Process Indicators

DDDM means educators and policymakers utilize and analyze school and student data to improve school effectiveness and to recognize the value of data. The term DDDM has been generally used with databased decision making, research-based decision making, and evidence-based decision making interchangeably. According to Marsh, Pane and Hamilton, DDDM means that schools "systematically collect and analyze various types of data, including input, process, outcome and satisfaction data, to guide a range of decisions to help improve the success of students and schools". The multiple sorts of indicators include: input indicators such as school demographics of students and teachers, and expenditures; process indicators related to operation of curriculum and instruction; outcome indicators connected with dropout rates and student test scores; satisfaction data connected with opinions from teacher and students, etc.

DDDM is a sphere of currently emergent research areas for monitoring student progress and school improvement, certifying educational problems and needs, and assessing program effectiveness. DDDM is based on accountability indicators which refer to comprehensive statistical information linked to generate and utilize the accurate information of process and performance on complex school organization. The current accountability indicators are composed of quantitative inputand-result oriented indicators such as standardized test score, dropout rates, graduation rates, and so on. They, intrinsically, may be designed to promoting the equality of educational result through the advancement of student learning and the enhancement of professionalism for taking care of the poor and leftbehind students. It is evident that accountability policy can strikingly close the achievement gaps among students by paying attention to the reading and math standard and high-qualified teachers.

and high-qualified teachers. However, school organization has both a tightly-coupled and a loosely-coupled perspective. The tightlycoupled frame highlights centralized control, coordination by written rules, vertical communication, hierarchy, supervision, compliance, efficiency, and extrinsic incentive. Meanwhile, school organization is a professional organization, which provides an operational core for schooling. Also it is a loosely-coupled system in that schools can be conceptualized as "differentiated organizations", or "culturally heterogeneous organizations", which means that they have internally complex and distinctive cognitive and emotional strategies. Therefore a school is a loosely-coupled lens focused on professional organization oriented to educators' professional knowledge and judgment. In this respect, school organizations are likely to interact dynamically with a variety of individual and group-level contextual factors. As Greenfield indicated, a school's organization should be understood as "an object of understanding".

In spite of the loosely-coupled image, as Hoy and Miskel said, the demands for accountability may make school organization more formalization, more centralization, less professionalization. The tightly coupled policy has been influenced by the government's increasing involvement in schooling. Current educational policy was designed to improve education through "a tightly-coupled DDDM based on higher standards, testing, and accountability. However, teachers mostly have worked in solitary classrooms where they are not easily evaluated by colleagues or supervisors. Firestone and Herriott indicated "in schools, the actual work of bringing students in contact with what is taught is done by teachers who have considerable discretion. In effect, a major portion of the school's central purpose cannot be controlled by the administrative cadre". Put differently, teachers are educational critics that distinguish and evaluate their works and students' needs in their own way within specific contexts.

In an era of strict demand of accountability, top-down accountability policy is focused on students' academic performance. However, it may need to be balanced with teacher-centered indicators focused on the active involvement of professionals and the mutual collaboration of practitioners. O'Day indicated the importance of the rich generation, valid interpretation, and relevant circulation of information and data among accountability players because the conflicts result from the miscommunication between administrators and professionals who have different accountability views: administrators focused on students' academic performance by state's high-stakes test such as reading and math score, attendance rate, and graduate rate; however, professionals put an emphasis on educators' professional knowledge and judgment according to peer review and sanction. In this respect, she argues that well-informed data catalyze as a medium of communication between both sides.

on between both sides. As O'Day indicated, the rich generation, valid interpretation, and relevant circulation of the proper data and information related to school reality are likely to contribute to being successful for organizational capacity and improvement. The data and information should be related to generating and focusing on information relevant to teaching and learning and to changes for the continual "calibration" and "feedback". They are likely to motivate educators and others to attend to relevant information and to expand the effort necessary to augment or change strategies in response to this information. Furthermore, they are able to develop the knowledge and skills to promote valid interpretation of information and appropriate attribution of causality at both the individual and system levels. Because the teacher-based indicators are dependent on an acquired and processed indicators by teachers who in a actual context have a sense of the operational situations, problems and alternatives for enhancing school improvement and effectiveness. In this vein, it is reasonable for DDDM to be based on not input-andoutcome-based indicators but process indicators that can describe "contexts" and explain "causes", in that "a snapshot of school practice is not sufficient; assessment of change is needed".

Young and Wayman and Stringfield identified that schools show distinctive responses to use and approach data in terms of their organizational contexts and cultural norms. DDDM needs to be based on the flexible and diverse process indicators used to provide timely diagnostic information of improvement, to capture a better qualitative characteristic of teaching and learning, to explain "whys" when students and schools don't reach the standard and to provide which support to schools. In this respect, process indicators can be linked to substantive instruction support and curriculum provisions by calibrating through a productive and reflective "test talk" or "communication" with stakeholders. By using process indicators, school-level working condition or district-level agenda setting can be related to establishing collaborative works and learning norms and climate by helping to understand everyday instruction-related practices within the contexts and by helping find how to align and arrange district-driven policies with their contexts and change endeavors.

Scholars suggested four types of indicators, context, input, process, and product for the decision making in terms of accountability. In terms of context indicators, it would be the students' achievement level which needed to be improved, instructional and personal barriers to study in classroom, students' absence and dropout rate, etc. It could be referred as input indicators: school budget and resources and time invested to solve the school problem in order to achieve educational goal, and so on. It would be considered degree of the relationship and understanding between students and teachers, adequacy of time schedule, teaching activities, and school resources as process indicators. It may be thought of the output on whether learner achieved learning objects and the indicators which is related to the output such as parents and students satisfaction in terms of product indicators.

DDDM is based on contextual factors or school cultural and institutional factors: data quality, calibration, principal leadership, faculty involvement, educator collaboration, and other institutional supports. First, data quality is related to keeping highquality, accurate data, and an accurate and quality database. It provides the following information for educators and policy makers: what programs have been provided to students and how students completed the programs, how the test result has been improved, and what teachers have used an adequate teaching method for improving student achievement by a school year. Second, calibration defined as collective reflectivity or deliberation is combined with how educators define indicator use, how teaching conduct under these definitions, how they assess student learning, and how they react to results. Third, principal leadership is connected with principals' investment and support for the use of data system. The existing research recognizes a role of principal as one of the critical factors to improve school management and student achievement. Principal is also considered as an important player in the data use. However, school leadership needs to be focused on distributed leadership, being stretched over more broadly and distributed beyond individuals because the role of school principals for DDDM is limited. Fourth, faculty involvement has to do with teachers' engagement and interest to the data generation, use and application for their classroom and school program. According to Marsh, Pane and Hamilton, factors to promote the data use depend on accountability policies and intrinsic motivation: Federal, state, and local accountability policies such as incentives and pressure to use data; the internal desire of teachers to make better use of data. Fifth, collaboration is consistent with educators' data sharing and co-using. Collaboration for DDDM in the level of school is closely related with organizational culture and school leadership. Finally, institutional supports are coupled with the education authorities provide deeper and continuous professional development, establish a friendly data warehouse, and give teachers sufficient time to access and examine data.

Based on the above discussions, as Figure 1 shows, we will elaborate on how five elements are correlated with DDDM. DDDM is divided into two parts: three basic elements and two cultural catalysts. Three basic factors are "who makes use of indicators or data for what", referring to data or indicator, generating or supporting users, and calibration. Data/indicator is a connecting factor between users-generating or supporting users. Generating users are a principal, a school faculty or a school data team for exploring the problems and alternatives for school improvements and accountability in terms of school results and "what's-going-on" through calibration. Administrative staffs, who establish database system, computer software or data warehouse, support DDDM by providing professional development program in order to collect, monitor, use, and interpret indicators of schools' contexts, processes and results through calibration or collective thinking process for authentic pedagogy, accountability, and school effectiveness.

Figure 1.

The conceptual structure of DDDM.

Catalysts are embedded in the calibration meaning collectively cognitive inquiry through the interaction between users. Copland pointed out that capacity building and school improvement would bring from collective cognitive processes through organizational learning and distributed cognition. According to Spillane, distributed cognition works in a situation composed of routines, tools, structures, and institutions. A routine includes regular procedures and committee for determining activities to achieve school and team activities. A tool encompasses from the documents regarding student's achievement to protocol. A structure is related to a form of institution such as class teachers' and regular teachers' meeting, team structure within school organization, and committee and spontaneous forms regarding temporary team. An institution includes vision, goal, and regulations of school organization. These make a difference in that each school has a discrete calibration; so it has a distinctive mode and characteristic of leadership, collaboration, and involvement for DDDM.

Therefore, the catalysts are embedded in the school situation and in each situation they are emergent for DDDM. Put differently, these facilitating factors are derived from the calibration nested in interaction between users. As discussed earlier, Young and Wayman and Springfield proved that schools tend to show distinct indicator use and approach in the context of their organizational cultural features. In this respect, the cultural catalysts, referring to distributed leadership, collaboration and involvement, have a significant effect on "how or under what conditions users put to use indicators" in terms of leadership, climate and culture within a school or across schools.