{
  "@context": {
    "dcterms": "http://purl.org/dc/terms/",
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  "dcterms:identifier": [
    "tag:aim-pro.eu,2026:oer/913c3eb809be",
    "https://arxiv.org/abs/2403.13487",
    "arxiv:2403.13487"
  ],
  "dcterms:title": [
    "The future of generative AI chatbots in higher education"
  ],
  "dcterms:type": [
    {
      "@id": "dcmitype:Text"
    },
    "preprint"
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  "dcterms:creator": [
    "Joshua Ebere Chukwuere"
  ],
  "dcterms:description": [
    "The integration of generative Artificial Intelligence (AI) chatbots in higher education institutions (HEIs) is reshaping the educational landscape, offering opportunities for enhanced student support, and administrative and research efficiency. This study explores the future implications of generative AI chatbots in HEIs, aiming to understand their potential impact on teaching and learning, and research processes. Utilizing a narrative literature review (NLR) methodology, this study synthesizes existing research on generative AI chatbots in higher education from diverse sources, including academic databases and scholarly publications. The findings highlight the transformative potential of generative AI chatbots in streamlining administrative tasks, enhancing student learning experiences, and supporting research activities. However, challenges such as academic integrity concerns, user input understanding, and resource allocation pose significant obstacles to the effective integration of generative AI chatbots in HEIs. This study underscores the importance of proactive measures to address ethical considerations, provide comprehensive training for stakeholders, and establish clear guidelines for the responsible use of generative AI chatbots in higher education. By navigating these challenges, and leveraging the benefits of generative AI technologies, HEIs can harness the full potential of generative AI chatbots to create a more efficient, effective, inclusive, and innovative educational environment."
  ],
  "dcterms:subject": [
    "cs.CY (arxiv)"
  ],
  "dcterms:language": [
    "en"
  ],
  "dcterms:license": [
    {
      "@id": "http://creativecommons.org/licenses/by-nc-sa/4.0/"
    }
  ],
  "dcterms:rights": [
    "CC-BY-NC-SA-4.0 — assessed as OPEN_NC by the harvester's licence gate. Conditions: attribution required, non-commercial use only, adaptations must carry the same licence. open but Non-Commercial — SME/commercial reuse needs care"
  ],
  "dcterms:accessRights": [
    "open"
  ],
  "dcterms:format": [
    "application/pdf",
    "text/markdown"
  ],
  "dcterms:extent": [
    "210592 bytes (original)",
    "41372 bytes (extracted text)"
  ],
  "dcterms:issued": [
    "2024-03-20"
  ],
  "dcterms:provenance": [
    "Retrieved from arXiv on 2026-10-09 in response to the search string “(all:\"artificial intelligence\" OR all:\"machine learning\" OR all:\"generative AI\" OR all:\"deep learning\" OR all:\"reinforcement learning\" OR all:\"large language model\") AND (all:\"AI concepts\" OR all:\"types of AI\" OR all:\"AI fundamentals\" OR all:\"recognizing AI\" OR all:\"recognising AI\" OR all:\"general versus narrow AI\" OR all:\"narrow AI\" OR all:\"general AI\" OR all:\"machine intelligence\" OR all:\"AI strengths and weaknesses\" OR all:\"traditional software\" OR all:\"rule-based systems\" OR all:\"introduction to AI\" OR all:\"introduction to artificial intelligence\" OR all:\"artificial intelligence introduction\" OR all:\"AI primer\" OR all:\"foundations of artificial intelligence\" OR all:\"overview of AI\" OR all:\"understanding AI\" OR all:\"history of AI\" OR all:\"AI essentials\" OR all:\"AI terminology\" OR all:\"metaphors for AI\" OR all:\"AI fundamental concepts\" OR all:\"AI key concepts\" OR all:\"philosophy of AI\" OR all:\"critical AI literacy\")”. arXiv served the resource and is not asserted to be its publisher or author.",
    "Text extracted from pdf to Markdown by pdf; the original is retained unchanged beside it."
  ]
}