Smartchoice: An online recommender system to support low-income families in public school choice

AI Magazine

Volumn 30, Issue 2, 2009, Pages 46-58

  Wilson, David C ^a   Leland, Suzanne ^b   Godwin, Kenneth ^b   Baxter, Andrew ^b   Levy, Ashley ^b   Smart, Jamie ^d   Najjar, Nadia ^c   Andaparambil, Jayakrishnan ^d  

^a University of North Carolina at Charlotte   (United States)

^b UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE   (United States)

^c Homecorp Realty   (United States)

^d NONE

Author keywords

[No Author keywords available]

Indexed keywords

SCHOOL BUILDINGS; STUDENTS;

CONTENT-BASED RECOMMENDER SYSTEMS; INFORMATION ACCESS; INFORMATION OVERLOADS; NO CHILD LEFT BEHIND ACT; ON-LINE APPLICATIONS; ONLINE RECOMMENDER SYSTEMS; POTENTIAL IMPACTS; SOCIO-ECONOMIC STATUS;

RECOMMENDER SYSTEMS;

EID: 77955026749     PISSN: 07384602     EISSN: None     Source Type: Journal    
DOI: 10.1609/aimag.v30i2.2239     Document Type: Article

References (46)

1. Ambler, J. 1994. Who Benefits from Educational Choice: Some Evidence from Europe. Journal of Policy Analysis and Management 13(3): 454-476.
2. Bailou, D.; Sanders, W.; and Wright, P. 2004. Controlling for Student Background in Value-Added Assessment of Teachers. Journal of Educational and Behavioral Statistics 29(1): 37-65.
3. Basu, C.; Hirsh, H.; and Cohen, W. W. 1998. Recommendation as Classification: Using Social and ContentBased Information in Recommendation. In Proceedings of the Fifteenth National Conference on Artificial Intelligence, 714-720. Menlo Park, CA: AAAI Press.
4. Bollen, K., and Curran, P. 2006. Latent Curve Models: A Structural Equation Perspective. New York: Wiley-Interscience.
5. Brown, C. 2004. Choosing Better Schools: A Report on Student Transfers under the No Child Left Behind Act. Washington, DC: Citizens' Commission on Civil Rights.
6. Burke, R.; Hammond, K.; and Young, B. 1997. The FlndMe Approach to Assisted Browsing. IEEE Expert 12(4): 32-40.
7. Burke, R. 2002. Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction 12(4): 331-370.
8. Chubb, J., and Moe, T. 1990. Politics, Markets, and America's Schools. Washington, DC: Brookings Institution.
9. Coons, J., and Sugarman, S. 1978. Education by Choice: The Case for Family Control. Berkeley, CA: University of California Press.
10. Dunk, E. V., and Dickman, A. 2003. School Choice and the Question of Accountability: The Milwaukee Experience. New Haven, CT: Yale University Press.
11. GAO. 2004. No Child Left Behind Act: Education Needs to Provide Additional Technical Assistance and Conduct Implementation Studies for School Choice Provision. Report to the Secretary of Education GAO-05-7, U.S. Government Accountability Office, Washington, D.C.
12. Godwin, K., and Kemerer, F. 2002. School Choice Tradeoffs: Liberty, Equity, and Diversity. Austin, TX: University of Texas Press.
13. Hargittai, E. 2005. Survey Measures of Web-Oriented Digital Literacy. Social Science Computer Review 23(3): 371379.
14. Hastings, J., and Weinstein, J. M. 2007. No Child Left Behind: Estimating the Impact on Choices and Student Outcomes. Technical Report 13009, National Bureau of Economic Research Working Paper Series, Cambridge, MA.
15. Haythomthwaite, C. 2007. Social Facilitators and Inhibitors to Online Fluency. In Proceedings of the 40th Annual Hawaii International Conference on System Sciences. Los Alamitos, CA: IEEE Computer Society.
16. Herlocker, J. L.; Konstan, J. A.; and Riedl, J. 2000. Explaining Collaborative Filtering Recommendations. In CSCW '00: Proceedings of the 2000 ACM conference on Computer Supported Cooperative Work, 241-250. New York: ACM Press.
17. Hill, P. T. 2007. NCLB School Choice and Children in Poverty. In Standards-Based Reform and the Poverty Gap, ed. A. Gamoran. Washington, DC: Brookings Institution.
18. Howell, W. 2006. Switching Schools? A Closer Look at Parents' Initial Interest in and Knowledge about the Choice Provisions of No Child Left Behind. Peabody Journal of Education 81(1): 140-179.
19. Hoxby, C., and Weingarth, G. 2005. Taking Race out of the Equation: School Reassignment and the Structure of Peer Effects. Technical report, Department of Economics, Harvard University, Cambridge, MA.
20. Kim, J., and Sunderman, G. 2004. Does NCLB Provide Good Choices for Students in Low-Performing Schools? Technical report, The Civil Rights Project at Harvard University, Cambridge, MA.
21. Konstan, J. A.; Miller, B. N.; Maltz, D.; Herlocker, J. L.; Gordon, L. R.; and Riedl, J. 1997. Grouplens: Applying Collaborative Filtering to Usenet News. Communications of the ACM40(3): 77-87.
22. rulwich, B. 1997. Lifestyle Finder: Intelligent User Profiling Using Large-Scale Demographic Data. AI Magazine 18(2): 37-45.
23. Leland, S.; Godwin, K.; and Baxter, A. 2007. Examining School Choice through the Eyes of Parents. Paper presented at the Annual Meetings of the Midwest Political Science Association, Chicago, IL, April 12-15.
24. McCaffrey, D.; Lockwood, J.; Koretz, D.; and Hamilton, L. 2003. Evaluating Value-Added Models for Teacher Accountability. Technical report, Rand Corporation, Santa Monica, CA.
25. McCaffrey, D.; Lockwood, J.; Koretz, D.; Louis, T.; and Hamilton, L. 2004. Models for Value-Added Modeling of Teacher Effects. Journal of Educational and Behavioral Statistics 29(1): 67-101.
26. McDermott, K. A., and Jensen, L. S. 2005. Dubious Sovereignty: Federal Conditions of Aid and the No Child Left Behind Act. Peabody Journal of Education 80(2): 39-56.
27. Meier, D., and Wood, G. H. 2004. Many Children Left Behind: How the No Child Left Behind Act Is Damaging Our Schools. Boston: Beacon Press.
28. Montaner, M.; López, B.; and de la Rosa, J. L. 2003. A Taxonomy of Recommender Agents on the Internet. Artificial Intelligence Review 19(4): 285-330.
29. Pazzani, M. J., and Billsus, D. 2007. Content-Based Recommendation Systems. In The Adaptive Web: Methods and Strategies of Web Personalization, ed. P. Brusilovsky, A. Kobsa, and W. Nejdl, 325-341. Berlin: Springer-Verlag.
30. Raudenbush, S. 2004. What Are Value-Added Models Estimating and What Does This Imply for Statistical Practice? Journal of Educational and Behavioral Statistics 29(1) 121-129.
31. Resnick, P., and Varian, H. R. 1997. Recommender Systems. Communications of the ACM40(3): 56-58.
32. Rosenstein, M., and Lochbaum, C. 2000. Recommending from Content: Preliminary Results from an E-Commerce Experiment. In CHI '00 Extended Abstracts on Human Factors in Computer Systems, 291-292. New York: ACM Press.
33. Rubin, D.; Stuart, E.; and Zanutto, E. 2004. A Potential Outcomes View of Value-Added Assessment in Education. Journal of Educational and Behavioral Statistics 29(1): 103.
34. Sarwar, B.; Karypis, G.; Konstan, J.; and Riedl, J. 2000. Analysis of Recommendation Algorithms for E-Commerce. In Proceedings of the 2nd ACM Conference on Electronic Commerce, 158-167. New York: ACM Press.
35. Sarwar, B.; Karypis, G.; Konstan, J.; and Reidl, J. 2001. Item-Based Collaborative Filtering Recommendation Algorithms. In Proceedings of the Tenth International Conference on World Wide Web, 285-295. New York: ACM Press.
36. Schäfer, J. B.; Frankowski, D.; Herlocker, J.; and Sen, S. 2007. Collaborative Filtering Recommender Systems. In The Adaptive Web: Methods and Strategies of Web Personalization, ed. P. Brusilovsky, A. Kobsa, and W. Nejdl, 291-324. Berlin: Springer-Verlag.
37. Schafer, J. B.; Konstan, J.; and Riedl, J. 1999. Recommender Systems in E-Commerce. In EC '99: Proceedings of the 1st ACM Conference on Electronic Commerce, 158-166. New York: Association for Computing Machinery.
38. Schneider, M.; Teske, P.; Roch, C.; and Marschall, M. 1997. Networks to Nowhere: Segregation and Stratification in Networks of Information about Schools. American Journal of Political Science 41(4): 1201-1223.
39. Singer, J., and Willett, J. 2003. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford University Press.
40. Smyth, B., and Cotter, P. 2001. Personalized Electronic Programme Guides. AIMagazine 22(2): 89-98.
41. Soboroff, I., and Nicholas, C. 1999. Combining Content and Collaboration in Text Filtering. Paper presented at the IJCAI-99 Workshop on Machine Learning for Information Filtering. Stockholm, Sweden, July 31-August 6.
42. Southworth, S., and Mickelson, R. 2007. The Interactive Effects of Race, Gender and School Composition on College Track Placement. Social Forces 86(2) 497-523.
43. Tekwe, C.; Carter, R. L.; Ma, C.-X.; Algina, J.; Lucas, M. E.; Roth, J.; Ariet, M.; Fisher, T.; and Resnick, M. B. 2004. An Empirical Comparison of Statistical Models for ValueAdded Assessment of School Performance. Journal of Educational and Behavioral Statistics 29(1): 11-36.
44. Terveen, L.; Hill, W.; Amento, B.; McDonald, D.; and Creter, J. 1997. PHOAKS: A System for Sharing Recommendations. Communications of the ACM 40(3): 59-62.
45. U.S. Department of Education. 2001. No Child Left Behind Act of 2001. 2001-PL107110. Washington, DC: Government Printing Office.
46. Wilson, D. C.; Leland, S.; Godwin, K.; Baxter, A.; Levy, A.; Smart, J.; Najjar, N.; and Andaparambil, J. 2008. The Law of Choice and the Decision Not to Decide. In Proceedings of the 20th Conference on Innovative Applications of Artificial Intelligence. Menlo Park, CA: AAAI Press.