{"id":"https://openalex.org/W4294808777","doi":"https://doi.org/10.1108/itse-10-2021-0188","title":"An explainable attention-based bidirectional GRU model for pedagogical classification of MOOCs","display_name":"An explainable attention-based bidirectional GRU model for pedagogical classification of MOOCs","publication_year":2022,"publication_date":"2022-09-06","ids":{"openalex":"https://openalex.org/W4294808777","doi":"https://doi.org/10.1108/itse-10-2021-0188"},"language":"en","primary_location":{"id":"doi:10.1108/itse-10-2021-0188","is_oa":false,"landing_page_url":"https://doi.org/10.1108/itse-10-2021-0188","pdf_url":null,"source":{"id":"https://openalex.org/S43354291","display_name":"Interactive Technology and Smart Education","issn_l":"1741-5659","issn":["1741-5659","1758-8510"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interactive Technology and Smart Education","raw_type":"journal-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/A5004378141","display_name":"Hanane Sebbaq","orcid":"https://orcid.org/0000-0002-1254-350X"},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]},{"id":"https://openalex.org/I127336678","display_name":"Ecole Mohammadia d'Ing\u00e9nieurs","ror":"https://ror.org/00md3qm14","country_code":"MA","type":"education","lineage":["https://openalex.org/I127336678"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Hanane Sebbaq","raw_affiliation_strings":["RIME Team, MASI Laboratory, E3S Research Center, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIME Team, MASI Laboratory, E3S Research Center, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat, Morocco","institution_ids":["https://openalex.org/I127336678","https://openalex.org/I126477371"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053843586","display_name":"Nour-eddine El Faddouli","orcid":"https://orcid.org/0000-0002-3467-2177"},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]},{"id":"https://openalex.org/I127336678","display_name":"Ecole Mohammadia d'Ing\u00e9nieurs","ror":"https://ror.org/00md3qm14","country_code":"MA","type":"education","lineage":["https://openalex.org/I127336678"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Nour-eddine El Faddouli","raw_affiliation_strings":["RIME Team, MASI Laboratory, E3S Research Center, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIME Team, MASI Laboratory, E3S Research Center, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat, Morocco","institution_ids":["https://openalex.org/I127336678","https://openalex.org/I126477371"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0936,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.83405867,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"19","issue":"4","first_page":"396","last_page":"421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9983999729156494,"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":0.9983999729156494,"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/T10028","display_name":"Topic Modeling","score":0.9923999905586243,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.986299991607666,"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":0.7149428129196167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6880186796188354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.560329020023346},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.5405859351158142},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4891813099384308},{"id":"https://openalex.org/keywords/verb","display_name":"Verb","score":0.4471912980079651},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.4453299939632416},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.422770619392395},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4167296588420868},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.41585785150527954},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.18647629022598267}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149428129196167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6880186796188354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.560329020023346},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.5405859351158142},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4891813099384308},{"id":"https://openalex.org/C2776397901","wikidata":"https://www.wikidata.org/wiki/Q24905","display_name":"Verb","level":2,"score":0.4471912980079651},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4453299939632416},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.422770619392395},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4167296588420868},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.41585785150527954},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.18647629022598267},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/itse-10-2021-0188","is_oa":false,"landing_page_url":"https://doi.org/10.1108/itse-10-2021-0188","pdf_url":null,"source":{"id":"https://openalex.org/S43354291","display_name":"Interactive Technology and Smart Education","issn_l":"1741-5659","issn":["1741-5659","1758-8510"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interactive Technology and Smart Education","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W88644838","https://openalex.org/W152012340","https://openalex.org/W248626835","https://openalex.org/W1707854878","https://openalex.org/W1714222232","https://openalex.org/W1924770834","https://openalex.org/W1980867644","https://openalex.org/W1982281773","https://openalex.org/W2003802332","https://openalex.org/W2014545475","https://openalex.org/W2031556512","https://openalex.org/W2063370556","https://openalex.org/W2120773535","https://openalex.org/W2131314393","https://openalex.org/W2133564696","https://openalex.org/W2152163007","https://openalex.org/W2162821268","https://openalex.org/W2165427613","https://openalex.org/W2470673105","https://openalex.org/W2556882739","https://openalex.org/W2576343506","https://openalex.org/W2587657135","https://openalex.org/W2591354889","https://openalex.org/W2592949994","https://openalex.org/W2782573387","https://openalex.org/W2809333429","https://openalex.org/W2895675920","https://openalex.org/W2902962093","https://openalex.org/W2914767245","https://openalex.org/W2947843940","https://openalex.org/W2981731882","https://openalex.org/W2991474482","https://openalex.org/W3011091101","https://openalex.org/W3035640233","https://openalex.org/W3049585767","https://openalex.org/W3092047717","https://openalex.org/W3104306954","https://openalex.org/W3121726600","https://openalex.org/W3123079990","https://openalex.org/W3130450512","https://openalex.org/W3131761072","https://openalex.org/W3144152020","https://openalex.org/W3177369441","https://openalex.org/W3190268244","https://openalex.org/W3193740800","https://openalex.org/W3197066695","https://openalex.org/W3205679577","https://openalex.org/W4233329786","https://openalex.org/W6631190155","https://openalex.org/W6695661434","https://openalex.org/W6770432743","https://openalex.org/W6781905506"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W3107474891","https://openalex.org/W4211165872","https://openalex.org/W2746217931","https://openalex.org/W2810280135","https://openalex.org/W3107602296","https://openalex.org/W2984206076","https://openalex.org/W4214879735","https://openalex.org/W2993873509","https://openalex.org/W3212082274"],"abstract_inverted_index":{"Purpose":[0],"The":[1,163,213,362],"purpose":[2],"of":[3,12,21,52,96,120,138,153,166,172,186,207,251,288,306,325,347,372],"this":[4,25,79,167,191,263,292,294,329,367,391,393],"study":[5,26,56,80,168,179,295,314,330,368,394],"is,":[6],"First,":[7],"to":[8,16,181,256,269,366,396,401],"leverage":[9],"the":[10,18,46,50,53,67,82,121,126,135,149,170,201,226,232,236,247,252,258,265,275,284,297,304,307,311,316,323,326,344,370,403],"limitation":[11],"annotated":[13,173,373,378],"data":[14,176,184,381,404],"and":[15,33,48,70,211,356,359],"identify":[17],"cognitive":[19,127,136,286,345,387],"level":[20,128],"learning":[22,29,146,161,174,188,219,279,337,379],"objectives":[23,175,280],"efficiently,":[24],"adopts":[27],"transfer":[28],"by":[30],"using":[31],"word2vec":[32,319],"a":[34,58,102,183,271],"bidirectional":[35,298],"gated":[36],"recurrent":[37],"units":[38],"(GRU)":[39],"that":[40,200,273,339],"can":[41],"fully":[42],"take":[43],"into":[44,134,145],"account":[45],"context":[47,68],"improves":[49],"classification":[51,137,281,346],"model.":[54],"This":[55,178,196,240,313],"adds":[57],"layer":[59,238],"based":[60,282,302,383],"on":[61,283,303,384],"attention":[62,237],"mechanism":[63],"(AM),":[64],"which":[65,221,254],"captures":[66],"vector":[69,354],"gives":[71],"keywords":[72],"higher":[73],"weight":[74],"for":[75,105,278,343],"text":[76],"classification.":[77,260],"Second,":[78],"explains":[81],"authors\u2019":[83],"model\u2019s":[84],"results":[85],"with":[86,310,318,333,360],"local":[87],"interpretable":[88],"model-agnostic":[89],"explanations":[90],"(LIME).":[91],"Design/methodology/approach":[92],"Bloom's":[93,113,289],"taxonomy":[94,228],"levels":[95,119,287],"cognition":[97],"are":[98,340],"commonly":[99],"used":[100,342],"as":[101],"reference":[103],"standard":[104],"identifying":[106],"e-learning":[107,139],"contents.":[108],"Many":[109],"action":[110,229],"verbs":[111],"in":[112,217,245],"taxonomy,":[114],"however,":[115],"overlap":[116],"at":[117],"different":[118],"hierarchy,":[122],"causing":[123],"uncertainty":[124],"regarding":[125],"expected.":[129],"Some":[130],"studies":[131],"have":[132,397],"looked":[133,144],"content":[140],"but":[141,190,400],"none":[142],"has":[143],"objectives.":[147],"On":[148],"other":[150],"hand,":[151],"most":[152,248],"these":[154],"research":[155],"papers":[156],"just":[157],"adopt":[158],"classical":[159,335],"machine":[160,336,355],"algorithms.":[162],"main":[164,266,363],"constraint":[165,364],"is":[169,268,369,376],"availability":[171],"sets.":[177],"managed":[180],"build":[182,402],"set":[185,382],"2,400":[187],"objectives,":[189,220],"size":[192],"remains":[193],"limited.":[194],"Findings":[195],"study\u2019s":[197,241],"experiments":[198],"show":[199],"proposed":[202,214,327],"model":[203,215,234,272,301],"achieves":[204],"highest":[205],"scores":[206],"accuracy:":[208],"90.62%,":[209],"F1-score":[210],"loss.":[212],"succeeds":[216],"classifying":[218],"contain":[222],"ambiguous":[223],"verb":[224],"from":[225],"Bloom\u2019s":[227,385],"verbs,":[230],"while":[231],"same":[233],"without":[235],"fails.":[239],"LIME":[242],"explainer":[243],"aids":[244],"visualizing":[246],"essential":[249],"features":[250],"text,":[253],"contributes":[255],"justifying":[257],"final":[259],"Originality/value":[261],"In":[262,291],"study,":[264],"objective":[267,380],"propose":[270],"outperforms":[274],"baseline":[276],"models":[277],"six":[285],"taxonomy.":[290],"sense,":[293],"builds":[296],"GRU":[299],"(BiGRU)-attention":[300],"combination":[305],"BiGRU":[308],"algorithm":[309],"AM.":[312],"feeds":[315],"architecture":[317],"embeddings.":[320],"To":[321,389],"prove":[322],"effectiveness":[324],"model,":[328],"compares":[331],"it":[332],"four":[334],"algorithms":[338],"widely":[341],"text:":[348],"Bayes":[349],"naive,":[350],"logistic":[351],"regression,":[352],"support":[353],"K-nearest":[357],"neighbors":[358],"GRU.":[361],"related":[365],"absence":[371],"data;":[374],"there":[375],"no":[377,398],"taxonomy's":[386],"levels.":[388],"overcome":[390],"problem,":[392],"seemed":[395],"choice":[399],"set.":[405]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
