A Demonstration of Evidence-Based Action Research Using Information Dashboard in Introductory Programming Education

Matsuzawa, Yoshiaki; Tanaka, Yoshiki; Kitani, Tomoya; Sakai, Shingo

doi:10.1007/978-3-319-74310-3_62

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…We have to distinguish between static analyses based on the source code (as is the case for certain types of software metrics) and dynamic analyses based on the run-time behavior and results of programs (including "testing" approaches such as JUnit for Java). Matsuzawa et al (2017) used coding metrics to analyze characteristics of programming exercises and visualized these through a dashboard. The provision of this visualization could improve the teaching and understanding of classroom exercises in introductory programming.…”

Section: "Computational Metacognition"mentioning

confidence: 99%

Computational Thinking—More Than a Variant of Scientific Inquiry!

Hoppe

Werneburg

2019

Computational Thinking Education

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The essence of Computational Thinking (CT) lies in the creation of "logical artifacts" that externalize and reify human ideas in a form that can be interpreted and "run" on computers. Various approaches to scientific inquiry (learning) also make use of models that are construed as logical artifacts, but here the main focus is on the correspondence of such models with natural phenomena that exist prior to these models. To pinpoint the different perspectives on CT, we have analyzed the terminology of articles from different backgrounds and periods. This survey is followed by a discussion of aspects that are specifically relevant to a computer science perspective. Abstraction in terms of data and process structures is a core feature in this context. As compared to a "free choice" of computational abstractions based on expressive and powerful formal languages, models used in scientific inquiry learning typically have limited "representational flexibility" within the boundaries of a predetermined computational approach. For the progress of CT and CT education, it is important to underline the nature of logical artifacts as the primary concern. As an example from our own work, we elaborate on "reactive rule-based programming" as an entry point that enables learners to start with situational specifications of action that can be further expanded into more standard block-based iterative programs and thus allows for a transition between different computational approaches. As an outlook beyond current practice, we finally envisage the potential of meta-level programming and program analysis techniques as a computational counterpart of metacognitive strategies.

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Section: "Computational Metacognition"mentioning

confidence: 99%

Computational Thinking—More Than a Variant of Scientific Inquiry!

Hoppe

Werneburg

2019

Computational Thinking Education

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“…For example, Fu et al [7] proposed a real-time dashboard for C programming courses, which visualizes student situations by focusing mainly on compile errors. Matsuzawa et al [8] developed a dashboard with four coding metrics: working time, lines of code, compile-error correction time, and block-editor usage ratio. Aside from the dashboard, López-Pernas et al [9] combined data from two different systems to understand students' programming learning processes by using process and sequence mining techniques.…”

Section: Introductionmentioning

confidence: 99%

Visualizing Source-Code Evolution for Understanding Class-Wide Programming Processes

et al. 2022

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The COVID-19 pandemic has led to an increase in online classes, and programming classes are no exception. In such a learning environment, understanding every student’s programming process is mostly impractical for teachers, despite its significance in supporting students. Giving teachers feedback on programming processes is a typical approach to the problem. However, few studies have focused on visual representations of the evolution process of source-code contents; it remains unclear what visual representation would be effective to this end and how teachers value such feedback. We propose two feedback tools for teachers. These tools visualize the temporal evolution of source-code contents at different granularities. An experiment was conducted in which several university teachers performed a user evaluation of the tools, particularly with regard to their usefulness for reviewing past programming classes taught by another teacher. Questionnaire results showed that these tools are helpful for understanding programming processes. The tools were also found to be complementary, with different aspects being highly evaluated. We successfully presented concrete visual representations of programming processes as well as their relative strengths and weaknesses for reviewing classes; this contribution may serve as a basis for future real-time use of these tools in class.

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