{"id":"https://openalex.org/W7119521868","doi":"https://doi.org/10.3390/info17010060","title":"Machine Learning Approaches for Early Student Performance Prediction in Programming Education","display_name":"Machine Learning Approaches for Early Student Performance Prediction in Programming Education","publication_year":2026,"publication_date":"2026-01-08","ids":{"openalex":"https://openalex.org/W7119521868","doi":"https://doi.org/10.3390/info17010060"},"language":"en","primary_location":{"id":"doi:10.3390/info17010060","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17010060","pdf_url":"https://www.mdpi.com/2078-2489/17/1/60/pdf?version=1767899049","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/17/1/60/pdf?version=1767899049","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037040399","display_name":"Seifeddine Bouallegue","orcid":"https://orcid.org/0000-0001-5338-2223"},"institutions":[{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":true,"raw_author_name":"Seifeddine Bouallegue","raw_affiliation_strings":["Department of Software Systems, University of Doha for Science and Technology, Doha 24449, Qatar"],"raw_orcid":"https://orcid.org/0000-0001-5338-2223","affiliations":[{"raw_affiliation_string":"Department of Software Systems, University of Doha for Science and Technology, Doha 24449, Qatar","institution_ids":["https://openalex.org/I60342839"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Aymen Omri","orcid":"https://orcid.org/0000-0003-2551-9100"},"institutions":[{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Aymen Omri","raw_affiliation_strings":["Department of Software Systems, University of Doha for Science and Technology, Doha 24449, Qatar"],"raw_orcid":"https://orcid.org/0000-0003-2551-9100","affiliations":[{"raw_affiliation_string":"Department of Software Systems, University of Doha for Science and Technology, Doha 24449, Qatar","institution_ids":["https://openalex.org/I60342839"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122323041","display_name":"Salem Al-Naemi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105992","display_name":"Qatar Science and Technology Park","ror":"https://ror.org/01gshyb58","country_code":"QA","type":"archive","lineage":["https://openalex.org/I4210105992"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Salem Al-Naemi","raw_affiliation_strings":["College of Computing and IT, University of Doha for Science and Technology, Doha 24449, Qatar"],"raw_orcid":"https://orcid.org/0000-0002-2834-5962","affiliations":[{"raw_affiliation_string":"College of Computing and IT, University of Doha for Science and Technology, Doha 24449, Qatar","institution_ids":["https://openalex.org/I4210105992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037040399"],"corresponding_institution_ids":["https://openalex.org/I60342839"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":16.3077,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96690253,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"17","issue":"1","first_page":"60","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.490200012922287,"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":0.490200012922287,"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/T10533","display_name":"Teaching and Learning Programming","score":0.2612000107765198,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.15620000660419464,"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/generalizability-theory","display_name":"Generalizability theory","score":0.6983000040054321},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4498000144958496},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.445499986410141},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4374000132083893},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.4374000132083893},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42089998722076416},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.358599990606308},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.34619998931884766},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.34200000762939453}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8640000224113464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7547000050544739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7181000113487244},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6983000040054321},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4498000144958496},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42089998722076416},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.3098999857902527},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C2777598771","wikidata":"https://www.wikidata.org/wiki/Q5341279","display_name":"Educational data mining","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2858999967575073},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2635999917984009},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info17010060","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17010060","pdf_url":"https://www.mdpi.com/2078-2489/17/1/60/pdf?version=1767899049","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:dd37ad8ea537498cbfccaaa919d7e594","is_oa":true,"landing_page_url":"https://doaj.org/article/dd37ad8ea537498cbfccaaa919d7e594","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 17, Iss 1, p 60 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info17010060","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17010060","pdf_url":"https://www.mdpi.com/2078-2489/17/1/60/pdf?version=1767899049","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8010547757148743}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7119521868.pdf","grobid_xml":"https://content.openalex.org/works/W7119521868.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Intelligent":[0],"recommender":[1],"systems":[2,22],"are":[3,222],"essential":[4],"for":[5],"identifying":[6],"at-risk":[7,237],"students":[8,64],"and":[9,27,78,113,119,144,214,235,247],"personalizing":[10],"learning":[11,37,117,129,241,246],"through":[12],"tailored":[13],"resources.":[14],"Accurate":[15],"prediction":[16,55,130],"of":[17,35,63,103,172,219],"student":[18,51],"performance":[19],"enables":[20],"these":[21],"to":[23,39,53,90,232],"deliver":[24,244],"timely":[25,248],"interventions":[26],"data-driven":[28,228],"support.":[29],"This":[30,227],"paper":[31],"presents":[32],"the":[33,75,94,108,138,170,173,181,200,211,215,223],"application":[34],"machine":[36,128],"models":[38,131,177],"predict":[40],"final":[41,95],"exam":[42],"grades":[43,112],"in":[44,66],"a":[45,59,67,100],"university-level":[46],"programming":[47,68],"course,":[48],"leveraging":[49],"multi-modal":[50],"data":[52,86,136],"improve":[54],"accuracy.":[56],"In":[57],"particular,":[58],"recent":[60],"raw":[61],"dataset":[62,150,193],"enrolled":[65],"course":[69],"across":[70],"36":[71],"class":[72],"sections":[73],"from":[74,137,194],"Fall":[76,139,183],"2024":[77,140,184],"Winter":[79,195],"2025":[80],"terms":[81],"was":[82,87,105],"initially":[83,133],"processed.":[84],"The":[85,157],"collected":[88],"up":[89],"one":[91],"month":[92],"before":[93],"exam.":[96],"From":[97],"this":[98,124,149],"data,":[99],"comprehensive":[101],"set":[102],"features":[104],"engineered,":[106],"including":[107],"student\u2019s":[109],"background,":[110],"assessment":[111],"completion":[114,217],"times,":[115],"digital":[116],"interactions,":[118],"engagement":[120],"metrics.":[121],"Building":[122],"on":[123,148,180,190],"feature":[125],"set,":[126],"six":[127],"were":[132,146,178,187],"developed":[134],"using":[135,151],"term.":[141],"Both":[142],"training":[143],"testing":[145],"conducted":[147],"cross-validation":[152],"combined":[153],"with":[154,197],"hyperparameter":[155],"tuning.":[156],"XGBoost":[158,198],"model":[159],"demonstrated":[160],"strong":[161],"performance,":[162],"achieving":[163,199],"an":[164,191],"accuracy":[165],"exceeding":[166,203],"91%.":[167],"To":[168],"assess":[169],"generalizability":[171],"considered":[174],"models,":[175],"all":[176],"retrained":[179],"complete":[182],"dataset.":[185],"They":[186],"then":[188],"evaluated":[189],"independent":[192],"2025,":[196],"highest":[201],"accuracy,":[202],"84%.":[204],"Feature":[205],"importance":[206],"analysis":[207],"has":[208],"revealed":[209],"that":[210,243],"midterm":[212],"grade":[213],"average":[216],"duration":[218],"lab":[220],"assessments":[221],"most":[224],"influential":[225],"predictors.":[226],"approach":[229],"empowers":[230],"instructors":[231],"proactively":[233],"identify":[234],"support":[236],"students,":[238],"enabling":[239],"adaptive":[240],"environments":[242],"personalized":[245],"interventions.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-01-09T00:00:00"}