Modeling the learning progressions of computational thinking of primary grade studentsLinda M. Seiter, Brendan Foreman
Publikationsdatum:
Zu finden in: ICER 2013 (Seite 59 bis 66), 2013
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Zusammenfassungen
We introduce the Progression of Early Computational Thinking (PECT) Model, a framework for understanding and assessing computational thinking in the primary grades (Grades 1 to 6). The model synthesizes measurable evidence from student work with broader, more abstract coding design patterns, which are then mapped onto computational thinking concepts.
We present the results of a pilot-test study of the PECT Model in order to demonstrate its potential efficacy in detecting both differences in computational thinking among students of various ages as well as any clear overall progressions in increasing computational sophistication. Results of this sort are vital for establishing research-based and age-appropriate curricula for students in the primary grades, i.e., developing non-trivial, challenging but not overly daunting lesson plans that utilize the cognitive development stage of each grade level most effectively.
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Zeitleiste
18 Erwähnungen
- WiPSCE 2014 - Proceedings of the 9th Workshop in Primary and Secondary Computing Education, Berlin, Germany, November 5-7, 2014 (Carsten Schulte, Michael E. Caspersen, Judith Gal-Ezer) (2014)
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- ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research, ICER 2016, Melbourne, VIC, Australia, September 8-12, 2016 (Judy Sheard, Josh Tenenberg, Donald Chinn, Brian Dorn) (2016)
- Mixed Methods for the Assessment and Incorporation of Computational Thinking in K-12 and Higher Education (Joshua Levi Weese) (2016)
- ICER 2017 - Proceedings of the 2017 ACM Conference on International Computing Education Research, ICER 2017, Tacoma, WA, USA, August 18-20, 2017 (Josh Tenenberg, Donald Chinn, Judy Sheard, Lauri Malmi) (2017)
- Principled Assessment of Student Learning in High School Computer Science (Eric Snow, Daisy Rutstein, Marie A. Bienkowski, Yuning Xu) (2017)
- Demystifying computational thinking (Valerie J. Shute, Chen Sun, Jodi Asbell-Clarke) (2017)
- ICLS 2018 1/3 (2018)
- Blocks or Text? - How Programming Language Modality Makes a Difference in Assessing Underrepresented Populations (David Weintrop, Heather Killen, Baker Franke)
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- Starting from Scratch - Outcomes of Early Computer Science Learning Experiences and Implications for What Comes Next (David Weintrop, Alexandria K. Hansen, Danielle B. Harlow, Diana Franklin) (2018)
- Programming Misconceptions for School Students (Alaaeddin Swidan, Felienne Hermans, Marileen Smit) (2018)
- Proceedings of the 13th Workshop in Primary and Secondary Computing Education, WiPSCE 2018, Potsdam, Germany, October 04-06, 2018. (Andreas Mühling, Quintin I. Cutts) (2018)
- Thinking out of the box - comparing metaphors for variables in programming education (Felienne Hermans, Alaaeddin Swidan, Efthimia Aivaloglou, Marileen Smit) (2018)
- How Machine Learning impacts the Undergraduate Computing Curriculum (R. Benjamin Shapiro, Rebecca Fiebrink, Peter Norvig) (2018)
- ICER 2019 - Proceedings of the 2019 ACM Conference on International Computing Education Research, ICER 2019, Toronto, ON, Canada, August 12-14, 2019 (Robert McCartney, Andrew Petersen, Anthony V. Robins, Adon Moskal) (2019)
- Computing Education Theories - What Are They and How Are They Used? (Lauri Malmi, Judy Sheard, Päivi Kinnunen, Simon, Jane Sinclair) (2019)
- Proceedings of the 14th Workshop in Primary and Secondary Computing Education, WiPSCE 2019, Glasgow, Scotland, UK, October 23-25, 2019 (2019)
- Cognitive Correlates of Computational Thinking - Evaluation of a Blended Unplugged/Plugged-In Course (Katerina Tsarava, Luzia Leifheit, Manuel Ninaus, Marcos Román-González, Martin V. Butz, Jessika Golle, Ulrich Trautwein, Korbinian Moeller) (2019)
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- WiPSCE '21 - The 16th Workshop in Primary and Secondary Computing Education, Virtual Event / Erlangen, Germany, October 18-20, 2021 (Marc Berges, Andraes Mühling, Michal Armoni) (2021)
- Code Perfumes - Reporting Good Code to Encourage Learners (Florian Obermüller, Lena Bloch, Luisa Greifenstein, Ute Heuer, Gordon Fraser) (2021)
- Computational Thinking in Education - A Pedagogical Perspective (Aman Yadav, Ulf Dalvad Berthelsen) (2021)
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