{"id":"W7123421001","doi":"10.1109/fie63693.2025.11328607","title":"An Approach to Learning Path Personalization in E-Tutoring with Knowledge Space Theory","year":2025,"lang":"","type":"article","venue":"","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Personalization; Representation (politics); Ontology; Space (punctuation); Knowledge space; Path (computing); Domain (mathematical analysis); Intelligent tutoring system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002617473,0.0004746043,0.0004866437,0.001160118,0.0008216826,0.002941841,0.002085504,0.00119377,0.004161408],"category_scores_gemma":[0.009136233,0.0003970565,0.0007262179,0.001028653,0.002714907,0.004532513,0.00364109,0.001763801,0.0004977374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414056,"about_ca_system_score_gemma":0.00142364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001336582,"about_ca_topic_score_gemma":0.001535028,"domain_scores_codex":[0.9970847,0.001658097,0.0001139867,0.0004570056,0.0005595978,0.0001266442],"domain_scores_gemma":[0.9956064,0.002648646,0.000275158,0.0008622151,0.0003750669,0.0002326226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001305635,0.0004511625,0.002700815,0.0003254822,0.00009199015,0.0001868169,0.007229641,0.06122801,0.005467101,0.6175946,0.001662752,0.3029312],"study_design_scores_gemma":[0.00006596871,0.0002627359,0.001385895,0.000111533,0.00006730466,0.0003186468,0.001556016,0.4381204,0.005572133,0.5117063,0.04077386,0.00005919236],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009498117,0.000187162,0.9819098,0.0005450542,0.00002556295,0.00008805609,0.00002097234,0.000228528,0.007496851],"genre_scores_gemma":[0.4131711,0.0002787449,0.5822639,0.0001272106,0.00004965304,0.0002904444,0.00005244962,0.00007474519,0.003691654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004161408,"threshold_uncertainty_score":0.01392132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492118434430811,"score_gpt":0.2668517292839177,"score_spread":0.2519305449396096,"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."}}