EEB504 Data-Informed Practice (8)

Abstract

This subject addresses the knowledge and skills required to engage with the policy and practice of data-informed practice. The subject will distinguish the approach as applied to education from its use in other fields highlighting the strengths, limitations and potential uses of the data available in educational contexts. Knowledge management, analytics, emergent feedback, the data-definition matrix, and data-based decision-making cycle will be defined and interrogated as a context for knowledge and skill-building in the ethical use of data to inform planning, instruction and learning. Key basic psychometric concepts and existing data repositories and approaches will be investigated using a problem-based approach focused on curriculum-based measurement. The critical role of information technology in the process of data-informed practice will also be examined. Assessment in the subject involves the analysis and resolution of problem-based case studies that provide an opportunity to apply the skills and knowledge learned in the modules of study. A background in measurement and statistics are not required to successfully complete this subject.

+ Subject Availability Modes and Location

Session 1
Distance	Canada Campus
Session 3
Distance	Canada Campus

Continuing students should consult the SAL for current offering details: EEB504
Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject information

Duration	Grading System	School:
One session	HD/FL	Ontario School of Education

Learning Outcomes

Upon successful completion of this subject, students should:
Upon successful completion of this subject, students should: - demonstrate an understanding of the difference between knowledge management, analytics and data-informed practice in education and its use in other fields; - recognise and understand the assumptions on which data-informed practice resides; - explain and apply the data-definition matrix including the distinction between proximal and distal data and low and high power interventions as the key elements of a schema for data-informed practice; - explain the concept of emergent feedback and the way it differs from formative and summative feedback; - explain and apply the concepts of effect, and effect size, triangulation and inference; - know, understand and apply basic principles of measurement required to engage with data-based decision-making processes; - understand the strengths and weaknesses in the design and use of existing data management tools; - understand the strengths and limitations of large-scale tests and how to use the data they provide; - recognise, understand and consider the ethical considerations associated with data-informed practice; - know, understand and apply the key elements in the cycle of data-informed planning and target setting; - analyse, resolve, and evaluate problem-based cases requiring data-informed practice for instructional decision-making in applied educational settings; and - understand the role of information technology in the management, analysis and reporting of data for informing practice.

Syllabus

The subject will cover the following topics:
- assumptions and research underpinning data-informed practice; - national and state policy drivers for data-informed practice; - knowledge management and analytics; - cross-field comparison of data-informed practice; - the data-definition matrix and its use; - measurement and evaluation concepts required for data-informed practice; - ethical considerations in the use of data-informed practice; - analysis of existing data sources including the alignment of those sources in the school planning process; - the cycle of data-informed practice and planning; - the analysis of data-informed practice case studies; - the data-driven professional; and - the role of technology in data-informed practice.

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