{"id":"W3213417900","doi":"10.1177/1071181321651019","title":"Reshaping Human Factors Education in Times of Big Data: Practitioner Perspectives","year":2021,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Big data; Curriculum; Data science; Task (project management); Underpinning; Computer science; Visualization; Engineering ethics; Engineering; Human–computer interaction; Artificial intelligence; Psychology; Systems engineering; Data mining; Pedagogy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05789473,0.0004781644,0.0006553736,0.004667601,0.005188659,0.01086828,0.001952824,0.006075538,0.003869082],"category_scores_gemma":[0.05769475,0.000603939,0.0003434427,0.005533332,0.006271133,0.01263738,0.007873097,0.01167859,0.0009336268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006208481,"about_ca_system_score_gemma":0.03221909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007227472,"about_ca_topic_score_gemma":0.02039626,"domain_scores_codex":[0.9845912,0.00882591,0.0006399677,0.0007644077,0.003048286,0.002130262],"domain_scores_gemma":[0.8773859,0.06385493,0.004545215,0.002538042,0.02718695,0.0244889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008504136,0.001463698,0.02741227,0.004008626,0.0000499575,0.00103075,0.1997118,0.0007232374,0.001543381,0.04024214,0.09667742,0.6270517],"study_design_scores_gemma":[0.00007630347,0.0006514087,0.02060733,0.01290013,0.00004387673,0.0009662166,0.5113895,0.001761018,0.0007726479,0.0382853,0.4124362,0.0001100149],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05371246,0.06393912,0.01143957,0.8552077,0.00218621,0.0001244747,0.00004187854,0.0001049732,0.01324368],"genre_scores_gemma":[0.7229123,0.1364696,0.03224385,0.1002924,0.00219084,0.0003706792,0.00008744752,0.0001096909,0.005323303],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05789473,"threshold_uncertainty_score":0.3061802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05120654738031282,"score_gpt":0.3423317722924614,"score_spread":0.2911252249121485,"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."}}