{"id":"W7123913062","doi":"10.1109/fie63693.2025.11328198","title":"WIP: Multi-Agent Artificial Intelligence Model to Enhance Self-Regulated Learning and Conceptual Understanding in Computer Science Education","year":2025,"lang":"","type":"article","venue":"","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology; Mount Saint Vincent University","funders":"","keywords":"Artificial intelligence, situated approach; Learning sciences; Focus (optics); Conceptual model; Conceptual framework; Science learning; Cognition; Marketing and artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002392014,0.0005148951,0.0005291674,0.001295451,0.00117292,0.001365422,0.00103235,0.0001897718,0.00002208863],"category_scores_gemma":[0.0002434162,0.0005545677,0.00008259638,0.003268619,0.0005376764,0.001063805,0.001159603,0.0007953855,0.00006700203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001762585,"about_ca_system_score_gemma":0.002642571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002782525,"about_ca_topic_score_gemma":0.0001629286,"domain_scores_codex":[0.9947916,0.0002970927,0.00120316,0.001908599,0.0007031925,0.00109634],"domain_scores_gemma":[0.9981303,0.0002354768,0.0002777434,0.0004954887,0.0005147755,0.0003461844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000183652,0.0002671862,0.00065043,0.0000635822,0.00002277476,0.000004158936,0.02220367,0.3344963,0.002893544,0.5438594,0.00002517899,0.09549537],"study_design_scores_gemma":[0.0000758857,0.0001816764,0.0001548539,0.001367519,0.00001399916,0.000004974556,0.006734717,0.9783281,0.009898708,0.00196714,0.0007035179,0.000568901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04965256,0.0003112619,0.9445602,0.001248841,0.002369286,0.0008585161,5.7901e-7,0.0001737481,0.0008250124],"genre_scores_gemma":[0.8850942,0.00005458482,0.1073432,0.0004866571,0.0001205474,0.00002197562,7.918376e-7,0.00001856784,0.006859495],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.837217,"threshold_uncertainty_score":0.9996906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06440922632201972,"score_gpt":0.3377132946403404,"score_spread":0.2733040683183207,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}