{"id":"W3107236158","doi":"10.18260/1-2--36041","title":"Assessment of experiential learning in online introductory physics labs during COVID-19","year":2024,"lang":"en","type":"article","venue":"","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"City University of New York; American Society for Engineering Education","keywords":"Coronavirus disease 2019 (COVID-19); Experiential learning; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Computer science; Mathematics education; Data science; Engineering physics; Psychology; Physics; Medicine; Virology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007620595,0.00007256996,0.00009160682,0.00009170547,0.00001232419,0.00001221939,0.00004923101,0.00004076484,0.0001823164],"category_scores_gemma":[0.00002261019,0.00006901514,0.000024872,0.0002525435,0.00001859138,0.00006716433,0.00001801561,0.0002024519,0.000004504069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001423206,"about_ca_system_score_gemma":0.00005054021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002417151,"about_ca_topic_score_gemma":0.000006294679,"domain_scores_codex":[0.9995078,0.000008065125,0.0001481457,0.0001117586,0.0001037185,0.000120525],"domain_scores_gemma":[0.9998203,0.00002545694,0.000005558176,0.00007496468,0.000006874189,0.00006683329],"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":[0.000004585329,0.0002030568,0.006130513,0.006899757,0.00009568744,0.00002213369,0.0051975,0.6811234,0.2778454,0.004188929,0.002555559,0.01573346],"study_design_scores_gemma":[0.0005616059,0.00005183434,0.0653711,0.0002524355,0.00001849498,0.000009466044,0.001498494,0.8661978,0.01755988,0.0001996264,0.04781432,0.0004649924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508801,0.0003894484,0.04628396,0.0002102153,0.001184084,0.00004700696,0.000003436185,0.000500655,0.0005010896],"genre_scores_gemma":[0.9975527,0.00005893474,0.001622614,0.00001100143,0.000400875,0.000009220254,0.00002904402,0.00001734382,0.0002982848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2602855,"threshold_uncertainty_score":0.2814356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009685520656350453,"score_gpt":0.2815244026682346,"score_spread":0.2718388820118841,"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."}}