Please note that seats are limited, and registration will remain open until all spots are filled. Updates will be posted on the website as availability runs low.
Speakers
We are three postdoctoral researchers who became friends while overcoming the challenges of our PhDs. After years of struggle and growth, we realized the value of sharing the hard-earned knowledge we gained along the way. This led us to create DevStart—a platform where we share what we’ve learned through simple, accessible tutorials. Having presented at various workshops, we now want to take the next step and host our own, where we can have full control over what we teach and how we teach it.
Program Overview
Although this workshop will focus on leveraging Tobii eye-trackers for data collection, the concepts, preprocessing, and analysis techniques covered are universal and can be applied to eye-tracking data from any system.
Day 1
9-10: Help-desk setting up Python and R
Eye-Tracking Experiment Design and Data Collection
10:00 - 10:45 Theory of Eye-Tracking in Developmental Research
Introduction to eye-tracking technology and its applications in developmental science.Coffee break
11 - 11:45 Building Your First Eye-Tracking Experiment
Hands-on session to create a basic experiment in Python using PsychoPy.Lunch break
13 - 13:30 Coding Eye-Tracking Connection to Tobii Eye tracker
Learn how to integrate eye-tracking hardware with your experimental code for real-time data capture.13:30 - 14:15 Calibration with Tobii Infant Eye Tracker
Understand the steps required to calibrate eye-tracking equipment for use with infant participants.14:30 - 14:45 Data Collection
Learn best practices for collecting reliable and accurate eye-tracking data.Coffee break
15 - 16 Using I2MC for Robust Fixation Extraction
Process raw eye-tracking data and extract fixations using the I2MC algorithm.16 - 17:15 Measures of Interest
- Define and use AOIs (Areas of Interest) in your experiment.
- Focus on relevant time windows in eye-tracking data.
- Combine spatial and temporal parameters to extract meaningful metrics (e.g., saccadic latency, first fixation, looking time).
17:15 - 17:30 Conclusion and Q&A
Discuss the day’s topics, ask questions
Day 2
Data Analysis in R
9 - 9:30 Introduction to Linear Models in R
Learn the basics of linear models and their applications in analyzing experimental data.9:30 - 10 Linear Models with Continuous Variables, Categorical Variables, and Interaction Effects
Explore how to include different types of predictors in your models and interpret their effects.Coffee break
10:15 - 11:00 Estimating Effects, Means, and Contrasts
Understand how to extract meaningful insights from your models, including effects and group comparisons.11 - 12 Plotting the Results
Use R’s visualization tools to create clear, informative plots for presenting your results.Lunch break
13 - 13:45 Checking Model Assumptions
Learn diagnostic techniques to ensure your models meet key assumptions.13:45 - 14:45 Generalized Linear Models
Extend linear models to handle binary or count data, commonly used in developmental research.14:45 - 16 Mixed Effects Models (Random Effects)
- Understand the theory behind mixed-effects models.
- Learn how to include random intercepts and slopes in your analyses.
16 - 16:30 Wrap-Up and Discussion
Summarize key concepts and discuss how to apply these techniques in your research.18 - … Poster presentation
Poster Session
We are excited to host a poster session where participants can present their research, exchange ideas, and network with other attendees. The session will take place at the end of Day 2 and offers a fantastic opportunity to showcase your work, get feedback from peers, and spark potential collaborations. Whether you’re presenting or just attending, this session is a valuable addition to the workshop experience!
More details about the poster dimensions and guidelines will be shared soon, so stay tuned!
Material
Slides and presentation materials from the workshop will be shared on this website after the sessions, ensuring participants have access to all the key resources. However, most of the core material covered during the workshop is already part of the DevStart website, where it is available as detailed tutorials and documentation.
The DevStart website serves as the foundational resource for this workshop, offering step-by-step guides, experiment scripts, data processing pipelines, and statistical analysis tutorials. By building on these resources, the workshop aims to provide a practical, hands-on experience while promoting long-term learning and accessibility.
For any questions, feel free to reach out to us at: t.ghilardi@bbk.ac.uk.