Corrigendum to "Multiple initiatives, multiple challenges: The promise and pitfalls of implementing data" [Stud. Educ. Eval. 42 (2014) 54-62], DOI: 10.1016/j.stueduc.2013.10.003;Multiple initiatives, multiple challenges: The promise and pitfalls of implementing data

Studies in Educational Evaluation

Volumn 42, Issue , 2014, Pages 54-62

  Hubbard, Lea ^a   Datnow, Amanda ^b   Pruyn, Laura ^a  

^a UNIVERSITY OF SAN DIEGO   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Data use; Project based learning; School reform

Indexed keywords

EID: 84903733844     PISSN: 0191491X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.stueduc.2014.07.004     Document Type: Erratum

References (44)

1. Buck Institute website. PBL Planning Resources for Teachers. Retrieved from. Accessed: 18.11.12. http://www.bie.org/.
2. Cawelti G., Protheroe G. The school board and central office in school improvement. Handbook on restructuring and substantial school improvement 2007, 37-52. Center on Innovation and Improvement, Lincoln, IL.
3. Charmaz K. Constructing grounded theory: A practical guide through qualitative analysis 2006, Sage Publications, Thousand Oaks, CA.
4. Coburn C.E. Collective sensemaking about reading: How teachers mediate reading policy in their professional communities. Educational Evaluation and Policy Analysis 2001, 23(2):145-170.
5. Coburn C.E., Turner E.O. The practice of data use: An introduction. American Journal of Education 2012, 118(2):99-110.
6. Creswell J. Research design 2009, Sage Publications, Thousands Oaks, California. 3rd ed.
7. Daly A.J. Data, dyads, and dynamics: Exploring data use and social networks in educational improvement. Teachers College Record 2012, 114(11):1-21.
8. Datnow A., Park V., Wohlstetter P. Achieving with data: How high-performing school systems use data to improve instruction for elementary students 2007, Center on Educational Governance, Rossier School of Education, University of Southern California.
9. Dowd A. Data don't drive: Building a practitioner-driven culture of inquiry to assess community college performance 2005, Lumina Foundation for Education, Indianapolis, IN.
10. Earl L., Fullan M. Using data in leadership for learning. Cambridge Journal of Education 2003, 33(3):383-394.
11. Earl L., Katz S. Leading schools in a data rich world 2006, Corwin Press, Thousand Oaks, CA.
12. Foley E., Sigler D. Getting smarter: A framework for districts. Voices in Urban Education Winter, 2009, 22:5-12.
13. Fullan M. Change forces: The sequel 1999, Falmer Press, London, England.
14. Hamilton L., Halverson R., Jackson S., Mandinach E., Supovitz J., Wayman J. Using student achievement data to support instructional decision making (NCEE 2009-4067) 2009, National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education, Washington, DC.
15. Hatch T. What happens when improvement initiatives collide?. Phi Delta Kappan 2002, 8(8):626.
16. Honig M.I., Venkateswaran N. School-central office relationships in evidence use: Understanding evidence use as a systems problem. American Journal of Education 2012, 118(2):199-222.
17. Horn I.S., Little J.W. Attending to problems of practice: Routines and resources for professional learning in teachers' workplace interactions. American Educational Research Journal 2010, 47(1):181-217.
18. Ikemoto G.S., Marsh J.A. Cutting through the "data driven" mantra: Different conceptions of data-driven decision making. Evidence and decision making (National Society for the Study of Education Yearbook, Vol. 106, Issue 1, pp. 105-131) 2007, National Society for the Study of Education, Chicago. P.A. Moss (Ed.).
19. International Baccalaureate Diploma Programme website. Retrieved from. Accessed: 24.11.12. http://www.ibo.org/general/who.cfm.
20. Leithwood K. Characteristics of high performing school districts: A review of empirical evidence 2008, College of Alberta School Superintendents, Calgary, AB.
21. Levin B., Datnow A., Carrier N. Changing school district practices 2012, Jobs for the Future, Boston, MA. http://www.studentsatthecenter.org/papers/changing-school-district-practices.
22. Levin J., Datnow A. The principal as agent of mediated educational reform: Dynamic models of case studies of data driven decision making. School Effectiveness and School Improvement 2012, 23(2):179-201.
23. Madda C., Halverson R.M., Gomez L. Exploring coherence as an organizational resource for carrying out reform initiatives. Teachers College Record 2007, 109(8):1957-1979.
24. Data driven school improvement: Linking data and learning. 2008, Teachers College Press, New York. E.B. Mandinach, M. Honey (Eds.).
25. Mandinach E.B., Honey M., Light D. A theoretical framework for data driven decision making. Paper presented at the annual meeting of the American Educational Researchers Association 2006.
26. Markham, T. (2012). Top ten tools for PBL. Retrieved from. Accessed: 25.11.12. http://www.thommarkham.com/.
27. Marsh J. Interventions promoting educators' use of data: Research insights and gaps. Teachers College Record 2012, 114(11):1-48.
28. Marsh J., Kerr K.A., Ikemoto G.S., Darilek H., Suttorp M., Zimmer R., et al. The role of districts in fostering instructional improvement: Factors affecting data use 2005, 72. RAND Education.
29. McPhee A., Patrik F. "The pupils will suffer if we don't work": Teacher professionalism and reactions to policy change in Scotland. Scottish Educational Review 2009, 41(1):86-96.
30. Means B., Padilla C., Gallagher L. Use of education data at the local level: From accountability to instructional improvement 2010, U.S. Department of Education, Office of Planning, Evaluation, and Policy Development, Washington, DC.
31. Merriam S.B. Qualitative research and case study applications in education 1998, Jossey-Bass Publishers, San Francisco.
32. Moss P.A. Exploring the macro-micro dynamic in data use practice. American Journal of Education February, 2012, 118(2):223-232. 10.1086/663274.
33. Rallis S.F., Rossman G.B. Communicating quality and qualities: The role of the evaluator as critical friend. Visions of quality: How evaluators define, understand, and represent program quality 2001, 107-120. JAI Press, Oxford, UK. A.P. Benson, D.M. Hinn, C. Lloyd (Eds.).
34. th yearbook of the National Society for the Study of Education 2005, 147-174. Blackwell Publishing, Malden, MA. J.L. Herman, E.H. Haertel (Eds.).
35. Schildkamp K., Lai M.K. Introduction. Data-based decision making in education: Challenges and opportunities 2012, 1-9. Springer, Dordrecht, Netherlands. K. Schildkamp, M.K. Lai, L. Earl (Eds.).
36. School Accountability Report Card (SARC), 2011. Data Almanac.
37. Spillane J.P. Data in practice: Conceptualizing the data-based decision-making phenomenon. American Journal of Education 2012, 118(2):113-141.
38. Spillane J.P., Reiser B.J., Reimer T. Policy implementation and cognition: Reframing and refocusing implementation research. Review of Educational Research 2002, 72(3):387-431.
39. Stake R.E. The art of case study research 1995, Sage Publications, Thousand Oaks, CA.
40. Supovitz J.A. Can high stakes testing leverage educational improvement? Prospects from the last decade of testing and accountability reform. Journal of Educational Change 2009, 10(2 & 3):211-227.
41. Supovitz J., Taylor B.S. The impacts of standards-based reform in Duval County, Florida 1999-2002 2003, Consortium for Policy Research in Education, Philadelphia, PA.
42. U.S. Department of Education, Office of Elementary and Secondary Education. (April, 2006). Improving Data Quality for Title I Standards, Assessments, and Accountability Reporting: Guidelines for States, LEAs, and Schools (Non-Regulatory Guidance). (Produced by DTI Associates, A Haverstick Company, under U.S. DOE Contract No. ED-01-CO-0066/0009), pp. 6-7. Retrieved from U.S. Department of Education website,. Accessed: 23.11.12. http://www2.ed.gov/policy/elsec/guid/standardsassessment/nclbdataguidance.pdf.
43. Yin R.K. Case study research: Design and methods. Applied Social Research Methods Series 2009, Vol. 5. Sage Publications, Thousand Oaks, CA. 4th ed.
44. Young V.M. Teachers' use of data: Loose coupling, agenda setting, and team norms. American Journal of Education 2006, 112(4):521-548.