ChatGPT vs. Google in terms of navigation performance and self-learning success

Research purpose was to compare students' experiences of learning code via ChatGPT and Google in terms of navigation performance and academic success. The independent variables was age, gender, JavaScript experience, and ChatGPT usage, while the dependent variables was Navigation Performance Score (Disorientation, Satisfaction, Cognitive Load) and Test Score. Data collected from 471 fully distance education students from Web Design and Coding program. Navigation performance was measured using the Hyper-MNP scale developed by Firat and Kabakci Yurdakul (2016). The scale consists of a total of 15 items, 7 of which are positive statements and 8 of which are negative statements. The scale has a three-factor structure including disorientation (6 items), satisfaction (5 items), and cognitive load (4 items). The items are 5-point Likert type. Welch's t-test results showed a significant difference in favor of ChatGPT for all dependent variables.