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A framework for hypothesis-driven approaches to support data-driven learning analytics in measuring computational thinking in block-based programming

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John StamperAuthors Info & Claims

LAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference

Pages 530 - 531

https://doi.org/10.1145/3027385.3029440

Published: 13 March 2017 Publication History

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Abstract

K-12 classrooms use block-based programming environments (BBPEs) for teaching computer science and computational thinking (CT). To support assessment of student learning in BBPEs, we propose a learning analytics framework that combines hypothesis- and data-driven approaches to discern students' programming strategies from BBPE log data. We use a principled approach to design assessment tasks to elicit evidence of specific CT skills. Piloting these tasks in high school classrooms enabled us to analyze student programs and video recordings of students as they built their programs. We discuss a priori patterns derived from this analysis to support data-driven analysis of log data in order to better assess understanding and use of CT in BBPEs.

References

[1]

Baker, R., & Siemens, G. 2014. Educational data mining and learning analytics. In K. Sawyer (Ed.), Cambridge Handbook of the Learning Sciences.

Google Scholar

[2]

Berland, M., Martin, T., Benton, T., Petrick Smith, C., & Davis, D. 2013. Using Learning Analytics to Understand the Learning Pathways of Novice Programmers. JLS, 22(4), 564--599.

Google Scholar

[3]

Mislevy, R.J. & Haertel. G. 2006. Implications of Evidence-Centered Design for Educational Testing. Educational Measurement: Issues and Practice, 25(4), 6--20.

Crossref

Google Scholar

[4]

Piech, C., et al. 2012. Modeling how students learn to program. In Proceedings of the 43rd SIGCSE (pp. 153--160). ACM.

Digital Library

Google Scholar

[5]

Robins, A., Rountree, J., & Rountree, N. 2003. Learning and teaching programming: A review and discussion. Computer Science Education, 13(2), 137--172.

Crossref

Google Scholar

[6]

Rupp, A. A., et al. 2012. Putting ECD into Practice: The Interplay of Theory and Data in Evidence Models within a Digital Learning Environment. JEDM, 4(1), 49--110.

Google Scholar

[7]

Werner, L., Denner, J., Campe, S., & Kawamoto, D.C. 2012. The Fairy Perf. Assessment: Measuring computational thinking in middle school. In Proceedings of the 43rd SIGCSE. ACM.

Digital Library

Google Scholar

[8]

Winne, P. H., & Baker, R. S. 2013. The potentials of educational data mining for researching metacognition, motivation and self-regulated learning. Journal of Educational Data Mining, 5(1).

Google Scholar

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Liu ZFulwider G(2023)Balancing Granularity and Context in Designing Evidence Models for Stealth AssessmentGames as Stealth Assessments10.4018/979-8-3693-0568-3.ch005(101-124)Online publication date: 29-Sep-2023
https://doi.org/10.4018/979-8-3693-0568-3.ch005
Muñoz RAlegría JRobles G(2023)Assessment of Computational Thinking Skills: A Systematic Review of the LiteratureIEEE Revista Iberoamericana de Tecnologias del Aprendizaje10.1109/RITA.2023.332376218:4(319-330)Online publication date: Nov-2023
https://doi.org/10.1109/RITA.2023.3323762
Shen JChen GBarth-Cohen LJiang SEltoukhy M(2020)Connecting computational thinking in everyday reasoning and programming for elementary school studentsJournal of Research on Technology in Education10.1080/15391523.2020.183447454:2(205-225)Online publication date: 30-Nov-2020
https://doi.org/10.1080/15391523.2020.1834474
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Information

Published In

LAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference

March 2017

631 pages

ISBN:9781450348706

DOI:10.1145/3027385

General Chairs:
Alyssa Wise
New York University, USA
,
Phillip H. Winne
Simon Fraser University, Canada
,
Grace Lynch
Society for Learning Analytics Research
,
Program Chairs:
Xavier Ochoa
Escuela Superior Politecnica del Litoral, Ecuador
,
Inge Molenaar
Radboud University, The Netherlands
,
Shane Dawson
University of South Australia, Australia
,
Publications Chair:
Marek Hatala
Simon Fraser University, Canada

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.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 March 2017

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LAK '17

LAK '17: 7th International Learning Analytics and Knowledge Conference

March 13 - 17, 2017

British Columbia, Vancouver, Canada

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LAK '17 Paper Acceptance Rate 36 of 114 submissions, 32%;

Overall Acceptance Rate 236 of 782 submissions, 30%

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Liu ZFulwider G(2023)Balancing Granularity and Context in Designing Evidence Models for Stealth AssessmentGames as Stealth Assessments10.4018/979-8-3693-0568-3.ch005(101-124)Online publication date: 29-Sep-2023
https://doi.org/10.4018/979-8-3693-0568-3.ch005
Muñoz RAlegría JRobles G(2023)Assessment of Computational Thinking Skills: A Systematic Review of the LiteratureIEEE Revista Iberoamericana de Tecnologias del Aprendizaje10.1109/RITA.2023.332376218:4(319-330)Online publication date: Nov-2023
https://doi.org/10.1109/RITA.2023.3323762
Shen JChen GBarth-Cohen LJiang SEltoukhy M(2020)Connecting computational thinking in everyday reasoning and programming for elementary school studentsJournal of Research on Technology in Education10.1080/15391523.2020.183447454:2(205-225)Online publication date: 30-Nov-2020
https://doi.org/10.1080/15391523.2020.1834474
Fagerlund JHäkkinen PVesisenaho MViiri J(2020)Computational thinking in programming with Scratch in primary schools: A systematic reviewComputer Applications in Engineering Education10.1002/cae.2225529:1(12-28)Online publication date: 8-May-2020
https://doi.org/10.1002/cae.22255
TOSİK-GÜN EGÜYER T(2019)Bilgi İşlemsel Düşünme Becerisinin Değerlendirilmesine İlişkin Sistematik Alanyazın TaramasıAhmet Keleşoğlu Eğitim Fakültesi Dergisi10.38151/akef.5975051:2(99-120)Online publication date: 20-Dec-2019
https://doi.org/10.38151/akef.597505
Arieli-Attali MWard SThomas JDeonovic Bvon Davier A(2019)The Expanded Evidence-Centered Design (e-ECD) for Learning and Assessment Systems: A Framework for Incorporating Learning Goals and Processes Within Assessment DesignFrontiers in Psychology10.3389/fpsyg.2019.0085310Online publication date: 26-Apr-2019
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Fagerlund JMalmi LKorhonen AMcCartney RPetersen AMalmi LMcCartney R(2018)A Study on the Assessment of Introductory Computational Thinking via Scratch Programming in Primary SchoolsProceedings of the 2018 ACM Conference on International Computing Education Research10.1145/3230977.3231013(264-265)Online publication date: 8-Aug-2018
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Price TBarnes T(2017)Position paper: Block-based programming should offer intelligent support for learners2017 IEEE Blocks and Beyond Workshop (B&B)10.1109/BLOCKS.2017.8120414(65-68)Online publication date: Oct-2017
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Grover S(2017)Assessing Algorithmic and Computational Thinking in K-12: Lessons from a Middle School ClassroomEmerging Research, Practice, and Policy on Computational Thinking10.1007/978-3-319-52691-1_17(269-288)Online publication date: 25-Apr-2017
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Measuring Student Learning in Introductory Block-Based Programming: Examining Misconceptions of Loops, Variables, and Boolean Logic

A Framework for Using Hypothesis-Driven Approaches to Support Data-Driven Learning Analytics in Measuring Computational Thinking in Block-Based Programming Environments

Computational thinking in high school courses

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