Comparative perspectives from STEM and Non-STEM instructors - 1-s2.0-S2666557324000302-main
AI in Education: Comparative Perspectives from STEM and Non-STEM Instructors
1. Introduction to AI Integration in Education
The integration of Artificial Intelligence (AI) into education is seen as a promising approach to enhancing teaching and learning experiences.
The success of AI implementation relies on the perspectives of instructors, which can differ significantly between STEM (Science, Technology, Engineering, Mathematics) and non-STEM (Humanities, Social Sciences, Arts, and Business) educators.
Understanding instructor perspectives is critical, particularly in contexts such as Iran, where education shapes future generations.
2. Research Overview
Study Aim: To examine the viewpoints of 536 STEM and non-STEM instructors regarding AI integration in education through quantitative and qualitative methodologies, particularly surveying and semi-structured interviews.
Findings: Both groups expressed positive attitudes towards AI technologies, but differences emerged in their concerns regarding the capabilities and limitations of AI in educational settings.
3. Key Terminology and Concepts
AI: Artificial Intelligence
STEM: Science, Technology, Engineering, Mathematics
Non-STEM: Humanities, Social Sciences, Linguistics, Arts, Business
ChatGPT: Chat Generative Pre-trained Transformer
4. Benefits and Drawbacks of AI in Education
4.1 Benefits
Scalability: AI can enhance educational scalability, allowing for more personalized learning experiences.
Timeliness: AI tools can provide immediate feedback to students and instructors.
Accessibility: AI promotes increased access to educational resources and materials irrespective of location.
4.2 Drawbacks
Ethical Concerns: Issues such as privacy, data security, and algorithmic biases present significant challenges.
Overreliance: Risk of students becoming passive learners reliant on AI for information and solutions, potentially diminishing critical thinking skills.
5. Instructors’ Perspectives on AI Integration
5.1 STEM vs. Non-STEM Responses
STEM Instructors: Generally view AI positively regarding adaptive learning, capacity for data analysis, and support in collaborative tasks.
Non-STEM Instructors: Express more concern about AI’s potential to undermine social and emotional learning and the importance of human instructor-student interaction.
5.2 Research Findings
Both groups acknowledge the necessity for professional development to effectively integrate AI in education.
STEM instructors showed higher confidence in AI’s ability to personalize learning compared to their non-STEM counterparts.
6. Challenges Associated with AI Implementation
Job Displacement: Fears about potential job loss due to automation in educational contexts.
Access Inequality: Concerns about the digital divide exacerbating inequalities between students with different socioeconomic backgrounds.
7. Implications and Recommendations
Educator Training: Essential for successful integration of AI technologies in teaching practices, needing ongoing professional development and support.
Ethical Guidelines: Development of frameworks to ensure responsible use of AI, particularly concerning student data and privacy issues.
Interdisciplinary Collaboration: Encouraging synergy between STEM and non-STEM disciplines to derive comprehensive policies for AI in education.
8. Conclusion
The study indicates that while both STEM and non-STEM instructors recognize the potential of AI in enhancing education, their differing perspectives must be considered when developing strategies for effective implementation.
Appendices
Appendix A: Summary of key themes from teacher interviews and qualitative responses on AI benefits, drawbacks, and challenges.