CS-CLIMATE

Fostering collaborative dialogue for rigorous learning and diverse student retention in computer science. (Funding: National Science Foundation, CNS-1453520, CNS-1622438)

Introduction

A rich body of evidence suggests that collaborative learning holds many benefits for computer science students, yet there is growing recognition that neither collaborative learning itself, nor the innovative curricula in which it may be situated, are “magic bullets” capable of single-handedly solving the computing pipeline problem. In contrast to being a one-size-fits-all solution, collaborative learning is highly dependent upon characteristics of the collaborators and on fine-grained interactions. This project is led by PI Kristy Boyer at the University of Florida and is funded by her CAREER award.

Project Description

The overarching research question of the CS-CLIMATE project is, “How can we identify and support the facets of collaborative dialogue that are particularly effective for fostering learning, sense of identity, motivation, and continued engagement for diverse computer science learners?” The project will investigate this question through three thrusts: 1) Collect a rich set of computer science collaborative learning data. The project will leverage the ASCEND learning environment developed by our lab, which supports remote collaboration with textual natural language dialogue, synchronized code editing, and integrated repository control for two or more collaborators. Partnering with three participating institutions: North Carolina State University, Meredith College (an all-women’s institution), and Florida A&M University (a minority-serving university with 90% African American enrollment), the full suite of collected data will also include student characteristics of gender, race/ethnicity, personality profile, and achievement goal orientation, while measures of outcomes include learning, sense of computing identity, motivation, and engagement. 2) Examine the fine-grained facets of collaborative dialogue that are particularly effective for diverse computer science learners. By leveraging machine-learning frameworks for dialogue analysis developed within our lab, the project will see the creation of fine-grained, theoretically informed models that capture collaborative dialogue and problem solving phenomena associated with learning, identity development, motivation, and engagement. 3) Implement and evaluate evidence-based pedagogical support for fostering effective collaborative dialogue. The project will extract a set of evidence-based pedagogical strategies for fostering effective collaborative dialogue tailored to student characteristics. These evidence-based pedagogical supports will be evaluated through quasi-experimental studies. It is hypothesized that CS-CLIMATE pedagogical support will significantly improve learning, sense of identity, motivation, and continued engagement for students overall, and for women and African American students in particular. In addition to testing this primary hypothesis, the project will produce fine-grained sequential analyses and rich qualitative findings that further the state of knowledge about how diverse students learn computing.

publications

2019
[19]In Their Own Words: Gender Differences in Student Perceptions of Pair Programming. Kimberly Michelle Ying, Lydia G. Pezzullo, Mohona Ahmed, Kassandra Crompton, Jeremiah Blanchard, Kristy Elizabeth Boyer. Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19), 2019, pp. To appear. [bib]
2018
[18]The Importance of Producing Shared Code Through Pair Programming. Mehmet Celepkolu, Kristy Elizabeth Boyer. Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE), Baltimore, Maryland, 2018, pp. 765-770. [bib]
[17]"I Think We Should...": Analyzing Elementary Students' Collaborative Processes for Giving and Taking Suggestions. Jennifer Tsan, Fernando J. Rodríguez, Kristy Elizabeth Boyer, Collin Lynch. Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE), Baltimore, Maryland, 2018, pp. 622-627. [bib]
[16]Thematic Analysis of Novice Students’ Reflections on Pair Programming. Mehmet Celepkolu, Kristy Elizabeth Boyer. Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE), Baltimore, Maryland, 2018, pp. 771-776. [bib]
[15]Predicting Student Performance Based on Eye Gaze During Collaborative Problem Solving. Mehmet Celepkolu, Kristy Elizabeth Boyer. Proceedings of the 4th International Workshop on Group Interaction Frontiers in Technology (GIFT), 2018. [bib]
[14]"Alright, What Do We Need?": A Study of Young Coders’ Collaborative Dialogue. Jennifer Tsan, Collin F. Lynch, Kristy Elizabeth Boyer. International Journal of Child-Computer Interaction, vol. 17, 2018, pp. 61-71. [bib]
2017
[13]Think First: Fostering Substantive Contributions in Collaborative Problem-Solving Dialogues. Mehmet Celepkolu, Joseph B. Wiggins, Kristy Elizabeth Boyer, Kyla McMullen. Proceedings of the 12th International Conference on Computer Supported Collaborative Learning (CSCL), Philadelphia, Pennsylvania, 2017, pp. 295–302. [bib]
[12]Conversational UX Design for Kids: Toward Learning Companions. Joseph B. Wiggins, Lydia G. Pezzullo, Kristy Elizabeth Boyer, Bradford W. Mott, Eric N. Wiebe, James C. Lester. Proceedings of the Conversational UX Design CHI 2017 Workshop, Denver, Colorado, 2017. [bib]
[11]Toward Conversational Agents that Support Learning: A Look at Human Collaborations in Computer Science Problem Solving. Fernando J. Rodríguez, Kimberly Michelle Price, Mickey Vellukunnel, Kristy Elizabeth Boyer. Proceedings of the Conversational UX Design CHI 2017 Workshop, Denver, Colorado, 2017. [bib]
[10]Deconstructing the Discussion Forum: Student Questions and Computer Science Learning. Mickey Vellukunnel, Philip Sheridan Buffum, Kristy Elizabeth Boyer, Jeffrey Forbes, Sarah Heckman, Ketan Mayer-Patel. Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE), Seattle, Washington, 2017, pp. 603-608. [bib]
[9]Exploring the Pair Programming Process: Characteristics of Effective Collaboration. Fernando J. Rodríguez, Kimberly Michelle Price, Kristy Elizabeth Boyer. Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE), Seattle, Washington, 2017, pp. 507-512. [bib]
2016
[8]Gender Differences in Facial Expressions of Affect During Learning. Alexandria K. Vail, Joseph F. Grafsgaard, Kristy Elizabeth Boyer, Eric N. Wiebe, James C.. Lester. Proceedings of the 24th International Conference on User Modelling, Adaptation, and Personalization, Halifax, Canada, 2016, pp. 65-74. [bib]
[7]The Affective Impact of Tutor Questions: Predicting Frustration and Engagement. Alexandria K. Vail, Joseph B. Wiggins, Joseph F. Grafsgaard, Kristy Elizabeth Boyer, Eric N. Wiebe, James C.. Lester. Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, North Carolina, 2016, pp. 247-254. [bib]
[6]Predicting Learning from Student Affective Response to Tutor Questions. Alexandria K. Vail, Joseph F. Grafsgaard, Kristy Elizabeth Boyer, Eric N. Wiebe, James C. Lester. Proceedings of the 13th International Conference on Intelligent Tutoring Systems, Zagreb, Croatia, 2016, pp. 154-164. [bib]
[5]How Early Does the CS Gender Gap Emerge? A Study of Collaborative Problem Solving in 5th Grade Computer Science. Jennifer Tsan, Kristy Elizabeth Boyer, Collin F. Lynch. Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE), 2016, pp. 388-393. [bib]
[4]Reference Resolution in Situated Dialogue with Learned Semantics. Xiaolong Li, Kristy Elizabeth Boyer. Proceedings of the 17th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL 2016), 2016, pp. 329–338. [bib]
[3]Do You Think You Can? The Influence of Student Self-Efficacy on the Effectiveness of Tutorial Dialogue for Computer Science. Joseph B. Wiggins, Joseph F. Grafsgaard, Kristy Elizabeth Boyer, Eric N. Wiebe, James C. Lester. International Journal of Artificial Intelligence in Education, 2016, pp. 1-24. [bib]
[2]Collaboration and Gender Equity in Game-Based Learning for Middle School Computer Science. Philip Sheridan Buffum, Megan Hardy Frankosky, Kristy Elizabeth Boyer, Eric N. Wiebe, Bradford W. Mott, James C. Lester. IEEE Computing in Science and Engineering, Special Issue - Best of Respect 2015, 2016, pp. 18—28. [bib]
[1]Empowering All Students: Closing the CS Confidence Gap with an In-School Initiative for Middle School Students. Philip Sheridan Buffum, Megan Hardy Frankosky, Kristy Elizabeth Boyer, Eric N. Wiebe, Bradford W. Mott, James C. Lester. Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE), 2016, pp. 382-387. [bib]