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 E: Assessing Students’ Engagement and Responses
Case Study E: Assessing Students’ Engagement and Responses
Case Study F: Balancing Quantitative and Qualitative Data to Drive Change
Case Study F: Balancing Quantitative and Qualitative Data to Drive Change
Case Study G: Using Standard Blackboard Features to Assess Students’ Usage of the VLE
Case Study G: Using Standard Blackboard Features to Assess Students’ Usage of the VLE
Case Study H: Using Data to Identify Students that have not Accessed the VLE and Incorporating Feedback into Module
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 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
