{"id":"W3129078225","doi":"10.3926/jotse.1050","title":"Enhance learning experience using technology in class","year":2021,"lang":"en","type":"article","venue":"Journal of Technology and Science Education","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Class (philosophy); Mathematics education; Computer science; Multimedia; Educational technology; Psychology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007378259,0.0000768422,0.0001436884,0.002032168,0.0002279853,0.00009625865,0.000785386,0.0001309638,0.000005307611],"category_scores_gemma":[0.001562022,0.000076353,0.0000173169,0.005257064,0.0005770965,0.001032516,0.000196663,0.000551483,0.000002189819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002027367,"about_ca_system_score_gemma":0.002486087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000028442,"about_ca_topic_score_gemma":0.000001697755,"domain_scores_codex":[0.9988734,0.00004306356,0.0003253674,0.0002981825,0.0002279563,0.0002320732],"domain_scores_gemma":[0.9987242,0.00003665944,0.0003550651,0.0002886025,0.0005444009,0.00005104525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000002727776,0.0002354267,0.1516184,0.00001151535,0.000003178091,0.00001949935,0.003024567,0.0006935548,0.3122143,0.128818,0.00001928654,0.4033396],"study_design_scores_gemma":[0.0005125808,0.0005176876,0.09642471,0.0007229712,0.00001549151,0.007427716,0.03372009,0.03600737,0.6538595,0.1561058,0.01402885,0.0006572577],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9610378,0.001032925,0.02787838,0.008747081,0.001018971,0.00004095356,1.459423e-8,0.00003400678,0.0002099192],"genre_scores_gemma":[0.9248063,0.00008090532,0.07489447,0.00006526615,0.00003755641,0.000004423905,5.289033e-8,0.000002731986,0.0001082705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4026824,"threshold_uncertainty_score":0.4410211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060021840759628,"score_gpt":0.3323394169295961,"score_spread":0.3217391985219998,"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."}}