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This OER is from a collection of ‘MU: UDL & U’ Plus One resources created by Maynooth University colleagues with the support of HEA PATH4 funding.
This OER, as part of the ‘MU: UDL & U’ Plus One collection, was created to help staff to make small, manageable, incremental changes to teaching, learning and assessment design and practice in order to contribute to a more inclusive learning environment and experience for all students.
Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA)
This work is licensed under a CC BY-NC-SA license, allowing sharing and adaptation for non-commercial use with proper attribution, provided derivative works use the same license.
https://creativecommons.org/licenses/by-nc-sa/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 is an interactive multimedia open educational resource (OER), created using H5P, on the topic of Open Education. It has been developed by the Department of Technology Enhanced Learning at Munster Technological University.
The purpose of which is to give an overview of OEPs, using interactive features of H5P
The purpose of this resource is to allow Moodle teachers to quickly create quizzes for Moodle. Users can quickly select between questions types through a single interface and export their questions as an XML file which can be imported into Moodle.
An open educational resource that supports academic, professional, and support staff to build more neuro-inclusive teaching, services, and policies in higher education. This resource was conceptualised & developed through the experiences of neurodivergent students in third-level education, with co-creation at the heart of every stage of the process
This OER presents an updated Assessment Redesign Framework for higher education in the age of GenAI. It supports educators and programme teams in designing valid, transparent, and scalable assessments, integrating AI literacy, process-focused approaches, and guidance on AI detection, large cohorts, and emerging agentic AI challenges.
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