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The aim of the this workbook is to provide a series of resources; contextual information, methods and approaches to the area of self and peer assessment.
The workbook is not exhaustive, but attempts to focus on core issues and needs. The added literary and web references provide further readings and activites if so required. Key areas covered include: – Defining Self and Peer Assessment, – Implementing Peer Assessment, – Devising Assessment Criteria. Around each themed area you will find worksheets and activity lists, plus substantial references to original and core literature.
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 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.
This resource showcases initiatives from both academic and professional support areas across DCU, which have been funded under SATLE – the Strategic Alignment of Teaching and Learning Enhancement Funding in Higher Education. Examples are provided under the themes of Education for Sustainable Development, Digital transformation & Academic Integrity
This Podcast Series has been developed by CPID Staff involved in teaching and engaging in educational research. It consists of podcasts with well-known educational academics and experts, exploring various educational concepts/topics taught on programmes offered by the CPID, and on SATLE funded educational research projects.
This guideline document seeks to support the implementation of MTU policies and procedures which underpin Academic Integrity and help to address the implications of Generative Artificial Intelligence on assessment practices.
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URL: https://drive.google.com/file/d/0BxV1LO6iHp1yWUVCSVVBYjdCUzQ/edit
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