{"id":"W2760499945","doi":"10.19173/irrodl.v18i6.2880","title":"The Effect of Universal Design for Learning (UDL) Application on E-learning Acceptance: A Structural Equation Model","year":2017,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Structural equation modeling; Universal Design for Learning; Mathematics education; Technology acceptance model; Psychology; Curriculum; Variance (accounting); Computer science; Path analysis (statistics); Knowledge management; Mathematics; Pedagogy; Usability; Human–computer interaction; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01868518,0.0008145281,0.001273173,0.001655782,0.0008116771,0.003036858,0.001880776,0.002146598,0.007400765],"category_scores_gemma":[0.04509673,0.0007407241,0.003874793,0.001661491,0.001567983,0.002723618,0.002729581,0.002538243,0.001001038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002528475,"about_ca_system_score_gemma":0.004333964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008770275,"about_ca_topic_score_gemma":0.003861828,"domain_scores_codex":[0.9877113,0.008448812,0.0005670338,0.001178539,0.00130592,0.0007884612],"domain_scores_gemma":[0.9236824,0.0651511,0.004433725,0.00212761,0.003183699,0.001421497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001515066,0.004630624,0.8240284,0.0008768139,0.001803452,0.0005555307,0.01599332,0.03184875,0.001665475,0.01754673,0.001655227,0.09788061],"study_design_scores_gemma":[0.000486418,0.007657664,0.4249883,0.001034411,0.002031207,0.0003553469,0.007789134,0.531545,0.001823874,0.01661607,0.005448091,0.0002245025],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777275,0.0002945998,0.01621464,0.001053184,0.00004919248,0.0004048779,0.0002454891,0.0001054223,0.003905058],"genre_scores_gemma":[0.9928226,0.0001734284,0.005410171,0.00009949845,0.00001313898,0.0004491483,0.0001653865,0.00001643633,0.0008503012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01868518,"threshold_uncertainty_score":0.09881783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2601790817571207,"score_gpt":0.532084904394526,"score_spread":0.2719058226374054,"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."}}