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BMOL40100

Academic Year 2024/2025

Biomolecular Sci Research Proj (BMOL40100)

Subject:
Biomolecular & Biomed Science
College:
Science
School:
Biomolecular & Biomed Science
Level:
4 (Masters)
Credits:
15
Module Coordinator:
Assoc Professor Peadar Ó Gaora
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

A literature review is a summary of the current scientific understanding of a subject or topic. The information is obtained in a systematic way, so that the summary you give is reliable.

The aim is to gain an understanding of the current status of our knowledge of a topic. This information might then be used in other ways:
- to plan scientific research
- to evaluate a commercial opportunity
- to design national policy e.g. healthcare
- to inform a research audience
- to educate an undergraduate or postgraduate cohort

Preparing a literature review therefore involves:

•Searching for reliable, accurate and up-to-date material on the topic or subject
• Reading the key points from this literature
• Synthesizing the key ideas, theories and concepts into a summary of what is known about the topic
• Discussing and evaluating these ideas, theories and concepts
• Identifying particular areas of debate or controversy
• Giving some of your own thoughts about potential future developments in the field

In this module you will explore and evaluate the use of Generative AI in preparing a literature review. You will evaluate AI-driven design, and produce a final review suitable for a specific audience.

About this Module

Learning Outcomes:

After completing this module, the student should have the following skills:

1. Ability to assemble, document and critically evaluate and summarise peer-reviewed
scientific literature relating to a specific topic.
2. Ability to evaluate the effectiveness and accuracy of Generative and other AI
tools (e.g. Large Language Models like ChatGPT, and other AI approaches).
3. Ability to design and present material suitable for a research workshop, an
advanced level teaching course or equivalent.

Indicative Module Content:

The ability to assess the current status of our knowledge of a topic is an important
scientific skill. This information may be used (i) to educate students or scientists
about a topic at a very high level, (ii) to plan future scientific research, (iii) to evaluate
a commercial opportunity, or (iv) to design a national policy. Generative AI, a type of
artificial intelligence that can quickly generate new content such as text, images and
sound is now influencing how scientific information is analysed. Some Generative AI
tools (Large Language Models such as ChatGPT) are useful for helping to write
reports. Other AI tools can be used to quickly identify the most relevant (or the most
recent) scientific papers related to a specific topic. In this module, you will be
assigned a topic and will use AI and Generative AI tools to design a workshop (eg a
half-day workshop for a scientific or industrial audience) or an advanced lecturing
module (lectures) suitable for undergraduate or postgraduate students.
Based on the appropriate scientific publications, you will then synthesise the key
ideas, theories and concepts into a literature review. You will use this information to
evaluate and critique the original AI-driven design. Finally, you will prepare and
present your work to classmates and staff.

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

300

Lectures

1

Project Supervision

10

Total

311


Approaches to Teaching and Learning:
The module will begin with some classes introducing the student to the use of AI
tools, including Generative AI. Each student will engage with a supervisor who is
familiar with, or interested in, the topic assigned. The student will meet regularly with
the supervisor (usually every week for the first 6-8 weeks). The supervisor will
provide feedback on design approaches. Students will be required to submit reports
on specified dates throughout the trimester. A final written literature review will then be submitted.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Thesis/Dissertation: A review of the scientific literature relating to a specific topic determined by the supervisor Week 10 Standard conversion grade scale 40% No
50
No
Individual Project: Presentation of one (chosen by staff) out of of three lectures prepared during the course of the project on an aspect of the scientific topic under review. Followed by Q&A with staff members. Week 11 Standard conversion grade scale 40% No
20
No
Report(s): 1. AI generated draft of a course on the topic under study (wk2)
2. Assessment of the AI-designed course and final draft (wk3)
Slides for
3. Lecture 1 (wk5)
4. Lecture 2 (wk 6)
5. Lecture 3 (wk7)
Week 2, Week 3, Week 5, Week 6, Week 7 Standard conversion grade scale 40% No
30
No

Carry forward of passed components
Yes
 

Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Assoc Professor Gerard Cagney Lecturer / Co-Lecturer
Assoc Professor Carmel Hensey Lecturer / Co-Lecturer
Assoc Professor Caroline Herron Lecturer / Co-Lecturer
Assoc Professor Tara McMorrow Lecturer / Co-Lecturer
Dr Seema Nathwani Lecturer / Co-Lecturer
Dr Jens Rauch Lecturer / Co-Lecturer
Dr Craig Slattery Lecturer / Co-Lecturer

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - 1 Wed 13:00 - 13:50