A revolution is taking place in school leadership. New policies call for higher academic standards and accountability. So-called “accountability systems” include more methods to develop and monitor school change. Researchers have joined the fray, adding their opinions about the reinvention of instructional leadership in schools.
More focus on student results leads to local changes aligned with the performance goals of the educational system. The general presumption is that these changes will come automatically, since public reporting of school outcomes creates pressure for reform. The development of direct incentives that yield innovation, efficiency, and solutions to performance problems will also be a source of change.
Accountability systems force the development of standards required for improved instructional and assessment practices. They also act as incentives for participation in the process. This simple logic of an accountability system is compelling, providing an irresistible rationale for educational reform.
The recent debate in the U.S. on the legitimacy of using standardized tests to gauge student learning has led to new leadership efforts and spending to help schools achieve better test scores. These efforts have pressured new instructional leadership, characterized by school analysts, researchers, and school leaders focusing on data in their decision-making. This new instructional paradigm was envisioned earlier in research.
This new instructional style has also been called “learning-centered” leadership. It began with a push by state education leaders to process student data from available achievement tests. Private companies enjoyed financial benefits, selling data reporting systems to schools to help them sort the data. State education leaders hired consultants, who created data analysis workshops and data retreats to instruct school leaders on effective data use. School leaders adopted new school reform plans and curricula coordinated with state learning standards, resulting in far-reaching changes in student learning. Positive results only happened when practitioners were willing to change their ways and conform to the new standards.
The biggest problem in data-driven decision-making is the implementation of new accountability practices. Most schools already had active, working internal accountability systems. Schools already made decisions based on data, such as class attendance, test scores, student discipline, available budgets, and teacher reputations. Administrative reliance on these old internal accountability systems has caused the most resistance to reforms in school instructional practice.
To use data to improve student performance, leaders need to factor in external accountability instead of traditional methods. This new model improves on traditional practices such as teacher evaluation, professional development, curriculum design, and building new cultures of learning. Older techniques will have to be changed to address the challenges of contemporary schools.
Practical systems rely on two-way information flow, connecting classroom practice with external accountability measures. This requires stronger links between teaching and leadership, teacher collaboration, learning matched with current instructional goals, and close monitoring of instructional outcomes. To succeed here, the leader must assist students in taking tests, avoid favoring test preparation over learning, and justify instructional practices changes to the community.
Here are seven factors to consider when doing this:
- Data Acquisition: Data acquisition refers to the processes of seeking, collecting, and preparing useful information for teaching and learning activities. The data gathered and processed at this stage comes from student test scores. However, other fields of information are needed to inform teaching and learning. Data storage is a vital element of data acquisition. There is a need to use local data systems, since the NCLB Act, when it was active, required certain information on student performance. Schools have created a retail demand for data storage and data analysis products.
- Data Reflection: Data reflection is the manipulation of student learning data toward improved teaching and learning practices. DDIS data reflection is a structured opportunity for both teachers and leaders to make useful sense of data, rather than guessing “what works.”Data reflection can be done at a school-wide level, grade level, or even in subject-area meetings. Problem framing is a vital element of data reflection. This involves active thought on how data can improve outcomes, leading to a plan of action.
- Program Alignment: This involves matching the school’s instructional program to the content and performance standards in classrooms. Program alignment is an essential part of planning for instructional leadership, probably the most sensitive part of DDIS, in order to influence the outcome of the new policies.
- Program Design: It is through program design that the school’s policies, plans, and procedures are defined in such a manner that reported problems are addressed. Curricula, student service programs, and instructional strategies are modified to improve student learning. Program design also involves the inspection of the school’s access to budgets and grants, for starting and maintaining a new program.
- Formative Feedback: Feedback is always a crucial in the adoption of new strategies. The DDIS model creates a continuous and timely flow of information, designed to improve student outcomes. This feedback is different from data acquisition and reflection. It applies to information gathered to measure the school’s progress measured in terms of student performance.
- Test Preparation: This last part of the DDIS model consists of activities designed to assess, motivate, and develop student academic abilities, as well as strategies to improve performance on state and district assessment tests. Test preparation covers a wide range of issues, such as test formats, testing skills, and addressing weak areas, as well as test preparation.“Teaching to the test” refers to study content, called “formulaic instruction.” It is teaching students topics that are tested, without regard to holistic learning. Leaders in schools across the U.S. have changed multiple aspects of school life to gear their instructional programs toward test content. Schools where the DDIS mode was put into action didn’t narrow their curriculum to the test content. The researchers noticed instead that, in schools with DDIS systems, there were rich instructional systems designed to help students meet state exam standards.
A DDIS system of instructional leadership is insightful, innovative, and results-oriented. It increases precision in predicting student outcomes and developing key areas of study relevant to academic improvement.
Improvements and changes in instructional leadership have kept it relevant, even in the face of other leadership styles. It is accepted that schools must practice some level of instructional leadership. Instructional leadership remains a crucial aspect of the school setting.
