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Guide to Developing Enabling Policies for Digital Teaching and Learning
The guide provides a stepped approach to developing an enabling policy for digital teaching and learning.
Following the format of most National Forum initiatives and reports, the guide was developed following consultation across the sector in conjunction with a review of policies in Ireland and abroad.
An updated version of this guide was published in 2021 and is available here: https://hub.teachingandlearning.ie/resource/guide-to-developing-enabling-policies-for-digital-and-open-teaching-and-learning/
Creative Commons Attribution (CC BY)
This work is licensed under a CC BY license, allowing sharing and adaptation with proper attribution.
https://creativecommons.org/licenses/by/4.0/If you have modified or adopted this resource, share your version here. Tracking adaptations helps us measure impact and connects others with useful updates.
This OER presents findings from a comparative study of novice programmers engaging in face-to-face and hybrid pair programming. It explores collaboration patterns, role switching, satisfaction, and challenges, offering evidence-based insights for educators seeking to prepare students for effective teamwork in modern hybrid software development.
This OER explores novice programmers’ experiences of pair programming across face-to-face, hybrid, and remote settings. It provides insights into collaboration, role switching, satisfaction, and challenges, helping educators and students understand how to effectively prepare learners for modern hybrid software development environments.
This OER guides students through human-in-the-loop software development, demonstrating how AI tools can be effectively supervised, refined, and integrated across the Software Lifecycle. Designed for computing educators and learners, it combines agile practice, teamwork, DISC awareness, testing, and critical reflection on human–AI collaboration.
This OER introduces students to designing and developing AI-powered assistants for agile software development using Flowise (no code). Learners as a team explore Retrieval Augmented Generation (RAG) and agent-based systems, applying AI to real-world agile practices while considering technical design, evaluation, and cost-aware decision-making
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