{"id":"W2127573943","doi":"10.1016/j.compedu.2009.05.001","title":"Examining the benefits and challenges of using audience response systems: A review of the literature","year":2009,"lang":"en","type":"review","venue":"Computers & Education","topic":"Innovative Teaching Methods","field":"Social Sciences","cited_by":695,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Formative assessment; Audience response; Attendance; Set (abstract data type); Confusion; Normative; Computer science; Class (philosophy); Control (management); Psychology; Mathematics education; Political science; Artificial intelligence","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":[0.008470789,0.0001745415,0.000710505,0.0001220657,0.0003174587,0.0000469535,0.0005954924,0.0001306997,6.703276e-7],"category_scores_gemma":[0.001369337,0.0001012535,0.000104847,0.0009728682,0.0002472015,0.0001040792,0.00007082716,0.0002965327,1.896171e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001575544,"about_ca_system_score_gemma":0.001461486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006296491,"about_ca_topic_score_gemma":0.000003682786,"domain_scores_codex":[0.9920054,0.006798997,0.0005142604,0.0002439386,0.0002960098,0.0001413743],"domain_scores_gemma":[0.9964813,0.001542966,0.001150837,0.0004405104,0.000358736,0.00002565593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001184799,0.0000164598,0.000002531648,0.02816939,0.0000142913,5.455226e-8,0.0117274,8.327148e-7,3.802061e-7,0.01285593,0.0001138755,0.9470977],"study_design_scores_gemma":[0.0000132046,0.00001754134,0.0002158841,0.4359496,0.0001344178,0.00001093483,0.0009445043,0.000003268582,1.743569e-7,0.00004938335,0.5625618,0.00009935693],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001915626,0.9964653,0.00009295383,0.000743565,0.00126435,0.0009250687,0.00000395673,0.0000101879,0.0003030102],"genre_scores_gemma":[0.0001060163,0.9965607,0.002919159,0.00009092002,0.0002588568,0.0000162377,0.000002049848,0.000009977116,0.00003610329],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9469983,"threshold_uncertainty_score":0.4128997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2524059933821606,"score_gpt":0.4481211044375519,"score_spread":0.1957151110553912,"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."}}