Overall Grade: Distinction

Dissertation: Investigating the reproducibility of highly visible Social and Personality Psychology publications. Supervisor: Dr Reny Baykova.

Taught content included research reform and open science, advanced frequentist statistics, Bayesian statistics, qualitative research methods, and programming experiments in Python.

Overall Grade: 1st

Dissertation: Investigation into whether activity in the Zygomaticus Major and Corrugator Supercilii varies according to the emotional valence of mind-wandering thoughts. Supervisor: Dr Sophie Forster.

Taught content covered statistics, cognitive, social, educational, developmental, organisational, applied, health, and clinical psychology, as well as cognitive neuroscience and psychobiology. More specialised modules included psychology of consciousness, psychology of sleep, attention, and comparative psychology. I also completed six modules on British Sign Language and Deaf Culture

Skills developed:

• BSL CEFR level B2
• Analysing data in R
• fEMG data analysis

The Reality Bending Lab, run by Dr Dominique Makowski, applies experimental, computational, and neurophysiological methods to investigate how cognitive, emotional, and bodily mechanisms shape our experience of reality.

This position constituted part of my MRes. My main focus was a study seeking to validate a gamified measure of processing speed.

Key Contributions:

• Developed an experiment in javascript, integrating psychometric tasks, questionnaires, dynamic instructions and additional control features.
• Prepared ethics applications, recruitment materials, and OSF preregistration.
• Designed and piloted preprocessing and analysis pipelines in R, including data cleaning, validation checks, and visualisation.
• Contributed to two peer reviews and assisted with troubleshooting on other lab projects.

Skills developed:

• Programming behavioural experiments in JsPsych and Unity
• Reproducible data analysis, preprocessing, and visualisation in R
• Collaborative development using GitHub
• Academic writing and presentations
• Peer review

The School Inclusion Group, led by Dr Matt Easterbrook and Dr Ian Hadden, applies social psychological research and data-driven methods to help school leaders identify and overcome psychological barriers to belonging, attendance, behaviour, and attainment.

As an RA I developed a reproducible R script that automatically generates fully formatted .docx reports for participating schools, enabling analysis of differences in students' experiences and outcomes across demographic characteristics.

Key Contributions:

• Developed a reproducible R project to programmatically manipulate and analyse school-level datasets and produce fully formatted .docx reports.
• Parameterised workflow to increase flexibility and efficiency.
• Automated document formatting and structured reporting for consistent stakeholder outputs.
• Streamlined repetitive tasks, reducing error risk and improving workflow robustness.

As a Research Assistant for the University of Sussex School of Psychology Equality, Diversity and Inclusion (EDI) Committee, I developed reproducible R scripts to support three projects. Analyses for the Research Excellence Framework (REF) selection process, and Athena Swan focused on promoting gender equity, while the Inclusive Culture Survey (ICS) assessed differences in experiences, perceptions and opportunities across a wide range of demographic characteristics.

Key Contributions

• REF: Developed an R script to generate clear HTML summary reports including statistical analyses and visualisations of results, assessing gender differences in paper submission rates and testing for potential bias at each stage of the selection process.
• ICS: Designed a reproducible R script to produce interactive HTML reports with nested tables, descriptive and inferential statistics, and visualisations. The script was designed to handle annual datasets, updating current-year analyses while tracking changes over time.
• Athena Swan: Extracted gender-related findings from ICS data and automated exports to Excel and Word reports to support Athena Swan submissions.

Skills developed:

• Reproducible data analysis and visualisations using R
• Automated report generation from R into HTML, Excel, and Word
• Dynamic, multi-level, nested tables in HTML
• Clear communication of equity-related findings

The Sussex JRA Scheme offers high performing undergraduate students an opportunity to obtain funding (£1,600) to conduct a full-time research project over the summer, and concludes with an Undergraduate Research Poster Exhibition.

My project built on work I was involved in at Sussex Attention Lab, seeking to develop an EEG cap that easily and effectively accommodates all hair types. I worked under the supervision of Dr Chris Racey, with mentorship from Dr Paloma Manguele and Dr Andre Maia-Chagas.

The prototype was shown as part of Sussex Neuroscience Open Science Demos at the British Neuroscience Association 2023 International Festival of Neuroscience.

Skills developed:

• 3D design in FreeCAD and 3D printing using PrusaSlicer
• Collecting EEG data using antneuro and e-prime
• Preprocessing EEG data in MATLAB
• Creating academic posters

The Sussex Attention Lab, led by Dr Sophie Forster, applies cognitive psychology and cognitive neuroscience methods to investigate how and why attention fails in daily life, from external distractions to mind-wandering, and how these processes relate to individual differences and clinical conditions.

I undertook this role during a placement year as part of my undergraduate degree and was involved in two main projects:

• I joined the Inclusive Electrode Project (IEP) which aims to produce an open source EEG electrode system that holds electrodes in place equally well to conventional caps but overcoming the limits of caps when applied to individuals with voluminous, thick or curly hair. We presented this work at the Sussex Neuroscience Showcase (2022) and the Sussex Neuroscience Open Science Demos at the British Neuroscience Association 2023 International Festival of Neuroscience.
• I was heavily involved in conducting a new study that investigates associations between ADHD symptomatology and semantic distance in a word association task.

In addition to these, I provided supplementary support to various other projects.

Key contributions:

• Prepared a preregistration
• Prepared preprocessing and analysis scripts in R
• Reviewed literature and contributed to academic writing
• Assessed the reproducibility of a published paper
• Created a reproducible R script to produce personalised feedback reports for study participants.
• Participated in public demonstration events

Skills developed:

• EEG data collection including 10-20 system placement calculations
• 3D design using TinkerCAD
• Data analysis in R, SPSS, MPlus and MATLAB
• Creating academic posters.

My Pickle was a Community Interest Company that collated resources to improve accessibility and awareness of support services across a wide range social, health and well-being challenges.

As a volunteer researcher, I gathered information about national organisations to be listed on the website, and sought and reviewed life stories for publication.

Key Contributions:

• Self-taught web scraping in R to automate the collection of key search terms for service listings, improving efficiency and consistency in data gathering.
• Reviewed and edited life stories to ensure clarity and relevance, safeguard personal privacy, and maintain sensitivity in how experiences were shared.
• Researched and curated information on support services, ensuring comprehensive and accessible listings for site visitors.

This prize is awarded to the student who achieved the highest overall classification mark on a BPS accredited degree programme.

Awarded to the highest performing student for Psychology Foundation Year

In recognition of outstanding contribution to the Foundation Years Cohort

I contributed to this project during my research placement and in the final year of my BSc, with a focus on study design and data analysis.

Key Contributions:

• Designed experimental and control word lists by writing code to randomly generate two sets of CEFR A1 nouns, constrained so that both lists were matched on mean and standard deviation of word length.
• Conducted latent semantic analysis to obtain semantic distances between cues and participant responses.
• Performed statistical analyses (linear mixed-effects models and correlations)
• Contributed to the reporting of methods and results.