This study explores the use of video analysis and Optical Character Recognition (OCR) to generate accurate logs for tracking user search behaviors for external resources during collaborative problem-solving activities on the RoboReady educational platform. The research included 15 teams of engineering students who interacted with a website designed around the PISA 2015 collaborative problem-solving framework. Video recordings of the user’s screens were analyzed using image processing and OCR to extract URLs and timestamps of visited web pages. The study compares these logs with those collected through server-side tracking, noting the limitations of the latter in capturing external resource usage. The methodology includes frame extraction, URL isolation, and text recognition using Tesseract OCR and Google Cloud Vision API. Challenges like noisy OCR output and the necessity for manual verification are addressed. The generated logs provide insights into user’s navigation and resource usage. However, limitations such as video quality dependency, scalability issues, and the need for manual intervention are also discussed. This research enhances the understanding of user’s behavior in online learning environments and offers methodological insights for studying digital learning interactions.