{"id":"https://openalex.org/W3110818405","doi":"https://doi.org/10.1109/fie44824.2020.9274061","title":"Data Mining Approach for Determining Student Attention Pattern","display_name":"Data Mining Approach for Determining Student Attention Pattern","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3110818405","doi":"https://doi.org/10.1109/fie44824.2020.9274061","mag":"3110818405"},"language":"en","primary_location":{"id":"doi:10.1109/fie44824.2020.9274061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fie44824.2020.9274061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Frontiers in Education Conference (FIE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025435055","display_name":"Sujan Poudyal","orcid":null},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sujan Poudyal","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053349857","display_name":"Mahnas Mohammadi-Aragh","orcid":"https://orcid.org/0000-0002-3094-3734"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Jean Mohammadi-Aragh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081134905","display_name":"John E. Ball","orcid":"https://orcid.org/0000-0002-6774-4851"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John E. Ball","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99041443"],"apc_list":null,"apc_paid":null,"fwci":1.3544,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.85732778,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9747999906539917,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7565494179725647},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.66553795337677},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6361180543899536},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6233584880828857},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6210474967956543},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5821003913879395},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5225386619567871},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5054831504821777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48112931847572327},{"id":"https://openalex.org/keywords/educational-data-mining","display_name":"Educational data mining","score":0.4728527367115021},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.45643675327301025},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4507947266101837},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.4460509717464447},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3296751379966736}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7565494179725647},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.66553795337677},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6361180543899536},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6233584880828857},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6210474967956543},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5821003913879395},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5225386619567871},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5054831504821777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48112931847572327},{"id":"https://openalex.org/C2777598771","wikidata":"https://www.wikidata.org/wiki/Q5341279","display_name":"Educational data mining","level":2,"score":0.4728527367115021},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.45643675327301025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4507947266101837},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.4460509717464447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3296751379966736},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fie44824.2020.9274061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fie44824.2020.9274061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Frontiers in Education Conference (FIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1566133440","https://openalex.org/W1687397888","https://openalex.org/W1982814196","https://openalex.org/W2049829621","https://openalex.org/W2079195815","https://openalex.org/W2087668131","https://openalex.org/W2097171469","https://openalex.org/W2122274740","https://openalex.org/W2150796457","https://openalex.org/W2277048181","https://openalex.org/W4242247490","https://openalex.org/W6639028550"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W4224922629","https://openalex.org/W4375930530","https://openalex.org/W1517488976","https://openalex.org/W4200306072","https://openalex.org/W2181773302","https://openalex.org/W2335086884","https://openalex.org/W2807997743"],"abstract_inverted_index":{"This":[0],"Research":[1],"Full":[2],"Paper":[3],"presents":[4],"the":[5,58,146,163,194,199,224,229,243,275,303],"approach":[6],"of":[7,87,129,148,165,233,305],"traditional":[8,307],"engineering":[9,308,318],"analysis":[10,175,309],"techniques":[11,16,37,65,154,272,310],"on":[12,238],"education.":[13],"Data":[14],"mining":[15,36,64,201],"have":[17],"been":[18],"successfully":[19],"employed":[20],"to":[21,42,47,60,125,157,176,193,311,316],"extract":[22,48,158],"hidden":[23],"information":[24,183],"from":[25],"large":[26,43,74],"data":[27,35,45,63,84,92,119,137,141,196,200,313],"sets":[28,46],"within":[29],"various":[30],"contexts.":[31],"We":[32,171,227],"hypothesized":[33],"that":[34,95],"can":[38,66,288],"similarly":[39],"be":[40,289],"applied":[41,156],"educational":[44,312],"and":[49,52,131,151,168,218,266],"analyze":[50],"patterns":[51,72,161],"create":[53],"insights.":[54,320],"Specifically,":[55],"we":[56,203,258],"examined":[57],"degree":[59],"which":[61,77],"standard":[62],"distinguish":[67],"between":[68],"different":[69,206,235],"student":[70,90,118,127,159],"attention":[71,91,160,192,240],"in":[73,76,145,162,187,242,314],"lectures":[75],"personal":[78],"computers":[79],"were":[80,142,155],"actively":[81],"used.":[82],"Our":[83,282,300],"set":[85],"consists":[86],"electronically":[88],"captured":[89,144],"(on-task,":[93],"off-task)":[94],"was":[96,253],"recorded":[97,195],"at":[98],"20":[99],"second":[100],"intervals":[101],"throughout":[102],"each":[103,248],"course":[104],"lecture":[105,244],"over":[106],"one":[107,169,232],"semester.":[108],"With":[109],"Institutional":[110],"Review":[111],"Board":[112],"(IRB)":[113],"approval,":[114],"methods":[115],"involved":[116],"capturing":[117],"via":[120],"a":[121],"backend":[122],"monitoring":[123,130],"system":[124],"reduce":[126,132],"awareness":[128],"false":[133],"behavior":[134],"changes":[135],"during":[136],"collection":[138],"periods.":[139],"The":[140],"originally":[143],"form":[147,164],"images":[149],"(screenshots),":[150],"image":[152],"processing":[153],"zero":[166],"(off-task)":[167],"(on-task).":[170],"conducted":[172],"descriptive":[173],"statistical":[174],"add":[177],"other":[178],"features":[179],"such":[180],"as":[181],"characterization":[182],"(e.g.,":[184],"total":[185],"logged":[186],"attention,":[188],"average":[189],"class":[190],"period":[191],"sets).":[197],"For":[198,255],"analysis,":[202],"used":[204,259],"three":[205],"supervised":[207],"machine":[208],"learning":[209],"classification":[210,249,276,286,298],"algorithms:":[211],"Support":[212],"Vector":[213],"Machine":[214],"(SVM),":[215],"Decision":[216],"Tree,":[217],"K-Nearest":[219],"Neighbors":[220],"(KNN)":[221],"for":[222],"classifying":[223],"students'":[225],"dataset.":[226],"classified":[228],"students":[230],"into":[231],"four":[234],"classes":[236],"based":[237],"their":[239],"pattern":[241],"class.":[245],"Before":[246],"applying":[247,274,306],"algorithm,":[250],"feature":[251],"extraction":[252],"performed.":[254],"this":[256],"purpose,":[257],"Haar":[260],"wavelets,":[261],"Principal":[262],"Component":[263],"Analysis":[264,269],"(PCA),":[265],"Linear":[267],"Discriminant":[268],"(LDA)":[270],"dimensionality-reduction":[271],"before":[273],"algorithm.":[277],"Their":[278],"performance":[279],"is":[280],"compared.":[281],"results":[283],"indicate":[284],"high":[285],"accuracies":[287],"obtained":[290],"using":[291],"these":[292],"dimensional":[293],"reduction":[294],"algorithms":[295],"followed":[296],"by":[297],"algorithms.":[299],"result":[301],"highlights":[302],"importance":[304],"order":[315],"provide":[317],"education":[319]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
