{"id":"W4226376364","doi":"10.5267/j.ijdns.2022.3.008","title":"Factors influencing behavior intentions to use virtual reality in education","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Applied Science Private University","keywords":"Virtual reality; Curriculum; Psychology; Set (abstract data type); Expectancy theory; Software deployment; Scarcity; Variety (cybernetics); Knowledge management; Computer science; Pedagogy; Social psychology; Human–computer interaction; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00123714,0.00005853445,0.00007769792,0.0003158554,0.0002271827,0.0002862634,0.002602428,0.000008706676,0.00001201697],"category_scores_gemma":[0.0002279477,0.00005161532,0.00001368299,0.0009702244,0.00006249936,0.003840835,0.001879468,0.0001533604,9.339505e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001603635,"about_ca_system_score_gemma":0.0006875942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007370514,"about_ca_topic_score_gemma":0.00003592294,"domain_scores_codex":[0.9984648,0.00004270626,0.0003009647,0.0002130886,0.0008427195,0.0001356962],"domain_scores_gemma":[0.999065,0.00007774457,0.0001580799,0.0002388269,0.00035785,0.0001025259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003381475,0.0003334878,0.8941124,0.000001613098,0.00001455194,0.00001714683,0.001900004,0.01593568,0.001809026,0.01511502,0.004392869,0.06633439],"study_design_scores_gemma":[0.0001212526,0.0001030213,0.9831715,0.0000300378,0.000003998208,0.000104963,0.0002718745,0.008327108,0.0000985338,0.0005184539,0.007148898,0.0001003512],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734075,0.00002935458,0.02344581,0.001163184,0.001844742,0.00005127329,0.0000270834,0.000007120543,0.00002394443],"genre_scores_gemma":[0.9945952,0.00002578561,0.004689744,0.0005296186,0.0001199692,0.000002512872,0.00001112926,0.000002336975,0.0000236478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08905911,"threshold_uncertainty_score":0.4836002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06825599444161976,"score_gpt":0.3371056699498824,"score_spread":0.2688496755082627,"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."}}