{"id":"W3100118749","doi":"10.1177/016146811711900301","title":"Crossing Disciplinary Boundaries to Improve Technology-Rich Learning Environments","year":2017,"lang":"en","type":"article","venue":"Teachers College Record The Voice of Scholarship in Education","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Discipline; Learning analytics; Computer science; Instructional design; Leverage (statistics); Learning sciences; Educational technology; Modalities; Metaphor; Data science; Psychology; Mathematics education; Multimedia; Artificial intelligence; Sociology","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":[0.01127914,0.000565449,0.0007427382,0.002117569,0.003588436,0.01167293,0.002529713,0.001722068,0.005987671],"category_scores_gemma":[0.03579082,0.0003330536,0.0006061918,0.00154639,0.003573329,0.009831467,0.01658395,0.002592165,0.001785337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001650196,"about_ca_system_score_gemma":0.004904426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005749363,"about_ca_topic_score_gemma":0.00117058,"domain_scores_codex":[0.9882322,0.006227859,0.001156064,0.001747331,0.002006302,0.0006303136],"domain_scores_gemma":[0.9729951,0.01237208,0.002496978,0.004544134,0.003660934,0.003930813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001163039,0.00175452,0.03114555,0.002135034,0.0001045652,0.0008331586,0.08056942,0.005223682,0.008549433,0.1388326,0.01082172,0.719914],"study_design_scores_gemma":[0.0000932719,0.00120727,0.02878081,0.004249085,0.0001704564,0.001611081,0.1032858,0.008965112,0.01537861,0.3873599,0.4487223,0.0001764241],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3939644,0.009223412,0.3999404,0.02425916,0.0008778956,0.001122383,0.0002298855,0.002072296,0.1683102],"genre_scores_gemma":[0.7029523,0.002548035,0.2812773,0.003084956,0.0001123244,0.0008978985,0.0002109016,0.000209343,0.008706915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01167293,"threshold_uncertainty_score":0.05965048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0397844839805093,"score_gpt":0.3969004660544729,"score_spread":0.3571159820739636,"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."}}