Improving Engagement in Program Construction Examples for Learning Python Programming
Autor: | Roya Hosseini, Kamil Akhuseyinoglu, Kerttu Pollari-Malmi, Peter Brusilovsky, Christian D. Schunn, Lauri Malmi, Teemu Sirkiä |
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Přispěvatelé: | University of Pittsburgh, Professorship Malmi L., Department of Computer Science, Aalto-yliopisto, Aalto University |
Rok vydání: | 2020 |
Předmět: |
Program construction
Computer science Teaching method Computer-Assisted Instruction Worked examples 02 engineering and technology Education 020204 information systems Computer software 0202 electrical engineering electronic engineering information engineering computer.programming_language business.industry 05 social sciences Educational technology 050301 education Introductory programming education Python (programming language) Computational Theory and Mathematics Learner engagement Software construction CS1 Software engineering business 0503 education computer Classroom study Python |
Zdroj: | International Journal of Artificial Intelligence in Education. 30:299-336 |
ISSN: | 1560-4306 1560-4292 |
DOI: | 10.1007/s40593-020-00197-0 |
Popis: | This research is focused on how to support students’ acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student’s learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage students. The goal of this work is to investigate the value of the “engaging” features in programming examples. We introduce PCEX, an online tool developed to present program construction examples in an engaging fashion. We also present the results of a controlled study with a between-subject design that was conducted in a large introductory Python programming class to compare PCEX with non-interactive worked examples focused on program construction. The results of our study show the positive impact of interactive program construction examples on student’s engagement, problem-solving performance, and learning. |
Databáze: | OpenAIRE |
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