Martin Schön

It's just about learning the multiplication table

One of the first and basic mathematical knowledge of school children is the multiplication table. At the age of 8 to 10 each child has to learn by training step by step, or more scientifically, by using a behavioristic learning concept. Due to this fact it can be mentioned that we know very well about the pedagogical approach, but on the other side there is rather less knowledge about the increase of step-by-step knowledge of the school children. In this publication we present some data documenting the fluctuation in the process of acquiring the multiplication tables. We report the development of an algorithm which is able to adapt the given tasks out of a given pool to unknown pupils. For this purpose a web-based application for learning the multiplication table was developed and then tested by children. Afterwards so-called learning curves of each child were drawn and analyzed by the research team as well as teachers carrying out interesting outcomes. Learning itself is maybe not as predictable as we know from pedagogical experiences, it is a very individualized process of the learners themselves. It can be summarized that the algorithm itself as well as the learning curves are very useful for studying the learning success. Therefore it can be concluded that learning analytics will become an important step for teachers and learners of tomorrow.

Learning Analytics: From Theory to Practice - Data Support for Learning and Teaching

Much has been written lately about the potential of Learning Analytics for improving learning and teaching. Nevertheless, most of the contributions to date are concentrating on the abstract theoretical or algorithmic level, or, deal with academic efficiencies like teachers’ grading habits. This paper wants to focus on the value that Learning Analytics brings to pedagogic interventions and feedback for reflection. We first analyse what Learning Analytics has to offer in this respect, and, then, present a practical use case of applied Learning Analytics for didactic support in primary school Arithmetic.

Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication

In this work we focus on a specific application named “1x1 trainer” that has been designed to assist children in primary school to learn one digit multiplications. We investigate the database of learners’ answers to the asked questions by applying Markov chain and classification algorithms. The analysis identifies different clusters of one digit multiplication problems in respect to their difficulty for the learners. Next we present and discuss the outcomes of our analysis considering Markov chain of different orders for each question. The results of the analysis influence the learning path for every pupil and offer a personalized recommendation proposal that optimizes the way questions are asked to each pupil individually.

Automated podcasting system for universities

This paper presents the results achieved at Graz University of Technology (TU Graz) in the field of automating the process of recording and publishing university lectures in a very new way. It outlines cornerstones of the development and integration of an automated recording system such as the lecture hall setup, the recording hardware and software architecture as well as the development of a text-based search for the final product by method of indexing video podcasts. Furthermore, the paper takes a look at didactical aspects, evaluations done in this context and future outlook.