{"id":"W3168521265","doi":"10.31046/wabashcenter.v2i2.1559","title":"Active Learning in Lecture-Based Courses","year":2021,"lang":"en","type":"article","venue":"The Wabash Center Journal on Teaching","topic":"Education and Critical Thinking Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Mathematics education; Active learning (machine learning); Pedagogy; Student engagement; Psychology; Computer science; 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":[],"consensus_categories":[],"category_scores_codex":[0.002014867,0.00007665185,0.0000995763,0.00006550675,0.001219121,0.0002193333,0.0001873739,0.00003865838,0.0004170877],"category_scores_gemma":[0.001236866,0.00005521606,0.00006738653,0.0001238425,0.00006697488,0.00009833287,0.00001961656,0.00139036,0.00003917156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002942815,"about_ca_system_score_gemma":0.0004624132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003531567,"about_ca_topic_score_gemma":0.0001268073,"domain_scores_codex":[0.9975799,0.001446929,0.0001652468,0.0001117013,0.0004141706,0.0002820786],"domain_scores_gemma":[0.9992659,0.0004237576,0.00006722787,0.00007116589,0.00007131656,0.0001006407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001735823,0.001920532,0.06993737,0.00002103209,0.0001322113,0.0003531235,0.3287345,0.002589292,0.000578034,0.1380997,0.005753137,0.4517075],"study_design_scores_gemma":[0.00164422,0.00009362694,0.02254802,0.000924194,0.0000257136,0.00006383973,0.06073491,0.0001783552,0.001807159,0.02161257,0.8899319,0.0004355372],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7943537,0.0001593525,0.002707417,0.1311229,0.001836072,0.0001113672,9.397858e-7,0.00006598742,0.06964223],"genre_scores_gemma":[0.9921623,0.00004713269,0.0004453098,0.00565144,0.0003196944,0.000002114946,0.00000193415,0.000008353647,0.001361718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8841787,"threshold_uncertainty_score":0.9376618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02530915277571123,"score_gpt":0.3424458119642029,"score_spread":0.3171366591884917,"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."}}