{"id":"W4405629337","doi":"10.70637/xvc8m613","title":"L’utilisation de ChatGPT 3.5 pour la rétroaction corrective écrite interactive en enseignement-apprentissage du français langue seconde : une étude exploratoire","year":2024,"lang":"en","type":"article","venue":"Actes des Journées de linguistique","topic":"Text Readability and Simplification","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Corrective feedback; Affordance; Psychology; Quality (philosophy); Perception; Computer science; Affect (linguistics); Language acquisition; Mathematics education; Pedagogy; Communication; Cognitive psychology","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":[0.0008103846,0.000247078,0.0002098517,0.0002166737,0.0002534029,0.0006950601,0.000407257,0.0001948455,0.00006673671],"category_scores_gemma":[0.001265961,0.0002472183,0.0001365227,0.0004274503,0.00008882242,0.0009417401,0.000103268,0.0005949035,0.00005896186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005894363,"about_ca_system_score_gemma":0.0002460167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006821954,"about_ca_topic_score_gemma":0.0005301574,"domain_scores_codex":[0.9981004,0.0004902393,0.0003362086,0.0004983004,0.0002044244,0.0003704391],"domain_scores_gemma":[0.9979702,0.001072544,0.0001268278,0.0003698653,0.0003159303,0.0001446936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001121272,0.0005293571,0.0118631,0.0004459777,0.0004042587,0.0005213774,0.4607635,0.0006298487,0.06236719,0.03719214,0.001961908,0.4232092],"study_design_scores_gemma":[0.001002694,0.0003921706,0.4465648,0.001379526,0.0001977796,0.001637138,0.0186287,0.2973331,0.09834058,0.0950274,0.03810364,0.001392441],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5071609,0.0007444981,0.4872147,0.001229924,0.000608666,0.0002112005,0.00001491464,0.00043145,0.002383783],"genre_scores_gemma":[0.988277,0.0001751581,0.0106771,0.0001365231,0.0004650959,0.00007378746,0.00002915845,0.0000310191,0.0001351418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4811161,"threshold_uncertainty_score":0.999998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01161495420842918,"score_gpt":0.2669293219336712,"score_spread":0.255314367725242,"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."}}