{"id":"W2587818513","doi":"10.22318/icls2016.175","title":"Real-time visualization of student activities to support classroom orchestration","year":2016,"lang":"en","type":"article","venue":"International Conference of Learning Sciences","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Orchestration; Visualization; Computer science; Human–computer interaction; Data visualization; Multimedia; 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":[0.001026634,0.00009779606,0.0001588586,0.0002724606,0.00009262403,0.0001312466,0.0009031712,0.00003530346,0.0001568401],"category_scores_gemma":[0.0003027377,0.00007128719,0.00004688495,0.000254186,0.0001299319,0.0007980487,0.0001568126,0.00004962382,0.00003875723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005447977,"about_ca_system_score_gemma":0.0002010725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005775154,"about_ca_topic_score_gemma":0.000004239011,"domain_scores_codex":[0.9982589,0.0001474896,0.0003569237,0.0002992236,0.0007775977,0.0001598511],"domain_scores_gemma":[0.9987409,0.0002941032,0.000361291,0.0001204022,0.0004378835,0.00004546372],"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":[0.000008439937,0.00003184391,0.02798599,0.000005932744,0.0000148008,9.543051e-7,0.001800822,0.0009483144,0.3722572,0.58805,0.00002215594,0.008873578],"study_design_scores_gemma":[0.001487214,0.009412069,0.2076889,0.003254107,0.00003174032,0.00005864844,0.00890677,0.04662274,0.6940587,0.008961367,0.01781777,0.001699991],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5834635,0.000002019619,0.3936019,0.0005497169,0.0003841761,0.00009722788,0.000001801381,0.00006070916,0.02183897],"genre_scores_gemma":[0.9881604,0.00001343974,0.005150207,0.000007505266,0.00005124155,0.000006098006,0.000001108131,0.00000395483,0.006606041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5790886,"threshold_uncertainty_score":0.2907007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07039243338493613,"score_gpt":0.3517719638282765,"score_spread":0.2813795304433404,"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."}}