From Datafication to School Improvement: The Promise and Perils of Data-Driven Decision Making

From Datafication to School Improvement: The Promise and Perils of Data-Driven Decision Making

Hesham R.I. Badawy, Ahmed M. Alkaabi
Copyright: © 2023 |Pages: 25
DOI: 10.4018/978-1-6684-7818-9.ch015
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Abstract

This chapter examines datafication effects on educational practices. While the use of data and technology-enabled personalized learning environments increased accountability and guided educational practices and policies, it raised concerns about privacy, data quality, and potential misuse. Therefore, the reconfiguration of data use in schools involves data quality, collection, management, analysis, interpretation, visualization, integration, and literacy. Schools should make effective decisions and support student learning and educational improvement by taking a holistic and collaborative approach, involving all stakeholders and ensuring ethical and responsible use of data. The chapter makes recommendations for improving outcomes and developing a productive learning environment, including embracing a growth mindset, emphasizing student-centered decision making, fostering a culture of improvement, involving all stakeholders, using data to support learning and well-being, utilizing real-time data and feedback, leveraging technologies, and utilizing creative analysis techniques.
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The Datafication Of Education

The growing use of data in decision-making, also known as “datafication,” has become more significant in recent years, and the availability of data will continue to grow, making it critical for school leaders to develop strategies for using data in responsible and effective ways (Agerfalk & Galliers, 2016). There has been an advancing trend of datafication in education, where data is increasingly being used to inform decision-making in schools (Schwab & Parks, 2020). This trend has been motivated by a goal to improve student outcomes and boost accountability (Davies & Cuff, 2016) and by technological advancements and the accessibility of a wealth of data on student achievement, teacher effectiveness, and school operations (Chen & Bryer, 2016). The datafication of education has several implications for educational practices. One of the implications is personalized learning, where the use of data and technology in education has made it possible to create environments for personalized learning, where instructional practices are adapted to the unique requirements and skills of each student. A second implication is increased accountability, as the datafication of education has increased accountability, as data is used to evaluate teacher effectiveness and school performance (Chen & Bryer, 2016). A third implication is data-driven decision-making, where data is utilized to guide educational practices and policies.

The advantages and constraints of data-driven decision-making must be considered in education, as it can result in better student outcomes, according to Davies and Cuff (2016). The increased use of data in education has raised concerns about privacy, data quality, and the potential for data misuse (Agerfalk & Galliers, 2016; Grek & Hargreaves, 2013). Additionally, some researchers have argued that datafication can lead to an over-reliance on data at the expense of teacher expertise and judgment (Davies & Cuff, 2016). As Wilder (2019) highlighted, ensuring the ethical use of data in education is a major challenge. Furthermore, the quality and type of data available can limit the accuracy of decisions made based on that data (Mertler, 2021). The ongoing improvement process, rather than a static endpoint, should be the way quality is perceived, as stated by Musah and colleagues (2023).

Key Terms in this Chapter

Governance: The act or process of governing or overseeing the control and direction of something (such as a country or an organization).

Datafication: The transformation of social action into online quantified data, thus allowing for real-time tracking and predictive analysis.

School Improvement: A continuous process, centered on maximizing outcomes for all students, and sustaining this improvement over time. School improvement needs to 'touch every classroom', be the work of every teacher and impact every student.

Data-Driven Decision Making (DDDM): Is defined as using facts, metrics, and data to guide strategic business decisions that align with your goals, objectives, and initiatives.

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