{"id":"W3152386218","doi":"10.29173/iasl8011","title":"A Learning Object Approach for Designing Information Literacy Instructional Materials","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Learning object; Computer science; Personalization; Interoperability; Context (archaeology); Flexibility (engineering); Object (grammar); Instructional design; Relation (database); Information literacy; Multimedia; Literacy; Affordance; Human–computer interaction; World Wide Web; Artificial intelligence; Pedagogy","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":[0.001789937,0.001009503,0.0005837145,0.002101979,0.001011659,0.004612566,0.001863428,0.001600065,0.008944774],"category_scores_gemma":[0.002326613,0.0007236197,0.00104919,0.001355621,0.00164843,0.00354495,0.001710741,0.001392165,0.004151958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001089483,"about_ca_system_score_gemma":0.00139587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001129557,"about_ca_topic_score_gemma":0.001580678,"domain_scores_codex":[0.9986089,0.0005134824,0.0001569717,0.0002208178,0.0004196516,0.00008018202],"domain_scores_gemma":[0.9988731,0.0004672138,0.00008868837,0.000141122,0.0003393306,0.00009046071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001570091,0.0002631844,0.001318706,0.002319651,0.00005997051,0.001305454,0.005274766,0.01794479,0.04682074,0.3811206,0.009689791,0.5337252],"study_design_scores_gemma":[0.0001050844,0.0006590611,0.0009496336,0.000835639,0.0001432663,0.001678375,0.001693331,0.06147207,0.04230799,0.1227319,0.7672693,0.0001544907],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002489481,0.0002576342,0.9835194,0.0002221321,0.00007395993,0.0004298942,0.00006086192,0.0007327822,0.01221381],"genre_scores_gemma":[0.01940401,0.0004127766,0.9670501,0.0001565782,0.00002790753,0.0007246106,0.0001611505,0.0002411124,0.01182173],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008944774,"threshold_uncertainty_score":0.02992326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02067234385049974,"score_gpt":0.2669105980799151,"score_spread":0.2462382542294154,"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."}}