Statistical Science


Teaching in Mathematical and Statistical Sciences (TMSS) seminars

This seminar series aims to promote a discussion around teaching and learning in higher education.  It provides the opportunity to hear about some of the latest work in the field of education research, explore new teaching methods and material, share good teaching practice, and take part in discussions. Seminars are free and open to all to attend. 


22 June 2022 - Pilar Garcia-Souto (UCL)

Date and Time:        Wednesday, 22 June 2022 12:00-13:00

Title and Abstract: "Individual Peer Assessed Contribution to group work (IPAC)"

Having group work projects within a module/programme has many educational benefits. However, it also raises concerns regarding fairness of individual marks and student engagement. This seminar explains the IPAC methodology for assessment of group work, how it addresses these initial concerns as well as brings other educational benefits and opportunities for student development. Finally, we do a quick demonstration of the IPAC software that allows tutors to implement this practice easily and time efficiently.

Location: Online | Join via Zoom

11 July 2022 - Matthias Troffaes (Durham University)

Title and Abstract: "A linked approach to teaching frequentist and Bayesian statistics: interpretation, foundation, notation, unification?"

In this presentation, I will share some of my views on teaching frequentist and Bayesian statistics, with the aim for students to come to a solid understanding and appreciation of both formalisms. I will discuss the relevance of some foundational aspects which are often not part of first year undergraduate statistics. I will show that with careful use of notation, at the price of slightly deviating from statistical tradition, both ways of doing statistics can be put on a clear common foundation.

Location: Online | Join via Zoom

31 October 2022 - Joachim Engel (Ludwigsburg University of Education)

Date and Time:        Monday, 31 October 2022 12:00-13:00

Title and Abstract: "Civic Statistics: Conceptualization of a new Perspective on Statistical Literacy"

Location: Online | Join via Zoom

14 November 2022 - Andy Wills (University of Plymouth)

Date and Time:        Monday, 14 November 2022 13:00-14:00

Title and Abstract: "From SPSS to R in Undergraduate Psychology."

In 2018, the School of Psychology at the University of Plymouth began teaching R to all new undergraduates. We're a typical School in terms of entry grades. Our first cohort of students taught R graduated in 2021. They were taught R throughout all three years of the programme. And, in their final project, almost 90% of students primarily used R. In many cases, the work they produced was impressive. In this talk, I'll outline how we made this transition, what we learned, and give some suggestions about how to achieve a similar transition in other UG psychology programmes.

Location: Online | Join via Zoom

21 November 2022 - Jackie Carter (The University of Manchester)

Date and Time:        Monday, 21 November 2022 13:00-14:00

Title and Abstract: "How data fellowships open doors to data careers"

This talk will draw on findings from a Data Fellowship programme that was established in 2013 through the University of Manchester’s Q-Step programme. The data fellows are drawn from social science undergraduate degrees and since starting with 19 in 2014 we have now placed 330 student into around 60 organisations to do data-led research projects. The results have been published in articles and a book and Jackie will provide insight into these placements and talk about how the programme is opening up opportunities for social science graduates to enter data and statistical careers. She has developed a ‘research and analytical skills’ and ‘professional skills’ framework based on British Academy and LinkedIn and McKinsey reports. She is currently talking to employers about their ‘data skills’ needs and she is hoping her current research will result in a data skills framework that is more inclusive and not focused predominantly on STEM subjects. Her aim is to contribute to creating a more diverse talent pipeline into data careers. 

Location: Online | Join via Zoom

7 December 2022 - Sebastian del Bano Rollin (QMUL)

Date and Time:        Wednesday, 7 December 2022 13:00-14:00

Title and Abstract: "Injecting professional skills and certification in the maths curriculum"

We will present several ideas on including professional skills and certification in the university mathematics curriculum with particular emphasis on practical limitations and challenges.

Location: In peson | Venue: Room 505, 25 Gordon Street 

12 December 2022 - Sibel Kazak (Middle East Technical University)

Date and Time:        Monday 12 December 2022 13:00-14:00

Title and Abstract: "Pre-service mathematics teachers’ experiences of using photographs as data sources"

Today’s students have become exposed to the concept of data in various forms from different data sources, including real-time data collected by sensory devices, text/video/photograph from social media feeds, and so on. Engaging in statistical investigation with such non-traditional data draws attention to certain statistical topics, such as multivariate thinking, context, and trigger questions. Future mathematics teachers should experience such a statistical investigation process themselves. In this presentation, I will share some examples of pre-service mathematics teachers’ use of photographs as data sources and discuss how image-based data were acquired in these cases and organized for data analysis using the Common Online Data Analysis Platform (CODAP). 

Location: Online | Join via Zoom

18 January 2023 - Colette Mair (The University of Glasgow)

Date and Time:        Wednesday, 18 January 2023 12:00-13:00

Title and Abstract:  "Student and staff perceptions of student evaluations in statistics"

Student evaluations of teaching are embedded into higher education to assess the quality of teaching.  There is debate surrounding the reliability, effectiveness and bias of student evaluations. They may not provide evidence of poor- or high-quality teaching, with a recent literature review suggesting that student evaluations have poor response rates and can openly prejudice marginalised groups. Recent NSS results show that within Scotland, students responded poorly to questions relating to their learning community and the student voice, with 49% of students agreeing that they are clear on how students’ feedback on a course has been acted on and only 59% of students agreed that they felt part of a community. In addition, 69% of students agreed that staff value students’ views and opinions on a course.  These levels of agreement are reflected in response rates from within the University of Glasgow, and more precisely within the School of Mathematics and Statistics with the added complication of only 53% of statistics students agreeing that their programme offered them opportunities to apply what they have learnt.

During this seminar, I will introduce a project aiming to investigate the perceptions of student evaluations and the effectiveness of student-led group discussion groups within an undergraduate statistics programme. The project addresses the following questions: 

  1. How do staff engage with student evaluations?
  2. How do students engage with student evaluations? 
  3. What is the effect of in-class discussions on students’ engagement with evaluations? 
  4. How should student evaluations be disseminated to staff and students? 

I will present the results of two surveys in response to questions 1 and 2 that address staff and student impressions of student evaluations in addition to discussing plans for the student discussion groups and the specific structure of these groups.

Location: Online | Join via Zoom

25 January 2023 - Ben Davies (University of Southampton)

Date and Time:        Wednesday, 25 January 2023 12:00-13:00

Title and Abstract:  "Assessment for learning of proof-based mathematics

Proof is a famously difficult aspect of the undergraduate mathematics curriculum, for students and assessors alike. Early undergraduate courses are often taught with a ‘definition-theorem-proof' structure (Weber 2004), and primarily assessed by closed-book timed exams (Iannone and Simpson, 2011). While much research has focused on understanding and highlighting specific issues in this area, we are aware of limited work seeking ambitious interventions to help mitigate the myriad well-documented issues with pedagogic practice and assessment validity.  

In this talk, I will discuss a novel approach to delivering and assessing UG mathematics content based on Standards-based grading (Nilson and Stanny, 2015) with oral assessment. This approach focused on supporting students to demonstrate core competencies through a variety of formative and summative assessments. These included a formative revise-and-resubmit protocol for written portfolio work, and multiple summative oral assessments throughout the semester. This approach resulted from years of dissatisfaction with traditional assessment for undergraduates’ understanding of proof, a desire to embed meaningful student-centered assessment for learning, and the urgent need to adapt to online instruction and assessment as a result of the COVID-19 pandemic. While immensely disruptive in many ways, this latter need provided the impetus and institutional flexibility to make this novel practice possible.   

A primary benefit of this novel approach centers on structured opportunities for students to engage in two-way mathematical discourse, both written and verbal. I argue that this is particularly valuable in contexts where the values and norms of mathematical communication (Dawkins and Weber, 2017) are often overlooked or misunderstood by students who elect to focus on the technical content at stake (David and Zazkis, 2020). I also reflect on the impact of changes in assessment for student engagement and the overall delivery of the course. It is well-known that assessment and feedback practices drive learning, so while the innovations described are primarily derived from a reformed assessment structure, it should be noted that the standards-based approach permeated all aspects of students’ experience.   

  • David, E. J., & Zazkis, D. (2020). Characterizing introduction to proof courses: a survey of U.S. R1 and R2 course syllabi. International Journal of Mathematical Education in Science and Technology, 51(3), 388-404. https://doi.org/10.1080/0020739X.2019.1574362  
  • Dawkins, P. and Weber, K. (2017). Values and norms of proof for mathematicians and students. Educational Studies in Mathematics95, 123-142.  
  • Iannone, P., & Simpson, A. (2011). The summative assessment diet: how we assess in mathematics degrees. Teaching mathematics and its applications, 30(4), 186-196.  
  • Nilson, L. B., & Stanny, C. J. (2015). Specifications grading : restoring rigor, motivating students, and saving faculty time (First edition. ed.). Stylus.   
  • Weber, K. (2004). Traditional instruction in advanced mathematics courses; a case study of one professor’s lecture and proofs in an introductory real analysis course. Journal of Mathematical Behavior, 23(1), 115-133.  

Location: In peson | Venue: See below

8 February 2023 - Tom Wicks (The University of Nottingham)

Date and Time:        Wednesday, 8 February 2023 12:00-13:00

Title and Abstract:  "Compulsory Year 3 Projects in a Mathematics Degree"

In this talk, I will give an overview of our compulsory group project module for Year 3 Mathematics students at University of Nottingham. I will give a brief description of the development of the module over several years before it was compulsory, then explain our rationale for how the module operates, from student training workshops to project deliverables and marking processes. There will be plenty of time allowed at the end for discussion of how this format could work for similar programmes at UCL.

Location: In peson & online | See below for more details.

8 March 2023 - Matthew Towers (UCL)

Date and Time:        Wednesday, 8 March 2023 12:00-13:00

Title and Abstract:  "Teaching Python to mathematicians using CoCalc"

I will talk about some aspects of teaching Python programming to complete beginner math students using Jupyter notebooks hosted on the online CoCalc platform.

Location: In peson & online | See below for more details.
3 May 2023 - Rehan Shah (QMUL)

Date and Time:        Wednesday, 3 May 2023 12:00-13:00

Title and Abstract:  "Teaching Ethics in Mathematics? You Must Be Joking!"

For the last 20 years it has become increasingly obvious, and increasingly pressing, that mathematicians should be taught some ethical awareness so as to realise the impact of their work. This extends even to those more highly trained, ranging from graduate students to academic staff. But what should we be teaching mathematicians and how should we do it? In this talk, I will discuss the need for the consideration of ethical aspects within mathematics and outline some of the ways in which we can incorporate the teaching of ethics within mathematics courses at university.

Location: In peson & online | See below for more details.

10 May 2023 - Sinem Demirci (UCL)

Date and Time:        Wednesday, 10 May 2023 12:00-13:00

Title and Abstract: "Pedagogical Content Knowledge in Data Science Education: An Assessment of Readiness to Teach Data Science in Higher Education"

Data science, which has an interdisciplinary nature, is a relatively new discipline that requires mastering many skills and concepts associated with statistics, computer science and mathematics. In this context, the issue of how to teach subjects and concepts in data science is still being evolved. On the other hand, the number of individuals employed in many occupational areas related to data science is increasing rapidly. Various studies are carried out in higher education to meet the increasing demand and to contribute to the literature; thus, more research on data science education is needed. To that end, the purpose of this talk is to introduce initial outcomes of our study, Pedagogical Content Knowledge (PCK) of the introductory data science instructors. PCK is one of the theoretical frameworks that provide an insight to an integration of content and pedagogy to teaching that enable instructors to monitor their teaching practices (Shulman, 1987). As the Introduction to Data Science course provides a baseline for understanding the nature of data science and promote capacity building, determining PCK of the instructors could provide an insight for the needs in data science education. Although the teaching materials and best practices based on the standards provide some clues on the needs, when viewed from the PCK framework, it is necessary to emphasize the PCK components of data science educators in a holistic way.

Location: Online | Join via Zoom

In-person location: Christopher Ingold Building, Ramsey Lecture Theatre G21

Online location: Please use the Zoom link to join online talks | https://ucl.zoom.us/j/91298863773


NameRoleEmail* ✉
Chak Hei (Hugo) LoLecturer (Teaching)chak.lo
Cecilia BusuiocAssociate Professor (Teaching)cecilia.busuioc
Alex DonovLecturer (Teaching)a.donov


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