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Assessment of Data Representation in Scratch Via the SOLO Taxonomy

Author

Listed:
  • Anastasios Ladias

    (Former Bureau of School Directors, Ministry of Education, Greece)

  • Theodoros Karvounidis

    (Dept. of Informatics, University of Piraeus, Piraeus, Greece)

  • Dimitrios Ladias

    (Department of Informatics, National and Kapodistrian University of Athens, Greece)

  • Christos Douligeris

Abstract

The work addresses the significance of robotics in education, emphasizing its role in enhancing STEM skills through programming and sensory feedback. Scratch, a multimedia programming environment, is highlighted as a tool for robotic projects. Within Scratch, this work discusses data representation, distinguishing between visible and transparent data. The current work focuses on the visible data. Variables in Scratch are made tangible, helping users understand their function. Developers define their own data, such as values, variables, lists, and call parameters, while Scratch also provides system data. This system data can be numeric, alphanumeric, or logical, and its representation in code varies. To evaluate how data are used in Scratch by novice programmers, this work also proposes an evaluation framework using the Structure of the Observed Learning Outcome (SOLO) taxonomy. This evaluation framework can be used by the teacher as a tool either to evaluate with measurable criteria the students’ code (on issues related to the way the data indicates their presence in Scratch) or to develop their personal teaching paths, thus creating mental scaffolds that assist students to master new knowledge.

Suggested Citation

  • Anastasios Ladias & Theodoros Karvounidis & Dimitrios Ladias & Christos Douligeris, 2023. "Assessment of Data Representation in Scratch Via the SOLO Taxonomy," European Journal of Engineering and Technology Research, European Open Science, pages 23-30, March.
    • Handle: RePEc:epw:ejeng0:y:2023:id:63134
    DOI: 10.24018/ejeng.2023.1.CIE.3134
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