Undergraduate Course: Research Design and Reproducible Science Skills (BIME10079)
Course Outline
| School | Deanery of Biomedical Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 10 (Year 4 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course aims to provide students with an understanding of the principles of research design, to equip students with the core knowledge skills to approach research according to best research practice and to develop academic scientific writing skills essential to the development of a successful data science researcher or practitioner.
Through its focus on practical approaches, the course will prepare students to conduct their own well-designed reproducible projects with a strong data component. |
| Course description |
This course introduces the dynamic process of research, research ethics and integrity, and best practice providing a foundation for the research project component of the programme.
The course focuses on the skills needed to critically appraise published research and carry out original research. The course will first introduce the core principles and assumptions of research enquiry, methods, design, ethics, integrity and best practice. Next, the course will introduce research design, hypothesis or research question(s) formulation and testing, allowing students to develop a more critical understanding of different study designs and the type of research questions they can answer. The course will then cover writing a research protocol, identifying a research question, ethical considerations and project monitoring and evaluation. In later weeks, the course will introduce the problem statement, background research into the current understanding of the research question (literature review), generating a hypothesis or research question, gathering/creating data, data analysis, and presenting results. Finally, students will be introduced to academic writing, peer-review, referencing, and issues in scientific writing (plagiarism, authorship and reproducible research). This course will provide a strong foundation for the research project component of the programme.
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Course Delivery Information
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| Academic year 2024/25, Not available to visiting students (SS1)
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Quota: 30 |
| Course Start |
Full Year |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 20,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
166 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% ICA:
Group data project (50%) - Learning Outcomes 1, 2, 3
Critical appraisal essay (50%) - Learning Outcomes 1, 4
Group Project: Data storytelling is the skill of extracting insights from datasets and presenting them to an audience using narratives and visualisations. This course's practical assessment component will involve a data storytelling project in which students will work in groups to solve realworld problems across health and biomedical sciences. This assessment will be built iteratively throughout the course, with students adding new components each week. The submission will be in the form of a public GitHub repository with contributions from all group members, which will demonstrate their ability to produce reproducible outputs and communicate research to outside audiences.
Critical Appraisal Essay: The students will write a 2000-word essay to critically appraise a published paper related to data science in health and biomedical sciences. The essay will likely cover aspects of study design, the choice of datasets, data analysis, and data ethics. |
| Feedback |
Students will receive formative feedback on their work in the weekly seminars. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Demonstrate a critical understanding of research design, ethics and integrity and best practice in data science.
- Apply the most appropriate research design, ethical principles and best practices to plan a project that produces trustworthy, reliable, viable and reproducible research.
- Demonstrate the ability to effectively communicate research to relevant audiences.
- Critically appraise published literature on topics related to data science in health and biomedical sciences.
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Reading List
Recommended reading:
The Turing Way: A Handbook for Reproducible Data Science
(Version v0.0.4), by The Turing Way Community, Becky Arnold, Louise Bowler, Sarah Gibson, Patricia Herterich, Rosie Higman, ¿ Kirstie Whitaker. (2019, March 25).
Available freely at http://doi.org/10.5281/zenodo.3233986
A list of additional readings will be provided on the course virtual learning environment.
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Additional Information
| Graduate Attributes and Skills |
Mindsets:
Enquiry and lifelong learning
Students on this course will be encouraged to seek out ways to develop their research expertise. They will also be encouraged to strive for excellence in their practice and to use established and developed approaches to resolve research issues as they arise in their practice.
Aspiration and personal development
Students will be encouraged to draw on the quality, depth and breadth of their experiences to expand their potential and identify areas they wish to develop and grow. Students will also be encouraged to understand their responsibility and contribute positively, ethically and respectfully to the academic community while acknowledging that different students and community members will have other priorities and goals.
Outlook and engagement
Students will be expected to take responsibility for their learning. Students will be asked to use their initiative and experience, often explicitly relating to their disciplinary context, to engage with and enhance the learning of students from the diverse communities on the programme. Students will also be asked to reflect on the experience of their peers and identify opportunities to enhance their learning.
Skills:
Research and enquiry
Students will use self-reflection to seek out learning opportunities. Students will also use the newly acquired knowledge and critical assessment to identify and creatively tackle problems and assimilate the findings of primary research and peer knowledge in their arguments, discussions and assessments.
Personal and intellectual autonomy
Students will be encouraged to use their personal and intellectual autonomy to critically evaluate learning materials and exercises. Students will be supported through their active participation in self-directed learning and collaborative activities to critically evaluate concepts, evidence and experiences.
Personal effectiveness
Students will need to be effective and proactive learners that can articulate what they have learned and have an awareness of their strengths and limitations, and a commitment to learning and reflection to complete this course successfully.
Communication
Effective professionals require excellent oral and written communication, presentation and interpersonal skills. The structure of the interactive (problem-based learning examples, collaborative activities) and assessment elements incorporate constant reinforcement and development of these skills.
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| Keywords | Research design,Open Science,reproducibility |
Contacts
| Course organiser | Dr Kasia Banas
Tel:
Email: |
Course secretary | Mr Stewart Smith
Tel:
Email: |
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