{"id":"W2079372207","doi":"10.1109/mitp.2014.78","title":"The Next Step for Learning Analytics","year":2014,"lang":"en","type":"article","venue":"IT Professional","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Learning analytics; Analytics; Computer science; Data science; Software analytics; Data analysis; Cultural analytics; Big data; Business intelligence; Business analytics; Semantic analytics; Web analytics; World Wide Web; Knowledge management; Data mining; Web intelligence; The Internet; Software; Management; Software development","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":[0.000858207,0.00008774382,0.00009781487,0.00003350878,0.0007452673,0.0001762457,0.0006335796,0.00005394452,0.00000610761],"category_scores_gemma":[0.000525113,0.00005408057,0.00007661382,0.0001573445,0.00003967589,0.000148758,0.0001775923,0.0002980318,0.00005530914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001086582,"about_ca_system_score_gemma":0.00009090402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001326073,"about_ca_topic_score_gemma":0.000004941554,"domain_scores_codex":[0.9989724,0.0001266204,0.0001740178,0.0002058412,0.0002560373,0.0002650464],"domain_scores_gemma":[0.9984915,0.0009441333,0.0001033473,0.0002735842,0.0001222762,0.00006518446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002441763,0.0001149751,0.005234368,0.00003894815,0.00005570387,0.000002057162,0.0005208188,0.00513138,0.0002472069,0.5855762,0.07116287,0.331891],"study_design_scores_gemma":[0.0001468371,0.00005192441,0.0005617421,0.00002302724,0.000003997881,0.000001368144,0.00008154621,0.6204517,0.00001573159,0.007172358,0.3714215,0.00006829682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004466603,0.00008110746,0.9151571,0.07629967,0.001345646,0.0001432636,8.990556e-7,0.0001687273,0.002336969],"genre_scores_gemma":[0.860368,0.00001924164,0.06669144,0.002437231,0.0008663459,0.00002586112,0.0000107,0.00002078827,0.06956036],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8559014,"threshold_uncertainty_score":0.5732068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03226958673053724,"score_gpt":0.3272596038051167,"score_spread":0.2949900170745794,"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."}}