Science Practice Hub - A new space for scientific exchange and development

The Science Practice Hub (SciPHub) provides a space for researchers across faculties to reflect on science practices critically and share expertise to strengthen the capability of research. It is a joint initiative from the Centre for Research and Enterprise in Language (CREL) and the Institute for Lifecourse Development (ILD), open to every interested researcher.

  • Science dialogues (Dr Uher): regular seminars led by volunteers (research staff). Active and constructive dialogue among scholars from different sciences about key topics in the making of science (e.g., objectivity, scientific terms, measures).
  • ReproducibiliTea Journal Club (Dr Samara): UK Reproducibility Network supported journal club on Open & Reproducible Science; discussion on reproducibility/replication, meta-science.
  • Practice workshops (Dr Palacios): focused on quantitative and computational methods as well as mathematical modelling applied to language questions.
  • Science lectures (Dr Arche): lectures given by guest speakers on controversial issues on science practice (e.g., methodology, epistemology).

Leaders and founding members

  • Dr Maria J Arche - CREL Director, Associate Professor of Linguistics & Spanish
  • Dr Jana Uher - Senior Lecturer in Psychology, School of Human Sciences
  • Dr Anna Samara - Lecturer in Psychology, School of Human Sciences
  • Dr Ana Paula Palacios - Senior Lecturer in Statistics, School of Computing & Mathematical Sciences


ReproducibiliTEA Journal Club

ReproducibiliTEA Journal Club is an international network initiative that has now spread to 117 institutions in 25 different countries. The main goal of ReproducibiliTEA is to create opportunities for discussion about various themes in and around the Open Science movement.

Who it is for: While ReproducibiliTea was born in psychology and the social sciences, we are explicitly recruiting across disciplines, as these issues affect every corner of science. This means that everyone is welcome, whether you've never heard about open science or are an expert, are an economist, historian, biologist, computer scientist, or anything else.

When will it take place: Meetings are currently scheduled to take place on Fridays (13.00-14.00) every three weeks

To participate, we recommend reading the main article in the link in advance, but understand that this will not always be possible. One or more discussion leaders will come prepared with a brief summary of the paper to get everyone on the same page, and some questions to get the conversation started. We'll proceed with lively discussion, and will each hope to leave a slightly better researcher than we arrived!

14 May 2021 | Does qualitative research seek reproducible findings?

Dr Oliver Robinson, Associate Professor of Psychology
Time: 1:00-2:00pm

Location: Online via MS Teams join the session here

Our next and final ReproducibiliTEA session for the academic year will be led by Dr Oliver Robinson, Associate Professor of Psychology, School of Human Sciences. Dr Oliver Robinson will lead a session entitled “Does qualitative research seek reproducible findings?", followed by discussion on reproducibility issues pertaining to qualitative methods of research.

Link to article

26 March 2021 | Low replicability can support robust and efficient science

Dr. Karolina Janacsek, Associate Professor in Human Sciences

This session will be led by Dr. Karolina Janacsek. Karolina is an Associate Professor in Human Sciences with expertise in the psychological and neural basis of procedural memory, and more broadly, Experimental and Clinical Neuroscience. Karolina will discuss a recent paper by Lewandowsky and Oberauer which suggests, based on modelling data, that publication of potentially nonreplicable single studies could help minimize cost (waste of resources) and support efficient science.

Link to article

5 March 2021 | Replication in Second Language Research

Luigi Palumbo, Double degree PhD student (Greenwich-Groningen)

The session will be led by Luigi Palumbo, PhD student co-supervised by Dr Maria Arche. Luigi will summarize and discuss a paper by Emma Marsden and colleagues that makes interesting reflections on the replication crisis and how it affects second language acquisition research.

Link to article

12 February 2021 | Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them

Dr. Thomas Evans, Associate Professor in Occupational Psychology

This session will be led by Dr. Thomas Evans, Associate Professor in Occupational Psychology in the School of Human Sciences. Tom will discuss a recent paper published in Psychological Science by Flake & Fried (2019) on questionable measurement practices and how to avoid them.

Link to article

22 January 2021 | To Which World Regions Does the Valence-Dominance Model of Social Perception Apply?

Dr Harry Farmer, Lecturer in Psychology

Dr Harry Farmer will present on the Psychological Science Accelerator, an interesting new project that aims to bring together researchers in a globally distributed network of psychological science laboratories that coordinates data collection for democratically selected studies.

Link to article

Practice workshops

18 November 2020 | Frequentist statistical analysis: foundational ideas and common mistakes

Dr Malgorzata Wojtys (University of Plymouth)
Presentation Slides | Video

Adherence to standards of rigor and transparency when performing statistical analyses in linguistic research is crucial in obtaining reliable and trustworthy results. In recent years, many systematic reviews pointed out a number of problems in this area such as experiments not being reproducible, statistical assumptions not being carefully checked or misinterpreting results of statistical procedures and drawing unjustifiable conclusions. In this talk, we focus on fundamental ideas underlying some of the most popular frequentist statistical methods used in linguistic research with an aim to improve and deepen participants' understanding of those methods. We will review concepts related to hypothesis testing such as the significance level, the p-value, the power, Type I and Type II errors with a focus on their meaning and interpretation. Statistical assumptions underlying hypothesis testing will be discussed and illustrated using examples. The most common mistakes and misconceptions will be emphasized. Further examples involving analysis of variance (ANOVA) and linear mixed models will be presented.