GPT Search for Revolutionizing Research for Early-Career Education Scholars: A Mediation and Multi-Modality Perspective
DOI:
https://doi.org/10.58524/oler.v5i1.466Keywords:
Chat GPT, Early-Career, GPT, GPT Search, ResearchersAbstract
In the domain of academic research, the ongoing discourse centers around the intersection between the integration of artificial intelligence (AI) and some critical phenomena including early-career researchers’ challenges, the co-evolution of AI and research methodologies, continuous innovation, reorientation, and multi-modal advancement of various AI tools. Against this backdrop, Open AI’s GPT Search has just emerged as a versatility step towards its Chat GPT 4.0. The present perspective paper explores how this novel search engine can make broader paradigm shifts in traditional research approaches in literature search, data analysis, and writing discussions. Grounded in the authors’ scholarship, subjective insights (authorial experimental observations), critical appraisal of the extant literature, and experiential engagement, this paper perspectivizes that with its mediation and multi-modality functioning GPT Search promises to support conducting literature searches that are uniquely helpful for semantic relevance, large search syntaxes, and aggregated and index-specific results from multi-databases in one single search command. Additionally, GPT Search can also transform early-career researchers’ labor-intensive manual data analysis into automatic but more efficient qualitative data analysis. Furthermore, this search engine offers a reverse approach to writing discussions for articles and theses. The paper is the preliminary perspective that is supposed to trigger further empirical studies to advance the ongoing discourse around AI-integrated research with special attention to the novel research tool i.e., GPT SearchReferences
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