{"id":"W4392153281","doi":"10.1109/upcon59197.2023.10434888","title":"Improving Personalized Education: A Machine Learning Method for Flexible Learning Environments","year":2023,"lang":"en","type":"article","venue":"","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Personalized learning; Artificial intelligence; Machine learning; Robot learning; Human–computer interaction; Multimedia; Teaching method; Open learning; Mathematics education; Robot; Cooperative learning; Mobile robot","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":[],"consensus_categories":[],"category_scores_codex":[0.0008496495,0.0001462998,0.0001746435,0.0001885197,0.0004100034,0.0001767854,0.0004105077,0.00005707583,0.00005034307],"category_scores_gemma":[0.000320546,0.0001367593,0.0001193694,0.0005171464,0.00001902224,0.0002314333,0.0002170917,0.0003149004,0.0002008366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004357265,"about_ca_system_score_gemma":0.0001126358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008713335,"about_ca_topic_score_gemma":0.000001813015,"domain_scores_codex":[0.9986408,0.0001310518,0.0001969575,0.0004399929,0.0002354758,0.0003557452],"domain_scores_gemma":[0.9992482,0.000279678,0.0001169252,0.0002231871,0.00003046375,0.0001015627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001560337,0.0001410878,0.003969152,0.0001049735,0.00007501129,0.000004883885,0.001901654,0.03729806,0.00958098,0.05677402,0.001908571,0.888226],"study_design_scores_gemma":[0.000287099,0.00009198995,0.0001305352,0.00001157442,0.00001110598,0.000005537595,0.0002808189,0.8283526,0.0003470925,0.001078327,0.1692459,0.0001574009],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001063254,0.0001187902,0.9923812,0.003672861,0.000198622,0.0001336026,7.467194e-7,0.0009736818,0.001457297],"genre_scores_gemma":[0.03050615,0.00004203295,0.6243691,0.0003894441,0.0002233017,0.00005134329,0.00006775074,0.00003375998,0.344317],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8880686,"threshold_uncertainty_score":0.5576882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02010527971335934,"score_gpt":0.3227371523356509,"score_spread":0.3026318726222916,"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."}}