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Dear Greg,

Thank you for your request for information made under the Freedom of
Information Act (FOIA) 2000.

We confirm that we hold some of the information of the description
specified in your request; please see our response below and in the
attached document.

Your request

I would like to request information on module results in deciles, as well
as the mean grade and the median grade, for the 2021/2022, 2022/2023 and
2023/2024 cohorts for the following modules (which are part of the MSc
Data Science programme):

Introduction to Machine Learning (COMP0088) Statistical Design of
Investigations (STAT0029) Introduction to Statistical Data Science
(STAT0032) Statistical Computing (STAT0030) Research Project (STAT0034)
Stochastic Systems (STAT0009) Forecasting (STAT0010)
Stochastic Methods in Finance (STAT0013)
Stochastic Methods in Finance II (STAT0018)
Quantitative Operational Risk Modelling (STAT0020)
Applied Bayesian Methods (STAT0031)
Inference at Scale (STAT0043)
Applied Multivariate and High-Dimensional Methods (STAT0046) Graphical
Models (COMP0080) Applied Machine Learning (COMP0081) Information
Retrieval and Data Mining (COMP0084) Statistical Natural Language
Processing (COMP0087) Applied Deep Learning (COMP0197)

By ‘module results in deciles’, I mean the number of students with module
marks falling into the following categories (as per previous FOI requests
to UCL regarding module results):

00.01-9.99 10.00-19.99 20.00-29.99 30.00-39.99 40.00-49.99 50.00-59.99
60.00-69.99 70.00-79.99 80.00-89.99 90.00+

Our response

We do not hold all of the information in the format you have requested
(median grades) and we are unable to provide you with individualised
bespoke data because this would constitute us creating new data. However,
we have a standard set of data which displays module results in deciles
(sections for each 10% of the possible score a student could achieve).

The tables in the attached document show the number of students who
completed the modules listed (broken down into 10-point deciles), the mean
mark and the marks they achieved, in the 2021/22, 2022/23, and 2023/24
academic years. Please note the following:

• The figure under each mark range (00.01-9.99, 10.00-19.99, 20.00-29.99
etc.) is the number of students who achieved that specific range of
marks. For example, with regards to the module code ‘COMP0080’ in
table 1, this shows that 11 students achieved a mark between
50.00-59.99. Similarly, for the same module code, 13 students achieved
a mark between 70.00-79.99.

• If a module does not appear for one of the years, no one took it that
year. However, there are no results for STAT0034 Research Project in
the 2023/24 academic year as the submission deadline for the final
project for the module has just passed.

• The marks for 2023/24 modules are preliminary as the results of Late
Summer Assessments are not yet known.

• As you can see, we are unable to disclose the exact number of students
where 5 or fewer received a specific range of marks. This is because
to provide the exact numbers may inadvertently lead to the
identification of these individuals. Whilst there are no personally
identifiable details within the data being withheld, that data, when
combined with other data that may already be available in the public
domain, could be used by ‘motivated intruders’ and other knowledgeable
third parties to identify the individuals concerned. Linking together
separate strands of data available in this way can indirectly lead to
an individual being identified which would breach the first data
protection principle. Further, these individuals would have no
expectation that their identities, by virtue of disclosing this type
of information, would be made known to the wider public and it would
be considered unfair to do so.

As this data would be likely to become personal data, this information is
exempt from disclosure and has been withheld under section 40(2) of the
FOIA by virtue of s40(3A)(a). 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.

It is for these reasons that this information is exempt under section
40(2) of the Act. As the section 40(2) exemption is absolute, 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 have any queries or concerns, please contact me using the details
provided in this letter and including the request reference number. 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, please write to:

Vice-President (Operations)

University College London

Gower Street

London

WC1E 6BT

 

Please note that 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’s Office (ICO) by using the
following web address: [2]www.ico.org.uk/foicomplaints or by writing to
the ICO at the following address:

 

Wycliffe House

Water Lane

Wilmslow

SK9 5AF

0303 123 1113

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

You should do this within two months of our final decision. Further
information on the FOIA is available on the ICO’s website:
[4]https://ico.org.uk/for-the-public/offici...

 

Kind regards,

Fawwaz Noibi

Data Protection and Freedom of Information Administrator

Data Protection Office

Office of the General Counsel

University College London

Tel:        020 3108 6389 (ext. 56389)

Email:    [5][email address]

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References

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