{"id":"W4415929319","doi":"10.4018/979-8-3373-7729-2.ch004","title":"Transforming Curriculum Design with AI Learning Analytics in the University Context","year":2025,"lang":"","type":"book-chapter","venue":"Advances in computational intelligence and robotics book series","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West; Western University","funders":"","keywords":"Curriculum; Learning analytics; Context (archaeology); Analytics; Preparedness; Key (lock); Applications of artificial intelligence; Big data; Instructional design","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006535334,0.0005915495,0.0006760932,0.0005867665,0.0006481739,0.0002771938,0.0009382236,0.0002369079,0.00001545736],"category_scores_gemma":[0.00007254649,0.0004902293,0.0001207815,0.000663068,0.0009372478,0.002179842,0.0001758366,0.001744985,0.000008361956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001365038,"about_ca_system_score_gemma":0.0005240775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003682495,"about_ca_topic_score_gemma":0.0003523482,"domain_scores_codex":[0.997064,0.0002564623,0.0007567111,0.0008413264,0.0005995233,0.0004820119],"domain_scores_gemma":[0.9973421,0.001535702,0.0003523917,0.0002760813,0.0004049479,0.00008876519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004045176,0.00004174644,0.0005568381,0.00008766558,0.00002857125,0.0001361091,0.001120132,0.5519964,4.199989e-8,0.424183,0.000003908869,0.02180512],"study_design_scores_gemma":[0.0002301127,0.0006507723,0.00003858553,0.001937142,0.00009020387,0.00008628036,0.003795445,0.8944152,0.000004437426,0.0661157,0.0320157,0.0006203917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00001528575,0.008757507,0.9798548,0.005879158,0.0001612071,0.0004383217,0.000005987842,0.00003692575,0.004850775],"genre_scores_gemma":[0.5938886,0.1312721,0.237425,0.002396718,0.0002030045,0.000008457439,0.00008280585,0.00007778573,0.03464551],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7424298,"threshold_uncertainty_score":0.999755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01910787778350669,"score_gpt":0.2688826993823245,"score_spread":0.2497748215988178,"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."}}