University of Illinois Urbana-Champaign

Challenges of interpreting Python Tutor visualizations

Balasubramanian, Niranjana

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https://hdl.handle.net/2142/124436

Description

Title
Challenges of interpreting Python Tutor visualizations
Author(s)
Balasubramanian, Niranjana
Issue Date
2024-05-01
Director of Research (if dissertation) or Advisor (if thesis)
Lewis, Colleen M.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • Python Tutor
  • Program Visualizer
  • Microgenetic analysis
  • Understanding representations
  • Interpreting Python Tutor representations
  • Novice programmers
Abstract
Background: Programming can be challenging for novice programmers. Computer science courses often focus on syntax alone and students may view program execution as a “black box”. To develop the “glass-box” view, visualizations that display program execution may be useful. Python Tutor is a program visualization tool developed for use in educational settings. Purpose: In this thesis, we attempt to understand the demands placed upon novices in learning to use Python Tutor for the first time. This includes analyzing students’ interaction with Python Tutor and observing how they use and interpret the features they see in the visualization. Methods: We conducted think-aloud interviews where students were asked to step through code samples on Python Tutor. We present our microgenetic analysis for one student and explore how he progressively builds an understanding of the representation and Python. Findings: We observed that Python Tutor visualizations include components that may be difficult for novices to understand. Python Tutor also does not provide any explanation for the keywords and technical terms it uses on the visualizations, likely making it difficult for novices to fully comprehend the visualizations. Implications: The results of this study can help in understanding and improving the design and features of Python Tutor that may be difficult for novices to comprehend. Additionally, our work can help educators understand challenges students may face when learning to understand the Python Tutor visualizations.
Graduation Semester
2024-05
Type of Resource
Thesis
Copyright and License Information
Copyright 2024 Niranjana Balasubramanian

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