BASS Philosophy and Data Analytics / Course details

Discover the art and science of qualitative research in this engaging and hands-on course unit. Designed for second-year criminology students, this unit introduces you to key methodologies and equips you with practical skills to design, conduct, and analyse qualitative research.

You will explore real-world research challenges, including ethics, research design, and researcher integrity, through fascinating case studies of well-known projects. You will learn and practice a variety of data collection techniques, such as interviewing (narrative and elicitation methods), ethnography (including covert, visual and online approaches), and analysing unsolicited data like social media posts, policy documents, and news articles.

Step into the shoes of a researcher by tackling ethical dilemmas in a role-play scenario and gain confidence in analysing qualitative data using thematic, content, discourse, and visual methods—with guidance on leveraging AI tools. By the end of the course, you’ll be ready to write up your findings and produce a compelling research proposal, setting the stage for your future independent research.

This unit blends theory with hands-on practice, preparing you to critically engage with qualitative methodologies and apply them in real-world settings. 

This course unit aims to equip second-year criminology students with a comprehensive understanding of qualitative research methods, emphasising both theoretical foundations and practical application. Students will critically engage with key methodological literature, exploring the ethical, epistemological, and theoretical challenges that qualitative researchers face. By examining exemplars of classic qualitative research projects, students will gain insight into the complexities of research design, researcher integrity, and the practical implications of their methodological choices.

The course also seeks to develop hands-on practical skills in a range of qualitative techniques. Students will explore diverse approaches to data collection, including soliciting narrative data (such as narrative and elicitation interviews, and diaries), ethnographic methods (such as observation, visual, covert, and netnography), and the use of unsolicited data from social media, discussion forums, letters, news, and policy documents.

Through interactive activities, such as role-playing an ethics committee review, students will confront real-world ethical challenges and refine their research proposals. They will also build analytical expertise, including thematic analysis, discourse analysis, and the analysis of visual data, while critically engaging with emerging tools like AI.

Finally, students will develop the skills to produce a well-structured research proposal and effectively write up qualitative research, preparing them for advanced independent research projects.

Syllabus (indicative curriculum content):

Week 1: Four exemplars of well-known qualitative research projects, each illustrating issues that qualitative researchers face. These include: ethics, theoretical and epistemological issues, research design, and researcher integrity. 
Week 2: Soliciting narrative data: interviews and diaries, and approaches to interviewing people (narrative, elicitation techniques)
Week 3: Ethnography (approaches to observation: visual, covert, netnography) 
Week 4: Unsolicited user-generated data: discussion forums and social media
Week 5: Unsolicited data: letters, news, policy documents, parliamentary debates
Week 6: Ethics & design. Students face an ethics committee in a role play scenario, and must respond to the committee.
Week 7: Analysis 1: thematic analysis of text-based data; qualitative data analysis software; using AI to help
Week 8: Analysis 2: content and discourse analytic approaches
Week 9: Analysis 3: visual data
Week 10: Writing your research proposal, and writing up the results of qualitative research.

This course unit is designed to enhance students' academic, professional, and personal development by equipping them with advanced qualitative research skills and transferable competencies that are highly valued in criminology and beyond. The intended learning outcomes directly support the following student outcomes and employability skills:

1. Advanced Research and Analytical Skills
Students will develop the ability to design, conduct, and analyse qualitative research, preparing them for roles that require strong research skills, such as social research, policy analysis, market research, or academic research. Development of a broad range of traditional and innovative techniques like interviewing, ethnography, and thematic analysis enhancing their capacity to gather and interpret complex data, a valuable skill for employers across sectors.

2. Critical Thinking and Problem-Solving
By engaging with ethical dilemmas, epistemological debates, and methodological challenges, students will strengthen their critical thinking and decision-making skills. These abilities are transferable to roles requiring independent judgment and strategic problem-solving.

3. Professional Communication Skills
The emphasis on writing a research proposal and reporting findings will develop students’ ability to communicate complex ideas clearly and persuasively. This skill is crucial for producing high-quality reports, grant applications, and presentations in professional and academic settings.

4. Digital and Technological Literacy
Students will engage with emerging tools, such as AI for data analysis, fostering digital literacy and adaptability. These skills are increasingly essential in data-driven industries, such as social media analysis.

5. Ethical Awareness and Integrity
Role-playing an ethics committee scenario and addressing ethical challenges will cultivate a strong sense of responsibility and integrity. These qualities are particularly important for roles in public service, non-profits, and any sector involving human-centred work.

6. Project Management and Organisational Skills
The requirement to devise a research proposal and prepare for an unseen exam will enhance students’ ability to manage long-term projects and perform under pressure. These skills are directly applicable to roles that require multitasking, meeting deadlines, and effective time management.

7. Adaptability and Resilience
The blend of practical tasks, theoretical engagement, and exam assessment will foster adaptability, resilience, and the ability to think on one’s feet—qualities that are valuable in dynamic and fast-paced work environments.

By the end of the course, students will be well-equipped with the intellectual, practical, and interpersonal skills needed to succeed in research, policy, and a wide range of professional roles. These outcomes will also provide a strong foundation for postgraduate study or independent research projects, including their third-year dissertation.

Teaching will take place in a 3 hour workshop each week. The precise structure and format of the workshops will vary week by week.

Each week will involve some lecture style content, and much hands-on practice-based learning and skills acquisition. This will include small group work, role-play, and independent work. Students will be asked to bring a laptop to class so that some computer-based exercises can be completed in the relevant weeks. Students who do not have access to a laptop can work in pairs or groups or borrow one from the lecturers for the duration of the class.

In most weeks, students will be required to complete compulsory reading and exercises in preparation for workshops.

This course unit is specifically designed to support the development of students’ digital literacy by integrating the use of digital tools and technologies into key aspects of teaching, learning, and assessment. These skills are embedded in the intended learning outcomes and are developed through practical activities, critical engagement with digital data, and exposure to emerging technologies.

1. Use of AI in Qualitative Analysis
● Students will explore the role of AI in qualitative data analysis, such as assisting with thematic or discourse analysis. This hands-on experience will help students critically assess the benefits and limitations of AI in research, preparing them for data-driven industries where such technologies are increasingly used.
● The intended learning outcomes reflect this by emphasising the ability to engage with and apply digital tools to support analysis.

2. Working with Digital Data
● Students will learn to collect and analyse unsolicited user-generated data from online platforms, such as social media, discussion forums, and digital archives (e.g., news and policy documents). This involves learning how to navigate, extract, and critically evaluate digital data sources.
● These activities align with the learning outcomes related to practical research skills and demonstrate the application of digital methods to contemporary qualitative research challenges.

3. Engaging with Visual and Multimedia Data
● The course incorporates the analysis of visual data, requiring students to use digital tools to interpret and present such materials effectively. This enhances their ability to work with multimedia content, a skill increasingly relevant in digital marketing, media analysis, and online content creation.
● This is reflected in the intended learning outcomes under practical skills and transferable skills, where students develop the capacity to analyse diverse forms of data.

4. Digital Ethics and Responsibility
● Students will engage in ethical discussions about working with digital data, such as privacy concerns when analysing data from social media or forums. This not only enhances their understanding of digital ethics but also prepares them for responsible digital practice in professional settings.
● This is supported by intended learning outcomes related to ethics and critical thinking about methodological choices.

5. Supporting Students’ Digital Skills Development
● During the course, students will have opportunities to engage with qualitative data analysis software (e.g., NVivo or similar tools) and familiarise themselves with digital workflows for organising and coding qualitative data.
● Workshops and guided activities will ensure that students develop confidence in using these tools, further enhancing their employability.

6. Transferable Digital Skills
● By incorporating digital methods into the research proposal and role-play assessment tasks, the course ensures students can apply their digital skills in real-world research scenarios. These skills are directly transferable to roles in data analysis, digital research, and related fields.

By embedding digital literacy throughout the teaching and learning activities, students will leave the course with the ability to confidently navigate and critically engage with digital tools and technologies. This not only supports their academic development but also enhances their employability in today’s increasingly digital workplace.
 

• Research Proposal - 1500 word assessment (worth 50%);
• Written unseen exam, in person, MCQ and short answer questions - 1.5 hours (worth 50%);

This unit is only available to the following degree programmes:

• BA Criminology:
• BA Criminology with International Study;
• BA Social Sciences;