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
Research gap analysis derived from 3 education papers in our local library.
The gap
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.
Consensus across the literature
Clustered from 3 gap mentions across 3 papers via embedding cosine ≥ 0.62.
Research trend
Established — well-defined area with open sub-problems.
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
Explore this gap further
Search “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” across open scholarly engines for the latest related literature.
Working on this gap? Publish with us.
Science AI Journal reviews manuscripts in under 15 minutes with 8 specialised AI reviewers calibrated on 23,000+ real peer reviews. Open access, CC BY 4.0.
Free tools for your next paper
Related gaps in Education
- The findings of the study have practical implications for the education sector, as they highlight the need for intensive training in higher education institutions to bridge the gap in understanding anThe findings of the study have practical implications for the education sector, as they highlight the need for intensive training in higher …
- There is a need to establish a standard framework of AI tools which can be integrated with the Education System.There is a need to establish a standard framework of AI tools which can be integrated with the Education System.
- Although research has identified oral language, print knowledge, and phonological sensitivity as important emergent literacy skills for the development of reading, few studies have examined the relatiAlthough research has identified oral language, print knowledge, and phonological sensitivity as important emergent literacy skills for the …
- In Australia, most intellectually gifted students are in mixed-ability classes and teachers are expected to differentiate to meet the specific learning needs of students across the full range of abiliIn Australia, most intellectually gifted students are in mixed-ability classes and teachers are expected to differentiate to meet the specif…