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AI Student Partner

 

Job Description

Please note, there is a maximum of 30 hours available per student to be worked flexibly and remotely across the 10 week period (12/08/24-18/10/24), with the majority of the hours being worked in August and September.

King?s College London is committed to supporting its students to use generative AI confidently, effectively, appropriately and responsibly in their academic studies and beyond. Following two workshops with student exploring how they want to be supported to develop their AI literacy, this role will now help bring those recommendations to life through the creation of a Student AI Resource to be launched in the new academic year (October 2024). The resources will be co-created between staff and students over the summer of 2024. 

This role will mainly be remote working using Microsoft Teams for online meetings. Once everyone has returned to campus in September 2024, we may then meet face-to-face but this will be agreed betweem all team members (students and staff).

We particularly welcome applications from students who are underrepresented and/or identify as belonging to a marginalised group.

As part of this role you will be:

  • Working with staff to agree the structure and content of the resource. 
  • Desk research/sector scoping to identify what is being done elsewhere.
  • Creating content for the resource including interactive content.
  • Creating quizzes and/or other mechanisms to check learning.
  • Exploring potential avenues for incentivisation e.g. LinkedIn Learning badges/certificates.
  • Testing out resources, quizzes and editing content. 
  • Ensuring there are links between guidance given to staff (e.g., Programme Leads) and the student resources. 
  • Providing a student perspective for the comms going out to staff to raise their awareness of the resource. 
  • Drafting/informing communications to students including development of a comms plan.
  • Helping establish an evaluation plan for the resource and plan future steps.

If you'd like to discuss the role, please email Abbie King (abbie.king@kcl.ac.uk).



Qualifications

Please indicate on your personal statement your level of study (UG/PGT/PGR/Recent graduate) and programme of study. 

  • Essential: Current King?s College London student (undergraduate, postgraduate taught or postgraduate research) or recent graduate of King?s College London (graduated within the past 12 months).


Skills

Please provide a short personal statement detailing your interest in the role. The skills and experiences we are asking you to demonstrate should fit students with a wide range of experiences and we actively encourage applications from students who are underrepresented and/or identify as belonging to a marginalised group. We will provide training and support for you to confidently tackle this role and develop within it. 

  • Interest in the development of AI in the Higher Education sector and its impact on students / education. 
  • Interest in inclusive educational practices. 
  • Desire to improve the student experience.
  • Desirable: some experience of content creation (this doesn?t have to be related to your programme of study and could relate to your extra curricular interests).
  • Also of interest but not essential: Animation skills.
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The Policy Institute is looking for a research assistant to work with Professor Duffy at the Policy Institute on a project analysing longitudinal survey datasets to study the evolution of attitudes and values for generations in the UK and worldwide. The project will involve two main tasks, which are expected to last for a total of 10 days, listed below:

Task 1: Longitudinal data cleaning and data visualisation

We want to update a PowerPoint resource pack consisting of c.100 charts using data from sources including Ipsos, Eurostat, the US General Social Survey, the British Social Attitudes, the European Social Survey and more. The research assistant will work with the Policy Institute team updating existing code (currently available in R/Stata) to extend longitudinal series, produce results breakdowns by cohorts/generations and update the charts sourcing using the most recent data points for these studies. 

 

Task 2: Investigating the divergence between Gen Z men and women 

We would like to produce a new set of c.40 charts, taken from the larger resource pack from Task 1 that split Gen Z men and women over time, on a smaller selection of questions and data sources, where sample size allows. The research assistant will work with the Policy Institute researchers to identify topics and data sources to carry out this task, and then produce a set of visualisations and statistical models to identify any statistically significant differences between Gen Z gender groups. 

FURTHER INFORMATION 

The post is available on a fixed term basis. The research assistant will be able to organise their working hours and patterns with flexibility, but we are aiming to complete work on both tasks by 28th February 2025. 

 



Qualifications

Essential skills: Enrolled in a Bachelor?s degree in a relevant social science discipline (e.g. politics, economics, social sciences, geography, etc.).

Desirable: Enrolled in a postgraduate (eg. MSc/MA/PhD) degree in a relevant social science discipline (e.g. politics, economics, social sciences, geography, etc.).



Skills

Essential skills: Knowledge of quantitative research methods. Experience using statistical software including R, Stata and/or SPSS. Experience using PowerPoint. Excellent written and oral communication skills. Punctual, reliable, committed, proactive. Ability to work independently and as part of a team.

Desirable skills: Experience with the analysis of longitudinal survey data. Experience producing charts using Excel and Powerpoint. Interest in public opinion and public attitudes research. Interest in generations research. 

STACK is a quiz question type in KEATS which allows module leaders to ask mathematically sophisticated questions where students provide sophisticated answers. The questions are built using a computer algebra system (Maxima) which means that they can be randomised, students answers can be automatically marked, and dynamic and high-quality feedback provided. 

Successful applicants will be trained in creating questions using STACK and then work with the leader(s) of a first or second year undergraduate mathematics module to develop a bank of questions for the module using STACK, supported by Dr. David Sheard. The possible modules involved are

  • 4CCM141A    Probability and statistics I
  • 4CCM131A    Introduction to dynamical systems
  • 4CCM114A    Linear algebra and geometry II
  • 5CCM221A    Real analysis
  • 5CCM211A    Applied differential equations
  • 5CCM212A    Complex analysis
  • 4CCM112A    Calculus II
  • 4CCM111A    Calculus I
  • 4CCM113A    Linear algebra and geometry I

 

Responsibilities:

Successful applicants will be required to:

  • Attend training on how to author questions in STACK (included in pay).
  • Meet and work with the module leader(s) of a course to develop educational resources in STACK.
  • Ensure the STACK resources they create meet minimum quality standards as agreed at the start of the role.
  • Work to weekly/fortnightly deadlines throughout the teaching semester.
  • Seek help/guidance when needed and use online reference material as appropriate (including programming documentation and educational literature).
  • Submit timesheets regularly and adhere to administrative requirements of the position.

 

Benefits:

Successful applicants will:

  • Have the opportunity to collaborate closely with academics in the design of teaching resources. 
  • develop skills including programming, unit testing, and teamwork. 
  • develop understanding of pedagogy, especially related to assessment for learning and feedback. 

These may be particularly relevant to people thinking of a future career in academia or education generally.

These positions are advertised as one-off, fixed-term positions. In total, successful applicants will be expected to work 50 hours

Please provide a short personal statement summarising which of the desirable and advantageous and skills/experience you have, how you satisfy the qualifications requirement, and which of the modules listed in the job description you would like to write STACK questions for. You may wish to upload a 1 page CV as well.

If you have any questions about the role or application process, please email David Sheard at david.1.sheard@kcl.ac.uk.



Qualifications

Applicants should be one of the following:

  • Level 6 or 7 undergraduate student with a mark of 70+ in the module(s) from the list they would like to work on
  • Postgraduate taught student with a mark of 70+ in a similar module to the one(s) from the list they would like to work on
  • PhD student with sufficient subject knowledge to effectively GTA the module(s) from the list they would like to work on


Skills

Desirable:

  • Programming experience, especially in Maxima or Mathematica
  • Good organisational and teamworking skills
  • Excellent academic written English

 

Advantageous:

  • Some familiarity with editing KEATS pages
  • Interest in teaching, pedagogy, or assessment design

Attendance at 2-day Flex:Change Workshop at Macadam Building, STRAND. 



Applicants to claim 14 hours via timesheet.



Qualifications

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Skills

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