Core Module Information
Module title: Understanding and Executing Quantitative Research

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: SSC11119
Module leader: Roberto Kulpa
School School of Applied Sciences
Subject area group: Social Science
Prerequisites

There are no pre-requisites for this module to be added

Description of module content:

The module introduces you to key elements of the quantitative methodologies. It provides you with an applied understanding of how quantitative research and data function in the real-world, across private, public and business facing organisations. The module is structured into two interlinking parts. In the 1st part you will acquire a working knowledge and understanding of quantitative research, while in the 2nd part you will apply skills of quantitative data collection and analysis using appropriate tools.

The first part will focus on:
• Theoretical and epistemological bases for using numbers in social research, and the premise of where, how, and why to use quantitative data for the understanding of social policy and contemporary issues.
• Benefits and pitfalls of using statistical tools to inform social policy and impact initiatives in: the third sector, public administration, art and culture, academic and research, and business sectors.
• Critical engagement with the application, interpretation, (mis)representation and ethical use of quantitative evidence across private and public sectors, and popular culture.
• The role of ‘Big Data’ and ‘data surveillance’ in the contemporary world and their associated strengths and weaknesses.

The second part will consist of:
• A focus on surveys as the most popular quantitative method in social research (including, for example developing valid and reliable survey questions, piloting, managing non-response rate, engagement, administration).
• Sampling and the logic of ‘sample representation’ of general populations, the challenges of sampling, sampling frames, etc.
• Basic functionality of relevant statistical software (e.g. SPSS or similar) used for generating and analysing quantitative data.
• Key concepts, analytical strategies, and visualisation techniques such as: commonly used techniques for summarising data, and consideration of ‘typical’ and ‘outlier’ data/cases; tables and graphs; variables, mean, medians, value; cross-tabulation, single & bi-variate analysis.
• Exploring the relationships between variables: deciding if measures are linked and how (correlation or causation), introducing elaboration techniques, and measures of association (e.g. the Chi-square and Cramer’s V).

Learning Outcomes for module:

On completion of this module, you will be able to:
1. Understand and evaluate the links between theory and methodology, incl. benefits and limitations of quantitative evidence.
2. Demonstrate the ability to construct a valid and reliable research tool to produce quantitative data.
3. Use and perform basic operations with relevant statistical and online survey software to execute collection and interpretation of data.
4. Critically reflect on the uses and applications of data science, incl. ethical implications when using statistical evidence, or when doing quantitative research.

Full Details of Teaching and Assessment
2022/3, Trimester 1, FACE-TO-FACE,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: FACE-TO-FACE
Location of delivery: SIGHTHILL
Partner:
Member of staff responsible for delivering module: Roberto Kulpa
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
Teaching and leaning on the Understanding and Executing Quantitative Research module develops across several modalities and channels of delivery:
• through the regular weekly workshops, scheduled guest sessions, periodic programme-exclusive events,
• delivered on campus, online, through fieldwork and external visits,
• enhanced through individual, personalised tutoring and mentorship activities,
• regularly revised via formative feedback, self-evaluation exercises, and diverse assessment strategies enhancing and mobilising further learning.

We will make use of weekly 3h timeslots to deliver workshops that are creatively tailored to the applied and participatory nature of this module, responding to the group needs and (possibly diverse) level of research experience among students. Each workshop will have tutor’s and students’ input delivered in various formats, for instance: pre-recorded lecture or a mix of pre-recorded and in-class shorter presentations; student presentations; pair and small group discussions, all-class forum debates; problem-solving practical tasks and activities; computer lab work; 1-on-1 student-tutor time, peer-learning exercises. We will also use blended learning technologies in response to your needs, and diverse and applied nature of learned and practised content. We envisage making use of pre-recorded lectures; live, online meetings using WebEx, interactive VLE (Virtual Learning Environment) technologies such as Moodle quizzes, peer review and feedback workshops, online annotation and commentary tools on e-book platforms (Kortext or similar). We will also use computer labs to work with professional surveying/statistical software.

In particular, on this module:
• Lectures and in-class discussions will help you advance the understanding of the complex links between theory and methodology of quantitative research (LO1), and with critically reflecting on the uses and applications of data science (LO4).
• Practical tasks and small group exercises, incl. guided activities in the computer lab, will stimulate your imagination and creativity to demonstrate your ability to construct quantitative research tools and perform operations with the relevant software (LO2,3).
• Guided self-study and individual scholarship time that you dedicate to learning on this module, will form a core of your learning, supporting your achievement of module’s aims and objectives (LO1,2,3,4).


Formative Assessment:
Core formative feedback will happen in-class during the workshops. In each workshop session we practice critical capacities and skills of the applied work with/on quantitative data. You will receive feedback on your individual and small group work, ensuring tailored commentary to support your growth.
You will also learn from peer-feedback, when you will be asked to review and check other students work and explain your rationale.
This peer-review exercise is also a formative preparation for the Evaluation and Impact module, where you will learn professional evaluation strategies, consistently building cross-module feedback structure on our programme.


Summative Assessment:
You will submit Portfolio (100% weight of the final mark), in which you will include at minimum two outputs:
• 50% - Research Tool (corresponding to assessed LOs: 2,3).
• 50% - Critical Annotation and Reflection on the research tool (corresponding to assessed LOs: 1,4) (indicative word length: 1,000).
Length and format will be specified by and agreed with the ML, corresponding to format and specific choices & requirements of the chosen research tool and researched topic. Please note: it is not possible to specify the exact (or even indicative) word length, as the assessment asks for the research tool that is not word counted.

You will collect a portfolio evidencing designed, created and executed a research tool (LO2) using suitable techniques, tools, pre-existing/dummy datasets and software. You will present the output generated by the tool in a suitable format, evidencing your ability to perform quantitative research (LO3). Having executed the applied part, you will write a critical annotation on the tool, incl. self-reflection on the process, evidencing your critical understanding of quantitative research principles (LO1,4).


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Face To Face Practical classes and workshops 36
Independent Learning Groupwork (Independent Study) 24
Independent Learning Guided independent study 140
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Portfolio 100 1,2,3,4 12 , WORDS= 1000
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100
2022/3, Trimester 1, FACE-TO-FACE,
VIEW FULL DETAILS
Occurrence: 002
Primary mode of delivery: FACE-TO-FACE
Location of delivery: SIGHTHILL
Partner:
Member of staff responsible for delivering module: Roberto Kulpa
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
Teaching and leaning on the Understanding and Executing Quantitative Research module develops across several modalities and channels of delivery:
• through the regular weekly workshops, scheduled guest sessions, periodic programme-exclusive events,
• delivered on campus, online, through fieldwork and external visits,
• enhanced through individual, personalised tutoring and mentorship activities,
• regularly revised via formative feedback, self-evaluation exercises, and diverse assessment strategies enhancing and mobilising further learning.

We will make use of weekly 3h timeslots to deliver workshops that are creatively tailored to the applied and participatory nature of this module, responding to the group needs and (possibly diverse) level of research experience among students. Each workshop will have tutor’s and students’ input delivered in various formats, for instance: pre-recorded lecture or a mix of pre-recorded and in-class input; student presentations; pair and small group discussions, all-class forum debates; problem-solving practical tasks and activities; computer lab work; 1-on-1 student-tutor time, peer-learning exercises. We will also use various learning technologies, on top of regular in-person teaching, in response to your needs, and diverse and applied nature of learned and practised content. We envisage making use of pre-recorded lectures; live, online meetings using WebEx, interactive VLE (Virtual Learning Environment) technologies such as Moodle quizzes, peer review and feedback workshops, online annotation and commentary tools on e-book platforms (Kortext or similar). We will also use computer labs to work with professional surveying/statistical software.

In particular, on this module:
• Lectures and in-class discussions will help you advance the understanding of the complex links between theory and methodology of quantitative research (LO1), and with critically reflecting on the uses and applications of data science (LO4).
• Practical tasks and small group exercises, incl. guided activities in the computer lab, will stimulate your imagination and creativity to demonstrate your ability to construct quantitative research tools and perform operations with the relevant software (LO2,3).
• Guided self-study and individual scholarship time that you dedicate to learning on this module, will form a core of your learning, supporting your achievement of module’s aims and objectives (LO1,2,3,4).


Formative Assessment:
Core formative feedback will happen in-class during the workshops. In each workshop session we practice critical capacities and skills of the applied work with/on quantitative data. You will receive feedback on your individual and small group work, ensuring tailored commentary to support your growth.
You will also learn from peer-feedback, when you will be asked to review and check other students work and explain your rationale.
This peer-review exercise is also a formative preparation for the Evaluation and Impact module, where you will learn professional evaluation strategies, consistently building cross-module feedback structure on our programme.


Summative Assessment:
You will submit Portfolio (100% weight of the final mark), in which you will include at minimum two outputs:
• 50% - Research Tool (corresponding to assessed LOs: 2,3).
• 50% - Critical Annotation and Reflection on the research tool (corresponding to assessed LOs: 1,4) (indicative word length: 1000).
Length and format will be specified by and agreed with the ML, corresponding to the format and specific choices & requirements of the chosen research tool. Please note: it is not possible to specify the exact (or even indicative) word length, as the assessment asks for the research tool that is not word counted.

You will collect a portfolio evidencing designed, created and executed a research tool (LO2) using suitable techniques, tools, pre-existing/dummy datasets and software. You will present the output generated by the tool in a suitable format, evidencing your ability to perform quantitative research (LO3). Having executed the applied part, you will write a critical annotation on the tool, incl. self-reflection on the process, evidencing your critical understanding of quantitative research principles (LO1,4).


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Face To Face Practical classes and workshops 36
Independent Learning Groupwork (Independent Study) 24
Independent Learning Guided independent study 140
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Portfolio 100 1,2,3,4 12
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader