{"id":"https://openalex.org/W7140102061","doi":"https://doi.org/10.48550/arxiv.2603.19535","title":"Behavioral Engagement in VR-Based Sign Language Learning: Visual Attention as a Predictor of Performance and Temporal Dynamics","display_name":"Behavioral Engagement in VR-Based Sign Language Learning: Visual Attention as a Predictor of Performance and Temporal Dynamics","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7140102061","doi":"https://doi.org/10.48550/arxiv.2603.19535"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.19535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19535","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.19535","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Traini, Davide","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Traini, Davide","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Alcalde-Llergo, Jos\u00e9 Manuel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alcalde-Llergo, Jos\u00e9 Manuel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Buenestado-Fern\u00e1ndez, Mariana","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Buenestado-Fern\u00e1ndez, Mariana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ursino, Domenico","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ursino, Domenico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Yeguas-Bol\u00edvar, Enrique","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeguas-Bol\u00edvar, Enrique","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10648","display_name":"Virtual Reality Applications and Impacts","score":0.30489999055862427,"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"}},"topics":[{"id":"https://openalex.org/T10648","display_name":"Virtual Reality Applications and Impacts","score":0.30489999055862427,"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"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.17180000245571136,"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"}},{"id":"https://openalex.org/T11285","display_name":"Hearing Impairment and Communication","score":0.16840000450611115,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5558000206947327},{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.5479000210762024},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.49959999322891235},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.4049000144004822},{"id":"https://openalex.org/keywords/negative-binomial-distribution","display_name":"Negative binomial distribution","score":0.3483999967575073},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.34139999747276306},{"id":"https://openalex.org/keywords/visual-attention","display_name":"Visual attention","score":0.326200008392334},{"id":"https://openalex.org/keywords/binomial-distribution","display_name":"Binomial distribution","score":0.30320000648498535}],"concepts":[{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.6093999743461609},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5558000206947327},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.5479000210762024},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.5282999873161316},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.49959999322891235},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C199335787","wikidata":"https://www.wikidata.org/wiki/Q743364","display_name":"Negative binomial distribution","level":3,"score":0.3483999967575073},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C2986089797","wikidata":"https://www.wikidata.org/wiki/Q6501338","display_name":"Visual attention","level":3,"score":0.326200008392334},{"id":"https://openalex.org/C41054675","wikidata":"https://www.wikidata.org/wiki/Q185547","display_name":"Binomial distribution","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C74672266","wikidata":"https://www.wikidata.org/wiki/Q815859","display_name":"Language acquisition","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C522192633","wikidata":"https://www.wikidata.org/wiki/Q34228","display_name":"Sign language","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.26420000195503235},{"id":"https://openalex.org/C138496976","wikidata":"https://www.wikidata.org/wiki/Q175002","display_name":"Developmental psychology","level":1,"score":0.2615000009536743},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.19535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19535","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.19535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19535","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7565353512763977}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"analyzes":[2],"behavioral":[3,229],"engagement":[4,24,68,102,157,189,237],"in":[5,219,238],"SONAR,":[6],"a":[7,47,53,113,144],"virtual":[8],"reality":[9],"application":[10],"designed":[11],"for":[12,232],"sign":[13,221],"language":[14,222],"training":[15,181],"and":[16,33,38,70,134,182,199,214,224,234],"validation.":[17],"We":[18,58],"focus":[19],"on":[20],"three":[21],"automatically":[22],"derived":[23],"indicators":[25,69],"(Visual":[26],"Attention":[27],"(VA),":[28],"Video":[29],"Replay":[30],"Frequency":[31],"(VRF),":[32],"Post-Playback":[34],"Viewing":[35],"Time":[36],"(PPVT))":[37],"examine":[39,64],"their":[40,83],"relationship":[41],"with":[42,117,175],"learning":[43,106,140,223],"performance.":[44],"Participants":[45],"completed":[46],"self-paced":[48],"Training":[49],"phase,":[50],"followed":[51,73],"by":[52,74,92,120,159],"Validation":[54],"quiz":[55,71,118],"assessing":[56],"retention.":[57],"employed":[59],"Pearson":[60],"correlation":[61,116],"analysis":[62,91],"to":[63,81,100],"the":[65,105,209,226],"relationships":[66],"between":[67],"performance,":[72],"binomial":[75,129],"Generalized":[76],"Linear":[77],"Model":[78],"(GLM)":[79],"regression":[80],"assess":[82],"joint":[84],"predictive":[85],"contributions.":[86],"Additionally,":[87],"we":[88,154],"conducted":[89],"temporal":[90,156,168],"aggregating":[93,160],"moment-to-moment":[94,161],"VA":[95,111,133,162],"traces":[96,163],"across":[97,164],"all":[98,165],"learners":[99],"characterize":[101,155],"dynamics":[103],"during":[104,197,203],"session.":[107],"Results":[108],"show":[109],"that":[110,132],"exhibits":[112],"strong":[114],"positive":[115],"performance,followed":[119],"PPVT,":[121],"whereas":[122],"VRF":[123],"shows":[124],"no":[125],"meaningful":[126],"association.":[127],"A":[128],"GLM":[130],"confirms":[131],"PPVT":[135],"are":[136],"significant":[137],"predictors":[138],"of":[139,147,179,212,228],"success,":[141],"jointly":[142],"explaining":[143],"substantial":[145],"proportion":[146],"performance":[148],"variance.":[149],"Going":[150],"beyond":[151],"outcome-oriented":[152],"analysis,":[153],"patterns":[158],"learners.":[166],"The":[167],"profile":[169],"reveals":[170],"distinct":[171],"attention":[172,195,218],"peaks":[173,202],"aligned":[174],"informationally":[176],"dense":[177],"segments":[178],"both":[180],"validation":[183],"videos,":[184],"as":[185,187],"well":[186],"phase-specific":[188],"dynamics,":[190],"including":[191],"initial":[192],"acclimatization,":[193],"oscillatory":[194],"cycles":[196],"learning,":[198],"pronounced":[200],"attentional":[201],"assessment.":[204],"Together,":[205],"these":[206],"findings":[207],"highlight":[208],"central":[210],"role":[211],"sustained":[213],"strategically":[215],"allocated":[216],"visual":[217],"VR-based":[220],"demonstrate":[225],"value":[227],"trace":[230],"data":[231],"understanding":[233],"predicting":[235],"learner":[236],"immersive":[239],"environments.":[240]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}
