The Practical Education Decision Process: A Systematic Framework for Improved Decision Making in K-12 Resource Allocation

Abstract

Adapting ideas from sociotechnical frameworks applied to machine learning fairness, this thesis introduces the Practical Education Decision (PED) Process framework. A framework designed to guide resource allocation decisions in K-12 schools. The PED framework recognizes the complexity of the educational resource allocation problem where inputs and outputs are difficult to measure and how they interact and affect each other is difficult to determine. And yet, stakeholders must figure out how to best leverage their resources to improve outcomes within their school. In the PED Process framework, we offer a formal representation of how resource allocation problems are ultimately defined by practitioners, thus offering not only clarity to what is a complex domain but also insight as to where and how resource decisions can be improved upon, specifically by underscoring the value of refining data collection and embracing iterative decision making. Case studies are also presented to test the applicability of the framework and illustrate its potential value to practitioners.