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Using purposive sampling, 10 undergraduate students who use tools such as ChatGPT or AI-integrated learning management systems for at least one month participated in semi-structured interviews. Thematic analysis identified nine themes across affective, behavioral, cognitive, and ethical dimensions, highlighting emotional strain, reliance patterns, metacognitive regulation, and academic integrity concerns.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/the-lived-experiences-of-college-students-navigating-technostress-through-ai-learning-tools/324697/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/the-lived-experiences-of-college-students-navigating-technostress-through-ai-learning-tools/324697.png","ImageObject",300,407,{"name":92,"@type":93},"Riley","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-12","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",18,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What was the focus of the study on technostress?","Question",{"text":113,"@type":114},"The study focused on students’ lived experiences of technostress when navigating AI learning tools in higher education.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How were participants selected and what data were collected?",{"text":118,"@type":114},"Ten undergraduate students were selected through purposive sampling and took part in semi-structured interviews after using AI tools for at least one month.",{"name":120,"@type":111,"acceptedAnswer":121},"What key dimensions and themes emerged from the analysis?",{"text":122,"@type":114},"Nine themes emerged across four dimensions: affective, behavioral, cognitive, and ethical, including emotional strain, reliance patterns, metacognitive regulation, and academic integrity concerns.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},324697,1790181961,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":145,"read_time":146,"preview_page_count":4},1374391975076,"https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051","The Lived Experiences of College Students Navigating Technostress  \nThrough AI Learning Tools  \nBacunawa, Joanne Stefanie D., RPm,CRS; Caringal, Dal Valdemar T., RPm; Campos, Rafael B.; Dela Llana, Marlo Rey D; Jimenez, Rikxzel Josh D, RPm, CHRA  \nSchool of Graduate Studies, Mapua University Makati, Makati, Philippines DOI: [https://doi.org/10.47772/IJRISS.2026.1017PSY0016](https://doi.org/10.47772/IJRISS.2026.1017PSY0016)  \nReceived: 19 March 2026; Accepted: 24 March 2026; Published: 14 April 2026  \nABSTRACT  \nThis qualitative phenomenological study explored the experience of college students in navigating technostress while using AI learning tools in higher education. Through purposive sampling, 10 undergraduate students who use AI tools such as ChatGPT or AI‑integrated learning management systems for at least one month were invited to participate in semi‑structured interviews. Thematic analysis yielded nine themes across four dimensions: affective, behavioral, cognitive and ethical reflecting students’ emotional strain, patterns of reliance, metacognitive regulation and academic integrity concerns. Findings showed that unclear institutional policies and inconsistent faculty expectations intensify technostress while students cope through peer support, self‑imposed digital boundaries and critical verification of AI‑generated outputs. Participants articulated tensions between efficiency and originality. The study emphasizes the need for culturally grounded AI literacy, clearer guidelines on responsible AI use, and supportive learning environments that foster critical thinking, academic integrity and sustainable technology practices in line with quality and well‑being goals in higher education.  \nKeywords: Technostress, AI learning tools, Academic integrity, Student well‑being, Quality higher education INTRODUCTION  \nDigital learning becomes a vital part of society, as its rapid advancement transforms various fields of education (Zhang & Aslan, 2021) . Artificial intelligence (AI) offers diverse capabilities to support students' learning and development, providing transformative and personalized outcomes. These adapt to the specific needs of academic learning (Chen et al., 2020; Holmes et al., 2022, as cited in Vieriu and Petrea, 2025; Hennekeuser et al., 2024) . Consequently, higher education must define the role and limitations of AI learning tools (Holmes & Tuomi, 2022) .  \nThe development of artificial intelligence (AI) learning tools is specifically significant for supporting selfregulated learning, problem-solving, and feedback, helping students to adjust to their cognitive needs and encourage active participation (Azevedo & Aleven, 2013; Kasneci et al., 2023). Despite these risks, it has proven beneficial in reducing cognitive load, streamlining information access to students, and improving productivity (Chan and Hu, 2023; Idroes et al., 2023; Malik et al., 2023; Zhou et al., 2024) .  \nIn higher education, digital technology is central to academic work, as online learning platforms and AI learning tools ease the submission of assignments, access to course materials, and preparation for examinations. Although these technologies are designed for efficiency, this adds to the complexity of the learners’ work, which demands continuous adjustment and can become a psychological burden (Tarafdar et al., 2015) . Such a state is characterized by exhaustion, overwork, and anger. Technostress refers to the negative impacts of technological demands, such as exhaustion, overwork, and anger, which reduces learners’ attention and motivation. (Brod et al., 1984 as cited in Salazar-Concha et al., 2021) . This technostress features prominently in the literature on online and hybrid learning (Upadhyaya & Vrinda, 2021) .  \nMoreover, most research concentrates on general digital tools, like learning management systems, and thus leaves a large gap in newer, adaptive technologies. As AI is integrated into academic life, the aspects of students'","cbCain5YHbgVyu8N","https://ap.wps.com/l/cbCain5YHbgVyu8N","pdf",869269,34,"English","# Abstract\n# Introduction\n# Literature Review","[{\"question\":\"What was the focus of the study on technostress?\",\"answer\":\"The study focused on students’ lived experiences of technostress when navigating AI learning tools in higher education.\"},{\"question\":\"How were participants selected and what data were collected?\",\"answer\":\"Ten undergraduate students were selected through purposive sampling and took part in semi-structured interviews after using AI tools for at least one month.\"},{\"question\":\"What key dimensions and themes emerged from the analysis?\",\"answer\":\"Nine themes emerged across four dimensions: affective, behavioral, cognitive, and ethical, including emotional strain, reliance patterns, metacognitive regulation, and academic integrity concerns.\"}]","The Lived Experiences of College Students Navigating Technostress Through AI Learning Tools | PDF",1789968634,86]