Computer Science grade distribution
Dear University College London,
Please could you provide the following information:
1) The (anonymised) year means of all first-year students on the BSc/MEng Computer Science courses in the 2021-22 academic year. Note that by "year mean" I mean the credit-weighted average mark of the modules that students take in their first year of these courses.
2) Alternatively, if the information in (1) cannot be provided, could you instead provide: the 50th, 75th, 90th, 95th, 97th, and 99th percentile year means for first-year BSc/MEng Computer Science students in the 2021-22 academic year. Please provide a single set of percentiles for the combined BSc/MEng cohort, rather than separate figures for each course.
Yours faithfully,
Pranav Agarwal
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Hello,
Is there any estimate on when I may expect a response to my request? As 20 working days have almost passed.
Yours faithfully,
Pranav Agarwal
Dear Pranav,
Thank you for your Freedom of Information request of 23 July 2022.
Apologies for the delay in responding to your request.
We have completed the compilation of information in response to your
request which read as follows:
Please could you provide the following information:
1) The (anonymised) year means of all first-year students on the BSc/MEng
Computer Science courses in the 2021-22 academic year. Note that by "year
mean" I mean the credit-weighted average mark of the modules that students
take in their first year of these courses.
2) Alternatively, if the information in (1) cannot be provided, could you
instead provide: the 50th, 75th, 90th, 95th, 97th, and 99th percentile
year means for first-year BSc/MEng Computer Science students in the
2021-22 academic year. Please provide a single set of percentiles for the
combined BSc/MEng cohort, rather than separate figures for each course.
We can confirm that we do hold information of the description specified in
your request and this information is provided in the attached spreadsheet.
Whilst UCL is committed to openness and transparency, we are also mindful
of our obligations under the Data Protection regime, and therefore take
steps to anonymise data before it is released. We adopt the following
approach when releasing statistics that relate to people, to prevent
unauthorised disclosure of information that relates to individuals:
• Percentages that are based on a group of 22 individuals or
less are not provided, and this includes requests for percentile
information about marks.
• Averages based on 7 or fewer individuals are not provided.
We have identified that there is a risk of the identification of
underlying individuals in the information that you have requested. The
information has been withheld because, with such low numbers, even
providing this information on an anonymised basis it is possible that the
underlying individuals could be identified, which means that this is
personal data of third parties or, if linked with other personal
identifiers in the public domain, would be likely to become personal data.
This relates to the whole of question one, and the 97^th and 99^th
percentiles in question two. This information has been withheld under
Section 40(2) of the 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.
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Dear University College London,
Please pass this on to the person who conducts Freedom of Information reviews.
I am writing to request an internal review of University College London's handling of my FOI request 'Computer Science grade distribution'.
Part of the data I requested (specifically, the 97th and 99th percentile credit-weighted year means of 1st year Computer Science students in 2021/22) was withheld under section 40(2) on the basis that there is "is a risk of the identification of underlying individuals". I do not believe this risk exists, or that the exemption has been accurately applied.
UCL has previously released 99th percentile marks where the number of individuals in the group is much lower. For example, see these FOI requests:
https://www.whatdotheyknow.com/request/u...
https://www.whatdotheyknow.com/request/g...
Note that these requests received a response on the very same day as my request, and 99th percentile marks were provided (for all the modules where the total number of individuals was greater than 22). Note that the number of students on these modules is much fewer than the number of students in an entire Computer Science cohort. Given that the 99th percentiles were released in these cases with no worry of it allowing individuals to be identified, I believe that it was wrong to withhold the same percentile for my request, based on a much larger group.
As such I politely request that the data that was withheld (97th and 99th percentile credit-weighted year means of 1st year Computer Science students in 2021/22) be released.
A full history of my FOI request and all correspondence is available on the Internet at this address: https://www.whatdotheyknow.com/request/c...
Yours faithfully,
Pranav Agarwal
Hello,
Is there any update on the status of this internal review?
See a transcript of this request here: https://www.whatdotheyknow.com/request/c...
Yours sincerely,
Pranav Agarwal
Dear Sirs,
Please find attached the response to your request.
Best wishes,
Andy Smith | Interim Vice-President (Operations)
UCL | Gower Street | London | WC1E 6BT |
t: +44 (0)20 3108 3801 | e: [1][email address] | w:
[2]www.ucl.ac.uk
University College London | London’s Global University
Executive Assistant: Louise Moore | e: [3][email address] |
Diary Manager: Maria Lewis | e: [4][email address] |
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