Designing AI-Based Learning Assistant to Elevate Computational Thinking: A UX-Focused Redesign Approach - Hikmawan, Rizki; Rohendi, Dedi; Septiadi, Jaka; Arrumaisha, Nissa (Jurnal Paedagogy, 2025)
This study aims to evaluate and enhance the User Experience (UX) of SEKAPAI, a web-based AI learning assistant developed to support Computational Thinking (CT) development. The initial version was assessed using Cognitive Walkthrough, System Usability Scale (SUS), and User Experience Questionnaire (UEQ), involving ten participants. Data collected from these instruments were analyzed using descriptive statistics to quantify usability scores, and qualitative feedback from the walkthroughs was subjected to thematic analysis to identify pain points. The preliminary results showed a success rate of 90%, but also revealed issues in clarity and feature navigation. Based on user feedback, the platform underwent a redesign process guided by User-Centered Design (UCD) stages, resulting in improvements in structure, interaction flow, and interface clarity. The updated prototype showed clear improvements, supported by Maze testing with a UX score of 80 (’Good’) and a SUS increase to 86 (’Excellent’), and the task success rate improved to 97.14%, indicating a significant enhancement in user satisfaction and efficiency. This study not only validates the effectiveness of UCD in refining AI-based learning tools but also highlights the potential for future system development. These findings contribute to the design methodology of intelligent educational systems by aligning pedagogical goals with interactive design strategies.