Erosion of Critical Academic Skills Due to AI Dependency Among Tertiary Students

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 25 - 48

Published: April 25, 2025

This chapter investigates the perceived erosion of critical academic skills among 745 university students due to dependency on AI tools. The survey measured six key constructs: Dependency (AID), Cognitive Offloading (CO), Motivational Decline (MD), Academic Skills Erosion (ASE), Integrity Awareness (AIA), and External Pressures (EP), using a five-point Likert scale. Path Analysis was employed examine interrelationships these constructs. results revealed strong positive relationship between AID both CO MD, which indicated that increased reliance leads reduced cognitive engagement diminished motivation. Additionally, MD were positively associated with ASE, means who offload tasks experience are more likely exhibit deteriorating skills. While AIA had weak negative AID, EP showed moderate association highlighted role stress in driving reliance.

Language: Английский

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Reskilling and Upskilling Future Educators for the Demands of Artificial Intelligence in the Modern Era of Education

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 175 - 200

Published: April 25, 2025

The integration of artificial intelligence (AI) in education is altering teaching and requires educators to develop new competencies. Through a systematic review 247 articles published between 2022 2024, this chapter explores three major themes, namely, AI Teacher Competency Development, Challenges Reskilling Upskilling, Strategies for Effective Reskilling. It has become evident that have acquire digital literacy, data analytics skills, AI-specific pedagogical strategies, with corresponding need address ethical concerns around algorithmic bias, privacy, equity access. Moreover, institutional resistance, inequitable especially the fast evolution AI, which outpaces often existing training frameworks, are identified as evolving concerns. This chapter, therefore, proposes embed into continuous professional development, enhance interdisciplinary collaborations, adapt frameworks such P21, TPACK, DigCompEdu specific needs AI.

Language: Английский

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Investigation of the Opinions of Classroom Teachers Working in Science and Art Centers on the Pitfalls of Artificial Intelligence in Education

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 125 - 150

Published: April 25, 2025

This chapter examines the perspectives of classroom teachers at Science and Art Centers regarding artificial intelligence (AI). Employing a case design qualitative methodology, research collects insights from 18 during 2023-2024 academic year through semi-structured interviews, followed by content analysis. Findings indicate that AI enhances processes, reduces teacher workloads, boosts student engagement. However, challenges such as inadequate technological infrastructure, insufficient resources, internet connectivity issues hinder effective integration. Teachers also express concerns about potential ethical dilemmas associated with applications. The underscores necessity for comprehensive in-service training, practical guidance, high-quality resources to optimize utilization. Furthermore, it emphasizes importance establishing guidelines usage protocols address these foster responsible approach in educational settings.

Language: Английский

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Navigating the Ethical Frontier

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 251 - 274

Published: April 25, 2025

Artificial intelligence (AI) is transforming special education by enabling personalized learning pathways and innovative assistive technologies. However, its growing use raises critical ethical concerns, including algorithmic bias, data privacy, fairness. Biased algorithms can lead to misdiagnoses or inappropriate recommendations, while the collection of sensitive student increases privacy risks. Many educators also lack training critically assess AI-generated outputs. Ensuring inclusive transparent AI design essential providing equal opportunities avoiding reinforcement educational disparities. Policymakers, developers, must collaborate establish clear, enforceable guidelines that protect rights promote use. This chapter explores expanding role technologies in advocating for a balanced approach supports innovation prioritizing responsibility inclusion.

Language: Английский

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The Limits of AI in Teaching Partition Literature

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 49 - 72

Published: April 25, 2025

The application of generative AI in the classroom is transforming conventional methods literary analysis and instruction, but it also raises serious concerns limitations. This chapter critically examines these limitations within context teaching 1947 Partition literature Indian college classrooms. Using a qualitative experimental methodology, analyzes AI-generated responses to narratives, revealing ChatGPT's inability capture historical trauma, moral accountability, cultural depth embedded texts. Findings show that interpretations often flatten complex human experiences reduces them simplistic patterns or generalized tropes. argues such algorithmic risk distorting memory promoting academic irresponsibility. By exposing flaws, contributes current debates on higher education calls for human-led contexts marked by deep trauma.

Language: Английский

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Technoethics and the Use of Artificial Intelligence in Educational Contexts

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 227 - 250

Published: April 25, 2025

As emerging technologies, such as artificial intelligence (AI), become increasingly integrated into academic contexts, new challenges and ethical risks related to potential misuse also emerge. This chapter examines these issues from an perspective by analyzing how each affects both education research. Particular attention is given concerns algorithmic bias, data privacy, authorship attribution, the erosion of critical thinking in AI-assisted learning environments. The explores implications unequal access AI tools, which may exacerbate existing educational disparities. Reflection on essential for fostering culture based integrity, transparency, respect diversity, are fundamental creating a fairer more equitable environment. Ultimately, urges institutions establish clear technoethical guidelines, promote digital literacy, engage stakeholders open dialogue ensure responsible inclusive integration education.

Language: Английский

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Rethinking Educational Assessment in the Age of Generative AI

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: April 25, 2025

As artificial intelligence (AI) becomes increasingly integrated into educational contexts, they present new challenges to traditional assessment methods. A particularly pressing issue is academic dishonesty, which undermines learning authenticity and the credibility of institutions. With generative AI tools like ChatGPT making it easier for students produce automated answers, assessments are at risk measuring capabilities rather than students' actual knowledge. Thus, this chapter explores a range strategies designed adapt practices in response influence education. These offer actionable frameworks support authentic uphold integrity. Additionally, highlights future research directions guide further adaptation policies practices. Given rapid integration education sector, provides sensible insights that reinforce importance integrity-focused reforms sustaining meaningful outcomes an AI-driven world.

Language: Английский

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The Automation Trap

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 151 - 174

Published: April 25, 2025

With the growing presence of artificial intelligence (AI) in classrooms, its influence on how students think, learn, and interact deserves close scrutiny. However, increasing integration accessibility raise concerns about AI dependency among students. Excessive reliance may weaken essential cognitive skills, including critical thinking, problem-solving, creativity, which are crucial for academic professional success. Moreover, diminished human interaction with teachers peers threatens aspect education. This chapter critically examines risks over-reliance, emphasizing long-term consequences student development. Left unchecked, this lead to superficial learning hinder cultivation independent thought. The normalization AI-generated outputs also blur line between authentic algorithmic convenience. It highlights shift from as a supportive tool potential source advocates more balanced, human-centered technology

Language: Английский

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Equipping the Next Generation of Technicians

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 201 - 224

Published: April 25, 2025

As artificial intelligence (AI) continues to transform the demands of global workforce, technical education must evolve meet these emerging challenges. This chapter examines integration AI in with an emphasis on critical need for modern infrastructure and expertise. It highlights importance investing facilities such as AI-equipped laboratories, reliable internet, educator training programs foster innovation personalized learning. Collaboration between educational institutions industry is explored a means bridge gap academic theory real-world applications. Additionally, advocates revising curricula combine literacy skills, alongside thinking adaptability, evolving workforce demands. concludes call educators, policymakers, prioritize inclusive, forward-thinking strategies modernize ensure equity access opportunities.

Language: Английский

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AI Shaming Among Teacher Education Students

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 97 - 122

Published: April 25, 2025

As generative AI tools become increasingly integrated into educational practice, its use among pre-service teachers is often accompanied by hesitation and discomfort. This chapter examines the phenomenon of shaming teacher education students—the stigma reluctance to disclose tool due perceived threats academic authenticity. Drawing on classroom insights student reflections, it explores how social norms, institutional pressures, identity formation shape this behavior. These experiences reveal deep tension between embracing technological innovation maintaining traditional standards merit. The highlights implications for digital literacy, professional development, ethical technology integration. It calls a shift in narrative, framing not as shortcut but innovation. Actionable strategies educators institutions are proposed foster open, reflective, supportive environments responsible education.

Language: Английский

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