An Interactive Framework to Allocate and Manage Teaching Workload using Hybrid OLAP Cubes

Abstract

Assignment of teaching workload is an essential annual ritual in all academic institutions. Depending upon the structure and complexity, it can be a painful process for department heads and administrative deans who are responsible for resource allocation. We present a framework which uses business intelligence techniques to allow asynchronous data entry, analysis and reporting in a collaborative environment to assist with the decision-making process. To begin, the first-tier administrators make workload assignments in consultation with faculty using interactive web forms, data is pushed to the underlying database or cube, reports are rendered, and memos are auto-generated. Deans responsible for approval are able to review the information along several dimensions and make informed decisions regarding the assignments. Historical data remains available for future years for trends and analysis. Besides achieving the benefits from transparency of the process, the framework exploits both OLAP cubes and relational data stores for optimum performance.