Towards Data-Driven Programming Problem Generation for Mastery Learning
Pages 339 - 340
Abstract
Research into intelligent programming systems has lead to numerous means of providing help to students during programming tasks but not in generating the right problem for students to work through. My work will be in developing and analyzing a programming problem generator for mastery learning that will leverage student data and incorporate methods for instructional design for programming tasks to give students the best problem to practice and achieve proficiency
References
[1]
Paul Denny, Andrew Luxton-Reilly, and Beth Simon. 2008. Evaluating a new exam question: Parsons problems. In Proceedings of the fourth international workshop on computing education research. ACM, 113--124.
[2]
Yihuan Dong and Tiffany Barnes. 2017. Evaluation of a template-based puzzle generator for an educational programming game. In Thirteenth Artificial Intelligence and Interactive Digital Entertainment Conference .
[3]
Lytle et al. 2019. Use, Modify, Create: Comparing Computational Thinking Lesson Progressions for STEM Classes. In Proceedings of the 24th Annual conference on Innovation and Technology in computer science education. ACM.
[4]
Dan Garcia, Brian Harvey, and Tiffany Barnes. 2015. The beauty and joy of computing. ACM Inroads, Vol. 6, 4 (2015), 71--79.
[5]
James Garner, Paul Denny, and Andrew Luxton-Reilly. 2019. Mastery Learning in Computer Science Education. In Proceedings of the Twenty-First Australasian Computing Education Conference (ACE '19). ACM, New York, NY, USA, 37--46.
[6]
Mariane Hedegaard. 2002. The zone of proximal development as basis for instruction. In An introduction to Vygotsky. Routledge, 183--207.
[7]
Nicholas Lytle et al. 2019. CEO: A Triangulated Evaluation of a Modeling-Based CT-Infused CS Activity for Non-CS Middle Grade Students. In Proceedings of the ACM Conference on Global Computing Education (CompEd '19). ACM, New York, NY, USA, 58--64.
[8]
Jeanne Nakamura and Mihaly Csikszentmihalyi. 2009. Flow theory and research. Handbook of positive psychology (2009), 195--206.
[9]
Thomas W Price, Rui Zhi, and Tiffany Barnes. 2017. Evaluation of a Data-driven Feedback Algorithm for Open-ended Programming. In EDM .
[10]
Gillian Smith and Jim Whitehead. 2010. Analyzing the expressive range of a level generator. In Proceedings of the 2010 Workshop on Procedural Content Generation in Games. ACM, 4.
[11]
T. J. Tiam-Lee and K. Sumi. 2018. Procedural Generation of Programming Exercises with Guides Based on the Student's Emotion. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 1465--1470.
[12]
Kurt Vanlehn. 2006. The behavior of tutoring systems. International journal of artificial intelligence in education, Vol. 16, 3 (2006), 227--265.
[13]
Jeannette Wing. 2006. Computational thinking. Commun. ACM, Vol. 49, 3 (2006).
[14]
Rui Zhi, Nicholas Lytle, and Thomas W Price. 2018. Exploring Instructional Support Design in an Educational Game for K-12 Computing Education. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education. ACM, 747--752.
[15]
Rui Zhi, Thomas W Price, Nicholas Lytle, Yihuan Dong, and Tiffany Barnes. {n. d.}. Reducing the State Space of Programming Problems through Data-Driven Feature Detection.
- Towards Data-Driven Programming Problem Generation for Mastery Learning
Recommendations
Five years of Mastery Learning: What did we learn?
Koli Calling '18: Proceedings of the 18th Koli Calling International Conference on Computing Education ResearchOver the last five years we have developed our first year, first semester programming course into a mastery learning oriented course -- a delivery format allowing students to work at their own pace towards the achievement level they aim for. In this ...
Learning for mastery in an introductory programming course
ITiCSE '08: Proceedings of the 13th annual conference on Innovation and technology in computer science educationTeachers always look for new ways to make their teaching more effective. "The data show that mastery learning programs have positive effects on student achievement" [1]. We introduce work in progress of an educational research of teaching/learning (T/L) ...
Combining mastery learning with project-based learning in a first programming course: an experience report
ICSE '15: Proceedings of the 37th International Conference on Software Engineering - Volume 2One of the challenges in teaching a first programming course is that in the same course, the students must learn basic programming techniques and high level abstraction abilities, and the application of those techniques and concepts in problem solving ...
Comments
Information & Contributors
Information
Published In
July 2019
375 pages
ISBN:9781450361859
DOI:10.1145/3291279
- General Chairs:
- Robert McCartney,
- Andrew Petersen,
- Anthony Robins,
- Adon Moskal,
- Program Chairs:
- Robert McCartney,
- Anthony Robins
Copyright © 2019 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 30 July 2019
Check for updates
Author Tags
Qualifiers
- Abstract
Conference
ICER '19
Sponsor:
ICER '19: International Computing Education Research Conference
August 12 - 14, 2019
Toronto ON, Canada
Acceptance Rates
ICER '19 Paper Acceptance Rate 28 of 137 submissions, 20%;
Overall Acceptance Rate 189 of 803 submissions, 24%
Upcoming Conference
ICER 2025
- Sponsor:
- sigcse
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 187Total Downloads
- Downloads (Last 12 months)10
- Downloads (Last 6 weeks)1
Reflects downloads up to 06 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in