{"id":"W2223741719","doi":"10.1007/s11423-015-9420-7","title":"Comparing virtual and location-based augmented reality mobile learning: emotions and learning outcomes","year":2016,"lang":"en","type":"article","venue":"Educational Technology Research and Development","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":173,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Alberta; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Augmented reality; Situated; Boredom; Situated learning; Psychology; Mobile device; Eye tracking; Educational technology; Computer science; Human–computer interaction; Multimedia; Mathematics education; Artificial intelligence; Social psychology; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001274121,0.0003002145,0.0004688426,0.000474169,0.0002987794,0.001813978,0.0003530579,0.0005227532,0.005344265],"category_scores_gemma":[0.009241413,0.0001191589,0.0004631712,0.0003550678,0.0003867961,0.0009156818,0.0009172156,0.0007005492,0.0006803967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003521865,"about_ca_system_score_gemma":0.0003939632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008170701,"about_ca_topic_score_gemma":0.0007489638,"domain_scores_codex":[0.9991491,0.0002947453,0.00007113068,0.0001064766,0.0002337271,0.0001449217],"domain_scores_gemma":[0.9949824,0.002877258,0.0006947897,0.0001938311,0.000470888,0.0007808037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.04954357,0.03264486,0.3048571,0.001553798,0.0009461364,0.0005628595,0.02419212,0.005042282,0.03183025,0.001874734,0.003699356,0.5432529],"study_design_scores_gemma":[0.001983185,0.0622917,0.8608988,0.0003802856,0.001365524,0.0004833346,0.03004431,0.009714559,0.02216128,0.003013669,0.007384459,0.0002788915],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978325,0.0000764643,0.000256482,0.0000462271,0.00001953015,0.00002679234,0.00005009216,0.00001197261,0.001680061],"genre_scores_gemma":[0.9983491,0.00007424557,0.000221777,0.00002448384,0.000009935092,0.0000434838,0.00004535883,0.000004472561,0.001227082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005344265,"threshold_uncertainty_score":0.01787835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07039879862248781,"score_gpt":0.3661910491022177,"score_spread":0.2957922504797299,"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."}}