SPSS Computer Lab Tutor - Quantitative Data Analysis

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Faculty of Arts and Humanities

£13.44 hourly pay + £1.61 per hour holiday

Short term role

Geoffrey Manton

17 Jul 2024

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SPSS Computer Lab Tutor - Quantitative Data Analysis

Job Description

The current opportunity is available for current Manchester Met students, to apply you must be based in the UK for the duration of the role.

The role involves assisting in the delivery of the Q-Step summer research school which teaches sixth form/college students selected by the Nuffield Foundation and the University’s Widening Participation department. The research school runs over two weeks and is designed by the Manchester Q-Step centre.

Two roles are available and will involve supporting a lecturer to supervise and guide students who will carry out independent research in a dedicated on-campus study space with a team of other Year 12 First Generation students. You'll be involved in supporting students in gaining practical experience of working with quantitative data and carrying out research. This includes how to conduct data analysis in SPSS, do a literature review using peer reviewed articles and produce a poster of their results.

Dates: Monday 29 July to Thursday 15 August. The majority of the work will fall between Monday 5 August and Thursday 15 August with the week commencing Monday 29 July set aside for preparation/briefing time.

Hours: 4 days per week, 10:00am to 3:00pm with a lunch break in alignment with the teaching schedule.

Working pattern: Monday to Thursday both weeks.

Location: On campus work, Geoffrey Manton Building, Rosamond Street West, M15 6EB.

Person Specification

This role is only open to current Manchester Met Students who meet the following criteria -

We are looking for a motivated Manchester Met undergraduate student who has previous experience of working as a SPSS lab tutor. The role involves supporting and guiding sixth form/college students as part of a widening participation initiative aimed at improving access for those who are currently under-represented in Higher Education.

The ideal candidate must be available during the above dates and will have the following:

Essential:

Recently completed a BSc degree with a substantial quantitative research methods element in either Sociology and/or Criminology.
Practical experience of using SPSS software to conduct data analysis.
Previous teaching experience of supporting students to use SPSS software.
Knowledge and practical experience of univariate analysis (descriptive statistics, frequency tables) and bivariate analysis (cross tabulations and examining relationships between an independent and a dependent variable).
Knowledge and practical experience of other aspects of research including reviewing the academic literature, identifying research questions and writing up findings.
Good interpersonal and problem-solving skills.
Good organisation and time management.

Desirable:

An interest in widening participation and improving access to Higher Education
An interest in pursuing a career in education.
Is a First Generation student themselves.

How to Apply

Please apply via the Apply button, completing the form on the next page.

You will need to upload your CV as a .docx document to your 'My CVs' area before you apply to be able to include this in your application.

The deadline for applications is 11:59pm on Wednesday 17 July 2024.

Manchester Metropolitan University is committed to supporting the rights, responsibilities, dignity, health and wellbeing of staff and students through our commitment to equity, diversity and inclusion.

We are committed to providing accessible and inclusive recruitment. If you require or would benefit from support or reasonable adjustments throughout the recruitment process and in work, please contact us by e-mailing [email protected]. This information will only be used and shared with those who require it to implement any change(s) and only at the point this is required.

If you have any queries, or need any further information, please do not hesitate to contact us.

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