A mixed-methods approach combining quantitative assessments of AI literacy with qualitative explorations of teachers' experiences and sense-making processes is recommended but currently underutilized.

The gap

Consensus across the literature

Supporting evidence — 6 representative gaps

• Leveraging artificial intelligence (AI) to enhance student engagement and academic performance in higher education (2026) · doi

  Qualitative analyses of how students engage with AI tools under different instructional frameworks would complement these findings, offering deeper understanding of how engagement mediates AI's influence on learning outcomes.

  Keywords: qualitative analyses students engage tools different instructional frameworks complement offering deeper understanding engagement mediates influence
• Teachers, Students, and Thinking Machines: Rethinking the Role of Artificial Intelligence in Higher Education (2026) · doi

  Need to examine how sustained AI use reshapes teachers' epistemic authority and how prolonged student reliance on AI affects critical thinking, learner agency, and intellectual autonomy across multiple academic disciplines and semesters.

  Keywords: need examine sustained reshapes teachers epistemic authority prolonged student reliance affects critical thinking learner agency
• AI literacy and Ethical use: Developing and validating a Framework for Pre-service and In-service Teachers in Technology-Integrated Classrooms (2026) · doi

  A mixed-methods approach combining quantitative assessments of AI literacy with qualitative explorations of teachers' experiences and sense-making processes is recommended but currently underutilized.

  Keywords: mixed approach combining quantitative assessments literacy qualitative explorations teachers experiences sense making processes recommended currently
• Artificial Intelligence in English-Speaking Education: A WoS-Based Bibliometric Analysis of Technology, Pedagogy, and Ethics (2021-2025) (2026) · doi

  Future studies should prioritize mixed-method and longitudinal designs to examine how AI-supported speaking tools influence learner engagement, affective factors, and classroom practices over time, thereby addressing the fragmentation identified in this study.

  Keywords: future prioritize mixed longitudinal designs examine supported speaking tools influence learner engagement affective factors classroom
• La inteligencia artificial como mediadora del aprendizaje y sus implicaciones en el desarrollo del pensamiento crítico. (2026) · doi

  The paper asserts that the teacher's role must be redefined in AI-mediated learning contexts to maintain the student as an active protagonist and prevent cognitive dependence, yet provides no concrete framework for how educators should scaffold AI tool use, design interventions to preserve intellectual autonomy, or assess when AI mediation shifts from complementary to dependency-inducing.

  Keywords: teacher role AI mediation cognitive dependence intellectual autonomy scaffolding pedagogical framework
• Teachers’ perceptions of artificial intelligence in curriculum integration: opportunities, concerns, and professional development needs (2026) · doi

  Data were collected through written responses via semi-structured electronic interviews, limiting opportunities for probing and follow-up clarification; face-to-face interviews are needed to deepen understanding of teachers' specific concerns about AI's impact on students' socio-emotional development and interpersonal engagement.

  Keywords: semi-structured interviews qualitative data collection teachers' perceptions socio-emotional development