{"id":"W4367548848","doi":"10.1007/s10639-023-11804-7","title":"Multimodal learning analytics for assessing teachers’ self-regulated learning in planning technology-integrated lessons in a computer-based environment","year":2023,"lang":"en","type":"article","venue":"Education and Information Technologies","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; Fonds de Recherche du Québec-Société et Culture","keywords":"Context (archaeology); Learning analytics; Self-regulated learning; Salient; Think aloud protocol; Educational technology; Computer science; Analytics; Mathematics education; Data science; Psychology; Human–computer interaction; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005216412,0.0001533899,0.0001938285,0.002118703,0.0002010314,0.0002581537,0.0002974852,0.0002370403,8.127647e-7],"category_scores_gemma":[0.0004126879,0.0001541678,0.00003000872,0.001783881,0.00006026978,0.001168209,0.000125994,0.0006032128,0.00001213208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001591201,"about_ca_system_score_gemma":0.0002079277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001293378,"about_ca_topic_score_gemma":0.000001883274,"domain_scores_codex":[0.9989096,0.00004446341,0.0004083029,0.0002205804,0.0001319228,0.0002851214],"domain_scores_gemma":[0.9993694,0.0001276729,0.0002322808,0.0001859396,0.00006075322,0.0000239148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002133721,0.00009612295,0.04658388,0.00003779156,0.000009060226,9.210527e-7,0.00338222,0.3467945,0.00006077979,0.002464806,0.00007282379,0.6004949],"study_design_scores_gemma":[0.0004529351,0.00007903159,0.0164165,0.0001702153,0.000004040684,0.000002328583,0.01114948,0.9640806,0.000219519,0.0007821257,0.006467262,0.0001759112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5993446,0.0000856482,0.379019,0.01764135,0.0001163998,0.0002861373,9.619474e-7,0.003446505,0.00005938374],"genre_scores_gemma":[0.9116252,0.00005345891,0.08809338,0.00004045905,0.00000823199,0.00005304809,0.00007010296,0.000006939664,0.0000491613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6172861,"threshold_uncertainty_score":0.6286779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01571063352902556,"score_gpt":0.2955188446605152,"score_spread":0.2798082111314896,"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."}}