EDM201: Analysing Research Data in Education

Module code: EDM201

Module provider: Institute of Education

Credits: 20

Level: Postgraduate Masters

When you'll be taught: Semester 2

Module convenor: Dr Anthony Zhang, email: anthony.zhang@reading.ac.uk

Module co-convenor: Dr David Dobraszczyk, email: d.dobraszczyk@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: Yes

Last updated: 17 June 2024

Overview

Module aims and purpose

The aim of the module is to provide students with practical knowledge to analyse data collected from Education-related research. It also aims to equip students with the knowledge and skills to understand and evaluate a variety of quantitative and qualitative data analysis methods and to independently carry out a small-scale empirical research study for their dissertation.

Module learning outcomes

By the end of the module, it is expected that students will be able to:

1. Apply appropriate data analysis methods to analyse research data in the field of Education
2. Report education research data in line with the latest APA guidance
3. Critically evaluate data analysis methods and their application in research studies in the field of Education

Module content

• Introduction to statistics
• Introduction to Statistical Package for the Social Sciences (SPSS)
• Descriptive statistics and test assumptions
• Correlation and regression
• Parametric and non-parametric tests for group comparisons
• Introduction to qualitative data analysis
• Questionnaires and interviews
• Observations
• Document analysis plus visual data
• Critical evaluation of analysis and presentation of data. Frameworks and models

Structure

Teaching and learning methods

The central content areas will be covered through lectures and presentations. Blackboard will be used to provide access to essential readings, screencasts, online self-study material, and other forms of blended learning.

Practical workshop sessions will focus on statistical analysis using SPSS, qualitative data analysis, and documentary analysis. Group activities will further collaborative learning and focus on using data analysis tools, and presenting results in text and graphically.

Study hours

At least 12 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Students will be given weekly data analysis tasks to complete. Formative feedback regarding these tasks will be given at the practical workshops.

Reassessment

Additional costs