{"id":"W2936846186","doi":"10.1007/978-3-030-11434-3_36","title":"An Active Learning Strategy for Programming Courses","year":2019,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Innovative Teaching Methods","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hamilton Health Sciences","funders":"","keywords":"Debugging; Active learning (machine learning); Recall; Class (philosophy); Mathematics education; Computer science; Coding (social sciences); Reinforcement; Psychology; Artificial intelligence; Programming language; Cognitive psychology; Mathematics; Social 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006425734,0.0004533484,0.0002179019,0.0005761772,0.0009536462,0.003439071,0.001474352,0.001037324,0.01886764],"category_scores_gemma":[0.002125227,0.0001670258,0.0003079042,0.0005724058,0.000749037,0.004771648,0.002001977,0.001663244,0.004491514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008525305,"about_ca_system_score_gemma":0.001106545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004927436,"about_ca_topic_score_gemma":0.001177273,"domain_scores_codex":[0.9994447,0.0001928196,0.00001416194,0.00009499885,0.0001976262,0.00005571437],"domain_scores_gemma":[0.9991516,0.0004022002,0.00003839594,0.00008102185,0.0001456438,0.000181212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005398771,0.0003270596,0.0003806793,0.0001093408,0.000006993219,0.00008690119,0.002169967,0.000871382,0.002255831,0.5532116,0.0260023,0.4145239],"study_design_scores_gemma":[0.00006867362,0.0003155385,0.001588439,0.0002903151,0.00002490944,0.0003614026,0.003875208,0.01966088,0.004129766,0.5042598,0.4653953,0.00002979562],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02568205,0.001062456,0.3151024,0.003583609,0.0004830313,0.0001860442,0.00005322179,0.0005798278,0.6532673],"genre_scores_gemma":[0.259812,0.0009991557,0.1219766,0.0008496432,0.0002248332,0.0003172958,0.0001732787,0.0003300953,0.615317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01886764,"threshold_uncertainty_score":0.06311858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06744129641568486,"score_gpt":0.4193019224435182,"score_spread":0.3518606260278334,"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."}}