This guide details some of the key reporting features in Moodle that can be of benefit to staff who teach that wish to employ a data-informed approach to their practice.
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This guide details some of the key reporting features in Sakai that can be of benefit to staff who teach that wish to employ a data-informed approach to their practice.
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.
This guide introduces a number of innovative reporting systems currently in use in Irish institutions.
Case Study K: Using Standard Moodle Reports to Identify AtRisk Students in an Online Course
Case Study L: Using Examination Data Analysis Forms to Implement Year-on-Year Module Improvements
Case Study M: Developing a Cost-Neutral Tracker of Student Workload Distribution
Case Study N: Identifying Effective Resources for First Year Computing Students
Case Study P: An Automated Approach to Managing Clinical Placements
Data-Enabled Student Success Initiative (DESSI) Information Booklet
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.
Automated interventions can be highly impactful, once they are worded and structured carefully and thoughtfully. This resource introduces some of the key steps for ensuring effective student communications.
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.
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.
Case Study H: Using Data to Identify Students that have not Accessed the VLE and Incorporating Feedback into Module
Case Study I: Challenges in Identifying Correlation in a Small Module
Case Study J: Collating Data from Multiple Sources to Identify At-Risk Students
Assessing the Success of Analytics-led Interventions
Case Study A: Gauging Student Engagement in a Blended Programme