Exploring Computer Engineering Students' Perceptions When Introduced to Low-Code Platforms: A Study Using Inquiry Methods and Eye-Tracking Data

This work explores the initial interactions and perceptions of computer engineering students who have no prior experience with low-code platforms. Specifically, undergraduate computer engineering students participated in a comprehensive experiment at the Human-Computer Interaction Laboratory at the University of Patras, adhering to a structured experimental protocol encompassing questionnaire completion, exposure to an introductory video on low-code concepts, eye-tracking analysis, interaction with the platform, and interview. The investigation aims to uncover the perspectives of computer engineering students as they encounter a low-code platform for the first time, leveraging concurrent eye-tracking data to gain insights into their focal areas, the patterns that emerged in their approaches to tasks, and the elements that captured their attention. The findings suggest that students demonstrated efficient and swift recognition skills, showcasing various patterns in their task approaches, unveiling a spectrum of strategies and preferences. Interviews conducted post-interaction unveiled positive sentiments, with the majority acknowledging the low-code platform's effectiveness in minimizing application development time. Notably, ease of use emerged as a prominent aspect, with a substantial number finding the platform exceptionally user-friendly.