Comparing the Effects of GenAI and Traditional Search on Scientific Concept Understanding in a Simulation-Based Video Lecture: An Eye-Tracking Study

Using search tools for help-seeking during simulation-based video lectures has become increasingly popular and important. Intelligence search tools (such as GenAI) and traditional search engines, two of the most commonly used search methods, can aid students’ learning of scientific concepts. However, few studies have investigated how different search modes influence students’ understanding of these concepts. The present study aimed to identify the effects of GenAI search and traditional search on students’ understanding of scientific concepts in a simulation-based video lecture, focusing on visual attention, behavioral patterns, cognitive load, and learning performance. Our study adopted a between-subjects design with two experimental conditions: (a) Traditional search (n = 28) and (b) GenAI search (n = 29). We assigned participants to watch a video lecture, during which they could choose to operate a virtual simulation experiment or search for relevant information in a designated search area. Participants’ eye movements, behavior patterns, cognitive load and learning performance were measured and analyzed. The result revealed that traditional search prompted sustained attention to video learning materials, while GenAI search increased cross-area visual scanning and showed more frequent information search behavior. In addition, students’ retention performance improved, although their transfer performance did not show a significant increase in GenAI search. Furthermore, there was no significant difference in cognitive load between the two conditions. These results suggest that although GenAI encourages students to organize and process more information in the active exploration region, it has notable limitations in supporting deeper, context-dependent understanding and deductive reasoning regarding abstract concepts.