2026-10-14T18:06:26Z https://www.scidb.cn/oai

10.57760/sciencedb.43992 2026-07-23T15:16:59Z

2026-07-23 Dataset of SAG Learning Intervention Integrating Socratic Questioning, Agentic AI and Generative AI in Computing Literacy Course doi:10.57760/sciencedb.43992 en Research Topic: Construct the SAG learning model (Socratic Questioning + Agentic AI + Generative AI) for senior high school Computing Literacy (CL) courses. A 12-week quasi-experiment was conducted to compare the effects of the SAG model and the pure GAI learning model on senior high students’ digital competence, critical thinking, AI usage behaviors, and classroom learning experience.Data Collection Period: March 2026 – July 2026 (a full semester, 12-week instructional intervention)Research Site: Public senior high school in Guangdong Province, ChinaParticipants: 145 Grade 10 students divided into two groupsSAG Experimental Group: 75 students GAI Control Group: 70 studentsCourse Context: Mandatory Computing Literacy course, 1 session per week (40 mins per session) in computer labs. Curriculum covers information systems, networks, software, programming, cybersecurity, artificial intelligence, big data, etc.AI Tools Used: Agentic AI (WorkBuddy), Generative AI (Doubao)Research Design: Mixed-methods research (quantitative quasi-experiment + coding of AI interaction logs + semi-structured teacher interviews)Ethical Statement: The study was approved by the school ethics committee. Informed consent was obtained from all students, guardians, and the instructor. All data was anonymized to eliminate risks of personal sensitive information leakage. SAG learning model; Socratic Questioning; Agentic AI; Generative AI; Digital Competence; Critical Thinking; Senior High Computing Literacy Course; Quasi-experiment LYU QUANPIN RESTRICTED dataset Science Data Bank