{"id":"W1990936606","doi":"10.11120/beej.2013.00018","title":"In-class use of Laptop Computers to Enhance Engagement within an Undergraduate Biology Curriculum: Findings and Lessons Learned","year":2013,"lang":"en","type":"article","venue":"Bioscience Education","topic":"Innovative Teaching Methods","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"University of Windsor","keywords":"Laptop; Likert scale; Mathematics education; Class (philosophy); Curriculum; Student engagement; Class size; Computer science; Medical education; Psychology; Pedagogy; Medicine","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":[0.002017097,0.0005289968,0.0003779204,0.0005559829,0.0005519731,0.001130713,0.0007814848,0.0006058762,0.002197259],"category_scores_gemma":[0.006138278,0.0002282989,0.0003275303,0.0003655768,0.0004027124,0.0008549331,0.0008921139,0.000586469,0.0005302113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004732641,"about_ca_system_score_gemma":0.0007209089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009856062,"about_ca_topic_score_gemma":0.002051752,"domain_scores_codex":[0.9986346,0.0006315803,0.00006965784,0.0001691166,0.0002898919,0.0002051286],"domain_scores_gemma":[0.9944552,0.003142491,0.0003953939,0.0002427336,0.0008222928,0.0009420264],"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":[0.002132992,0.03513236,0.2939631,0.001987749,0.0002885932,0.003986363,0.04113374,0.0005537447,0.04924516,0.0003115313,0.00321255,0.5680522],"study_design_scores_gemma":[0.0001790029,0.02336463,0.9074507,0.0003333347,0.000255698,0.00161342,0.03821601,0.001010698,0.01885893,0.0001883302,0.008466315,0.000062923],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977446,0.0001139823,0.000246624,0.0001470432,0.00001029053,0.00007146037,0.0000209765,0.00001861274,0.001626387],"genre_scores_gemma":[0.9967172,0.0003752777,0.0008146523,0.0001363212,0.00002741113,0.00006423418,0.00004708714,0.0000125751,0.001805194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002197259,"threshold_uncertainty_score":0.01066756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1168309420194715,"score_gpt":0.4595334522720355,"score_spread":0.342702510252564,"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."}}