Student Intervention Guide
Analytics is invaluable for answering questions, but impact can only be achieved by acting on the answers. This guide outlines some of the key considerations for developing effective data-informed student interventions.
Case Study I: Challenges in Identifying Correlation in a Small 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
Case Study J: Collating Data from Multiple Sources to Identify At-Risk Students
Case Study L: Using Examination Data Analysis Forms to Implement Year-on-Year Module Improvements
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 M: Developing a Cost-Neutral Tracker of Student Workload Distribution
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
Case Study P: An Automated Approach to Managing Clinical Placements
Case Study P: An Automated Approach to Managing Clinical Placements
Case Study B: Gauging Student Engagement with an Online Orientation Module
Case Study B: Gauging Student Engagement with an Online Orientation Module
Topics for Consideration when Selecting an LA Vendor
Although bespoke platforms are not essential for developing a data-informed approach, for any institution that is considering doing so, identifying the right platform is important. This document lists a number of essential considerations for opting for a reporting system that is right for your institution’s reporting needs.
