Modeling difficulty of English exercises - probabilistic programming approach
Selecting test exercises with an appropriate difficulty level is one of the most important aspects of a high-quality assessment, but how do we know how difficult a given exercise is?
One of the possible approaches is to use Item Response Theory - a set of psychometric models which can be used to estimate learners’ proficiency and parameters of each exercise. This approach works well in most cases, however, is data intensive. So, the question arises what to do when we don't have enough data, when for example, we are introducing some new exercises.
Fortunately, probabilistic programming comes to our aid. Using Greta, we can build a custom IRT model, that allows us to quantify how different features of exercises impact their difficulty. In this talk, we will introduce the audience to the basics of IRT and probabilistic programming through a real-world application - estimating the difficulty of English tasks. For this purpose, we will use the previously mentioned Greta package, which lets us write statistical models in native R and sample from them automatically and efficiently.
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### Our Speaker
Damian Wiatrzyk
LinkedIn https://www.linkedin.com/in/damian-wiatrzyk-91803072/
Damian Wiatrzyk graduated from the Poznań University of Technology with a Bachelor's degree in Computer Science. Currently, he is studying for a Master's degree in Data Science at Adam Mickiewicz University and working as an Associate Data Scientist at Pearson IOKI.
### ABOUT THE X-EUROPE DATA SCIENCE WEBINARS
X-Europe Webinar Series is a joint online event of Vienna Data Science Group, Frankfurt Data Science, Budapest Data Science Meetup, BCN Analytics, Budapest.AI, Barcelona Data Science and Machine Learning Meetup, Budapest Deep Learning Reading Seminar, Warsaw R Users Group, PyData Slovakia, and Data Scientists Ireland.
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