arXiv — NLP / Computation & Language · · 3 min read

AI SciBrief as a Gateway to Research: A Framework for Onboarding Students into New Research Areas

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Computer Science > Computers and Society

arXiv:2606.12413 (cs)
[Submitted on 6 May 2026]

Title:AI SciBrief as a Gateway to Research: A Framework for Onboarding Students into New Research Areas

View a PDF of the paper titled AI SciBrief as a Gateway to Research: A Framework for Onboarding Students into New Research Areas, by Andrei Lazarev and 1 other authors
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Abstract:Students at all levels of higher education face a significant barrier in the form of information overload, which often paralyzes the initial stages of the research process and suppresses motivation. In response, this article introduces a pedagogical framework that leverages AI SciBrief, a platform powered by a Large Language Model (LLM) designed to automatically generate digests of scientific trends. We describe how this multidisciplinary tool - with initial coverage in finance, medicine, and education - can be integrated into the curriculum to overcome this "entry barrier." The framework provides concrete methodologies for utilizing these digests to facilitate topic selection for term papers, accelerate literature reviews for dissertations, and enable postgraduate students to continuously monitor emerging trends. We conclude that AI SciBrief functions as a "gateway to research" effectively reducing students' cognitive load and empowering them to transition more rapidly from information searching to knowledge creation.
Comments: This is the version of the article accepted for publication in TELE 2025 after peer review. The final, published version is available at IEEE Xplore: this https URL
Subjects: Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Computational Engineering, Finance, and Science (cs.CE); Computation and Language (cs.CL); Software Engineering (cs.SE)
Cite as: arXiv:2606.12413 [cs.CY]
  (or arXiv:2606.12413v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2606.12413
arXiv-issued DOI via DataCite
Journal reference: 2025 5th International Conference on Technology Enhanced Learning in Higher Education (TELE), Lipetsk, Russian Federation, 2025, pp. 365-369
Related DOI: https://doi.org/10.1109/TELE66816.2025.11211989
DOI(s) linking to related resources

Submission history

From: Andrei Lazarev [view email]
[v1] Wed, 6 May 2026 12:58:53 UTC (245 KB)
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