{"id":"W2024880150","doi":"10.1007/s11165-007-9076-3","title":"Personalizing and Contextualizing Multimedia Case Methods in University-based Teacher Education: An Important Modification for Promoting Technological Design in School Science","year":2007,"lang":"en","type":"article","venue":"Research in Science Education","topic":"Science Education and Pedagogy","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Office of International Science and Engineering","keywords":"Contextualization; Context (archaeology); Personalization; Mathematics education; Science education; Teaching method; Computer science; Bridge (graph theory); Multimedia; Pedagogy; Psychology; Medicine; World Wide Web","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":[0.02609827,0.0006772287,0.000424757,0.002186777,0.002341856,0.003331664,0.002574949,0.001433547,0.005202984],"category_scores_gemma":[0.06166713,0.0006315338,0.0004610522,0.001166115,0.001943282,0.004643389,0.004912494,0.001366169,0.0005146112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001637403,"about_ca_system_score_gemma":0.002801867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009418587,"about_ca_topic_score_gemma":0.004106894,"domain_scores_codex":[0.9744579,0.0213307,0.0008802178,0.001378817,0.001559905,0.0003925915],"domain_scores_gemma":[0.935946,0.04790057,0.002331846,0.0103302,0.002425607,0.001065699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004496124,0.003178081,0.01742176,0.001113777,0.0000612871,0.0002701245,0.1528426,0.001472929,0.01738279,0.02249922,0.00174412,0.7815638],"study_design_scores_gemma":[0.0008350756,0.006189661,0.133325,0.007309402,0.001260349,0.003933076,0.3262615,0.02238387,0.08838229,0.1073564,0.3020883,0.0006750567],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6255296,0.0009344317,0.3171684,0.003262164,0.0001986812,0.00708126,0.0001260575,0.001182988,0.04451633],"genre_scores_gemma":[0.6048732,0.000388165,0.3890707,0.0002700892,0.00005834319,0.002153041,0.00007171136,0.00014167,0.002973075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02609827,"threshold_uncertainty_score":0.1380225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4030691441519054,"score_gpt":0.5994886557695678,"score_spread":0.1964195116176624,"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."}}