SOCI8008 - Social Data Analysis

Module Details

Module Code: SOCI8008
Title: Social Data Analysis
Long Title: Social Data Analysis
NFQ Level: Advanced
Valid From: Semester 1 - 2024/25 ( September 2024 )
Duration: 1 Semester
Credits: 5
Field of Study: 3120 - Sociology
Module Delivered in: 1 programme(s)
Module Description: This module aims to teach and assist students to organise raw research data and analyze it using both quantitative and qualitative data analysis techniques. It is mostly beneficial to the writing process of a research dissertation.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Input data and conduct basic analysis to produce descriptive statistics, textual analysis or both depending on the research design.
LO2 Explore relationships between variables.
LO3 Reduce qualitative data: coding, thematic analysis, clusturing and partitioning.
LO4 Understand and present the strength and limitations of research conclusions and recommendations in the Social Sciences.
LO5 Use digital data analysis tools in Social Science.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).

11493 SOCI8002 Social Research Methods
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.

No requirements listed
 
Indicative Content
Transfer and input of Data
The transfer and input of data collected through research instrument in preparation for analysis.
Addressing of Research Questions
Use of design-appropriate analytical approaches.
Transforming Data
Reduce raw data to manageable data amenable to analysis. Coding methods and thematic analysis
Use of digital tools in Social Data Analysis
Identification and proficient use of appropriate digital tools is Social Research
Analysis and Interpretation
Link analysis to Social Research theoretical frameworks,positions, interpretation,conclusions and recommendations.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Presentation % of Total Mark 50
Timing Week 9 Learning Outcomes 3,4,5
Assessment Description
Coherent and logical presentation of findings related to the research questions. Link findings to reviewed literature and suggest conclusions.
Assessment Type Written Report % of Total Mark 50
Timing Sem End Learning Outcomes 1,2,3,5
Assessment Description
Reduction of data relevant to research questions and topic of dissertation,using different methods depending on the research design.
No End of Module Formal Examination
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Data analysis guided by research questions and research design Every Week 2.00 2
Lab Contact Data Inputting, Analysis and Interpretation Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Collection of Data, linking with thesis and interpretation Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Data analysis guided by research questions and research design Every Week 2.00 2
Lab Contact Data Inputting, Analysis and Interpretation Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Collection of Data, linking with thesis and interpretation Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Tom Clark,Liam Foster,Alan Bryman,Luke Sloan. (2021), Bryman's Social Research Methods, 6th. Oxford University Press, London, p.705, [ISBN: 9780198796053].
  • Tiffany Bergin. (2018), An Introduction to Data Analysis, SAGE Publications Limited, p.0, [ISBN: 9781446295144].
  • Andy Field. (2024), Discovering Statistics Using IBM SPSS Statistics, 6th. Sage Publications Limited, London, p.0, [ISBN: 9781529630008].
  • Aldrich, James O. & Rodriguez, Hilda M.. (2013), Building SPSS Graphs to Understand Data, SAGE, London, [ISBN: 978145221684].
  • Julie Pallant. (2020), SPSS Survival Manual, 7th. Open University Press, p.380, [ISBN: 9780335249497].
  • Judith Greene,Manuela D'Oliveira. (1999), Learning to Use Statistical Tests in Psychology, Taylor & Francis Group, p.248, [ISBN: 978-0335203772].
  • Dr Peter Allen, Kellie Bennett, Dr Brody Heritage. (2018), SPSS Statistics: A Practical Guide with Student Resource Access 12 Months, 4th Ed.. Cengage AU, p.352, [ISBN: 9780170421140].
  • Zina O'Leary. (2017), The Essential Guide to Doing Your Research Project, 3rd. SAGE, London, [ISBN: 9781473952089].
  • David Robert Thomas,Ian D Hodges. (2010), Designing and Managing Your Research Project, SAGE Publications, London, p.265, [ISBN: 9781848601932].
  • Harding, J.. (2019), Qualitative Data Analysis, 2nd. SAGE, London.
  • Janice D. Aurini,Melanie Heath,Stephanie Howells. (2016), 'How To' of Qualitative Research, SAGE, London, [ISBN: 9781446267097].
  • Johnny Saldana. (2016), The Coding Manual for Qualitative Researchers, 3rd. Sage Publications Limited, London, p.368, [ISBN: 9781473902497].
Supplementary Book Resources
  • Lyn Richards. (2014), Handling Qualitative Data, 3rd Ed.. SAGE Publications Limited, p.264, [ISBN: 9781446276068].
  • Silverman, David. (2015), Interpreting qualitative data, 5th. SAGE, London, [ISBN: 9781446295434].
  • Norman K. Denzin,Yvonna S. Lincoln. (1998), Collecting and Interpreting Qualitative Materials, SAGE Publications, Incorporated, p.476, [ISBN: 9780761914341].
  • Adrian Holliday. (2016), Doing & Writing Qualitative Research, Sage Publications Limited, London, p.216, [ISBN: 9781473953277].
This module does not have any article/paper resources
This module does not have any other resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_HSOCC_8 Bachelor of Arts (Honours) in Social Care Work 2 Elective