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Data Protection Office
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Dear Suchit Charaschanya

 

Thank you for your Freedom of Information request of 19^th July 2023.

 

We have completed the compilation of information in response to your
request for information about the mean mark, and the 5^th, 25^th, 75^th
and 95^th percentile marks for the 2022/23 academic year for the following
optional modules available to UCL MEng Mathematical Computation students
in their third and fourth year:

 

Year 3 Optional Modules:

 

Computer Systems Functional Programming Interaction Design
(COMP0019) (COMP0020) (COMP0021)
Database and Information Networked Systems Artificial Intelligence
Management Systems (COMP0023) and Neural Computing
(COMP0022) (COMP0024)
Introduction to Image Processing Computer Graphics
Cryptography (COMP0025) (COMP0026) (COMP0027)
Group Research Project Machine Learning for Quantum Computation
(COMP0031) Domain Specialists (COMP0157)
(COMP0142)
Machine Learning for Game Theory (ECON0027) Mathematical Methods 3
Visual Computing (MATH0016)
(COMP0169)
Biomathematics (MATH0026) Combinatorial Mathematical Ecology
Optimisation (MATH0028) (MATH0030)
Financial Mathematics Algebraic Number Theory History of Mathematics
(MATH0031) (MATH0035) (MATH0038)
Algebra 4: Groups and Philosophy of Arithmetic Probability and
Rings (MATH0053) (PHIL0184) Statistics II
(STAT0005)
Stochastic Processes Homological Algebra Galois Theory
(STAT0007) (MATH0021) (MATH0022)
Algebraic Topology Graph Theory and  
(MATH0023) Combinatorics (MATH0029)

 

Year 4 Optional Modules:

 

Introduction to Technology Affective Computing
Cryptography (COMP0025) Entrepreneurship and Human-Robot
(COMP0039) Interaction (COMP0053)
Computer Security I Computer Security II People and Security
(COMP0054) (COMP0055) (COMP0056)
Malware (COMP0060) Privacy Enhancing Supervised Learning
Technologies (COMP0061) (COMP0078)
Graphical Models Applied Machine Learning Bioinformatics
(COMP0080) (COMP0081) (COMP0082)
Advanced Topics in Information Retrieval and Statistical Natural
Machine Learning Data Mining (COMP0084) Language Processing
(COMP0083) (COMP0087)
Reinforcement Learning Requirements Engineering Software Abstractions
(COMP0089) and Software Architecture and Systems
(COMP0101) Integration (COMP0102)
Validation and Software Development Financial Institutions
Verification (COMP0103) Practice (COMP0104) and Markets (COMP0105)
Virtual Environments Inverse Problems in Computational
(COMP0113) Imaging (COMP0114) Modelling for
Biomedical Imaging
(COMP0118)
Acquisition and Complex Networks and Web Multi-agent Artificial
Processing of 3D Geometry (COMP0123) Intelligence
(COMP0119) (COMP0124)
Robotic Systems Distributed Systems and Machine Vision
Engineering (COMP0127) Security (COMP0133) (COMP0137)
Cryptocurrencies Perception and Interfaces Auditory Computing
(COMP0143) (COMP0160) (COMP0161)
Practical Program Quantum Information and Applied Deep Learning
Analysis (COMP0174) Communication (COMP0196) (COMP0197)
Cybersafety and Online Automated Software Mathematical Methods 4
Harms (COMP0236) Engineering (COMP0237) (MATH0056)
Advanced Modelling Lie Groups and Lie Evolutionary Games and
Mathematical Techniques Algebras (MATH0075) Population Genetics
(MATH0065) (MATH0082)
Computational and Quantitative and  
Simulation Methods Computational Finance
(MATH0086) (MATH0088)

 

 

We can confirm that we do hold information of the description specified in
your request and this information is provided in the attached spreadsheet.

 

Please note:

• No students took COMP0236 or COMP0237.
• There are no statistics for COMP0054, COMP0143 and COMP0157 because
there are no results due to the UCU national marking and assessment
boycott as part of action short of strike.

 

As you will see within the attached spreadsheet, the following information
has been withheld:

 

• The mean score where this is based on 7 or fewer students taking the
module (represented as ≤7); and
• The percentile scores where these are based on 22 or fewer students
taking the module (represented as ≤22).

 

This information has been withheld because, with such low numbers, even
providing the information without names, there is a risk the individuals
may be identifiable which means that these are personal data of third
parties, or if linked with other personal identifiers in the public
domain, would be likely to become personal data.  This information has
been withheld under Section 40(2) of the Freedom of Information Act 2000
(FOIA) by virtue of Section 40(3A)(i).

 

Section 40(2) of the FOIA allows a public authority to withhold
information under the FOIA where (i) the requested information is personal
data relating to someone other than the requester, and (ii) its disclosure
would breach any of the Data Protection principles.  In this case, we
believe that the requested information could relate to and identify
individuals and therefore would be personal data.  The disclosure of these
personal data would not be within the reasonable expectations of the
individuals concerned and it would be unfair to do so; this therefore
breaches the first Data Protection principle.

 

As the Section 40(2) exemption is an absolute one, there is no need to
conduct a public interest test.

 

 

You are free to use any information supplied for your own use, including
for non-commercial research purposes. The information may also be used for
the purposes of news reporting. However, any other type of re-use, for
example by publishing or issuing copies to the public, will require the
permission of the copyright owner.

 

If you are unhappy with our response to your request and wish to make a
complaint or request a review of our decision, please email
[1][email address]. Emails should include the words ‘Internal
Review’ in the subject and be marked For the Attention of the
Vice-President (Operations), alternatively you should write to:

 

Vice-President (Operations)

University College London

Gower Street

London

WC1E 6BT

 

Please note, complaints and requests for internal review received more
than two months after the initial decision will not be handled.

 

If you are not content with the outcome of the internal review, you may
apply directly to the Information Commissioner by using the following web
address: [2]www.ico.org.uk/foicomplaints. You should do this within two
months of our final decision.

 

If you have any queries or concerns, please contact me using the details
provided in this letter and including the request reference number.

 

Further information on the Freedom of Information Act is available from
the Information Commissioner’s Office:

 

Wycliffe House

Water Lane

Wilmslow

SK9 5AF

 

0303 123 1113

[3]https://ico.org.uk/

 

Kind regards,

 

Mehwish Sultan

Data Protection and Freedom of Information Adviser

University College London

Legal Services

E: [4][email address] Data Protection: [5][email address]
FOI: [6][UCL request email].

Telephone: +44 (0)203 108 7862 (internal 57862)

 

Working hours: Please note that I work from home on Mondays.

 

References

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