SmartChoice: An Online Recommender System to Support Low-Income Families in Public School Choice


46 AI MAGAZINE Families whose children attend schools that are not mak ing adequate yearly progress (AYP) under the guidelines of the 2001 No Child Left Behind (NCLB) Act are granted the legal right to make an important decision—whether to send their child to a different school. When this occurs, school districts must give students the option of moving to a school that is meeting its AYP goals. However, across the country, fewer than 6 percent of eligible students take advan tage of this provision of the law (GAO 2004, Brown 2004, Howell 2006). Part of the theory of action behind NCLB, and public school choice more generally, is that giving par ents information about school performance and allowing students to leave low-performing schools will improve stu dent outcomes and force poorly performing schools to im prove. However, this provision of NCLB has largely failed to be effective because parents must (1) be able to iden tify which schools will improve their child’s performance and (2) actively make choices about their child’s education. Research has shown that poor tactical implementations of NCLB policy can effectively strip parents, particularly low-income parents, of their legal options and rights, discourag ing and limiting practical participation and ultimately creat ing a culture of disincentive to exercise choice rights under current policy. Our applied research program examines whether a com prehensive community program, collectively referred to as the SmartChoice Program, centered on a computer-assisted decision support system, SmartChoice, can help to over come this implementation problem in current education pol icy. The decision system provides personalized recommen dations for individual students based on parents’ preferences and students’ needs,

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@article{Wilson2009SmartChoiceAO, title={SmartChoice: An Online Recommender System to Support Low-Income Families in Public School Choice}, author={David C. Wilson and Suzanne Leland and Kenneth Godwin and Andrew Baxter and Ashley Levy and Jamie Smart and Nadia Najjar and Jayakrishnan Andaparambil}, journal={AI Magazine}, year={2009}, volume={30}, pages={46-58} }