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Cited by 213Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationIntelligent Tutoring Systems and Adaptive Learning

Empowering education through Generative AI: Innovative instructional strategies for tomorrow's learners

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Kadaruddin, Kadaruddin·2023·International Journal of Business, Law, and Education
DOI 10.56442/ijble.v4i2.215
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Abstract

As the educational landscape endures continuous change, artificial intelligence (AI) has presented unprecedented opportunities to revolutionize instructional methods. Among these cutting-edge AI technologies, Generative AI has emerged as a promising instrument with the potential to empower educators and students through innovative instructional strategies. This article aims to investigate the various applications of Generative AI in education and cast light on its role in shaping the future of education. The objectives of this study are twofold: first, to investigate the various instructional strategies that can be enhanced by employing Generative AI, and second, to assess the potential impact of these strategies on student learning outcomes. To accomplish these goals, a comprehensive literature review was conducted analyzing existing studies and applications of Generative AI in educational settings. The results and discussions emphasize the numerous educational benefits of Generative AI. Educators can personalize learning experiences, create interactive content, and facilitate adaptive assessments by leveraging the capabilities of Generative AI. This individualized strategy has the potential to boost learner engagement and knowledge retention. However, despite the numerous advantages, ethical concerns and difficulties arise. The responsible incorporation of Generative AI in education requires addressing issues such as data privacy, algorithmic bias, and the educator's role in directing AI-driven learning experiences. The research concludes by emphasizing that Generative AI holds enormous promise for empowering education and transforming instructional practices. The findings highlight the importance of ongoing collaboration between educators, policymakers, and AI developers to ensure the ethical and equitable integration of Generative AI into educational environments. By embracing the potential of Generative AI while remaining vigilant regarding its challenges, the field of education can unlock novel opportunities to nurture an inclusive, adaptive, and learner-centric pedagogical landscape for tomorrow's learners.

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  • Passive acceptance of AI-generated responses can erode critical thinking and analytical processes central to PBL.

    “Such passive acceptance of AI-generated responses can erode critical thinking and analytical processes central to PBL (Kadaruddin, 2023;Sun et al., 2025).”

    From Measuring undergraduate students’ reliance on generative AI during problem-solving: Scale development and validation. (2025) · cites this paper as Kadaruddin, 2023

    The Introduction says generative AI can foster critical thinking and problem-solving, while the Results and Discussion and Conclusion discuss other implementation risks, chiefly privacy and bias. Searches for passive acceptance, overreliance on AI-generated answers, and problem-based learning found no passage saying that accepting AI responses can erode those skills in PBL. (LLM, conf=0.72)

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Research works printed but not linked: 24

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Authors
Kadaruddin, K.
Affiliations
Universitas Sembilanbelas November Kolaka (ID)
Corresponding author
Kadaruddin, Kadaruddin
Venue
International Journal of Business, Law, and Education
Publisher
Scientific Publications Community Inc.
Published
2023-08-02
Volume
4
Issue
2
Pages
618-625
ISSN
2747-139X (ISSN-L)
DOI
10.56442/ijble.v4i2.215
OpenAlex
W4385497035
Cited by
213
References
0
Citations by year
2026: 58 · 2025: 97 · 2024: 57 · 2023: 1
FWCI
38.54
Type
journal article
Language
en
Open access
Licence
Locations
International Journal of Business Law and Education (publishedVersion, cc-by-nc-sa)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
generative AI in education, teaching methods, personalized learning, adaptive testing, interactive content creation, learning outcomes, student engagement, data privacy, algorithmic bias, ethical use of AI, future of education

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