{"id":"W2807805230","doi":"10.1016/j.ecns.2018.04.004","title":"Modeling Students' Perceptions of Simulation-Based Learning Using the Technology Acceptance Model","year":2018,"lang":"en","type":"article","venue":"Clinical Simulation in Nursing","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":79,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; John Abbott College; Centre for Health Evaluation and Outcome Sciences","funders":"","keywords":"Technology acceptance model; Psychology; Perception; Fidelity; Variance (accounting); Context (archaeology); Usability; Conceptual model; Applied psychology; Teamwork; Conceptual framework; Knowledge management; Social psychology; Computer science; Human–computer interaction","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":[0.004167014,0.0005234373,0.0003517507,0.0006434587,0.0004203123,0.002599366,0.0005968158,0.001413697,0.004008389],"category_scores_gemma":[0.02765551,0.0002665351,0.0008707191,0.0004975508,0.0005712615,0.001333595,0.0009609725,0.001611945,0.0004732686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001432534,"about_ca_system_score_gemma":0.001022971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004520853,"about_ca_topic_score_gemma":0.003814666,"domain_scores_codex":[0.9974766,0.001545801,0.000160629,0.0001504679,0.0003455654,0.0003209124],"domain_scores_gemma":[0.9789973,0.01623607,0.001730236,0.0005334174,0.001360459,0.001142538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001862421,0.009525978,0.815962,0.0001789121,0.0003199269,0.0002516234,0.0116394,0.1151357,0.00476122,0.00431279,0.0005820735,0.03546808],"study_design_scores_gemma":[0.0002675428,0.008594574,0.2832053,0.0001682594,0.0002892262,0.0001770998,0.01648792,0.6780813,0.0070405,0.003622356,0.001894853,0.0001709694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986224,0.000006173524,0.0008037274,0.00003556401,0.000002010725,0.00001770938,0.000009137608,0.00000439266,0.0004989072],"genre_scores_gemma":[0.9994664,0.000009303401,0.0003331964,0.000008325625,7.828278e-7,0.00002003222,0.00001424165,0.000001311346,0.0001464498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004520853,"threshold_uncertainty_score":0.02203757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2529483992417287,"score_gpt":0.5698790225613184,"score_spread":0.3169306233195897,"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."}}