EDF5771 Digital data in education
Faculty of Education
EDF5771 Digital data in education is a level 5, 6-credit-point, postgraduate unit from the Faculty of Education, offered in 2022 in Semester 1 at Clayton. It needs EDF5610 and EDF5611.
- Credit points
- 6
- Offered in 2022
- Semester 1
- Clayton
- Assessment
- No exam
- 2 tasks
- Workload
- 144 hours
- per semester
This is the 2022 handbook entry. See the 2027 entry.
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Requisites
Before EDF5771
Prerequisites
Pass these before you enrol.
After EDF5771
No unit lists EDF5771 as a prerequisite in the 2022 handbook.
Overview
This unit explores a range of theoretical and practical issues arising from the growing importance of data in education. The unit is designed regardless of your level of familiarity with the topic. Data is understood broadly and includes a variety of approaches based on quantification, prediction and automation (i.e. Artificial Intelligence and automated decision-making). In this sense, the unit is organised around types of data as ‘case studies’ and for each one it asks a number of critical and practical questions: why is this data being collected? By whom (or what) is it being collected and then analysed? What are its outputs? Who is supposed to benefit from these outputs? What pedagogical or administrative decisions can be automated as a result? How can a non-specialist educator enhance her/his professional practice by engaging with these data and the associated technologies?
Offerings in 2022
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | Flexible |
Assessment
- Supported reflection (2000 words or equivalent)50%
- Data profile (2000 words or equivalent)50%
Learning outcomes
When you finish this unit, you should be able to:
- 1
evaluate critically the strengths and weaknesses of data-based technologies (including AI and various types of automation) and their impact on your professional practice
- 2
engage with debates currently occurring at the intersection of academic research, education policy and industry
- 3
use conceptual and practical strategies to engage productively (as a non-expert) with data-based and automation technologies currently used in schools as well as those that are more accessible
- 4
be familiar with some essential concepts such as data representation and abstraction, as well as key principles of computation.
Workload and teaching
- Teaching approachActive learning
Minimum total expected workload equals 144 hours per semester comprising:
(a.) Contact hours for flexible students:
- 12 contact hours and 12 hours equivalent of online activities over the semester; or
- 24 hours equivalent of online activities over the semester*
(b.) Additional requirements (all students):
- independent study to meet the minimum required hours per semester.
*International students studying in Australia are not permitted to undertake this contact hour delivery mode.
For the unit teaching schedule, please visit the timetable.
You will be provided with the opportunity to engage with relevant literature and resources. Further, you will be encouraged to deepen your understanding of topic areas through collegial discussion and debate, and by participating in activities designed to extend your understanding.
Learning resources
Recommended resources
Please visit the unit Moodle site for further information.
Where it fits
EDF5771 is part of 1 area of study in the 2022 handbook.
Contacts
- Chief Examiners
- Dr Jo Blannin
- Unit Coordinators
- Dr Jo Blannin
Common questions
When is EDF5771 offered?
In 2022, EDF5771 runs in Semester 1 at Clayton.
How much work is EDF5771?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does EDF5771 have an exam?
No. EDF5771 has 2 assessment tasks and no exam.
Which majors and minors include EDF5771?
EDF5771 is part of Digital learning.