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How Chat GPT Can Transform Autodidactic Experiences and Open Education?
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Chat GPT, powered by the advanced GPT-3 language model from OpenAI, has reached 1 million users only in 5 days. Facebook, Netflix, Instagram, and Twitter could reach this number in 300, 1200, 75, and 720 days. With 175 billion parameters, GPT-3 can generate writing that closely resembles human language. Chat GPT can engage in multiple ongoing conversations, understand and respond to natural language input, and offer customized and interactive assistance. This makes Chat GPT a promising tool for open education, as it can improve the independence and autonomy of autodidactic learners, while also being both practical and adaptable. By providing personalized support, direction, and feedback, Chat GPT has the potential to increase motivation and engagement among autodidactic learners.
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“ChatGPT has the potential to offer personalized learning experiences and support an effective learning process by providing students with customized feedback and explanations tailored to their needs and abilities”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [26]
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Metadata
- Authors
- Firat, M.
- ORCID
- Firat, Mehmet
- Publisher
- Center for Open Science
- Published
- 2023-01-12
- OpenAlex
- W4316041216
- Cited by
- 280
- References
- 12
- Citations by year
- 2026: 22 · 2025: 61 · 2024: 119 · 2023: 78
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- OSF Preprints (OSF Preprints) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- ChatGPT, GPT-3, open education, personalized learning support, learner autonomy, student motivation, student engagement
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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