A Learning Analytics Dashboard for Improved Learning Outcomes and Diversity in Programming Classes

Iris Groher, Michael Vierhauser

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

The increased emphasis on competency management and learning objectives in higher education has led to a rise in Learning Analytics (LA) applications. These tools play a vital role in measuring and optimizing learning outcomes by analyzing and interpreting student-related data. LA tools furthermore provide course instructors with insights on how to refine teaching methods and material and address diversity in student performance to tailor instruction to individual needs. This tool demonstration paper introduces our Learning Analytics Dashboard, designed for an introductory Python programming course. With a focus on gender diversity, the dashboard analyzes graded Jupyter Notebooks, to provide insights into student performance across assignments and exams. An initial assessment of the dashboard, applying it to our Python programming course in the previous year, has provided us with interesting insights and information on how to further improve our class and teaching materials. We present the dashboard’s design, features, and outcomes while outlining our plans for its future development and enhancement.
Original languageEnglish
Title of host publicationIn Proceedings of the 16th International Conference on Computer Supported Education (CSEDU 2024), May 2-4, 2024, Angers, France.
EditorsOleksandra Poquet, Alejandro Ortega-Arranz, Olga Viberg, Irene-Angelica Chounta, Bruce McLaren, Jelena Jovanovic
Pages618-625
Number of pages8
Volume2
ISBN (Electronic)9789897586972
DOIs
Publication statusPublished - May 2024

Publication series

NameInternational Conference on Computer Supported Education, CSEDU - Proceedings
Volume2
ISSN (Electronic)2184-5026

Fields of science

  • 102006 Computer supported cooperative work (CSCW)
  • 102015 Information systems
  • 102016 IT security
  • 102020 Medical informatics
  • 102022 Software development
  • 102027 Web engineering
  • 102034 Cyber-physical systems
  • 509026 Digitalisation research
  • 102040 Quantum computing 
  • 502032 Quality management
  • 502050 Business informatics
  • 503015 Subject didactics of technical sciences

JKU Focus areas

  • Digital Transformation

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