A sizable body of research on instructional practices supports the use of worked examples for acquiring cognitive skills in domains such as mathematics and physics. Although examples are also important in the domain of programming, existing research on programming examples is limited. Program examples are used by instructors to achieve two important goals: to explain program behavior and to demonstrate program construction patterns. Program behavior examples are used to demonstrate the semantics of various program constructs (i.e., what is happening inside a program or an algorithm when it is executed). Program construction examples illustrate how to construct a program that achieves a specific purpose. While both functions of program examples are important for learning, most of the example-focused research in computer science education focused on technologies for augmenting program behavior examples such as program visualization, tracing tables, etc. In contrast, advanced technologies for presenting program construction examples were rarely explored. This work introduces interactive Program Construction Examples (PCEX) to begin a systematic exploration of worked-out program construction examples in the domain of computer science education. A classroom evaluation and analysis of the survey data demonstrated that the usage of PCEX examples is associated with better student's learning and performance.
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Improving Engagement in Program Construction Examples for Learning Python Programming
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.
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- Award ID(s):
- 1822816
- PAR ID:
- 10188375
- Date Published:
- Journal Name:
- International journal of artificial intelligence in education
- Volume:
- 30
- ISSN:
- 1560-4292
- Page Range / eLocation ID:
- 299-336
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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