{"id":"W4407634256","doi":"10.1007/s40593-025-00461-1","title":"Teaching a Conversational Agent using Natural Language: Effect on Learning and Engagement","year":2025,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence in Education","topic":"AI in Service Interactions","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Monash University","keywords":"Computer science; Educational technology; Natural language; Natural (archaeology); Language acquisition; Mathematics education; Multimedia; World Wide Web; Natural language processing; Psychology; Geography","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":[0.0009504076,0.000106592,0.0001209796,0.000748308,0.0001023711,0.0002271512,0.0005080296,0.00003867133,0.00002305711],"category_scores_gemma":[0.0006679754,0.0001021086,0.000059599,0.0002054187,0.0000314544,0.000623853,0.0001109409,0.0006340097,0.000009568666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004855366,"about_ca_system_score_gemma":0.0002898696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002113713,"about_ca_topic_score_gemma":0.00003670035,"domain_scores_codex":[0.9985583,0.0002611557,0.000510109,0.0001798392,0.0003767675,0.0001137799],"domain_scores_gemma":[0.9986346,0.0006060704,0.0002946557,0.00009432385,0.0003329164,0.00003745947],"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":[0.00008940519,0.000302808,0.002857032,0.00001355709,0.00007184286,0.00001837727,0.008024328,0.00482876,0.007895808,0.06368076,0.00005004029,0.9121673],"study_design_scores_gemma":[0.0003389564,0.0006630953,0.0066194,0.001932109,0.00005893015,0.0003088896,0.02540076,0.8654251,0.04712161,0.0455841,0.006011486,0.0005356341],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8459202,0.0002319579,0.1421085,0.003953035,0.007132716,0.0001214113,4.593867e-7,0.00001723379,0.0005145207],"genre_scores_gemma":[0.9883443,0.00001680542,0.01076199,0.0004862527,0.0002874706,0.000004928371,0.000002049684,0.000004441304,0.00009172061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9116316,"threshold_uncertainty_score":0.4163867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0232553547357452,"score_gpt":0.3970391460338014,"score_spread":0.3737837912980562,"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."}}