There has been an increasing appetite for data in the world of education, and at all levels of the formal system (Stronge & Tucker, 2003). Demand for better data for the analysis of accountability, supervision and program evaluation among educators, has as a consequence of this, also risen significantly in recent years. Evidently, data-driven decision-making has recently become a mantra for school systems globally. Evaluation systems centered on accountability and data-driven schools more specifically, depend on valid and reliable assessment of the data in question. It is clear that data collection and analysis has become a requirement for most educators who are intent on registering career success. Data-driven decision-making in the school system will include benchmarking the performance of students, and further comparing the rates of success of adopted intervention programs. This will further provide a snapshot into the performance of students within given time periods and in turn will also direct focus on the effectiveness of formal education. For these reasons, data-driven decision-making is referred to as the status model. The model will serve core accountability purposes of informing teachers how much the students have grown between a given period using data collected (Sergiovanni, Starratt & Cho, 2014). On the other hand, growth model is effective since it provides additional information useful for evaluation purposes
In recent years, the drive for schools to enhance their learning outcomes has gained an increasing salience. According to Stronge & Tucker, (2003), schools have seen the need to make use of data to inform them of potential improvement strategies and further generate core information for accountability. Therefore, data-driven improvement and accountability have proven to be an effective strategy for teacher evaluation. To make educational accountability effective so as to contribute towards performance improvement, there is the need to develop a collaborative involvement with regards to data collection and analysis (Sergiovanni, Starratt & Cho, 2014). Furthermore, collective responsibility aimed at improving performance is critical. Failure to have these conditions in place will negatively affect potential improvement efforts in addition to the outcome-based accountability.
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Timely data is useful regarding providing feedback that will enable teachers and the entire school system to act appropriately and intervene where necessary in order to raise the school performance. Further, this will address all the potential problem areas enhancing the learning experience. The use of an accountable, data-driven approach will result in a systemic improvement. According to Stronge & Tucker, (2003), public accountability demands require a high level of transparency, and this is specifically so for better outcomes, and calls for relevant data. It is worth noting that data considered irrelevant will skew accountability focus, which undermines accountability credibility. On the other hand, good data will result in overall school improvement and accountability.
According to Sergiovanni, Starratt & Cho, (2014), school leaders have thus seen the need to generate good data to ensure that they arrive at an effective decision that will ensure an overall improvement in school. Valid data will have a positive effect on the school curriculum since the school leaders will be able to identify all areas of weaknesses and find a solution to improve the school performance.
In conclusion, data-driven improvement and accountability will enhance teacher evaluation, enhance quality and integrity. The use of multiple data sources has been shown to be an effective system of teacher evaluation which helps in the documentation of performance. Concerns have been raised focusing on the future of data driven and accountability in the evaluation of teachers. Schools and their management have seen the need to adopt and implement data driven and accountability strategies to ensure that they arrive at an informed decision that will result in improved school performance. Rich information is essential to ensure that education stakeholders make better decisions, provide important support to schools and students.
References
Sergiovanni, T. J., Starratt, R. J., & Cho, V., (2014). Supervision: A redefinition (9th ed.). New York, NY: McGraw-Hill.
Stronge, J. H., & Tucker, P. D. (2003). Handbook on teacher evaluation: Assessing and improving performance . Larchmont, NY: Eye on Education.