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The Hibernia College Quality Framework is the sole authoritative source of all Hibernia College quality assurance documents including policies, procedures, resources and strategy documents.
The Hibernia College Quality Framework is a suite of policies, procedures, resources and strategy document that reflect the College’s ongoing commitment to international best practice in blended learning through a range of mechanisms that seek to continually monitor, review, and enhance our programmes and our College.
Those involved in the development of QA documentation across the higher education sector may benefit from being able to adapt elements of the documentation published in the HCQF to suit their institutional contexts.
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 poster offers educators an overview of designing a syllabus on the Canvas learning management system that supports personalised learning pathways. It highlights (1) a gamified pedagogy grounded in gaming principles and (2) adaptive learning strategies using MasteryPaths.
In 2018, the Glucksman Library at the University of Limerick launched Leganto, a reading list management tool designed to streamline access to academic resources for students. Leganto ensures equitable access to academic content, helping students engage with reliable sources and easing their transition into university-level study.
This toolkit draws on our experiences facilitating a SATLE-funded community-engaged learning project that brought students of the School of Languages, Literatures, and Cultures (UCC) together with people in Cork seeking international protection for a series of three wellbeing and creativity workshops.
This lesson is designed to aid students in understanding how to engage generative AI in an academic setting without breaching academic integrity policy.
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