{"id":"https://openalex.org/W3168178829","doi":"https://doi.org/10.1145/3430895.3460143","title":"Comparative Analysis of the Feature Extraction Approaches for Predicting Learners Progress in Online Courses","display_name":"Comparative Analysis of the Feature Extraction Approaches for Predicting Learners Progress in Online Courses","publication_year":2021,"publication_date":"2021-06-07","ids":{"openalex":"https://openalex.org/W3168178829","doi":"https://doi.org/10.1145/3430895.3460143","mag":"3168178829"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430895.3460143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5002291803","display_name":"Farahnaz Soleimani","orcid":"https://orcid.org/0000-0001-7809-2978"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"funder","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farahnaz Soleimani","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112649019","display_name":"Jeonghyun Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"funder","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeonghyun Lee","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.194,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.737369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":81,"max":82},"biblio":{"volume":null,"issue":null,"first_page":"151","last_page":"159"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9999,"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":0.9999,"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":0.9528,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.943,"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/clickstream","display_name":"Clickstream","score":0.91279864},{"id":"https://openalex.org/keywords/learning-analytics","display_name":"Learning Analytics","score":0.8115597},{"id":"https://openalex.org/keywords/demographics","display_name":"Demographics","score":0.554527}],"concepts":[{"id":"https://openalex.org/C138744977","wikidata":"https://www.wikidata.org/wiki/Q5132438","display_name":"Clickstream","level":5,"score":0.91279864},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.8115597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7910231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6378141},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.58380616},{"id":"https://openalex.org/C2780084366","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demographics","level":2,"score":0.554527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5325904},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43966842},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.43295008},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4206403},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.27387697},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.20543563},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C127613066","wikidata":"https://www.wikidata.org/wiki/Q557770","display_name":"Web API","level":4,"score":0.0},{"id":"https://openalex.org/C130436687","wikidata":"https://www.wikidata.org/wiki/Q7978591","display_name":"Web modeling","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430895.3460143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.78,"display_name":"Quality education"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":20,"referenced_works":["https://openalex.org/W1615000945","https://openalex.org/W1758899182","https://openalex.org/W1969423031","https://openalex.org/W2066777211","https://openalex.org/W2119862467","https://openalex.org/W2250880511","https://openalex.org/W2525430002","https://openalex.org/W2602588427","https://openalex.org/W2735315095","https://openalex.org/W273955616","https://openalex.org/W2782681397","https://openalex.org/W2788983907","https://openalex.org/W2792116143","https://openalex.org/W2804302410","https://openalex.org/W2901091014","https://openalex.org/W2903964883","https://openalex.org/W2950047819","https://openalex.org/W3038917407","https://openalex.org/W4232754775","https://openalex.org/W4245039430"],"related_works":["https://openalex.org/W4313414442","https://openalex.org/W4307851609","https://openalex.org/W3168178829","https://openalex.org/W2975622968","https://openalex.org/W2799586942","https://openalex.org/W2769342982","https://openalex.org/W2768832457","https://openalex.org/W2504091800","https://openalex.org/W2331775400","https://openalex.org/W1987827786"],"abstract_inverted_index":{"Although":[0],"MicroMasters":[1,45,77],"courses":[2,43],"differ":[3,95],"from":[4,96],"traditional":[5],"undergraduate":[6],"level":[7],"MOOCs":[8],"in":[9,69,75,98,112],"student":[10],"demographics,":[11],"course":[12],"design,":[13],"and":[14,90,126,132],"outcomes,":[15],"the":[16,35,39,48,51,67,70,87,93,105,134,143,146],"various":[17,117],"aspects":[18],"of":[19,22,41,44,53,73,108,145],"this":[20],"type":[21],"program":[23],"have":[24],"not":[25],"yet":[26],"been":[27],"sufficiently":[28],"investigated.":[29],"This":[30],"study":[31],"aims":[32],"to":[33,65,104],"pave":[34],"path":[36],"towards":[37],"enhancing":[38],"design":[40],"constituent":[42],"programs":[46],"with":[47,86],"focus":[49],"on":[50,139],"application":[52,107],"Machine":[54],"Learning":[55],"algorithms.":[56],"Thereby,":[57],"we":[58,115],"use":[59],"a":[60,76,99],"large-scale":[61],"clickstream":[62,80],"edX":[63],"database":[64],"explore":[66],"trends":[68],"online":[71],"engagement":[72],"learners":[74],"program,":[78],"detect":[79],"events":[81],"that":[82],"are":[83],"highly":[84],"correlated":[85],"students'":[88],"progress,":[89],"investigate":[91],"how":[92],"engagements":[94,144],"those":[97],"classic":[100],"individual":[101],"MOOC.":[102],"Contrary":[103],"previous":[106],"machine":[109,119],"learning":[110,113,120],"algorithms":[111],"analytics,":[114],"implement":[116],"well-known":[118],"approaches":[121],"such":[122],"as":[123],"stepwise":[124],"regression":[125],"tree-based":[127],"algorithms,":[128],"evaluate":[129],"their":[130],"performance,":[131],"propose":[133],"best-performed":[135],"approach.":[136],"We":[137],"elaborate":[138],"noticeable":[140],"differences":[141],"between":[142],"considered":[147],"two":[148],"groups.":[149]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3168178829","counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-01-24T04:24:00.375907","created_date":"2021-06-22"}