Analytics for the Classroom Teacher

Course
en
English
18 h
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Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 6 Sequences
  • Introductive Level

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Course details

Syllabus

Module 0 - Orientation
Familiarisation of participants with the course structure, policies and outline.

Module 1 - Introduction to educational data for supporting data-driven decision making in school education
This module will:

  • Introduce the concept of educational data
  • Discuss how educational data can be used to inform data-driven decision-making at various levels of school operations, strengthening school autonomy
  • Identify data literacy for teachers as a core competency for supporting not only school accountability and compliance to (national) regulatory standards, but also continuous school self-evaluation and improvement
  • Introduce the need for data analytics technologies for efficient and effective educational data-driven decision-making, and highlight learning analytics and teaching analytics, which will be further discussed in the course

Module 2 - Teaching analytics: Analyse your lesson plans to improve them
This module will:

  • Introduce the need to capture and document teaching designs using lesson plans
  • Define the concept of teaching analytics as a way to enable the analysis of a teaching design and reflection upon it
  • Present the current state-of-the-art in teaching analytics tools that can be used by classroom teachers
  • Demonstrate how to use teaching analytics tools to analyse a lesson plan

Module 3 - Learning analytics: Analyse the classroom delivery of your lesson plans and discover more about your students
This module will:

  • Discuss the concept of personalisation in 21st century school education and the need for generating, updating and maintaining accurate student profiles
  • Define the concept of learning analytics as the means for supporting personalised teaching and learning, through the measurement, collection, analysis and reporting of students’ educational data generated during the learning process
  • Present the current state-of-the-art in learning analytics methods and tools that can be used by classroom teachers
  • Demonstrate how to use learning analytics tools to analyse the classroom delivery of a lesson plan, identify individual student needs and better support the individual student

Module 4 - Teaching and learning analytics to support teacher inquiry
This module will:

  • Introduce the concept of reflective practice as an important instrument for practice-based professional development as well as organisational learning and improvement
  • Define the concept of teacher inquiry as a key method for data-driven reflection on-action, related to the process where teachers build useful knowledge about teaching and learning through the deliberate and systematic study of their own practice
  • Present indicative teaching and learning analytics tools that can support teacher inquiry
  • Demonstrate how to use teaching and learning analytics tools to reflect on your teaching practice.

Module 5 – Conclusion
This concluding module will allow participants to:

  • Finalise their assignments
  • Discuss their overall MOOC learning experience with their peers, and
  • Reflect on their learning experience by submitting a course review and feedback survey.

Prerequisite

None.

Instructors

Demetrios Sampson
Professor of Learning Technologies
Curtin University

Editor

Curtin University is the largest tertiary education institution in Western Australia. Its main campus is in Perth, Western Australia. Founded in 1966, it was first known as the Western Australian Institute of Technology (WAIT) and from 1986 as Curtin University of Technology before taking its current name in 2010. It is named after John Curtin, Prime Minister of Australia during the Second World War.

Platform

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