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A Review of Generic Program Visualization Systems for Introductory Programming Education
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The Cambridge Handbook of Sociocultural Psychology
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What Is Learning Anyway? A Topographical Perspective Considered
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Structure and interpretation of computer programs
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Why students drop out CS1 course?
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The Method of Repeated Readings
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Karel the Robot: A Gentle Introduction to the Art of Programming
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Learning and Motivation in the Postsecondary Classroom
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EducationPaving the way for computational thinking
Guzdial, M. (2008) · Communications of the ACM · doi:10.1145/1378704.1378713 · Cited by 350
Self-efficacy and performance in mathematics: Reciprocal determinism in 33 nations.
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Assessment of Cognitive Load in Multimedia Learning Using Dual-Task Methodology
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New Pathways into Robotics: Strategies for Broadening Participation
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A Statics Concept Inventory: Development and Psychometric Analysis
Steif, P. S., & Dantzler, J. (2005) · Journal of Engineering Education · doi:10.1002/j.2168-9830.2005.tb00864.x · Cited by 339
Self-efficacy and mental models in learning to program
Ramalingam, V., LaBelle, D., & Wiedenbeck, S. (2004) · Annual Conference on Innovation and Technology in Computer Science Education · doi:10.1145/1007996.1008042 · Cited by 339
Cognitive strategies and looping constructs
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Comparing Block-Based and Text-Based Programming in High School Computer Science Classrooms
Weintrop, D., & Wilensky, U. J. (2017) · ACM Transactions on Computing Education · doi:10.1145/3089799 · Cited by 338
The role of learning from examples in the acquisition of recursive programming skills.
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Shaffer, D. W., & Resnick, M. (1999) · The Journal of Interactive Learning Research · Cited by 337
The subgoal learning model: Creating better examples so that students can solve novel problems.
Catrambone, R. (1998) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.127.4.355 · Cited by 337
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Uttal, D. H., Scudder, K. V., & DeLoache, J. S. (1997) · Journal of Applied Developmental Psychology · doi:10.1016/s0193-3973(97)90013-7 · Cited by 336
Educational Data Mining and Learning Analytics in Programming
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Geek Heresy: Rescuing Social Change from the Cult of Technology
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What is an Engineer? Implications of Elementary School Student Conceptions for Engineering Education
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Programmable Bricks: Toys to think with
Resnick, M., Martin, F., Sargent, R., & Silverman, B. (1996) · IBM Systems Journal · doi:10.1147/sj.353.0443 · Cited by 330
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Toward a Solution of the Learning Paradox
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Expert Blind Spot Among Preservice Teachers
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200 of 892 shown
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Heckman, S. S., Carver, J. C., Sherriff, M. S., & Al-Zubidy, A. (2021) · ACM Transactions on Computing Education · doi:10.1145/3470652 · Cited by 34
Tedre, M., & Pajunen, J. (2022) · ACM Transactions on Computing Education · doi:10.1145/3487049 · Cited by 24
Honda, F., Pires, F., Pessoa, M., & Oliveira, E. (2020) · Anais do ... Simpósio Brasileiro de Informática na Educação/Anais do Simpósio Brasileiro de Informática na Educação · doi:10.5753/cbie.sbie.2020.1753 · Cited by 7
Computational Modelling in High School Biology: A Teaching Intervention
Musaeus, L. H., Tatar, D. G., & Musaeus, P. (2022) · Journal of Biological Education · doi:10.1080/00219266.2022.2118353 · Cited by 8
The Landscape of Computer Science Education Courses: A Syllabi Analysis
Cunningham, K. I., Parker, M. C., & Zhang, J. (2023) · Koli Calling International Conference on Computing Education Research · doi:10.1145/3631802.3631831 · Cited by 3
Metadata
- Authors
- Fincher, S. A., Tenenberg, J., Dorn, B., Hundhausen, C., McCartney, R., & Murphy, L.
- Affiliations
- University of Kent (GB)
- ORCID
- Venue
- The Cambridge Handbook of Computing Education Research
- Publisher
- Cambridge University Press
- Published
- 2019-02-21
- Pages
- 40-55
- OpenAlex
- W2916826581
- Cited by
- 7
- References
- 2,102
- Citations by year
- 2023: 3 · 2022: 2 · 2021: 1 · 2020: 1
- FWCI
- 2.88
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Cambridge University Press eBooks (publishedVersion)
- Kent Academic Repository (University of Kent) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Social Sciences › Education › Educational Research and Methods
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- computing education, research trends, computer science education
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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