Module Details

Module Code: COMP9011
Title: Research Practice & Ethics
Long Title: Research Practice & Ethics
NFQ Level: Expert
Valid From: Semester 1 - 2018/19 ( September 2018 )
Duration: 1 Semester
Credits: 5
Field of Study: 4811 - Computer Science
Module Delivered in: 8 programme(s)
Module Description: The purpose of this module is to introduce students to the tools and techniques for doing research. In addition, students will examine the concept of research integrity and ethics applied to their field of study. On completion of this module students will develop a research proposal outlining the context of the topic, its research aims, objectives, methodologies, work plan, ethical considerations etc. This proposal will then be developed further in an implementation phase.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Develop a research proposal defining the project aims, objectives and research methodology that will be applied to the research project.
LO2 Review the current state of the art in the topic related to the proposed research outlining the contribution the research will make to the general field.
LO3 Evaluate the main research integrity and ethical considerations that need to be considered in the proposed project.
LO4 Develop a project schedule and plan that considers the identified research integrity and ethical considerations.
LO5 Communicate effectively the idea and contribution of the proposed research project.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Research Methods and Methodologies
Definitions. Knowledge kinds and interrelationships. Empirical Research. Basic Research. Applied Research. Practical Research. Action Research. Parameters of research. Kinds of research: qualitative, descriptive and experimental. Applying research methodologies to computing, software and software development. Case studies and examples.
Research and Research Strategies
Constitution of research papers. Standards. Search strategies including: web, library, inter-library loan, databases such as IEEE and ACM, search engines. Literature review and systematic literature review.
Research Planning
Issues within a research project that relate specifically to computing/software projects including: problem definition, software planning, specification and system definition, choosing environments for development, timing issues relating to the software process, prototyping, iteration, risk evaluation, slippage, performance issues, evaluations and conclusions.
Research Documentation
Documentation appropriate to research and the programme specifications. This includes research proposal documentation, report documentation, research paper formats and citation formats.
Ethics for Computer Scientists
Ethics in Information & communication technology. Ethics, privacy and information security. Computer Ethics. Cyber ethics. Social, regulation and legal issues. Ethical design. Impact of IoT on ethics - environment monitoring and data collection. Impact of AI on ethics. Posthuman era, machine ethics, unintended consequences. Case studies - Facebook Mood Manipulation Experiments, Internet of Things, Google Maps.
Research Ethics & integrity
Human subjects - ethical, legal, social and political issues. Research ethics committee in CIT. Categories of research ethics - questionnaires/surveys for adults versus children. Consent.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Essay % of Total Mark 40
Timing Week 9 Learning Outcomes 1,2
Assessment Description
The student will propose an initial research topic and will define some initial context behind the idea. In addition, the student will define some preliminary research aims and objectives. The student will then be expected to present their idea with the aim of effectively communicating the broad research topic and context.
Assessment Type Other % of Total Mark 60
Timing Sem End Learning Outcomes 1,2,3,4,5
Assessment Description
The student will develop the research proposal detailing fully the idea and relevant state of the art, aims, objective, methodologies, work plan schedule and ethical issues that need to be considered. The student may also be required to present their proposal.
No End of Module Formal Examination
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Lecture delivering theory underpinning learning outcomes. Every Week 2.00 2
Lab Contact Practical to develop individual proposal. Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Independent Study. Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Lecture delivering theory underpinning learning outcomes. Every Week 2.00 2
Lab Contact Practical to develop individual proposal. Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Independent Study. Every Week 4.00 4
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Martyn Denscombe. (2014), The Good Research Guide, 5. Open University Press, McGraw-Hill Education, [ISBN: 9780335264704].
Supplementary Book Resources
  • Steven J. Taylor, Robert Bogdan, Marjorie DeVault. (2016), Introduction to Qualitative Research Methods: A Guidebook and Resource, 4. Wiley, [ISBN: 9781118767214].
  • Prabhat Pandey, Meenu Mishra Pandey. (2015), Research Methodology: Tools and Techniques, 1. Bridge Center, [ISBN: 9786069350270].
  • James D. Lester. (2014), Writing Research Papers: A Complete Guide, 15. Pearson, [ISBN: 9780321952950].
  • K. Schwalbe. (2011), Information Technology Project Management, 6. Cengage Learning, [ISBN: 9781111221751].
  • Dennis Lock. (2007), Project management, Gower, Aldershot, [ISBN: 978-0566087721].
  • Nick Bostrom. (2016), Superintelligence: Paths, Dangers, Strategies, OUP Oxford, [ISBN: 9780198739838].
Recommended Article/Paper Resources
  • Shaw, M.. (2003), Writing Good Software Engineering Research Papers, Proceeding of the 25th International Conference on Software Engineering: IEEE Computer Society, p.726-736.
  • Nick Bostrom, Eliezer Yudkowsky. (2014), The Ethics of Artificial Intelligence, The Cambridge handbook of artificial intelligence, p.316-3,
    https://intelligence.org/files/EthicsofA I.pdf
  • Francine Berman and Vinton G. Cerf. (2017), Social and Ethical Behavior in the Internet of Things, Communications of the ACM, 60(2),
    http://www.cs.rpi.edu/~bermaf/Berman+Cer f_IoT.pdf
Supplementary Article/Paper Resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_KARIN_9 Master of Science in Artificial Intelligence 1 Mandatory
CR_KCLDC_9 Master of Science in Cloud Computing 2 Mandatory
CR_SCOBI_9 Master of Science in Computational Biology 3 Mandatory
CR_SNUHA_9 Master of Science in Nutrition & Health Analytics 3 Mandatory
CR_KSADE_9 Master of Science in Software Architecture & Design 1 Mandatory
CR_KINDD_9 Master of Science in Technical Communication 2 Mandatory
CR_SCPBI_9 Postgraduate Diploma in Science in Computational Biology 3 Mandatory
CR_KIDDE_9 Postgraduate Diploma in Science in Technical Communication 2 Mandatory