AI evidence extraction

Reimagining pedagogy for the GenAI era: Frameworks, challenges and institutional strategies

Meena Jha, Amara Atif · Australasian Journal of Educational Technology · 2025

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

7/10

Relevance

0/4

Quality (LMQS)

Evidence

Citations

17.37

FWCI

Top 10%

Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.14742/ajet.10645

Methodology & findings

Study design

Two in-depth case studies exploring how educators in Australian higher education integrate GenAI into teaching activities, reflective exercises and student-driven inquiry

Primary method

Qualitative case study analysis drawing on theoretical frameworks from critical digital pedagogy, AI Digital literacy and constructivist learning theory aligned to Bloom's taxonomy

Main result

The study found that "The findings highlight variability in student readiness, the cognitive demands of critically engaging with GenAI and the importance of scaffolded, iterative approaches." Additionally, "Educators reported enthusiasm and strain in managing GenAI integration, noting the importance of explicit instruction, reflective practice and peer learning."

Reports effect sizes.

Research paradigm

Interpretivist/Qualitative

Author conclusions

The authors conclude that "Educators can foster GenAI literacy by embedding scaffolded, critical reflection tasks on GenAI use into classroom practices" and "Educators should standardise GenAI usage templates across units to promote transparency and academic integrity." They also recommend that "Administrators should support cross-functional collaboration to embed GenAI literacy into curricula, staff training and student support systems."

Risk of bias

Case study design may introduce selection bias in choice of educator participants; limited geographic scope (Australian context only); potential self-selection bias of educators volunteering to participate in GenAI integration research; Selection bias possible due to case study approach (likely voluntary participation); unclear sampling strategy; no mention of blinding or inter-rater reliability checks in abstract; potential social desirability bias in educator self-reports; context-specific findings from Australian institutions may not generalize

Open questions raised

The paper identifies the need for continued research on translating institutional GenAI policies into effective classroom practices and the need for strategies to foster ethical GenAI literacy while upholding academic integrity
The study identifies the need for practical frameworks for embedding GenAI in learning environments and contributes to understanding how educators can promote ethical GenAI literacy and academic integrity through pedagogical design.
The study contributes to understanding "how educators can promote ethical GenAI literacy and uphold academic integrity through thoughtfully designed pedagogical strategies" while acknowledging the need for further work in translating institutional policies into effective classroom practices.

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