Retrieval of Relevant Data for Measuring the Impact of SpacedRepetition Algorithms on the Learning Success in Mobile Learning Games This paper presents an approach on how to retrieve relevant data from a huge set of gamedata in order to find evidence for the impact of using spacedrepetition algorithms on the learning success in a mobile learning game. After having collected approximately 12 million sets of playing data, the database needs to be preprocessed before analyzing it in order to filter out any data that is irrelevant or useless for our analysis or may even dilute its results. One structured and established way to do this is to follow the KDD process, which includes several consecutive steps of consolidating the available data, with preprocessing it being one of them. In order to be able to define the data were are looking for, we set up some proposals about how the relevant data should look like and how to retrieve it from our database.

Development of Mobile Application for Word Reordering Problems: An Attempt Oriented to Learning Analytics The authors have developed a mobile application for Word Reordering Problems (WRPs) which was designed to collect learnersu0027 study logs, such as finger trajectories, to calculate parameter values used in detecting hesitation of learners. Additionally, the authors also have developed a simple Learning Management System (LMS) to store learnersu0027 study logs and visualize various parameters or data charts generated by the logs. By comparing the study logs collected on the WRP mobile application with its web version, it is discussed whether or not the parameters provided by the mobile application could also be used to locate the hesitation correctly as previously researched using web application with supervised learning. Another objective of this research is to exploit the practical use of new data types provided by physical sensors embedded in mobile devices. A pilot study showed how the accelerometer values are influenced in the event of accidents such as a sudden stop of a train. By analyzing multiple new data types, we attempt to acquire more information in the process of solving WRPs on mobile devices.