Usability-Driven Design of Educational Technology Platforms

Authors

  • Marco Petrov Associate Professor, Department of Machine Learning, European Institute of AI, Berlin, Germany Author
  • Jonas Garcia Research Scientist, Department of Computer Science, Swiss Institute of Machine Intelligence, Zurich, Switzerland Author
  • Isabella Novak Research Scientist, Department of Artificial Intelligence, Western Europe Data Science University, Madrid, Spain Author

Keywords:

usability, educational technology, UX design, heuristic evaluation, user-centred design, cognitive load, edtech, learning effectiveness

Abstract

Usability -- the degree to which a platform enables users to achieve their goals effectively, efficiently, and with satisfaction (ISO 9241-11) -- is a foundational determinant of educational technology adoption and learning effectiveness. A platform that is difficult to navigate, cognitively overwhelming, or inconsistent in interaction design imposes extraneous cognitive load that reduces working memory capacity available for learning, increases task abandonment, and ultimately drives learner disengagement. Despite its importance, usability evaluation is inconsistently applied in edtech development: many platforms are developed with feature-first rather than learner-experience-first design processes, resulting in high-capability but low-usability platforms that underperform their educational potential. This paper proposes the Usability-Driven Educational Technology Design Framework (UDETF), a systematic methodology integrating usability evaluation, user-centred design (UCD) iteration, and learning effectiveness measurement across 22 edtech platforms in six educational sectors. UDETF evaluates five usability dimensions -- learnability, efficiency, memorability, error tolerance, and satisfaction -- and applies four evaluation methods (heuristic evaluation, cognitive walkthrough, think-aloud usability testing, and log-based analytics) across 2,640 learner sessions. UDETF introduces the EdTech Usability Score (EUS) and demonstrates that high-usability platforms achieve 28.4% higher learning gains and 42.4% lower dropout rates than low-usability equivalents. The framework provides a practical usability-driven design process for edtech product teams.

Author Biographies

  • Marco Petrov, Associate Professor, Department of Machine Learning, European Institute of AI, Berlin, Germany

    Associate Professor, Department of Machine Learning, European Institute of AI, Berlin, Germany

  • Jonas Garcia, Research Scientist, Department of Computer Science, Swiss Institute of Machine Intelligence, Zurich, Switzerland

    Research Scientist, Department of Computer Science, Swiss Institute of Machine Intelligence, Zurich, Switzerland

  • Isabella Novak, Research Scientist, Department of Artificial Intelligence, Western Europe Data Science University, Madrid, Spain

    Research Scientist, Department of Artificial Intelligence, Western Europe Data Science University, Madrid, Spain

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Published

2025-08-01

How to Cite

Usability-Driven Design of Educational Technology Platforms. (2025). Journal of Digital Learning Futures P-ISSN 3117-6054 and E-ISSN 3117-6062, 2(3), 33-40. https://galaxiauniverse.com/index.php/JDLF/article/view/398