[1] Allensworth, E., & Easton, J. Q. (2007). What Matters for Staying On-track and Graduating in Chicago Public High Schools: A Close Look at Course Grades, Failures, and Attendance in the Freshman Year. Chicago, IL: Consortium on Chicago School Research.
[2] Annenberg Learner (2015). Teacher Resources and Professional Development across the Curriculum (1997-2015).
http://www.learner.org/resources/browse.html
[3] Barnes, F. V., & Miller, M. (2001). Data Analysis by Walking around. The School Administrator, 58, 20-25.
[4] Barton, P. E. (2005). One-Third of a Nation: Rising Dropout Rates and Declining Opportunities. Policy Information Report. Princeton, NJ: Educational Testing Service.
[5] Bernhardt, V. L. (1998). Data Analysis for Continuous School Improvement. Larchmont, NY: Eye on Education.
[6] Blankstein et al. (2010). Data-Enhanced Leadership. Thousand Oaks, CA: Corwin Press.
[7] Copland, M. (2003). Leadership of Inquiry: Building and Sustaining Capacity for School Improvement. Educational Evaluation and Policy Analysis, 25, 375-395.
http://dx.doi.org/10.3102/01623737025004375
[8] Earl, L., & Katz, S. (2002). Leading Schools in a Data Rich World. In K. Leithwood et al. (Eds.), The Second International Handbook of Educational Leadership and Administration (pp. 1003-1022). Dordrecht, Netherlands: Kluwer.
http://dx.doi.org/10.1007/978-94-010-0375-9_34
[9] Edudemic (2015). The Teacher’s Guides to Technology and Learning.
http://www.edudemic.com/guides/
[10] Gandara, P. C., & Contreras, F. (2009). The Latino Education Crisis: The Consequences of Failed Social Policies. Cambridge, MA: Harvard University Press.
[11] Gaynor, A. (1998). Analyzing Problems in Schools and School Systems. Mawah, NJ: Lawrence Erlbaum.
[12] Heppen, J. B., & Therriault, S. B. (2008). Developing Early Warning Systems to Identify Potential High School Dropouts. Washington DC: The National High School Center at the American Institutes for Research.
[13] Jerald, C. (2006). Identifying Potential Dropouts: Key Lessons for Building an Early Warning Data System. Washington DC: Achieve, Inc.
[14] Kennelly, L., & Monrad, M. (2007). Approaches to Dropout Prevention: Heeding Early Warning Signs with Appropriate Interventions. Washington DC: National High School Center, American Institutes for Research.
[15] McCowan, T., & Unterhalter, E. (Eds.) (2015). Education and International Development: An Introduction. New York: Bloomsbury.
[16] National Academy of Sciences (2012). Next Generation Science Standards: Executive Summary. Washington DC: National Academies Press.
http://www.nextgenscience.org/
[17] National Research Council (2011). A Framework for K-12 Science Education: Practices, Cross-Cutting Concepts, and Core Ideas. Washington DC: National Academies Press.
http://www.nationalacademies.org/publications/index.html
[18] Orfield, G. (2004). Losing Our Future: Minority Youth Left Out. In G. Orfield (Ed.), Dropouts in America: Confronting the Graduation Rate Crisis (pp. 131-155). Cambridge, MA: Harvard Education Press.
[19] Pinkus, L. (2008). Using Early-Warning Data to Improve Graduation Rates: Closing Cracks in the Education System. Policy Brief. Washington DC: Alliance for Excellent Education.
[20] Prensky, M. (2010). Teaching Digital Natives: Partnering for Real Learning. Thousand Oaks, CA: Corwin.
[21] Robinson, V., Phillips, G., & Timperley, H. (2002). Using Achievement Data for School-Based Curriculum Review. Leadership and Policy in Schools, 1, 3-29.
http://dx.doi.org/10.1076/lpos.1.1.3.5402
[22] Rodriguez, L. F. (2014). The Time Is Now: Understanding and Responding to the Black and Latina/o Dropout Crisis in the United States. New York: Peter Lang.
[23] Rumberger, R. W. (2012). Dropping Out: Why Students Drop Out of High School and What Can Be Done about It. Cambridge, MA: Harvard University Press.
[24] Saginor, N. (2008). Diagnostic Classroom Observation: Moving beyond Best Practice. Thousand Oaks, CA: Corwin Press.
[25] Spillane, J. P. (2006). Distributed Leadership. San Francisco: Jossey-Bass Publishers.