{"id":"W4254429661","doi":"10.4018/978-1-5225-7365-4.ch016","title":"Automatic Item Generation","year":2018,"lang":"en","type":"book-chapter","venue":"Advances in educational technologies and instructional design book series","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Test (biology); Process (computing); Item bank; Industrial engineering; Artificial intelligence; Data science; Information retrieval; Machine learning; Item response theory; Engineering; Programming language; Statistics; Mathematics; Psychometrics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005400885,0.002441174,0.001313256,0.003867608,0.0007578593,0.002312201,0.002704327,0.001405477,0.09062523],"category_scores_gemma":[0.02809899,0.0009335512,0.001284973,0.004003203,0.0005321489,0.002211344,0.002754268,0.001790559,0.05157518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000744876,"about_ca_system_score_gemma":0.001148873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001048561,"about_ca_topic_score_gemma":0.001357536,"domain_scores_codex":[0.9956119,0.00175827,0.0003313102,0.0006501088,0.001499722,0.0001487463],"domain_scores_gemma":[0.983202,0.008266428,0.000353341,0.002849617,0.005144714,0.0001838237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002315333,0.0001341157,0.0007871452,0.0005976948,0.0000532397,0.0001316186,0.0003355691,0.001440348,0.004699147,0.01281113,0.1002553,0.8785232],"study_design_scores_gemma":[0.0004937989,0.0004923788,0.005099334,0.001092017,0.000211067,0.002441054,0.000641454,0.06697028,0.04370507,0.08402087,0.7945304,0.0003023658],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006348952,0.001232228,0.9026762,0.000560577,0.001209425,0.0026292,0.00547753,0.02926373,0.05060207],"genre_scores_gemma":[0.02554966,0.0007021422,0.9157094,0.0005236968,0.000252565,0.002859394,0.00960464,0.002995749,0.0418028],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09062523,"threshold_uncertainty_score":0.3031716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02134655998604585,"score_gpt":0.2720030772144069,"score_spread":0.250656517228361,"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."}}