AI Observatory: Waypoints & Signals – Issue 15
Signals of the week: Micro-interventions, AI readiness in higher ed, and rethinking grades
Each week, we spotlight signals of change in AI and education – and consider what they might mean for the future of learning in low- and middle-income countries. Using the Three Horizons framework, we track what’s beginning to upgrade existing systems, what may soon disrupt the status quo, and what could transform learning in the age of AI.
Upgrade: Incremental change within the system
Prompt clinics may strengthen teacher competencies and ease anxiety
In Peru, 45 first-year students training to become teachers took part in a pilot of a three-session AI prompt-engineering clinic. AI-literacy scores rose by a modest ~0.7 points and technology-anxiety scores fell by ~0.6 points, with gains and reductions moderately linked. (Source: Davila-Moran et al., August 2025)
Why this matters now… the authors present this as preliminary evidence that micro-level interventions such as early practical prompt-design activities may strengthen competencies, and cognitive and emotional gaps in teacher education.
Disrupt: Innovations challenge the status quo
Higher ed requires dedicated AI competency blueprint
A new UNESCO IESALC working paper identifies a critical gap in responding to AI in higher education: most existing competency frameworks are designed for K–12, high-resource contexts, or are STEM-specific. Building on UNESCO’s K–12 frameworks, the authors propose a higher-ed model spanning knowledge, skills, and human-centred values. (Source: UNESCO IESALC, 6th August 2025)
Watch for… coordinated development of AI competency frameworks in higher education. Scalable, flexible designs will be key to ensuring they strengthen AI readiness without widening the divide, diminishing academic integrity, or increasing plagiarism risks.
Transform: New visions of the future
Rethinking grades in the age of AI
In his essay, Hu Yong, a professor at Peking University, describes recent GPA reforms as part of a wider shift towards de-quantification in academic evaluation. He links these changes to the new pressures AI creates for assessment, argues the response should go beyond bans, and urges a rethink of the purpose and logic of evaluation. (The Economic Observer, 6th August)
What if… assessment restored intrinsic motivation, valued process as much as outcome, and reflected a learner’s full growth – especially for those left behind by score-driven systems in an AI era where adoption is uneven?
Swipe for a quick take 👇🏽
We’d love to hear from you! What’s been shaping your thinking on AI? Drop your thoughts (and reading recommendations) in the comments. Explore more from EdTech Hub’s AI Observatory.
EdTech Hub’s AI Observatory is made possible with the support of the UK’s Foreign, Commonwealth and Development Office.
