{"id":"W4387547293","doi":"10.18162/ritpu-2023-v20n2-10","title":"Reflection on the Construction and Impact of an Adaptive Learning Ecosystem","year":2023,"lang":"fr","type":"article","venue":"Revue internationale des technologies en pédagogie universitaire","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Reflection (computer programming); Context (archaeology); Metacognition; Domain (mathematical analysis); Learning analytics; Adaptive learning; Analytics; Conceptual model; Knowledge management; Data science; Artificial intelligence; Cognition; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003446226,0.0001737712,0.0001915,0.0005137118,0.0003105326,0.0000925286,0.0006322876,0.0002126035,0.000009942169],"category_scores_gemma":[0.0006600172,0.000151359,0.0001295844,0.0009930506,0.0004004004,0.0005893692,0.0003684069,0.0005282479,0.00003238716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000503349,"about_ca_system_score_gemma":0.0001122525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001047001,"about_ca_topic_score_gemma":0.00007536115,"domain_scores_codex":[0.9988248,0.0001950888,0.0001988276,0.0003512392,0.0001977123,0.0002322857],"domain_scores_gemma":[0.9985521,0.0005790648,0.0002551787,0.0003034525,0.0002778466,0.00003233733],"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":[0.0000437816,0.000059494,0.006920546,0.00008572639,0.0002764658,0.0001101622,0.001859589,0.05512147,0.000359329,0.1614625,0.0001925832,0.7735083],"study_design_scores_gemma":[0.0003597196,0.003155707,0.005359311,0.001311718,0.00007035492,0.0003668964,0.04621784,0.914886,0.0009917022,0.01792271,0.009011368,0.0003466549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793444,0.000308978,0.00485555,0.01307235,0.0003069816,0.0001256349,0.00003097225,0.0007842542,0.001170858],"genre_scores_gemma":[0.9759732,0.00151593,0.002877396,0.000003463509,0.00006024949,0.000001993818,0.0000115423,0.0000127906,0.01954346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8597645,"threshold_uncertainty_score":0.6172242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05677332988425581,"score_gpt":0.3095642010554347,"score_spread":0.2527908711711789,"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."}}