{"id":"https://openalex.org/W7161703528","doi":"https://doi.org/10.48550/arxiv.2605.16642","title":"Examining University Students' Artificial Intelligence-Generated Content (AIGC) Verification Intention from a Protection Motivation Perspective","display_name":"Examining University Students' Artificial Intelligence-Generated Content (AIGC) Verification Intention from a Protection Motivation Perspective","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161703528","doi":"https://doi.org/10.48550/arxiv.2605.16642"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.16642","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16642","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.16642","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136487357","display_name":"Yiran Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Du, Yiran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5136487357"],"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.09629999846220016,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.09629999846220016,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12128","display_name":"AI in Service Interactions","score":0.08649999648332596,"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/T12887","display_name":"Educational Strategies and Epistemologies","score":0.06080000102519989,"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/structural-equation-modeling","display_name":"Structural equation modeling","score":0.675599992275238},{"id":"https://openalex.org/keywords/qualitative-comparative-analysis","display_name":"Qualitative comparative analysis","score":0.6230999827384949},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.529699981212616},{"id":"https://openalex.org/keywords/coping","display_name":"Coping (psychology)","score":0.5109999775886536},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.46129998564720154},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.34150001406669617}],"concepts":[{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.6837000250816345},{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.675599992275238},{"id":"https://openalex.org/C94617000","wikidata":"https://www.wikidata.org/wiki/Q639854","display_name":"Qualitative comparative analysis","level":2,"score":0.6230999827384949},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.529699981212616},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.5238999724388123},{"id":"https://openalex.org/C73282008","wikidata":"https://www.wikidata.org/wiki/Q1759895","display_name":"Coping (psychology)","level":2,"score":0.5109999775886536},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C75630572","wikidata":"https://www.wikidata.org/wiki/Q538904","display_name":"Applied psychology","level":1,"score":0.3693999946117401},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.34150001406669617},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C190248442","wikidata":"https://www.wikidata.org/wiki/Q839486","display_name":"Qualitative research","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C162446236","wikidata":"https://www.wikidata.org/wiki/Q653137","display_name":"Content analysis","level":2,"score":0.27000001072883606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.16642","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16642","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.16642","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16642","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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Artificial":[0],"Intelligence-Generated":[1],"Content":[2],"(AIGC)":[3],"is":[4],"increasingly":[5],"used":[6,60],"by":[7],"students":[8,47],"to":[9,30,61,85,90,135,156,174],"support":[10],"learning":[11],"tasks,":[12],"yet":[13],"its":[14],"outputs":[15],"may":[16],"contain":[17],"inaccuracies,":[18],"fabricated":[19],"references,":[20],"bias,":[21],"and":[22,73,112,121,164,180,187],"unsupported":[23],"claims.":[24],"This":[25],"study":[26,169],"examined":[27],"students'":[28,154],"intention":[29],"verify":[31,157],"AIGC":[32,52,74,103,158,178],"from":[33],"the":[34,63,175],"perspective":[35],"of":[36,177,191],"Protection":[37,171],"Motivation":[38,172],"Theory.":[39],"A":[40],"cross-sectional":[41],"survey":[42],"was":[43,59,83],"conducted":[44],"with":[45,139],"432":[46],"who":[48],"had":[49,124],"experience":[50],"using":[51],"for":[53,183],"learning.":[54],"Structural":[55],"equation":[56],"modelling":[57],"(SEM)":[58],"test":[62],"hypothesised":[64],"relationships":[65],"among":[66],"threat":[67],"appraisal,":[68,70],"coping":[69,166],"protection":[71,99,116,140],"motivation,":[72,117],"verification":[75,92,104,137,179],"intention,":[76,138],"while":[77],"fuzzy-set":[78],"qualitative":[79],"comparative":[80],"analysis":[81],"(fsQCA)":[82],"applied":[84],"identify":[86],"configurational":[87],"pathways":[88],"leading":[89,134],"high":[91,136],"intention.":[93,105],"The":[94,127,168],"SEM":[95],"results":[96,129],"showed":[97],"that":[98,153],"motivation":[100,141],"positively":[101,114],"predicted":[102],"Perceived":[106],"severity,":[107],"perceived":[108,165],"vulnerability,":[109],"response":[110,122],"efficacy,":[111],"self-efficacy":[113],"influenced":[115],"whereas":[118],"maladaptive":[119],"rewards":[120],"cost":[123],"negative":[125],"effects.":[126],"fsQCA":[128],"further":[130],"revealed":[131],"three":[132],"configurations":[133],"appearing":[142],"as":[143],"a":[144],"core":[145],"condition":[146],"across":[147],"all":[148],"pathways.":[149],"These":[150],"findings":[151],"suggest":[152],"willingness":[155],"depends":[159],"on":[160],"both":[161],"risk":[162],"recognition":[163],"capacity.":[167],"extends":[170],"Theory":[173],"context":[176],"provides":[181],"implications":[182],"promoting":[184],"critical,":[185],"responsible,":[186],"academically":[188],"appropriate":[189],"use":[190],"generative":[192],"AI":[193],"in":[194],"higher":[195],"education.":[196]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-20T00:00:00"}