Case Study N: Identifying Effective Resources for First Year Computing Students
Case Study N: Identifying Effective Resources for First Year Computing Students
Case Study O: Assessing Students’ Engagement with Online Quizzes over the Course of their Programme
Case Study O: Assessing Students’ Engagement with Online Quizzes over the Course of their Programme
Irish Reporting Case Studies
Irish Reporting Case Studies
Learning Analytics Proposed Principles
An ethical approach to data use is critical for maintaining the confidence and trust of students and staff. This guide outlines a set of principles, developed in collaboration with the Irish sector, that may help to shape your own principles of data use.
Learning Analytics Institutional Policy
This report looks at the major recurring themes in a number of exemplar international analytics policies and highlights the actions institutions may wish to take in developing their own policies and strategies
Learning Analytics and Data Protection in Ireland
Learning Analytics and Data Protection in Ireland
Data Protection Checklist for Learning Analytics
Adapted from the Data Protection Commissioner’s Office’s data protection checklist, this guide outlines the key steps staff and institutions must take to ensure compliance with data protection legislation.
Importance of adopting a consultative approach to implementation of Learning Analytics
Collaboration and consultation are essential for whole-of-institution approaches. This resource outlines some of the colleagues that you may wish to consider working with to develop your approach.
Guide to identifying Research Questions in Learning Analytics
The value of data lies in answering questions so knowing what question(s) you want to answer is an essential first step. This guide details some of the areas that data can be used to investigate.
Guide to Data Quality
Data quality is a major challenge for most institutions as they begin to develop a data-enabled approach, but it is a critical early step. Any answers generated by your data will only be as accurate as the data itself. This resources highlights some of the key steps to ensuring the quality of the data you have access to.
