Introduction to Language Processing and Online Methods

Duygu Özge, METU

Natural language, especially in spoken form, quickly unfolds in real-time like a flowing stream and it is full of ambiguities; yet, humans mostly spend no conscious effort to extract meaning out of an utterance. In the first part of this course, we will explore what we know about the nature of human language processing capacity, and whether child parsing is qualitatively different from adult parsing. In the second part, we will review major online methods that allow us to investigate the mechanisms and processes underlying human language processing ability.

Introduction to Data Analysis in R

Martin Corley, University of Edinburgh

This is an introductory class for statistics using R for the novice. The first session covers the essentials of statistics in R such as plotting and calculating descriptive statistics, data manipulation, tidyverse R vs base R, simple graphics. The second session is devoted to basic and advanced methods of inferential statistics. We will start out with statistical inference, (generalized) linear models, categorical predictions, repeated measures, and then, time permitting, we will introduce mixed-effects logistic regressions.

Introduction to Data Visualization Using Python

Çağatay Türkay, University of Warwick

As an interdisciplinary discipline building on areas such as computer science, cartography, art, design, perception, cognition and statistics, data visualisation is now established as a methodology that is widely used both for communication of data and data artefacts, and also to explore and critically engage with data. Whether it is for data-driven decision making, exploratory analysis or scientific reporting, visualisation is a key element of any effective data-intensive process. The first part of the course will briefly discuss the theoretical underpinnings of visualisation research to build an understanding of basic principles and building blocks of visualisation design. The second part of the course will explore the issues and topics discussed in the first part through practical exercises where students will develop data visualisations using the Python programming language.

Designing and Analyzing Experiments in Visual-world Eye-tracking Paradigm

Hugh Rabagliati, University of Edinburgh

The visual world paradigm provides a naturalistic window into how we process language. In the first part of this course, I will describe the foundations of the method, and how it can be applied to study language and comprehension and production, with an emphasis on applying it to special populations. In the second part, I will focus on statistical analysis, and the pitfalls and opportunities provided by this method. Students should leave the class able to critically evaluate studies that use this paradigm, and be prepared to design their own experiments.

Designing and Analyzing Reading Experiments in Eye-tracking

Cengiz Acartürk, METU

Reading, in its most basic form, may be conceived as information extraction from text. The eyes jump on the text during reading, by producing so-called saccades and fixations, as well as more complex movements that are identified by specific patterns of them, such as regressions.  In this course, the students will learn how reading researchers design experiments depending on specific research objectives, how they prepare stimuli for data collection, how they collect data and how they analyze collected data for building computational models of reading.

Testing and Evaluating Narrative Abilities in Children

Maria Andreou & Vasileia Skrimpa, University of Cologne

Testing and Evaluating Socio-cognitive Abilities in Children with Autism Spectrum Disorder

Rachael Davis, University of Edinburgh

Traditionally, autism has been conceptualised by difficulties in social interaction and communication. However, there are currently a lack of definitive findings regarding differences in how autistic people interact and communicate with others. This is due, at least in part to the variability between autistic individuals and the methodologies that have been adopted.

In the first half of the course, we will discuss definitions and historical accounts of autism. We will focus on social theories and critically evaluate the evidence so far. In the second half of the course, we will review some of the most commonly used methods to evaluate socio-cognitive abilities in autistic people. This will introduce inclusive measures that can used for children with wide-ranging abilities. We will also consider how the neurodiversity movement is influencing methodological approaches that will be used with autistic children in future research.