{"id":"W1759801701","doi":"","title":"ON IMPROVING THE EFFECTIVENESS OF OPEN LEARNING ENVIRONMENTS THROUGH TAILORED SUPPORT FOR EXPLORATION","year":2001,"lang":"en","type":"article","venue":"","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Active learning (machine learning); Learning environment; Bayesian network; Human–computer interaction; Domain (mathematical analysis); Personalized learning; Knowledge management; Artificial intelligence; Open learning; Cooperative learning; Teaching method; Mathematics education; Psychology","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":[0.001378254,0.00009781312,0.0001406758,0.00002600866,0.0002256409,0.0001654468,0.0007041144,0.00003079138,0.00001342814],"category_scores_gemma":[0.0001289985,0.00006520042,0.00005332712,0.0001041406,0.00001774151,0.0008902263,0.0002367472,0.00009832709,0.0000251736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004521511,"about_ca_system_score_gemma":0.00002104596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001355021,"about_ca_topic_score_gemma":0.000001520106,"domain_scores_codex":[0.9989326,0.0002569736,0.0001868506,0.0002715945,0.0001781222,0.0001738772],"domain_scores_gemma":[0.9989892,0.0005541489,0.000140489,0.000267597,0.00003074671,0.00001787715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001271975,0.00006899732,0.000899141,0.00003845542,0.00003024139,0.000002506748,0.001155616,0.02487522,0.02509793,0.9306799,0.00003624332,0.01698853],"study_design_scores_gemma":[0.003737709,0.006069093,0.01371072,0.0006039451,0.00004318357,0.00002758655,0.002729309,0.1503653,0.5092632,0.03936586,0.2728994,0.001184752],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01711163,0.000006786882,0.9768116,0.00005747711,0.0002138338,0.0006806771,1.977825e-7,0.00002934041,0.00508844],"genre_scores_gemma":[0.9865636,0.000004062545,0.003985032,0.00004825339,0.00003765282,0.0001141325,0.000003107846,0.00001003103,0.009234158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9728266,"threshold_uncertainty_score":0.2658796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04748328725309171,"score_gpt":0.2922673610560457,"score_spread":0.244784073802954,"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."}}