An optimization-based DSS for student-to-teacher assignment: Classroom heterogeneity and teacher performance measures
作者:
Highlights:
• We illustrate the value of an optimization-based decision support system for principals to assign students to teachers.
• The DSS provides a zero-cost tool allowing principals to independently perform analysis under multiple criteria.
• The DSS has the ability to consider teacher performance metrics in the assignment decision.
• We illustrate the superiority of our DSS to current methods both in solution time and quality.
摘要
A significant amount of administrator's summer planning is spent attempting to assign hundreds of students to teachers. These assignments must satisfy federal guidelines, parent preferences, and principal preferences while pursuing classroom parity and equity in regards to academic performance, behavioral support, and demographics. In addition, teachers are often the most invested in these decisions given the impact on their day-to-day life and their future performance evaluations. This problem is a variant of a standard problem in operations research; however, administrators often lack the technical expertise or budgets to build and/or implement such models. We present an open-source spreadsheet model-based DSS to this purpose. We formulate the problem as a mixed integer program, present the implemented spreadsheet model interface, and illustrate on a set of student data. This DSS was implemented in the fall of 2018 for the assignment of close to 600 students to 24 classrooms saving dozens of staff and administration hours.
论文关键词:Decision support systems,Education,Assignment problems,Optimization,Optimization,Spreadsheets,Open source
论文评审过程:Received 1 October 2018, Revised 21 January 2019, Accepted 19 February 2019, Available online 5 March 2019, Version of Record 11 March 2019.
论文官网地址:https://doi.org/10.1016/j.dss.2019.02.006