{"id":"W2780627324","doi":"","title":"Teachers’ Perceptions of Learning with Information Technology in Mathematics and Science Education","year":2014,"lang":"en","type":"article","venue":"Journal of Computing in Teacher Education","topic":"Education and Technology Integration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics education; Perception; IBM; Thematic analysis; Educational technology; Work (physics); Information technology; Pedagogy; Psychology; Sociology; Computer science; Qualitative research; Engineering; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002391706,0.00006080348,0.0001345616,0.00144851,0.0001424406,0.00004517886,0.0001821336,0.0001015851,0.000009381046],"category_scores_gemma":[0.001548451,0.00005563004,0.00001365679,0.001108207,0.0003975076,0.0006235242,0.00001463566,0.0004029527,0.000001456957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002802929,"about_ca_system_score_gemma":0.002110268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002068462,"about_ca_topic_score_gemma":0.0001788671,"domain_scores_codex":[0.9990454,0.00009690719,0.0004360821,0.00007194986,0.0002268885,0.0001227362],"domain_scores_gemma":[0.9987495,0.00007684369,0.00058074,0.00008350127,0.0004707194,0.00003867968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.000002966855,0.0004086891,0.6466061,0.00001733247,0.000002156132,2.191895e-8,0.1181218,0.000124741,0.0005994589,0.06721491,0.00003311709,0.1668687],"study_design_scores_gemma":[0.0003155333,0.0001722967,0.407341,0.0005265192,0.00001452687,0.00002738405,0.5768691,0.001421681,0.0003074073,0.01147074,0.001407748,0.0001261304],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879969,0.00003850462,0.004168327,0.002825463,0.0002072728,0.0001154212,2.730881e-8,0.00001649731,0.004631566],"genre_scores_gemma":[0.9778636,0.00002188831,0.02192763,0.00002513608,0.00006371626,0.000002782561,8.797468e-7,0.000003447635,0.00009099271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4587472,"threshold_uncertainty_score":0.3743524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009238679446251117,"score_gpt":0.32693437952933,"score_spread":0.3176957000830788,"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."}}