Teachers adopting EAI should address digital literacy and ethical design challenges identified for each AI dimension¶

Strategy · All strategies
Evidence · 1 claim (1 for) · 1 study (1 review), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The review identifies challenges teachers must take on when including AI in education, adapted from Flores-Vivar & García-Peñalvo (2023), across dimensions such as accessibility, intelligent tutoring, virtual facilitators, intelligent content, teacher-AI collaboration, content management and analytics, and learning management automation. It stresses that "the implementation of these technologies in instructional processes involves a great educational and ethical challenge for teachers in relation to their design and implementation". Table 3 maps each dimension to a challenge and educational stage, including digital literacy plans and ethical issues associated with data processing.

Design Implications¶

Context¶

Requirements¶

• Teachers need digital literacy: knowing how the modalities work, their viability and usefulness in their subject, and how to extrapolate them to their classroom reality.

Constraints¶

• The review states AI requires specific software and the design of materials and technological resources, and notes a high economic cost.

Target Learners¶

• teachers at all educational stages implementing EAI

Target Learning Goals¶

• ethical and effective design and implementation of AI-based instructional processes

Claims¶

• College leaders identify educator unfamiliarity with GenAI, lack of training infrastructure, and institutional unpreparedness as key challenges [+W]

Related Strategies¶

• Mitigation strategies pairing each AI-DSS challenge with a targeted countermeasure
• Address core ethical challenges—data privacy, algorithmic fairness, and transparency—when deploying AI-driven personalized learning
• Manage ethical risks of AI-driven TEFL tools through data protection policies, fairness audits, human oversight, and balanced-use design
• Pursue inclusive digital strategies, educator professional development, and ethical AI governance for AI in adult education
• Foster communities of practice for AI governance instead of rigid top-down policies

Examples¶

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Key Sources¶

• García-Martínez, I., Fernández-Batanero, J. M., Fernández-Cerero, J., & León, S. P. (2023). Analysing the Impact of Artificial Intelligence and Computational Sciences on Student Performance: Systematic Review and Meta-analysis. Journal of New Approaches in Educational Research, 12(1), 171-197. https://doi.org/10.7821/naer.2023.1.1240