About this paper

Appears in:
Pages: 102-110
Publication year: 2011
ISBN: 978-84-615-0441-1
ISSN: 2340-1117

Conference name: 3rd International Conference on Education and New Learning Technologies
Dates: 4-6 July, 2011
Location: Barcelona, Spain

DATA DRIVEN DECISION MAKING AS AN INNOVATION: USING DIFFUSION THEORY TO UNDERSTAND TEACHER PROFESSIONAL LEARNING COMMUNITIES

J. Nash1, S. Hopper2

1Iowa State University (UNITED STATES)
2Des Moines Public Schools (UNITED STATES)
In the outcomes-focused era of today’s schools, school leaders and teachers find themselves looking for ways to be as effective as possible. A popular approach to improving teacher collaboration and student learning is the professional learning community (PLC). The idea that educators should assemble themselves in professional learning communities is an idea that continues to gain favor. Generally PLCs begin with a group of teachers meeting regularly, agreeing on key learning goals for students, developing common assessments, analyzing data on achievement for decision making, and finally some sort of action (new, improved lessons, for instance).

A key component in many PLCs is the systematic collection and analysis of various types of student performance data by teachers. This behavior, referred to as data driven decision-making, has become a mantra of educators in the United States and elsewhere. However, data driven decision making does not guarantee effective decision making. Having data does not necessarily mean that they will be used to drive decisions or lead to improvements.

The fact of the matter is that educators’ comfort level with data collection, analysis, and its role in student success is not high. Thus, in our research we allege that data driven decision making should be treated as an innovation. By doing so, school leaders seeking to implement PLCs within their schools can examine the different components of an innovation that are likely to lead to its success.

Using a sample of public school teachers in the United States (n=200), our research team utilized survey research to examine what happens when data driven decision making by teachers is treated as an innovation. The results suggest a relationship exist between a teacher's adoption of data driven decision making and their perceptions of it in terms of key innovation-adoption characteristics, such as whether it's a volunteer activity, whether it is perceived as creating personal prestige, whether it's compatible with their personal schemas, as well as ease of use and relative advantage.

Results from this study enhance understanding of how perceptions of DDDM influence adoption behaviors, helping school leaders better understand how to strategically implement the practice within professional learning communities and ensure “buy-in” across the school system. This study carries both theoretical and methodological significance for researchers. Understanding how innovation buy-in may influence the adoption of key success behaviors can help school leaders better understand how to strategically implement practices designed to enhance student outcomes.
@InProceedings{NASH2011DAT,
author = {Nash, J. and Hopper, S.},
title = {DATA DRIVEN DECISION MAKING AS AN INNOVATION: USING DIFFUSION THEORY TO UNDERSTAND TEACHER PROFESSIONAL LEARNING COMMUNITIES},
series = {3rd International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN11 Proceedings},
isbn = {978-84-615-0441-1},
issn = {2340-1117},
publisher = {IATED},
location = {Barcelona, Spain},
month = {4-6 July, 2011},
year = {2011},
pages = {102-110}}
TY - CONF
AU - J. Nash AU - S. Hopper
TI - DATA DRIVEN DECISION MAKING AS AN INNOVATION: USING DIFFUSION THEORY TO UNDERSTAND TEACHER PROFESSIONAL LEARNING COMMUNITIES
SN - 978-84-615-0441-1/2340-1117
PY - 2011
Y1 - 4-6 July, 2011
CI - Barcelona, Spain
JO - 3rd International Conference on Education and New Learning Technologies
JA - EDULEARN11 Proceedings
SP - 102
EP - 110
ER -
J. Nash, S. Hopper (2011) DATA DRIVEN DECISION MAKING AS AN INNOVATION: USING DIFFUSION THEORY TO UNDERSTAND TEACHER PROFESSIONAL LEARNING COMMUNITIES, EDULEARN11 Proceedings, pp. 102-110.
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