2021/22 Taught Postgraduate Module Catalogue

EDUC5268M Researching Digital Education (Examination)

30 creditsClass Size: 30

Module manager: TBC
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Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2021/22

This module is not approved as an Elective

Module summary

In this module you will explore the growing importance of data and digital information in education. You will have an opportunity to appreciate the theoretical, ethical and practical implications of data collection and analysis. You will engage with current, important debates about the relationship between data, knowledge and truth - in broader society and in education. The module will provide you with an awareness of basic quantitative methods, and you will examine concrete examples of how data can be collected and analysed in digital and traditional educational settings. You will be taught together with students taking EDUC5266M Designing Digital Education but instead of the coursework assignment will sit a formal written examination. This module is an option for students in countries where distance learning qualifications can be recognised only if formal written examinations are included in the assessment.

Objectives

This module takes inspiration from the latest methodological debates and trends in the social sciences. Students will examine the theoretical and methodological implications (and tensions) of the increasing pervasiveness of everything “digital”. They will explore practical examples of collecting, analysing and making sense of digital information and data. These examples will focus on online provision (blended or fully online), and teachers in traditional classrooms gathering and decoding various forms of digital data.

Learning outcomes
- Understanding the renewed importance of basic methodological skills in educational research/practice in the digital age.
- Examining the epistemological and truth-related ramifications of digital data and algorithms – this will include some references to the the so-called "post-truth" debate in new media research and political science.
- Examining two particular methodological approaches to digital research in two professional contexts (online provision and classroom-based).

Skills outcomes
- Recognising and solving data-related problems in educational practice;
- practical skills for the synthesis and analysis of digital information;
- developing basic data visualisations.

Syllabus

1. Introduction to the module: making sense of digital information and data. Why is it important in general? What does it mean for educational research and practice?

2. The intersection between methods, governance and data: how data is increasingly used to make important decisions in society and education.

3. Knowledge, truth and data in education: who and what to trust? What happens to knowledge and information when they are digitised? Discussion about replicability, quantification, standardisation, prediction and manipulation.

4. Algorithms explained: what are they? What do they do? How do they operate mathematically? How do they create “new” knowledge about the social world?

5. The importance of positionality: where does the researcher stand? Reflexivity, voice and how to acknowledge and moderate personal and cultural bias. This unit will show how these challenges apply as much to quantitative research as they do to qualitative one.

6. Methodological skills: the basics. This unit will cover topics such as populations, samples and simple statistical models – students will be redirected to other resources if they express an interest in quantitative methods. .

7. Collecting and analysing learner data in a digital learning course (part 1): What to collect? How to perform the analyses? Using simple surveys on their own or in conjunction with “trail” data.

8. Collecting and analysing learner data in a digital learning course (part 2): analysing conversations or content analysis in online forums.

9. Visualising data: using freely available online tools to represent information. Students will be invited to consider pros and cons of these tools (e.g. synthesis vs trivialisation).

10. Learner data in physical settings: real-time collection using mobile devices or other tools; overt and covert data collection; the pitfalls of surveillance.

11. The ethics of data in education: dilemmas, dos and don’ts, involving users to foster data literacy and data co-ownership.

12. Towards the examination.

Teaching methods

Delivery type	Number	Length hours	Student hours
e-Lecture	12	1.00	12.00
Group learning	12	3.00	36.00
Seminar	12	1.50	18.00
Tutorial	2	0.50	1.00
Independent online learning hours			113.00
Private study hours			120.00
Total Contact hours			67.00
Total hours (100hr per 10 credits)			300.00

Private study

Students will be provided each week with online ‘lectures’ in written and audio formats together with supplementary readings, material, tasks and activities. Students will also be expected to undertake directed reading of academic papers; to post reviews of these papers on an online discussion forum and to respond to reviews that other students have written.

Opportunities for Formative Feedback

Each participant will be expected to make a contribution of between 500-1000 words per unit, about a specific topic, in the asynchronous discussion or equivalent. Each person will be expected to contribute to (and occasionally facilitate) the weekly synchronous online seminar. Each student will have two individual tutorials to discuss progress.

Methods of assessment

Exams

Exam type	Exam duration	% of formal assessment
Standard exam (closed essays, MCQs etc) (S1)	3 hr 00 mins	100.00
Total percentage (Assessment Exams)		100.00

Students may sit the examination either in Leeds or at British Council offices in their home countries. Students choosing the British Council option will be required to pay the appropriate fee on the day of the examination.

Reading list

The reading list is available from the Library website

Last updated: 30/06/2021 12:18:04

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