{"id":"https://openalex.org/W3180053449","doi":"https://doi.org/10.1155/2021/9958203","title":"Performance Prediction for Higher Education Students Using Deep Learning","display_name":"Performance Prediction for Higher Education Students Using Deep Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3180053449","doi":"https://doi.org/10.1155/2021/9958203","mag":"3180053449"},"language":"en","primary_location":{"id":"doi:10.1155/2021/9958203","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/9958203","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/9958203.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2021/9958203.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100735641","display_name":"Shuping Li","orcid":"https://orcid.org/0000-0003-1890-1264"},"institutions":[{"id":"https://openalex.org/I4210116828","display_name":"Mudanjiang Normal University","ror":"https://ror.org/02dzkdp68","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116828"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuping Li","raw_affiliation_strings":["Mudanjiang Normal University, Mudanjiang 157011, China"],"affiliations":[{"raw_affiliation_string":"Mudanjiang Normal University, Mudanjiang 157011, China","institution_ids":["https://openalex.org/I4210116828"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034610982","display_name":"Taotang Liu","orcid":"https://orcid.org/0000-0003-4822-468X"},"institutions":[{"id":"https://openalex.org/I4210116828","display_name":"Mudanjiang Normal University","ror":"https://ror.org/02dzkdp68","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116828"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Taotang Liu","raw_affiliation_strings":["Mudanjiang Normal University, Mudanjiang 157011, China"],"affiliations":[{"raw_affiliation_string":"Mudanjiang Normal University, Mudanjiang 157011, China","institution_ids":["https://openalex.org/I4210116828"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034610982"],"corresponding_institution_ids":["https://openalex.org/I4210116828"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":13.6298,"has_fulltext":true,"cited_by_count":80,"citation_normalized_percentile":{"value":0.98932625,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9995999932289124,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9542999863624573,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9412999749183655,"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/mean-squared-error","display_name":"Mean squared error","score":0.8138988614082336},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7356421947479248},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6728533506393433},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.6313949823379517},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.6201409697532654},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.612832248210907},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5838675498962402},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5721791386604309},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.48097407817840576},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4587535858154297},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43211910128593445},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18992483615875244},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09875500202178955}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.8138988614082336},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7356421947479248},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6728533506393433},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.6313949823379517},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.6201409697532654},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.612832248210907},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5838675498962402},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5721791386604309},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.48097407817840576},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4587535858154297},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43211910128593445},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18992483615875244},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09875500202178955},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2021/9958203","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/9958203","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/9958203.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:9958203","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/complexity/2021/9958203.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:6081140787044550b0f880c134eb741d","is_oa":true,"landing_page_url":"https://doaj.org/article/6081140787044550b0f880c134eb741d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/9958203","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/9958203","pdf_url":"https://downloads.hindawi.com/journals/complexity/2021/9958203.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G3679294911","display_name":null,"funder_award_id":"BCA160055","funder_id":"https://openalex.org/F4320335869","funder_display_name":"National Social Science Fund of China"}],"funders":[{"id":"https://openalex.org/F4320335869","display_name":"National Social Science Fund of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3180053449.pdf","grobid_xml":"https://content.openalex.org/works/W3180053449.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W2187155979","https://openalex.org/W2588434662","https://openalex.org/W2730483724","https://openalex.org/W2781636776","https://openalex.org/W2786010338","https://openalex.org/W2795157614","https://openalex.org/W2804978390","https://openalex.org/W2905931716","https://openalex.org/W2922995703","https://openalex.org/W2938441647","https://openalex.org/W2944328891","https://openalex.org/W2945554622","https://openalex.org/W2968584812","https://openalex.org/W3005006660","https://openalex.org/W3009535750","https://openalex.org/W3028020181","https://openalex.org/W3047010778","https://openalex.org/W3047492485","https://openalex.org/W3091847065","https://openalex.org/W3094211122","https://openalex.org/W3102673529"],"related_works":["https://openalex.org/W2264067234","https://openalex.org/W3124243301","https://openalex.org/W1571502335","https://openalex.org/W1589409554","https://openalex.org/W2759038785","https://openalex.org/W2172232600","https://openalex.org/W3123876860","https://openalex.org/W3124172198","https://openalex.org/W2046181650","https://openalex.org/W2142633247"],"abstract_inverted_index":{"Predicting":[0],"students\u2019":[1,28],"performance":[2,29,48],"is":[3,84,171,186],"very":[4],"important":[5],"in":[6,32,59,127,218,226],"matters":[7],"related":[8],"to":[9,17,23,45,56,61,64,67,72,104,117,145,173,232],"higher":[10],"education":[11],"as":[12,14,92,94,133],"well":[13,93],"with":[15,136,177,202],"regard":[16],"deep":[18,124],"learning":[19],"and":[20,35,54,66,113,153,160,182,196,229],"its":[21,216],"relationship":[22],"educational":[24],"data.":[25],"Prediction":[26,101],"of":[27,49,78,81,98,111,151,207,220],"provides":[30,102],"support":[31,63,103],"selecting":[33],"courses":[34,112],"designing":[36],"appropriate":[37,116],"future":[38],"study":[39,114],"plans":[40,115],"for":[41,188,205],"students.":[42],"In":[43],"addition":[44],"predicting":[46],"the":[47,69,74,79,88,105,175,183,190,208,223,234],"students,":[50],"it":[51,86],"helps":[52],"teachers":[53],"managers":[55],"monitor":[57],"students":[58,96,106],"order":[60],"provide":[62],"them":[65],"integrate":[68],"training":[70,169],"programs":[71],"obtain":[73],"best":[75,235],"results.":[76],"One":[77],"benefits":[80],"student\u2019s":[82],"prediction":[83,128],"that":[85],"reduces":[87],"official":[89],"warning":[90],"signs":[91],"expelling":[95],"because":[97],"their":[99,109,118],"inefficiency.":[100],"themselves":[107],"through":[108,222],"choice":[110],"abilities.":[119],"The":[120,168,211],"proposed":[121,209,212],"method":[122],"used":[123,144,172,187,204],"neural":[125,147],"network":[126,148],"by":[129,157,165],"extracting":[130],"informative":[131],"data":[132,162,179],"a":[134],"feature":[135],"corresponding":[137],"weights.":[138],"Multiple":[139],"updated":[140],"hidden":[141,154],"layers":[142,155],"are":[143,163],"design":[146],"automatically;":[149],"number":[150],"nodes":[152],"controlled":[156],"feed":[158],"forwarding":[159],"backpropagation":[161],"produced":[164],"previous":[166],"cases.":[167],"mode":[170,185],"train":[174],"system":[176,213],"labeled":[178],"from":[180],"dataset":[181],"testing":[184],"evaluating":[189],"system.":[191],"Mean":[192],"absolute":[193],"error":[194,200],"(MAE)":[195],"root":[197],"mean":[198],"squared":[199],"(RMSE)":[201],"accuracy":[203],"evolution":[206],"method.":[210],"has":[214],"proven":[215],"worth":[217],"terms":[219],"efficiency":[221],"achieved":[224],"results":[225],"MAE":[227],"(0.593)":[228],"RMSE":[230],"(0.785)":[231],"get":[233],"prediction.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":8}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}