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Massive Open Online Courses (MOOCs) have become a proven and well-established educational practice, offering flexible and accessible learning opportunities to millions of people. These courses are delivered through electronic platforms. Hence, it is essential to ensure high levels of engagement and satisfaction. Achieving this requires high-quality of user experience (UX) that meets the needs of diverse learners. This study explores the usability of the All-Digital Academy (ADA) platform by combining two established UX evaluation methods: heuristic evaluation (HE) and user testing (UT). To this end, three (3) UX experts and 13 users were asked to interact with ADA platform. Results demonstrate that each method offers unique insights. More specifically, HE efficiently identified high-level design flaws, such as poor navigation consistency and error prevention gaps. Conversely, UT captured detailed user behaviors and preferences, highlighted task-specific challenges by providing direct feedback on system usability. For instance, users faced difficulties with complex tasks like finding specific learning content, reflected in lower success rates and longer task completion times. Despite these challenges, the ADA platform achieved a high SUS score of 74.2, indicating good usability. However, the study is limited by its focus on a single MOOC platform and a relatively small sample (13 users), which may affect the generalizability of the findings. Future work should explore the scalability of these methods across diverse platforms and larger, more varied participant groups. Additionally, AI-based interaction monitoring tools can be employed to enhance the evaluation of MOOC platforms. More specifically, real-time emotion recognition, eye-tracking, and behavioral analysis could provide deeper insights into user engagement and interaction patterns. By identifying subtle usability challenges and offering data-driven personalization opportunities, these tools can support the optimization of both the design and overall UX of MOOC platforms.

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Combining Heuristics and User Testing: Towards a Holistic Approach in User eXperience (UX) Evaluation of Open MOOC Platforms

  • 会议论文

  • 发表日期：

    2025年

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  • Alexandros Liapis,
  • Eleni Georgakakou,
  • Achilles Kameas

摘要

Massive Open Online Courses (MOOCs) have become a proven and well-established educational practice, offering flexible and accessible learning opportunities to millions of people. These courses are delivered through electronic platforms. Hence, it is essential to ensure high levels of engagement and satisfaction. Achieving this requires high-quality of user experience (UX) that meets the needs of diverse learners. This study explores the usability of the All-Digital Academy (ADA) platform by combining two established UX evaluation methods: heuristic evaluation (HE) and user testing (UT). To this end, three (3) UX experts and 13 users were asked to interact with ADA platform. Results demonstrate that each method offers unique insights. More specifically, HE efficiently identified high-level design flaws, such as poor navigation consistency and error prevention gaps. Conversely, UT captured detailed user behaviors and preferences, highlighted task-specific challenges by providing direct feedback on system usability. For instance, users faced difficulties with complex tasks like finding specific learning content, reflected in lower success rates and longer task completion times. Despite these challenges, the ADA platform achieved a high SUS score of 74.2, indicating good usability. However, the study is limited by its focus on a single MOOC platform and a relatively small sample (13 users), which may affect the generalizability of the findings. Future work should explore the scalability of these methods across diverse platforms and larger, more varied participant groups. Additionally, AI-based interaction monitoring tools can be employed to enhance the evaluation of MOOC platforms. More specifically, real-time emotion recognition, eye-tracking, and behavioral analysis could provide deeper insights into user engagement and interaction patterns. By identifying subtle usability challenges and offering data-driven personalization opportunities, these tools can support the optimization of both the design and overall UX of MOOC platforms.