Designing adaptivity in educational games to improve learning

The study of pedagogy has shown that students have different ways of learning and processing information. Students in a classroom learn best when being taught by a teacher who is able to adapt and/or change the pedagogical model being used, to better suit said students and/or the subject being taught. When considering other teaching mediums such as computer-assisted learning systems or educational video games, research also identified the benefits of adapting educational features to better teach players. However, effective methods for adaptation in educational video games are less well researched.This study addresses four points regarding adaptivity within educational games. Firstly, a framework for making any game adaptive was extracted from the literature. Secondly, an algorithm capable of monitoring, modelling and executing adaptations was developed and explained using the framework. Thirdly, the algorithm's effect on learning gains in players was evaluated using a customised version of Minecraft as the educational game and topics from critical thinking as the educational content. Lastly, a methodology explaining the process of utilising the algorithm with any educational game and the evaluation of said methodology were detailed

The applications of games with a purpose used for obtaining annotated language resources

Istnienie problemów AI-zupełnych przyczyniło się do poszukiwań alternatywnych sposobów rozwiązywania problemów sztucznej inteligencji, nie opartych wyłącznie na pracy komputera. Pomimo że komunikacja jest dla ludzi czymś oczywistym, nadal nie istnieje sposób jej automatyzacji. Aktualnie powszechnie stosowanym podejściem w rozwiązywaniu problemów NLP jest podejście statystyczne, którego powodzenie zależy od wielkości korpusu językowego. Przygotowanie rzetelnego zbioru danych jest zatem kluczowym aspektem tworzenia statystycznego systemu sztucznej inteligencji. Z uwagi na zaangażowanie specjalistów jest to proces czasochłonny i kosztowny. Jednym z obiecujących podejść, pomagających zredukować czas i koszt tworzenia otagowanego korpusu, jest korzystanie z gier skierowanych na cel. Ambicją niniejszej pracy jest przybliżenie poszczególnych etapów tworzenia gry przeznaczonej do pozyskania zasobów językowych oraz omówienie skuteczności jej działania. Analiza ta zostanie przeprowadzona na podstawie kolekcji gier Wordrobe wspierających anotacje korpusu języka naturalnego.The existence of AI-complete problems has led to a growth in research of alternative ways of solving artificial intelligence problems, which are not based solely on the computer. Although for us communication is obvious, there is still no way automate it. The current widely-used approach to solving the problems of NLP is a statistical one, whose success depends on the size of the training corpus. The preparation of a reliable set of data is therefore a key aspect in creating an artificial intelligence statistical system. Due to the involvement of a large number of specialists this is a very time-consuming and expensive process. One promising approache in helping reduce the time and cost of creating a tagged corpus is the use of games with a purpose. The objective of this paper is to present the stages of creating games with a purpose used for obtaining annotated language resources and to discuss its effectiveness. This analysis will be done based on the Wordrobe project, a collection of games created to support the gathering of an annotated corpus of natural language