org/10.1201/b10274-14

Powell, E. M., Finkelstein, S., Hicks, A., Phifer, T., Charugulla, S., Thornton, C., … Dahlberg, T. (2010). SNAG: social networking games to facilitate interaction. Extended abstracts on Human factors in computing systems - (CHI EA '10), 4249–4254. https://doi.org/10.1145/1753846.1754134

Finkelstein, S. L., Powell, E., Hicks, A., Doran, K., Charugulla, S. R., & Barnes, T. (2010). SNAG: using social networking games to increase student retention in computer science. Proceedings of the fifteenth annual conference on Innovation and technology in computer science education - ITiCSE '10, 142–146. https://doi.org/10.1145/1822090.1822131

Mostafavi, B., & Barnes, T. (2010). Towards the Creation of a Data-Driven Programming Tutor. In Intelligent Tutoring Systems (pp. 239–241). https://doi.org/10.1007/978-3-642-13437-1_31

Barnes, T., Stamper, J., & Croy, M. (2010). Using Markov Decision Processes for Automatic Hint. In Handbook of Educational Data Mining (pp. 467–480). https://doi.org/10.1201/b10274-36

Johnson, M., & Barnes, T. (2010). Visualizing Educational Data from Logic Tutors. In Intelligent Tutoring Systems (pp. 233–235). https://doi.org/10.1007/978-3-642-13437-1_29

Barnes, T., Dahlberg, T., Buch, K., & Bean, K. (2009). The STARS Leadership Corps: An innovative computer science learning community. Learning Communities Journal, 1(2), 5–18.

Barnes, T., & Stamper, J. (2008). Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data. In Intelligent Tutoring Systems (pp. 373–382). https://doi.org/10.1007/978-3-540-69132-7_41

Babu, S., Schmugge, S., Barnes, T., & Hodges, L. F. (2006). “What Would You Like to Talk About?” An Evaluation of Social Conversations with a Virtual Receptionist. In Intelligent Virtual Agents (pp. 169–180). https://doi.org/10.1007/11821830_14

Barnes, T., Bitzer, D., & Vouk, M. (2005). Experimental Analysis of the Q-Matrix Method in Knowledge Discovery. In Lecture Notes in Computer Science (Vol. 3488, pp. 603–611). https://doi.org/10.1007/11425274_62

Babu, S., Schmugge, S., Inugala, R., Rao, S., Barnes, T., & Hodges, L. F. (2005). Marve: A Prototype Virtual Human Interface Framework for Studying Human-Virtual Human Interaction. In Intelligent Virtual Agents (pp. 120–133). https://doi.org/10.1007/11550617_11

Barnes, T. M., & Savage, C. D. (1997). Efficient generation of graphical partitions. DISCRETE APPLIED MATHEMATICS, 78(1-3), 17–26. https://doi.org/10.1016/s0166-218x(97)00022-x