Pdf Human Ai Collaboration In Building Educational Semantic Scholar

Bonisiwe Shabane

-Nov 29, 2025, 8:59 PM

pdf human ai collaboration in building educational semantic scholar

Academia.edu no longer supports Internet Explorer. To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. 2025, International Journal of Science and Social Science Research [IJSSSR] Artificial intelligence is transforming the educational landscape by enhancing instructional methodologies employed by educators and the processes through which students acquire knowledge. Artificial intelligence serves as a collaborative partner to educators by automating repetitive tasks, personalizing learning experiences, and facilitating cognitive development. This study explores the potential of AI-driven tools and pedagogical strategies to foster more inclusive, adaptive, and effective educational experiences.

By reviewing existing literature and real-world applications, it highlights the benefits of AI-human collaboration, including improved teaching efficiency, better learning outcomes, and enhanced accessibility. The study further investigates critical challenges, including data privacy, bias, and the necessity for teacher training, underscoring the significance of ethical AI implementation. Looking ahead, the paper discusses future trends and the potential for wider AI adoption in education, ensuring technology serves as an enabler rather than a disruptor. This paper presents a comprehensive analysis of the integration of Artificial Intelligence (AI) in education, emphasizing its transformative potential for personalized learning and operational efficiency. It explores various AI tools, including intelligent tutoring systems, adaptive learning technologies, and virtual mentoring applications, highlighting their capacity to tailor educational content to individual needs. Advancements in immersive technologies, such as virtual and augmented reality, are also examined for their role in fostering interactive learning environments.

The paper discusses AI-driven pedagogical models like flipped classrooms and competency-based learning, supported by case studies that demonstrate improvements in student performance, accessibility, and engagement. Ethical concerns, including data security, algorithmic bias, and the digital divide, are critically evaluated alongside proposed solutions, such as enhancing transparency, educator training, and supportive policy frameworks. By synthesizing existing research and identifying future directions, this study provides a holistic perspective on the opportunities and challenges of AI in education. Received 2023 Oct 2; Accepted 2024 Mar 23; Collection date 2024 Dec. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit... The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.

If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from... To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. In service of the goal of examining how cognitive science can facilitate human–computer interactions in complex systems, we explore how cognitive psychology research might help educators better utilize artificial intelligence and AI supported tools... We also aim to provide historical perspective, both on how automation and technology has generated unnecessary apprehension over time, and how generative AI technologies such as ChatGPT are a product of the discipline of... We introduce a model for how higher education instruction can adapt to the age of AI by fully capitalizing on the role that metacognition knowledge and skills play in determining learning effectiveness. Finally, we urge educators to consider how AI can be seen as a critical collaborator to be utilized in our efforts to educate around the critical workforce skills of effective communication and collaboration.

The purpose of this paper is to explore how the current model of instruction in higher education might respond to technological innovations in “artificial intelligence.” “Artificial intelligence” is in quotes because we are now... But since by the time you read this some of the information will be outdated due to the astounding pace of technological innovations, it is not unreasonable to think that true artificial intelligence might... In the current work, we will use AI as a placeholder for both the current large language models that are now available and more advanced versions that are yet to be. The goal of the current work is to recommend how higher education instruction can respond to widely available AI. In service of this goal, we will first provide an overview of how the education enterprise has previously reacted to potential disruptive technological innovations. AI tools will be considered in this context, with the suggestion that they may pose a unique challenge and opportunity that other technologies have not.

We next develop a framework for understanding the role AI might play in the classroom by considering three components: a framework for categorization of educational goals in the cognitive domain (Bloom’s Taxonomy), the expectations... The result of this analysis suggests an increasingly important role for practices that improve metacognition. Finally, we will use this framework to suggest actionable practices that can incorporate, rather than work in opposition to, AI in its current or any future instantiation.

Pdf Human Ai Collaboration In Building Educational Semantic Scholar

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