Postgraduate Course: Applied research design in data science for health and social care (HEIN11090)
Course Outline
| School | Deanery of Molecular, Genetic and Population Health Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course aims to provide students with an understanding of the principles of the research process, to equip students with the core skills needed to develop a dissertation-level research project, and to develop academic scientific writing skills essential to the development of a successful data science researcher.
The course is designed for students who already have a fundamental understanding of the research process and can critically appraise existing research. In the course, students will learn how to apply this knowledge to inform their own research process, and how to conduct an independent research project in data science. |
| Course description |
1) Academic description
This course introduces the dynamic process of research, research ethics and integrity, and best practice, providing a foundation for the dissertation component of the programme.
2) Outline Content
The course will introduce students to the process of identifying a research question, choosing a study design that helps answer that question, and then conducting a research project. Students will be introduced to the principles of open science, good data management, inclusive collaboration, etc. Moreover, 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 dissertation component of the programme.
3) Student Learning Experience
Students will learn from research experts. The course is delivered online. Teaching sessions will be composed of written materials and video presentations, accompanied by guided reading in the form of links to journal articles with problem-based learning questions.
Discussion of the content and reading materials will be posted to an online forum, along with students' answers to the problem-based learning questions. Course tutors will moderate discussion boards.
Formative peer and teacher-led feedback will be given throughout the course through the discussion boards, and summative assessment feedback will be provided at the end of the course.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | Students must have passed Foundations of Research Design in Data Science for Health and Social Care (HEIN11089) or equivalent |
| Additional Costs | Students will be responsible for their computer equipment and internet access. |
Information for Visiting Students
| Pre-requisites | None |
Course Delivery Information
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| Academic year 2024/25, Available to all students (SV1)
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Quota: None |
| Course Start |
Flexible |
| Course Start Date |
19/05/2025 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 5,
Seminar/Tutorial Hours 1,
Online Activities 35,
Feedback/Feedforward Hours 5,
Formative Assessment Hours 5,
Revision Session Hours 1,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
46 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Summative assessment for this course will consist of a written research proposal (covering LOs 1-4). Students will be guided through the process with specific questions to answer within the proposal, and will be offered support and formative feedback via the course discussion boards. This assessment will be due after the final teaching week of the course.
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| Feedback |
Feedback is information provided to the students about their learning relative to learning outcomes. The two main types of feedback are formative and summative. Formative feedback is generated to engage learners to constantly reflect on how they can approach, orient and evaluate learning, which leads to successful learning outcomes. Summative feedback provides an evaluation of how much a student has learned at the end of the course through a final assessment.
Formative feedback will be provided throughout the course, for example, during live question and answer sessions, quizzes, and discussion boards. A formative task will also be offered before the student submitting their summative assessed coursework. All summative assignments will be marked, and feedback provided within fifteen working days (where possible).
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| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Apply understanding of data science concepts to develop suitable study methodology, from details of study design through to statistical analysis
- Work autonomously by taking responsibility for identifying and researching a topic of their choice
- Critique their own learning and research planning processes, and be able to apply this to future research projects and enquiries
- Demonstrate the ability to effectively communicate research to relevant audiences.
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Reading List
Recommended, but not essential:
Book:
W.E. Martin and K.D. Bridgmon (2012) Quantitative and statistical research methods from hypothesis to results.
(An electronic copy of Martin and Bridgmon (2012) is available to download from the University of Edinburgh Library.)
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Additional Information
| Graduate Attributes and Skills |
1) 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 professional 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 professional, educational, geographical or cultural 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.
2) 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, discussion boards and collaborative activities to critically evaluate concepts, evidence and experiences of peers and superiors from an open-minded and reasoned perspective.
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 researchers require excellent oral and written communication, presentation and interpersonal skills. The structure of the interactive (problem-based learning examples, discussion boards and collaborative activities) and assessment elements incorporate constant reinforcement and development of these skills. |
| Special Arrangements |
This course will be taught online using the Learn virtual learning environment. All course materials are protected by secure username and password access. |
| Keywords | Research design,ethics,integrity and best practice,data handling and analysis,academic writing |
Contacts
| Course organiser | Dr Nazir Lone
Tel:
Email: nazir.lone@ed.ac.uk |
Course secretary | Mrs Laura Miller
Tel: (0131 6)51 5575
Email: Laura.Miller@ed.ac.uk |
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