[Purpose/significance] The human-AI search context has significantly reshaped behavioral interactions and learning effect in learning-related search. This study aims to provide a comprehensive evaluation of learning effect and to examine how search tools and task types jointly influence learning outcomes. [Method/process] An experimen⁃tal method was adopted to design three types of learning-related search tasks: receptive, critical, and creative. Two kinds of search tools, traditional search engines and Generative AI (GenAI), were provided. Learning effect data were collected from users who completed different tasks with these tools. The analysis of learning effect was conducted from two perspectives: subjective learning experiences and objective learning outcomes.[Result/conclusion] Users′ learn⁃ing experiences were mainly influenced by task types, while the specific effect of the search tool used remained un⁃clear. In terms of learning outcomes, traditional search engines outperformed GenAI in receptive and critical tasks, par⁃ticularly in the number, coverage, and uniqueness of knowledge points as well as the depth of knowledge facets. For cre⁃ative tasks, however, both tools provided relatively limited support, with GenAI showing a slight advantage.