Section A: Assignment title, important dates and weighting
Section B: Student(s) to complete
Notes for students
·
For undergraduate modules, a score above
40% represent a pass performance at honours
level.
·
For postgraduate modules, a score of 50%
or above represents a pass mark.
·
Late submission of any item of coursework
for each day or part thereof (or for hard copy submission only, working day or
part thereof) for up to five days after the published deadline, coursework
relating to modules at Levels 3, 4, 5, 6 submitted late (including deferred
coursework, but with the exception
of referred coursework), will have the numeric grade reduced by 10 grade
points until or unless the numeric grade reaches or is 40. Where the numeric
grade awarded for the assessment is less than 40, no lateness penalty will be applied.
·
Late submission of referred coursework
will automatically be awarded a grade of zero
(0).
·
Coursework (including deferred coursework) submitted later than five days (five working days in the case of hard copy submission) after
the published deadline will be awarded a grade of zero (0).
·
Regulations
governing assessment offences including Plagiarism and Collusion are available
from https://www.herts.ac.uk/about-us/governance/university-policies-and-regulations-uprs/uprs (please refer to UPR AS14)
·
Guidance on avoiding plagiarism can be
found here: https://herts.instructure.com/courses/61421/pages/referencing-avoiding- plagiarism?module_item_id=779436
·
Modules may have several components of
assessment and may require a pass in all elements. For further details,
please consult the relevant Module
Handbook (available on Studynet/Canvas, under Module Information) or ask the
Module Leader.
Assignment Briefing Sheet (2020/21 Academic Year)
This Assignment assesses the
following module Learning Outcomes (from Definitive Module Document):
Knowledge and understanding:
LO1 Have a
conceptual understanding of how established techniques of research are used to
create and extend existing knowledge in computer science.
LO2 Be able to
identify a research problem from synthesizing problem definitions from relevant
literature.
LO3 Demonstrate originality in proposing alternative solutions within
a chosen area.
Skills and attributes
LO4 Critically evaluate research
literature and identify research problems to solve
LO5 Demonstrate
ability to propose alternative approaches for future work in a chosen area. LO6
Communicate research knowledge effectively in scholarly manner.
Aim: To provide exposure to
research areas in Computer Science drawn from the Department’s research profile
in order to provide preparatory ground for students to pursue a deeper
investigation of a research topic as part of their Master’s project.
Assignment Brief:
Research is not just for academics, governments
and commercial/industrial organisations typically have a research units where
teams of research and subject experts work systematically to create new
knowledge/products/services and/or the use of existing knowledge/products/services
in a new and creative way so as to generate
new concepts, methodologies and understandings. This could include
synthesis and analysis of
previous research to the extent that it leads to new and creative outcomes.
Research encompasses pure and strategic basic research, applied research and
experimental development. Applied research is original investigation undertaken
to acquire new knowledge but directed towards a specific, practical aim or
objective.
Assume
that you have been newly appointed as a research assistant of a university/a
large organisation with many research groups who are working on different
research projects, are working along with you. During your probation period,
your line manager has asked you to attend the company’s weekly research talks and prepare a portfolio, demonstrating that you have achieved the learning outcomes
of your Advanced Research topics in Computer Science
successfully and you are indeed,
ready to join a British
research team that produce
world leading research outcomes.
Portfolio is an individual assessment comprised of 2 parts. Task 1 and Task 2 will carry 40, and 60% marks of the overall module mark,
respectively. You will be awarded a preliminary mark out of 100% for both Task
1 and Task 2, and the weighting will be done as part of the portfolio.
During the online follow-up tutorial sessions, the
module team will provide general feedback and advice regarding your progress. You will also have the opportunity to submit a draft copy of Task 1 for feedback as indicated in the module guide.
Your portfolio
should include (in one document, structured appropriately) following;
Task 1:
a. A review report
on your own research area (relevant to your own MSc route)
b. Self-reflection
1: using the guidelines received in Week 2 tutorial.
Task 2:
a.
A review report on another distinct topic covered in
the lectures in the subject areas below.
As part of your tutorial
work you are preparing
these short reports
on each topic with the support of your tutors. Where a topic seems quite
broad, you can choose an aspect of it. The module will include 4-5 research
talks by active researchers in UH on their subject areas ;
i.
Networks, Security and Systems
ii.
Human Oriented Computing
iii.
Data Science
iv.
AI & Robotics
v.
Software Engineering
b.
Self-reflection 2: using the guidelines received in
Week 10 revision session.
The report
structure and the marking and feedback schemes and grade band descriptors are
given in Annex ‘A’.
All work should be
supported by a Title page showing the Module code, your name student number,
MSc route and the words “Portfolio Coursework”, citations and adequate
references (including approximately 15 high quality references) and appendices
where required.
Submission
Requirements: The complete portfolio in a single
document in PDF format should be uploaded to the canvas site for this module.
The document should be named to reflect your tutorial group A#, student# and
first name and surname as appears in the UH student records (example A01 123456 Deepthi Ratnayake).
Marks awarded for:
This assignment is worth 100 % of
the overall assessment for this module. A note to the Students: a score of 50%
or above represents a pass mark.
Type of
Feedback to be given for this assignment:
Formative verbal/written feedback
will be given for the portfolio milestone
reports through canvas
and during the scheduled
sessions as per the module delivery plan. Individual summative feedback will be
given through canvas for the final submission. The assignment will be marked
according to the attached marking scheme as such you should address each of the
marking components within your assignment.
Every week, review & reflection questions related to the assessment activities will be posted on StudyNet. These questions will help you to reflect on the activities you will be undertaking as part of the assessed work for the module. Self-assessing your work as you progress through the module and help you understand the subject better. Feedback is not just the marks and the commentary at the end of the module – it is also the regular advice about your work as you undertake the practical activities. If you fail to undertake the tutorial activities and you fail to engage with the class and with the instructors, you will disadvantage yourself.
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