education6 papersavg year 2026quality 8/5weak evidence

Educational activities that encourage critical AI engagement and assessment methods resilient to AI assistance need to be designed and validated in practice.

Research gap analysis derived from 6 education papers in our local library.

The gap

Educational activities that encourage critical AI engagement and assessment methods resilient to AI assistance need to be designed and validated in practice.

Consensus across the literature

Clustered from 6 gap mentions across 6 papers via embedding cosine ≥ 0.62.

Research trend

Established — well-defined area with open sub-problems.

Supporting evidence — 6 representative gaps

  • Systematic Literature Review on Students’ Perceptions of Ethical AI: Fairness, and Regulatory Understanding (2026) · doi

    Educational activities that encourage critical AI engagement and assessment methods resilient to AI assistance need to be designed and validated in practice.

    Keywords: educational activities encourage critical engagement assessment resilient assistance need designed validated practice
  • THE IMPACT OF AI IN EDUCATION (2026) · doi

    Any potential AI-led education system must be moral and reliable before being put into practice so that it does not cause more harm than good, with constant testing and improvements to ensure this.

    Keywords: potential education system must moral reliable practice cause harm good constant testing improvements ensure
  • Leveraging artificial intelligence (AI) to enhance student engagement and academic performance in higher education (2026) · doi

    Longitudinal investigations examining the sustained effects of AI interventions beyond a single academic year would further clarify their long-term educational impact.

    Keywords: longitudinal investigations examining sustained effects interventions beyond single academic year further clarify long term educational
  • Use of Artificial Intelligence in Education for Smart Classrooms and Adaptive Learning Systems (2026) · doi

    Continuous evaluation and research are necessary to assess the long-term impact of AI on teaching–learning processes and academic outcomes through monitoring frameworks that evaluate effectiveness of AI tools.

    Keywords: continuous evaluation necessary assess long term impact teaching learning processes academic outcomes monitoring frameworks evaluate
  • Intelligent Tutoring and Counselling Systems in Education: A Comprehensive Review of AI- Driven Personalized Learning and Career Guidance. (2026) · doi

    The paper is based exclusively on secondary data from recent scholarly resources without empirical validation through implementation in real educational settings. Future research must design, develop, and experimentally validate integrated AI-based tutoring and counselling systems in actual K-12 or higher education environments to assess real-world effectiveness.

    Keywords: empirical validation intelligent tutoring systems real educational setting implementation experimental design
  • Perception of Use of Ai Tools Among Students of Higher Education Institutes in Mumbai (2026) · doi

    The study found that 79.2% agree AI tools assist students with language barriers and learning difficulties, yet does not compare actual learning outcomes, assessment scores, or accessibility improvements between students using AI-assisted and traditional learning methods in remedial contexts.

    Keywords: AI tools language barriers learning difficulties accessibility student outcomes assessment

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