{"id":"https://openalex.org/W3126645029","doi":"https://doi.org/10.1145/3408877.3432439","title":"Early Performance Prediction using Interpretable Patterns in Programming Process Data","display_name":"Early Performance Prediction using Interpretable Patterns in Programming Process Data","publication_year":2021,"publication_date":"2021-03-03","ids":{"openalex":"https://openalex.org/W3126645029","doi":"https://doi.org/10.1145/3408877.3432439","mag":"3126645029"},"language":"en","primary_location":{"id":"doi:10.1145/3408877.3432439","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3408877.3432439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd ACM Technical Symposium on Computer Science Education","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2102.05765","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ge Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ge Gao","raw_affiliation_strings":["North Carolina State University, Raleigh, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Samiha Marwan","orcid":null},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samiha Marwan","raw_affiliation_strings":["North Carolina State University, Raleigh, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":null,"display_name":"Thomas W. Price","orcid":null},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas W. Price","raw_affiliation_strings":["North Carolina State University, Raleigh, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I137902535"],"apc_list":null,"apc_paid":null,"fwci":4.1081,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.94703712,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"342","last_page":"348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10533","display_name":"Teaching and Learning Programming","score":0.9994000196456909,"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/T10533","display_name":"Teaching and Learning Programming","score":0.9994000196456909,"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/T11122","display_name":"Online Learning and Analytics","score":0.9991999864578247,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/leverage","display_name":"Leverage (statistics)","score":0.791100025177002},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6173999905586243},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5081999897956848},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.364300012588501},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.35929998755455017},{"id":"https://openalex.org/keywords/programming-paradigm","display_name":"Programming paradigm","score":0.32710000872612}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.791100025177002},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.75},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6349999904632568},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6173999905586243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443000197410583},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5081999897956848},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42489999532699585},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C34165917","wikidata":"https://www.wikidata.org/wiki/Q188267","display_name":"Programming paradigm","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C50033165","wikidata":"https://www.wikidata.org/wiki/Q15712089","display_name":"Inductive programming","level":3,"score":0.31769999861717224},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C173404611","wikidata":"https://www.wikidata.org/wiki/Q528588","display_name":"Constraint programming","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3408877.3432439","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3408877.3432439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd ACM Technical Symposium on Computer Science Education","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2102.05765","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2102.05765","pdf_url":"https://arxiv.org/pdf/2102.05765","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2102.05765","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2102.05765","pdf_url":"https://arxiv.org/pdf/2102.05765","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1530885903","https://openalex.org/W1987936136","https://openalex.org/W2020420295","https://openalex.org/W2031092789","https://openalex.org/W2036955327","https://openalex.org/W2039029631","https://openalex.org/W2044342122","https://openalex.org/W2044490101","https://openalex.org/W2067438752","https://openalex.org/W2077361439","https://openalex.org/W2093991286","https://openalex.org/W2104916970","https://openalex.org/W2111760158","https://openalex.org/W2112328469","https://openalex.org/W2114184575","https://openalex.org/W2123536472","https://openalex.org/W2142368091","https://openalex.org/W2339183141","https://openalex.org/W2469269292","https://openalex.org/W2592733917","https://openalex.org/W2593348673","https://openalex.org/W2604398661","https://openalex.org/W2660393804","https://openalex.org/W2750279935","https://openalex.org/W2753422637","https://openalex.org/W2910922655","https://openalex.org/W2917619664","https://openalex.org/W2917871576","https://openalex.org/W2940692950","https://openalex.org/W2964982419","https://openalex.org/W3033291130"],"related_works":[],"abstract_inverted_index":{"Instructors":[0],"have":[1,27],"limited":[2,46],"time":[3],"and":[4,10,49,170,176,187],"resources":[5,12],"to":[6,16,47,90,94,172],"help":[7],"struggling":[8],"students,":[9],"these":[11,185],"should":[13],"be":[14],"directed":[15],"the":[17,100,153,166],"students":[18,130],"who":[19],"most":[20],"need":[21],"them.":[22],"To":[23],"address":[24],"this,":[25],"researchers":[26],"constructed":[28],"models":[29,44],"that":[30,60,108,165],"can":[31,143],"predict":[32,95,144],"students'":[33,76,112],"final":[34,145],"course":[35,97],"performance":[36,147],"early":[37],"in":[38,65,131],"a":[39,62,92,126,132],"semester.":[40],"However,":[41],"many":[42],"predictive":[43,110],"are":[45,109,168],"static":[48],"generic":[50],"student":[51,96],"features":[52],"(e.g.":[53],"demographics,":[54],"GPA),":[55],"rather":[56],"than":[57],"computing-specific":[58],"evidence":[59],"assesses":[61],"student's":[63],"progress":[64],"class.":[66],"Many":[67],"programming":[68,135,146,155,180],"environments":[69],"now":[70],"capture":[71],"complete":[72],"time-stamped":[73],"records":[74],"of":[75,106,111],"actions":[77],"during":[78],"programming.":[79],"In":[80,161],"this":[81,85],"work,":[82],"we":[83,103,163],"leverage":[84],"rich,":[86],"fine-grained":[87],"log":[88,101],"data":[89],"build":[91],"model":[93],"outcomes.":[98],"From":[99],"data,":[102],"extract":[104],"patterns":[105,138,167,186],"behaviors":[107],"success":[113],"using":[114,151],"an":[115],"approach":[116,124,142],"called":[117],"differential":[118],"sequence":[119],"mining.":[120],"We":[121,182],"evaluate":[122],"our":[123,141],"on":[125],"dataset":[127],"from":[128,140],"106":[129],"block-based,":[133],"introductory":[134],"course.":[136],"The":[137],"extracted":[139],"with":[148],"79%":[149],"accuracy":[150],"only":[152],"first":[154],"assignment,":[156],"outperforming":[157],"two":[158],"baseline":[159],"methods.":[160],"addition,":[162],"show":[164],"interpretable":[169],"correspond":[171],"concrete,":[173],"effective":[174],"--":[175,178],"ineffective":[177],"novice":[179],"behaviors.":[181],"also":[183],"discuss":[184],"their":[188],"implications":[189],"for":[190],"classroom":[191],"instruction.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2021-02-15T00:00:00"}
