Postgraduate Course: Foundations of research design in data science for health and social care (HEIN11089)

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 research design, to equip students with the core 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. The course is ideal for students from health, social and care services or computational backgrounds who want to know more about data science research in health, social, and care service contexts. The course makes no assumptions about students' previous research experience. However, basic knowledge of data science, health and social care organisation and delivery, statistics and data handling and analysis with R will be required.
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 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. 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.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites		Co-requisites
Prohibited Combinations		Other requirements	Students must have passed Introduction to Data Science for Health and Social Care (HEIN11037) or equivalent
Additional Costs	Students will be responsible for their computer equipment and internet access.

Information for Visiting Students
Pre-requisites	None
High Demand Course?	Yes

Course Delivery Information

Academic year 2024/25, Available to all students (SV1)		Quota: None
Course Start	Flexible
Course Start Date	16/09/2024
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 )
Assessment (Further Info)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 % Summative assessment for this course will consist of a written paper providing critical appraisal of a relevant published paper (covering LOs 1-3). Students will be guided through the process with specific questions to answer within the paper, and will be recommended to use a critical appraisal checklist (e.g. CASP). This assessment will be after the final teaching week of the course.
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).
No Exam Information

Academic year 2024/25, Available to all students (SV2)		Quota: None
Course Start	Flexible
Course Start Date	07/04/2025
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 )
Assessment (Further Info)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 % Summative assessment for this course will consist of a written paper providing critical appraisal of a relevant published paper (covering LOs 1-3). Students will be guided through the process with specific questions to answer within the paper, and will be recommended to use a critical appraisal checklist (e.g. CASP). This assessment will be after the final teaching week of the course.
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).
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. Demonstrate the ability to effectively communicate research to relevant audiences. Critically appraise published literature in topics related to data science in health and social care.

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.)

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,academic writing

Contacts
Course organiser	Dr Nazir Lone Tel: Email: nazir.lone@ed.ac.uk	Course secretary	Ms Rebecca Sewell Tel: (0131 6)51 7112 Email: Rebecca.Sewell@ed.ac.uk