{"id":"W4405675788","doi":"10.24908/pceea.2024.18538","title":"Mobile learning in engineering using smartphones: Two examples in acoustics and thermal courses","year":2024,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Acoustics; Computer science; Mobile device; Multimedia; Human–computer interaction; Engineering; Physics; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004329412,0.0002262808,0.0002179779,0.0007206762,0.00005392065,0.0001568215,0.0001714495,0.0001473361,0.000008720941],"category_scores_gemma":[0.0003531882,0.0002559946,0.00004909319,0.0007914801,0.00001384603,0.0003161294,0.0000304667,0.000592916,0.000002593689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002687779,"about_ca_system_score_gemma":0.0002109485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003033435,"about_ca_topic_score_gemma":0.0009538888,"domain_scores_codex":[0.9987971,0.000006161684,0.0003370676,0.0002227919,0.0002159968,0.000420894],"domain_scores_gemma":[0.9995694,0.0001003888,0.00005798918,0.00007369887,0.00007266334,0.0001258387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[5.614976e-7,0.000009767266,0.04957784,0.000496996,0.00003032885,6.919079e-7,0.002112319,0.8484824,0.09807576,0.0007225194,0.00007563704,0.0004151275],"study_design_scores_gemma":[0.0001840253,0.00001355102,0.05738886,0.001028499,0.00002527291,0.00001051766,0.0007482325,0.9318282,0.004152888,0.0000137138,0.004224528,0.000381743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953493,0.002011172,0.00008518837,0.00004561452,0.001304651,0.0002638633,0.000006073561,0.0002747849,0.0006593802],"genre_scores_gemma":[0.9976618,0.00005633946,0.001785497,0.000009683559,0.0001434045,0.00006983514,0.000004060488,0.00009491201,0.0001744219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09392288,"threshold_uncertainty_score":0.9999892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005443651316983003,"score_gpt":0.2185365907828093,"score_spread":0.2130929394658263,"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."}}