Leading Whole School Improvement: SMART School Improvement

Problems, possibilities, and opportunities for implementing data literacy in entire
school environments include the fact that many schools need to recognize that data literacy is
a crucial skill for all students. Numerous schools are still focused on traditional areas of
expertise such as language, science, writing, and math, thus compromising data literacy
(Bernhardt, 2017). Additionally, the increased proliferation of digital technology has made it
difficult for teachers and administrators to stay up-to-date with all of the latest tools and
resources available for teaching data analysis and visualization (Enakrire, 2020). There is
often a high cost of implementation at the school level due to the sheer number of students
and staff necessitating outside intervention through grants and donations. Cybercrime is
increasingly entering the learning environment making child pornography, fraud, and privacy
issues a concern.
However, possibilities and opportunities exist in the form of providing data literacy
training for all school staff, from administrators to janitors. This would ensure that everyone
in the school environment is comfortable working with data and understanding its
implications. Additionally, many schools are now incorporating digital citizenship lessons
into their curriculum, which teaches students how to be safe and responsible online, and
students are using digital resources to optimize learning leading to whole-school
improvement (Kippers et al., 2018). As more and more people become data literate, the
opportunities for using data to improve teaching and learning will continue to increase.
Finally, governments and social stakeholder groups have embraced modern technologies like
cloud computing to reduce implementation costs, thus combining data literacy benefits with
modern learning.

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Significance of Data in Analyzing Problems, Possibilities, Constraints, and Affordances

for implementing Whole-school Improvement

Through data collection and analysis, data can help identify areas in need of
improvement, such as language skills among students and communication among staff. It also
helps keep track of progress over time as digital technologies are employed in monitoring
students and staff performance, analyzing it, and forecast trends or patterns that could be
detrimental to entire learning environments and processes. Data is also integral in machine
learning and artificial intelligence, which is becoming crucial in future learning and school
management as digital technology becomes part of human life through learning,
entertainment, business, security, and communication.
Data can inform decision-making about resource allocation through special software
used in school management aspects such as HRM, performance management, project
management, and even student performance analysis. Such detailed application of data
literacy in whole-school improvement also extends to providing digitally coded and
automated feedback to policy-making stakeholders such as local and Federal government
institutions in performance management and policy evaluation capacity (Enakrire, 2020).
National policy and legal frameworks rely on modern data systems, which in turn work
through data literacy at the school level.
The proliferation of data literacy in learning environments such as schools must be
monitored carefully because of the risks involved. Privacy issues emanate because of the
existence of children, while cybercrime aspects such as fraud and radicalization come into
play based on the interaction between students and instructors outside of the home
environment and away from parents. Additionally, there are issues such as the negative
influence of online games, media content such as pornography and violence, and disruption
of learning because of spending too much time on social media (Kippers et al., 2018).

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However, data literacy will continue complementing learning and providing potential
solutions to traditional problems, thus whole-school improvement.

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References

Bernhardt, V. L. (2017). Data analysis for continuous school improvement. Routledge.
Enakrire, R. T. (2020). Data literacy for teaching and learning in higher education
institutions. Library Hi Tech News, ahead-of-print(ahead-of-
print). https://doi.org/10.1108/lhtn-01-2020-0005
Kippers, W. B., Poortman, C. L., Schildkamp, K., & Visscher, A. J. (2018). Data literacy:
What do educators learn and struggle with during a data use intervention? Studies in
Educational Evaluation, 56, 21-31. https://doi.org/10.1016/j.stueduc.2017.11.001