{"id":"W4352993290","doi":"10.1007/978-3-031-26876-2_46","title":"Adapting Experiential E-learning in Engineering Education with Industry 4.0 Vision","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Experiential learning; Interfacing; Experiential education; Engineering education; Engineering management; Engineering; Automation; Computer science; Multimedia; Human–computer interaction; Mathematics education; Psychology; Mechanical engineering","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0002165691,0.0004737769,0.0004936278,0.0004172765,0.00004458703,0.0001220731,0.0001134758,0.001025219,0.000009724252],"category_scores_gemma":[0.00003379448,0.0004836351,0.00004057994,0.0001752147,0.00002233755,0.00009714466,0.00005559351,0.002594608,0.000003878169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002442223,"about_ca_system_score_gemma":0.00002611602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005305842,"about_ca_topic_score_gemma":0.00004749751,"domain_scores_codex":[0.9985224,0.0000201082,0.0004451276,0.0003929348,0.0002138519,0.0004056007],"domain_scores_gemma":[0.999422,0.0001964485,0.00008043014,0.000195731,0.00002034366,0.0000850635],"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":[0.000007292791,0.000003757787,0.0005648615,0.0003426728,0.00002861152,0.00003271605,0.0004511271,0.9939044,0.0001544953,0.0004700418,0.00001557543,0.004024414],"study_design_scores_gemma":[0.0002287767,0.00006170048,0.0001574551,0.006299593,0.00001114694,0.00004060354,0.00007688805,0.9882903,0.00002168845,0.00001384889,0.004204002,0.0005940594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.133335,0.1452946,0.5697917,0.0000990101,0.027739,0.005673009,0.00001781491,0.008404352,0.1096456],"genre_scores_gemma":[0.9957318,0.0002644866,0.0003621656,0.000005989616,0.0008786749,0.00008473715,0.00004749631,0.0003086662,0.002315992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8623968,"threshold_uncertainty_score":0.9997615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006412017800645229,"score_gpt":0.2094936891081872,"score_spread":0.2030816713075419,"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."}}