{"id":"W4385218009","doi":"10.3390/psych5030050","title":"An Introduction to Bayesian Knowledge Tracing with pyBKT","year":2023,"lang":"en","type":"article","venue":"Psych","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton; University of Alberta","funders":"","keywords":"Python (programming language); Computer science; Tracing; Probabilistic logic; Bayesian probability; Machine learning; Statistical model; Data mining; Artificial intelligence; Data science; Programming language","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":[0.004423205,0.001313187,0.001056362,0.001844644,0.0007912457,0.004730291,0.003446002,0.002083265,0.05070179],"category_scores_gemma":[0.02599025,0.001664955,0.002448004,0.002726445,0.001563794,0.005404357,0.00475795,0.005999298,0.02021032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001603483,"about_ca_system_score_gemma":0.003163515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005232983,"about_ca_topic_score_gemma":0.004898572,"domain_scores_codex":[0.9971324,0.001053134,0.0002745991,0.000456864,0.0009115743,0.0001713308],"domain_scores_gemma":[0.9929276,0.004868236,0.000410288,0.0009335392,0.0006212678,0.0002390076],"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":[0.0002185235,0.0002317993,0.003305668,0.001245974,0.0001672879,0.0005713454,0.001037513,0.06410571,0.002349053,0.4358138,0.1092443,0.3817091],"study_design_scores_gemma":[0.00004942744,0.00004169486,0.001122665,0.0004713069,0.00002985173,0.000556295,0.0000812725,0.2694129,0.002453802,0.4618265,0.2638308,0.0001234603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003689817,0.0003920666,0.9822694,0.0006669723,0.0001445171,0.00008778719,0.00150945,0.01066302,0.003897835],"genre_scores_gemma":[0.02511288,0.001782203,0.9536494,0.001143757,0.0003315139,0.0009868141,0.003229035,0.005268757,0.008495565],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05070179,"threshold_uncertainty_score":0.1696144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02006556139158163,"score_gpt":0.2958401694424989,"score_spread":0.2757746080509173,"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."}}