{"id":"W4390816389","doi":"10.5430/wjel.v14n2p182","title":"Impact of Artificial Intelligence Versus Traditional Instruction for Language Learning: A Survey","year":2024,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Khalid University","keywords":"Generalizability theory; Computer science; Language acquisition; Context (archaeology); Artificial intelligence; Process (computing); Language education; Sample (material); Affect (linguistics); Mathematics education; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008282338,0.0001945388,0.0004784147,0.001235168,0.0006339318,0.001436496,0.0003746415,0.000625336,0.002363889],"category_scores_gemma":[0.03074234,0.0002622683,0.0004454048,0.001092144,0.000612679,0.001905597,0.001156269,0.001084501,0.0006371514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024257,"about_ca_system_score_gemma":0.001565068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329554,"about_ca_topic_score_gemma":0.001684733,"domain_scores_codex":[0.9921964,0.004157601,0.0007767548,0.0003234276,0.001823026,0.0007227229],"domain_scores_gemma":[0.9727519,0.01484895,0.00500173,0.000441322,0.004409362,0.002546676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002602788,0.001778508,0.8545792,0.0007047461,0.00009117139,0.0004355523,0.03572977,0.000349537,0.001539877,0.0004543348,0.002817118,0.10126],"study_design_scores_gemma":[0.00005371069,0.003849622,0.8640535,0.0005164699,0.00005850939,0.00088999,0.1081689,0.001245411,0.001272003,0.0002175703,0.01957896,0.00009528165],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964865,0.0002446728,0.0002341487,0.0006610802,0.00001804093,0.00007990187,0.0002179395,0.00001154423,0.002046105],"genre_scores_gemma":[0.9974639,0.0005142346,0.0004971024,0.0004907533,0.0000240642,0.0001323112,0.0001317328,0.000008434384,0.0007374692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008282338,"threshold_uncertainty_score":0.04380167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04166369102383122,"score_gpt":0.3331314636226187,"score_spread":0.2914677725987875,"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."}}