[Purpose/Significance] Artificial Intelligence Generated Content (AIGC) is gradually showing a trend of reshaping the content creation ecosystem. AIGC disinformation spreads quickly, widely, and confusingly, which greatly increases the difficulty of identification and erodes public trust. As one of the main audiences of AI technology, college students have a high level of acceptance and familiarity with AIGC, so it is of great significance to explore the factors influencing college students’ behavior in screening AIGC disinformation. The results of the study have reference and informative value for improving college students’ ability to screen AIGC disinformation, expanding and extending the current information literacy education content in colleges and universities, and enhancing college students’ AI literacy. [Method/Process] This study adopted semi-structured interview method to obtain the research corpus, and summarized the viewpoints based on the grounded theory. The researchers selected 14 students to conduct in-depth interviews to collect data, summarized the 16 subcategories affecting the AIGC disinformation identification behavior, and focused them into the 3 main categories of personal factors, informational factors, and situational factors, to construct a model of the influencing factors of the college students’ AIGC disinformation screening behavior. [Result/Conclusion] Personal factors, information factors, and situational factors interact with each other, and finally affect the screening behavior. Based on the constructed model, strategies for improving college students’ AIGC disinformation screening ability are proposed in three stages: behavior trigger, process, and outcome. These strategies include: ① enhancing the motivation to screen, setting up prompts for screening, and triggering screening behavior; ② mastering methods of screening, training critical thinking skills, and optimizing the screening process; ③ deepening the development of AI detection technology, popularizing AI education, and improving AI-related laws and regulations, with multiple stakeholders working collaboratively to enhance the effectiveness of screening.
[1] 中国信息通信研究院. AI框架发展白皮书[EB/OL].[2025-03-27]. http://www.caict.ac.cn/kxyj/qwfb/bps/202202/P020220226369908606520.pdf.(China Academy of Information and Communications Technology. White paper on AI framework development (2022)[EB/OL].[2025-03-27]. http://www.caict.ac.cn/english/research/whitepapers/202203/P020220322344729036910.pdf.)
[2] United Nations Educational Scientific and Cultural Organization. Journalism "fake news" and disinformation[EB/OL].[2025-03-27]. https://www.unesco.org/sites/default/files/journalism_fake_news_disinformation_print_friendly_0.pdf.
[3] 浙江省第十三届人民代表大会常务委员会.浙江省人民代表大会常务委员会关于网络虚假信息治理的决定[N].浙江日报, 2021-10-21(5).(The Standing Committee of the 13th Zhejiang Provincial People's Congress. Decision of the Standing Committee of the Zhejiang Provincial People's Congress on the governance of online disinformation[N]. Zhejiang daily, 2021-10-21(5).)
[4] 漆晨航.生成式人工智能的虚假信息风险特征及其治理路径[J].情报理论与实践, 2024, 47(3):112-120.(QI C H. Research on the risks of disinformation from generative artificial intelligence and its governance paths[J]. Information studies:theory & application, 2024, 47(3):112-120.)
[5] 胡泳.人工智能驱动的虚假信息:现在与未来[J].南京社会科学, 2024(1):96-109.(HU Y. AI-driven disinformation:present and future[J]. Nanjing journal of social sciences, 2024(1):96-109.)
[6] ALTMAE S, SOLA-LEYVA A, SALUMETS A. Artificial intelligence in scientific writing:a friend or a foe?[J]. Reproductive biomedicine online, 2023, 47(1):3-9.
[7] 暴雨轩,芦天亮,杜彦辉.深度伪造视频检测技术综述[J].计算机科学, 2020, 47(9):283-292.(BAO Y X, LU T L, DU Y H. Overview of deepfake video detection technology[J]. Computer science, 2020, 47(9):283-292.)
[8] 梁瑞刚,吕培卓,赵月,等.视听觉深度伪造检测技术研究综述[J].信息安全学报, 2020, 5(2):1-17.(LIANG R G, LYU P Z, ZHAO Y, et al. A survey of audiovisual deepfake detection techniques[J]. Journal of cyber security, 2020, 5(2):1-17.)
[9] 刘期湘,宋凡.互联网+人工智能时代"网络水军"的刑法规制及限度[J].山东警察学院学报, 2019, 31(6):21-29.(LIU Q X, SONG F. Criminal law regulation and limitation of "network water army" in the era of internet+artificial intelligence[J]. Journal of Shandong Police College, 2019, 31(6):21-29.)
[10] 陆建平,党自强. AIGC时代虚假信息的制造传播与国家安全及公民权益的维护[J].浙江大学学报(人文社会科学版), 2024, 54(5):42-58.(LU J P, DANG Z Q. Manufacture and dissemination of fake information vs. protection of national security and people's rights and interests in the AIGC era[J]. Journal of Zhejiang University (humanities and social sciences), 2024, 54(5):42-58.)
[11] 陆俊,卜冰华.媒介素养——信息素养教育的新坐标[J].图书馆工作与研究, 2013(6):34-37.(LU J, BU B H. Media literacy:the new coordinates of information literacy education[J]. Library work and study, 2013(6):34-37.)
[12] 陈凯泉,何瑶,仲国强.人工智能视域下的信息素养内涵转型及AI教育目标定位——兼论基础教育阶段AI课程与教学实施路径[J].远程教育杂志, 2018, 36(1):61-71.(CHEN K Q, HE Y, ZHONG G Q. The transformation of information literacy connotation in artificial intelligence (AI) perspective and target positioning of artificial intelligence (AI) education:also on the implementation path of artificial intelligence course and teaching in basic education[J]. Journal of distance education, 2018, 36(1):61-71.)
[13] 王佑镁,杨晓兰,胡玮,等.从数字素养到数字能力:概念流变,构成要素与整合模型[J].远程教育杂志, 2013, 31(3):24-29.(WANG Y M, YANG X L, HU W, et al. Conception continuum, system elements and integrated model:from digital literacy to digital competence[J]. Journal of distance education, 2013, 31(3):24-29.)
[14] 黄如花,李白杨.数据素养教育:大数据时代信息素养教育的拓展[J].图书情报知识, 2016(1):21-29.(HUANG R H, LI B Y. Data literacy education:expansion of information literacy instruction in the big data era[J]. Documentation, information & knowledge, 2016(1):21-29.)
[15] 许亚锋,彭鲜,曹玥,等.人机协同视域下教师数智素养之内涵、功能与发展[J].远程教育杂志, 2020, 38(6):13-21.(XU Y F, PENG X, CAO Y, et al. The connotation, function and development of teachers'data intelligence competence from the perspective of human-machine cooperation[J]. Journal of distance education, 2020, 38(6):13-21.)
[16] 张银荣,杨刚,徐佳艳,等.人工智能素养模型构建及其实施路径[J].现代教育技术, 2022, 32(3):42-50.(ZHANG Y R, YANG G, XU J Y, et al. The cultivation of AI literacy model and its implementation path[J]. Modern educational technology, 2022, 32(3):42-50.)
[17] 施雨,茆意宏.人工智能素养的概念、框架与教育[J].图书馆论坛, 2024, 44(11):90-100.(SHI Y, MAO Y H. Concept, framework and education for artificial intelligence literacy[J]. Library tribune, 2024, 44(11):90-100.)
[18] 黄如花,石乐怡,吴应强,等.全球视野下我国人工智能素养教育内容框架的构建[J].图书情报知识, 2024, 41(3):27-37.(HUANG R H, SHI L Y, WU Y Q, et al. Constructing content framework for artificial intelligence literacy instruction in China from a global perspective[J]. Documentation, information & knowledge, 2024, 41(3):27-37.)
[19] WEF. Global risks report 2025[R]. World Economic Forum, 2025.
[20] EDUCAUSE. 2024 Educause horizon report:teaching and learning edition[EB/OL].[2025-03-27]. https://library.educause. edu/-/media/files/library/2024/5/2024hrteachinglearning.pdf.
[21] 雷晓燕,邵宾.大模型下人工智能生成内容嵌入数字素养教育研究[J].现代情报, 2023, 43(6):99-107.(LEI X Y, SHAO B. Research on embedding AI generated content into digital literacy education under large model[J]. Journal of modern information, 2023, 43(6):99-107.)
[22] 黄雨婷,冯婕.信息素养视域下的虚假信息甄别:国际进展与我国对策[J].图书情报知识, 2021(2):121-132.(HUANG Y T, FENG J. False information identification in view of information literacy:international progress and China's countermeasures[J]. Documentation, information & knowledge, 2021(2):121-132.)
[23] LONG D, MAGERKO B. What is AI literacy?competencies and design considerations[C]//Proceedings of the 2020 CHI conference on human factors in computing systems. New York:ACM, 2020:1-16.
[24] 莫祖英,王垲烁.国外虚假信息研究热点解析(2010-2020年)[J].郑州航空工业管理学院学报, 2022, 40(6):72-80.(MO Z Y, WANG K S. Analysis of the hotspots in foreign disinformation research (2010-2020)[J]. Journal of Zhengzhou University of Aeronautics, 2022, 40(6):72-80.)
[25] 袁方.社会研究方法教程[M].北京:北京大学出版社, 2015.(YUAN F. Social research methods[M]. Beijing:Peking University Press, 2015.)
[26] 福格.福格行为模型[M].天津:天津科学技术出版社, 2021.(FOGG B J. Tiny habits[M]. Tianjin:Tianjin Science and Technology Press, 2021.)
[27] 李文文,吕海若,王诗语.社交媒体环境下大学生虚假信息甄别行为研究[J].情报理论与实践, 2023, 46(12):77-83.(LI W W, LYU H R, WANG S Y. Research on university student's disinformation vetting behavior on social media[J]. Information studies:theory & application, 2023, 46(12):77-83.)
[28] United Nations Educational Scientific and Cultural Organization. AI competency framework for students[EB/OL].[2025-03-27]. https://unesdoc.unesco.org/ark:/48223/pf0000391105/PDF/391105eng.pdf.multi.
[29] 中华人民共和国全国人民代表大会常务委员会.中华人民共和国网络安全法[EB/OL].[2025-03-27]. http://www. npc.gov.cn/zgrdw/npc/xinwen/2016-11/07/content_2001605. htm.(The National People's Congress of the People's Republic of China. The cybersecurity law of the People's Republic of China[EB/OL].[2025-03-27]. http://www.npc.gov.cn/zgrdw/npc/xinwen/2016-11/07/content_2001605.htm.)
[30] 徐孝娟,赵宇翔,史如菊,等. SOR理论在国内图书情报学领域的采纳:溯源、应用及未来展望[J].情报资料工作, 2022, 43(5):98-105.(XU X J, ZHAO Y X, SHI R J, et al. The adoption of SOR theory in the field of library and information science in China:traceability, application and future prospects[J]. Information and documentation services, 2022, 43(5):98-105.)
[31] SWELLER J. Cognitive load theory and educational technology[J]. Educational technology research and development, 2020, 68(1):1-16.
[32] 中华人民共和国国家互联网信息办公室.互联网信息服务深度合成管理规定[EB/OL].[2025-03-27]. https://www. gov.cn/zhengce/zhengceku/2022-12/12/content_5731431. htm.(Cyberspace Administration of China. Provisions on the administration of deep synthesis of internet-based information services[EB/OL].[2025-03-27]. https://www.gov.cn/zhengce/zhengceku/2022-12/12/content_5731431.htm.)
[33] 中华人民共和国国家互联网信息办公室.生成式人工智能服务管理暂行办法[EB/OL].[2025-03-27]. https://www.gov.cn/zhengce/zhengceku/202307/content_6891752.htm.(Cyberspace Administration of China. Interim measures for the administration of generative artificial intelligence services[EB/OL].[2025-03-27]. https://www.gov.cn/zhengce/zhengceku/202307/content_6891752.htm.)
