The study identifies that AI tools showing low transparency in outputs (43% disagreement) is a significant student concern, but deeper investigation into explainability mechanisms and their effectiven

The gap

Consensus across the literature

Supporting evidence — 3 representative gaps

• Students’ perceptions and responsible adoption of artificial intelligence in education: Ethical considerations, impacts, and academic performance (2026) · doi

  The study identifies that AI tools showing low transparency in outputs (43% disagreement) is a significant student concern, but deeper investigation into explainability mechanisms and their effectiveness is needed.

  Keywords: identifies tools showing transparency outputs disagreement significant student concern deeper investigation explainability mechanisms effectiveness needed
• Artificial Intelligence Adoption in Education Opportunities Challenges and Future Directions (2026) · doi

  The paper identifies algorithmic bias and lack of transparency in AI decision-making as significant ethical concerns but does not specify empirical studies that quantify bias rates in educational AI systems or benchmark explainable AI implementations in actual classroom settings. Research directly measuring fairness outcomes and algorithmic transparency across different student populations in personalized learning environments is needed.

  Keywords: algorithmic bias explainable AI fairness transparency educational AI systems personalized learning
• Intelligent Tutoring and Counselling Systems in Education: A Comprehensive Review of AI- Driven Personalized Learning and Career Guidance. (2026) · doi

  Explainable AI models remain absent from current intelligent tutoring and counselling systems, hindering transparency and user trust. Future development must create interpretable machine learning models that make AI decision-making processes transparent and accountable to educators, students, and stakeholders.

  Keywords: explainable AI transparent machine learning interpretability intelligent tutoring systems accountability