{"id":"W3122939006","doi":"","title":"Are We Ethically Bound to Use Student Engagement Technologies for Teaching Law","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Clicker; Class (philosophy); Set (abstract data type); Student engagement; Competence (human resources); Legal education; Active learning (machine learning); Law; Political science; Mathematics education; Sociology; Pedagogy; Public relations; Psychology; Computer science; Social psychology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03908401,0.0004163774,0.0006093943,0.001025663,0.00521388,0.02265967,0.00191999,0.009091135,0.004608144],"category_scores_gemma":[0.1058197,0.0004530071,0.0004339617,0.0008613836,0.02808403,0.02063969,0.01048853,0.0122907,0.00345196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002776711,"about_ca_system_score_gemma":0.006873582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007127958,"about_ca_topic_score_gemma":0.0009049256,"domain_scores_codex":[0.9185979,0.06200129,0.001667125,0.003460271,0.0105979,0.003675574],"domain_scores_gemma":[0.8973013,0.06541688,0.009942407,0.008799836,0.008392811,0.01014673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001028565,0.0007748225,0.02641693,0.0006802033,0.00007943578,0.0005348481,0.1716416,0.0006825504,0.002839811,0.4358201,0.04820874,0.3122181],"study_design_scores_gemma":[0.00007813395,0.0005217544,0.00636434,0.002460102,0.00004509983,0.0008506958,0.1525359,0.00188411,0.004624601,0.3961833,0.4343062,0.0001457284],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.1041472,0.005496146,0.0450667,0.7476699,0.001883295,0.0001355811,0.00004055415,0.0002534637,0.09530716],"genre_scores_gemma":[0.8851517,0.004325784,0.01245406,0.07899486,0.0009226306,0.0003938703,0.00004807554,0.0002020286,0.01750682],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03908401,"threshold_uncertainty_score":0.2066984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335115211788556,"score_gpt":0.4551359659755377,"score_spread":0.3216244447966822,"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."}}