Mendeley | Further Information

{"title"=>"Class attendance, peer similarity, and academic performance in a large field study", "type"=>"journal", "authors"=>[{"first_name"=>"Valentin", "last_name"=>"Kassarnig", "scopus_author_id"=>"57196466742"}, {"first_name"=>"Andreas", "last_name"=>"Bjerre-Nielsen", "scopus_author_id"=>"57196470273"}, {"first_name"=>"Enys", "last_name"=>"Mones", "scopus_author_id"=>"54995709800"}, {"first_name"=>"Sune", "last_name"=>"Lehmann", "scopus_author_id"=>"22985918200"}, {"first_name"=>"David Dreyer", "last_name"=>"Lassen", "scopus_author_id"=>"9243648500"}], "year"=>2017, "source"=>"PLoS ONE", "identifiers"=>{"isbn"=>"1111111111", "sgr"=>"85033470588", "scopus"=>"2-s2.0-85033470588", "issn"=>"19326203", "pui"=>"619130346", "doi"=>"10.1371/journal.pone.0187078", "arxiv"=>"https://arxiv.org/abs/1702.01262v2"}, "id"=>"0ac35117-60d5-37d0-a229-a2f7dd75d612", "abstract"=>"Identifying the factors that determine academic performance is an essential part of educational research. Existing research indicates that class attendance is a useful predictor of subsequent course achievements. The majority of the literature is, however, based on surveys and self-reports, methods which have well-known systematic biases that lead to limitations on conclusions and generalizability. Here we propose a novel method for measuring class attendance, using data collected from smartphone sensors. We demonstrate that early and consistent class attendance strongly correlates with academic performance. In addition, positive correlation is observed when comparing attendance of peers, suggesting either a strong peer effect or homophily with respect to attendance.", "link"=>"http://www.mendeley.com/research/class-attendance-peer-similarity-academic-performance-large-field-study", "reader_count"=>17, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>1, "Student > Master"=>3, "Student > Bachelor"=>2, "Unspecified"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>1, "Student > Master"=>3, "Student > Bachelor"=>2, "Unspecified"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>2, "Environmental Science"=>1, "Chemistry"=>1, "Psychology"=>3, "Social Sciences"=>3, "Computer Science"=>5, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>3}, "Psychology"=>{"Psychology"=>3}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Computer Science"=>{"Computer Science"=>5}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"Brazil"=>1}, "group_count"=>3}

CrossRef

• http://doi.org/10.37965/jait.2020.0040
• http://doi.org/10.3233/IDT-190012
• http://doi.org/10.1140/epjds/s13688-018-0138-8
• http://doi.org/10.2139/ssrn.3555766
• http://doi.org/10.1186/s40561-019-0112-3
• http://doi.org/10.1140/epjds/s13688-020-00245-8
• http://doi.org/10.5688/ajpe7550
• http://doi.org/10.1109/ACCESS.2019.2926743
• http://doi.org/10.2196/13888
• http://doi.org/10.1007/s13748-018-0164-6
• http://doi.org/10.1007/s00787-019-01294-9
• http://doi.org/10.1038/s41597-019-0325-x
• http://doi.org/10.1080/10899995.2020.1768002
• http://doi.org/10.2989/17280583.2019.1585359
• http://doi.org/10.1016/j.jad.2019.07.085
• http://doi.org/10.1080/00131881.2019.1660587
• http://doi.org/10.1177/0956797620956613
• http://doi.org/10.1080/00220485.2020.1804502

Scopus | Further Information

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