RSCH09038 2019 Data Science Research Thesis
The research project will allow the learner to investigate an area relevant to Data Science, integrating knowledge skills and competencies acquired at earlier stages of the Master’s programme, to research an area deemed appropriate by an academic supervisor. Learners will examine and define the issues/research problem, develop a research proposal, select and execute appropriate methodologies, analyse data, evaluate findings critically and draw justifiable conclusions, demonstrating self-direction and originality of thought. The consideration of ethical issues will be integral to this process, as these may arise at all stages. The learner will be allocated a supervisor who will advise on the direction of the work. Regular meetings with their supervisor will engage the student in discussion, which will deepen their learning and motivation. These meetings will help the student to maintain focus and challenge them on hypothesis and approaches to their experimental design and implementation. Throughout the period of research, the learner is encouraged to network with other researchers in academia and industry/sector (where an Industry link/project occurs) and to disseminate their research findings in oral and written format to both academic and professional audiences. Critical thinking skills will be developed through analysis of research data and the presentation of research outcomes in the format of thesis and a viva voce.
On completion of this module the learner will/should be able to;
Manage an independent research project with a support structure in place for supervision.
Source and critically evaluate academic literature (and literature from other appropriate sources), draw inferences from this body of knowledge, and conduct an extensive literature review.
Develop and justify a coherent research proposal with an acceptable research question or hypothesis to further knowledge and understanding of a Data Science problem.
Develop and execute a research strategy, design and project plan, incorporating consideration of research and technical ethics.
Select, apply and critically evaluate research methods and techniques, and analyse data according to accepted models of analysis.
Communicate the research process and findings via a written thesis, which meets postgraduate standards of technical expertise.
Reflect self‑critically and express the relevance and significance of the outcomes/conclusions of an inquiry and of the research process itself.
Demonstrate professional practice skills including research integrity, time-management, technical writing and oral communication skills.
Teaching and Learning Strategies
The thesis is an independent research project that will involve self‑directed learning in a core topic related to the programme. Students will avail of one to one supervision with a designated supervisor. This is a learner-centred approach where the learner assumes responsibility for learning. Regular meetings with their supervisor will engage the student in discussion which will deepen their learning and motivation. Critical thinking skills will be developed through analysis of research data and the presentation of research outcomes in the format of thesis, presentation and viva.
At the end of semesters 3 and 4, the student will submit a paper on their progress to date and present their work to their peers and other academic staff in the Institute ( and any other relevant stakeholders) in order to demonstrate and critically reflect on their progress and to receive feedback, insights and guidance.
As applications might raise challenging legal and ethical issues, it is essential that students are aware of the need for critical reflection on solutions, including how emerging ethical, legal or research reliability/validity issues could be articulated and dealt with. These interim presentations offer opportunities for projects to be critically scrutinised, and feedback given to ensure that ethical issues are fully considered. In addition, project proposals will also be submitted to the IT Sligo research ethics committee for clearance.
To undertake the research project successfully, students must fully engage with their research supervisor and manage their time effectively to ensure completion of their project work.
The student will complete the research thesis over 3 semesters, meeting with their supervisor for one hour each week during these 3 semesters.
Module Assessment Strategies
Assessment of this module will be based on:
- Thesis composed of a critical literature review of the research topic along with research paper drafted in a format adhering to Peer-review journal standards.
- Viva voce
- At the end of the first and second semesters of the project, students will submit a progress paper and present their projects to their peers, academic staff and other relevant stakeholders. These will serve as significant milestones for the students and enable critical reflection and feedback on their progress to date. It will also serve as an opportunity to ensure that projects are subject to critical scrutiny to identify any (possibly unforeseen) ethical or legal issues with the work.
Where a learner fails this module the Examiners will identify where the deficits in learning occurred. The learner will then have an opportunity to address these deficits and resubmit the project for a full re-examination, the next time this module is examined.
LO1: Manage an independent research project with a support structure in place for supervision.
This module is undertaken by learners over 3 semesters. The master’s thesis should focus on a data science problem and on applying the knowledge the student has learned during the MSc courses to solve that problem. Thesis topic and content will be negotiated with the supervisor, and refined throughout the course of the thesis.
LO2: Source and critically evaluate academic literature (and literature from other appropriate sources), draw inferences from this body of knowledge, and conduct an extensive literature review.
Students are expected to critically review key literature relevant to their chosen research area.
LO3: Develop and justify a coherent research proposal with an acceptable research question or hypothesis to further knowledge and understanding of a Data Science problem.
Students will formulate a research question/hypotheses/research objectives appropriate to their chosen problem area.
LO4: Develop and execute a research strategy, design and project plan, incorporating consideration of research and technical ethics, where appropriate.
Students will formulate a research strategy, design and plan appropriate to the question they have chosen, to be submitted to the supervisor. Ethical and legal issues relating to data collection and integration should be identified and addressed at this stage.
Learners will be expected to explore ethical dilemmas relevant to their proposed research topic, in doing so they are expected to develop appropriate strategies and documentation to deal with potential ethical dilemmas. Interim presentations will serve to enable scrutiny of the project by peers, academic staff and other possible stakeholders to identify any potential legal or ethical implications of the work.
The research study must also adhere to IT Sligo's Research Ethics Policy and Procedure. Where appropriate, project proposals will be submitted to the IT Sligo research ethics committee for clearance.
LO5: Select, apply and critically evaluate research methods and techniques, and analyse data according to accepted models of analysis.
Learners are required to demonstrate their ability in research, designing and executing experiments/numerical analysis/ analytical analysis, concept development and reporting in a manner appropriate to their chosen research question.
LO6: Communicate the research process and findings via a written thesis, which meets postgraduate standards of technical expertise.
The thesis should contain a
- Definition of the research questions and account of research design.
- Review of the relevant literature
- Theoretical, constructive or empirical parts developing answers to the research questions.
LO7: Reflect self‑critically and express the relevance and significance of the outcomes/conclusions of an inquiry and of the research process itself.
The student must demonstrate their ability to gather, generate and analyse data that leads to appropriate recommendations and conclusions.
Students will provide a detailed critique on their research question, process, outcomes and conclusion, as appropriate. Recommendations for outstanding questions/further research should be given.
LO8: Demonstrate professional practice skills including time-management, technical writing and oral communication skills.
Students completed work will demonstrate the knowledge, skills and competency that are required for a level nine award in this area. It will be presented and published in a manner appropriate to this award level e.g. typed, bound.
Coursework & Assessment Breakdown
|Title||Type||Form||Percent||Week||Learning Outcomes Assessed|
|1||Thesis||Project||Individual Project||60 %||End of Term||1,2,3,4,5,6,7,8|
|2||Viva Voce||Project||Individual Project||20 %||End of Term||1,2,3,4,5,6,7,8|
|3||Presentation of Work Completed||Project||Individual Project||10 %||Week 15||1,2,5,7|
|4||Interim Presentation and Paper 1||Continuous Assessment||Written Report||5 %||End of Semester||1,2,3,4,5,6,7,8|
|5||Interim Presentation and Paper 2||Continuous Assessment||Written Report||5 %||End of Semester||1,2,3,4,5,6,7,8|
Online Learning Mode Workload
|Directed Learning||Not Specified||Project Supervision||1||Weekly||1.00|
Required & Recommended Book List
2011-03-01 Succeeding With Your Master'S Dissertation: A Step-By-Step Handbook McGraw-Hill International
ISBN 9780335242252 ISBN-13 0335242251
Annotation This new edition of 'Succeeding with Your Master's Dissertation' continues to demystify the dissertation writing process. Taking a step-by-step approach to the dissertation life cycle, the book provides clear guidance on how to gain marks, as well as how to avoid losing them.
2014-04-22 A Concise Introduction to Mixed Methods Research SAGE Publications, Incorporated
ISBN 1483359042 ISBN-13 9781483359045
John W. Creswells A Concise Introduction to Mixed Methods Research is a brief overview of mixed methods research that takes readers through the essential steps in planning and designing a study. Rather than offering an extensive treatment of mixed methods, this concise book offers individuals in the social, behavioral, and health sciences a foundation for understanding mixed methods methodology. Practical for use in workshops, seminars, global webinars, and as a supplementary text in undergraduate and graduate classes, Creswells book is ideal for the beginner or the more advanced researcher looking for a quick primer in mixed methods, by an authoritative mixed methods scholar.
Loukides M, Mason H. , Patil, DJ (2018) Ethics and Data Science, O'Reilly Media 2018
This is project dependent, students will be guided by supervisor.
This is project dependent, students will be guided by supervisor.
Supervisors may advise students of additional readings appropriate to their project.