{"id":"https://openalex.org/W2548874434","doi":"https://doi.org/10.1145/2993148.2993197","title":"Adaptive review for mobile MOOC learning via implicit physiological signal sensing","display_name":"Adaptive review for mobile MOOC learning via implicit physiological signal sensing","publication_year":2016,"publication_date":"2016-10-31","ids":{"openalex":"https://openalex.org/W2548874434","doi":"https://doi.org/10.1145/2993148.2993197","mag":"2548874434"},"language":"en","primary_location":{"id":"doi:10.1145/2993148.2993197","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2993148.2993197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM International Conference on Multimodal Interaction","raw_type":"proceedings-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/A5059182099","display_name":"Phuong Thao Pham","orcid":"https://orcid.org/0000-0002-6205-1298"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Phuong Pham","raw_affiliation_strings":["University of Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101663420","display_name":"Jingtao Wang","orcid":"https://orcid.org/0000-0002-1712-7898"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingtao Wang","raw_affiliation_strings":["University of Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059182099"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":6.2707,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.96266065,"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":"37","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.998199999332428,"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":0.998199999332428,"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/T10162","display_name":"Online and Blended Learning","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9646000266075134,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/personalization","display_name":"Personalization","score":0.7960931658744812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.777696967124939},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5895781517028809},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.4850708544254303},{"id":"https://openalex.org/keywords/mobile-computing","display_name":"Mobile computing","score":0.43943560123443604},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.42643705010414124},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.38607901334762573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3677375912666321},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34900906682014465},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.19258561730384827},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10188481211662292}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.7960931658744812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.777696967124939},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5895781517028809},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.4850708544254303},{"id":"https://openalex.org/C144543869","wikidata":"https://www.wikidata.org/wiki/Q2738570","display_name":"Mobile computing","level":2,"score":0.43943560123443604},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.42643705010414124},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.38607901334762573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3677375912666321},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34900906682014465},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19258561730384827},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10188481211662292}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2993148.2993197","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2993148.2993197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM International Conference on Multimodal Interaction","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1859092166","https://openalex.org/W1977948731","https://openalex.org/W1982709543","https://openalex.org/W2006205070","https://openalex.org/W2010270685","https://openalex.org/W2013785827","https://openalex.org/W2018206893","https://openalex.org/W2040896124","https://openalex.org/W2044948700","https://openalex.org/W2047221353","https://openalex.org/W2049174585","https://openalex.org/W2051525497","https://openalex.org/W2064925920","https://openalex.org/W2068195761","https://openalex.org/W2068807113","https://openalex.org/W2093816571","https://openalex.org/W2094265147","https://openalex.org/W2117005569","https://openalex.org/W2137627475","https://openalex.org/W2140240581","https://openalex.org/W2144183573","https://openalex.org/W2146738284","https://openalex.org/W2151030757","https://openalex.org/W2164462899","https://openalex.org/W2172071592","https://openalex.org/W2189385236","https://openalex.org/W2250871723","https://openalex.org/W2339737456","https://openalex.org/W3098635928","https://openalex.org/W4301377693"],"related_works":["https://openalex.org/W3175610199","https://openalex.org/W2141531133","https://openalex.org/W2048100608","https://openalex.org/W2090296580","https://openalex.org/W1576249345","https://openalex.org/W4243905374","https://openalex.org/W2785815065","https://openalex.org/W1796074903","https://openalex.org/W4245955065","https://openalex.org/W4254967497"],"abstract_inverted_index":{"Massive":[0],"Open":[1],"Online":[2],"Courses":[3],"(MOOCs)":[4],"have":[5],"the":[6,57,101,118,129],"potential":[7],"to":[8,148],"enable":[9],"high":[10],"quality":[11],"knowledge":[12],"dissemination":[13],"in":[14],"large":[15],"scale":[16],"at":[17,111],"low":[18,26],"cost.":[19],"However,":[20],"today's":[21],"MOOCs":[22],"also":[23,70,107],"suffer":[24],"from":[25,135,158],"engagement,":[27],"uni-directional":[28],"information":[29,91],"flow,":[30],"and":[31,94,138],"lack":[32],"of":[33,56,131],"personalization.":[34],"In":[35,79],"this":[36],"paper,":[37],"we":[38,84,142],"propose":[39],"AttentiveReview,":[40],"an":[41,124],"effective":[42],"intervention":[43],"technology":[44],"for":[45],"mobile":[46,126,150],"MOOC":[47,151],"learning.":[48],"AttentiveReview":[49,69,88,106,132],"infers":[50],"a":[51,76,80],"learner's":[52],"perceived":[53],"difficulty":[54],"levels":[55],"corresponding":[58],"learning":[59,95,152],"materials":[60,156],"via":[61],"implicit":[62],"photoplethysmography":[63],"(PPG)":[64],"sensing":[65],"on":[66],"unmodified":[67],"smartphones.":[68],"recommends":[71],"personalized":[72],"review":[73,103,120,155],"sessions":[74],"through":[75],"user-independent":[77],"model.":[78],"32-participant":[81],"user":[82],"study,":[83],"found":[85],"that:":[86],"1)":[87],"significantly":[89,112],"improved":[90],"recall":[92],"(+14.6%)":[93],"gain":[96],"(+17.4%)":[97],"when":[98,115],"compared":[99,116],"with":[100,117],"no":[102],"condition;":[104,121],"2)":[105],"achieved":[108],"comparable":[109],"performances":[110],"less":[113],"time":[114],"full":[119],"3)":[122],"As":[123],"end-to-end":[125],"tutoring":[127],"system,":[128],"benefits":[130],"outweigh":[133],"side-effects":[134],"false":[136,139],"positives":[137],"negatives.":[140],"Overall,":[141],"show":[143],"that":[144],"it":[145],"is":[146],"feasible":[147],"improve":[149],"by":[153],"recommending":[154],"adaptively":[157],"rich":[159],"but":[160],"noisy":[161],"physiological":[162],"signals.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":2}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
