One of the main drawbacks of delivering new teaching lessons in e-learning systems is the lack of motivation for using those systems. This paper analyses which elements of computer games for learning mathematics have a beneficial effect on intrinsic motivation and give students continuous feedback in order to improve the learning process. While the control group has access to the basic version of the educational computer game, the experimental group uses the version enriched with additional motivational elements which include enhanced graphics for indulging in the game, messages of support while playing the game, and the possibility to compare results with fellow peers in terms of trophies and medals won.
Group work and student collaboration during problem solving sessions are teaching methods which positively affect learning outcomes and socialisation. It is extremely complex to find a way of applying these methods to make them appropriate for and interesting to the new digital generation of students. This paper proposes a model which enables social network collaboration between primary school students within the system for mobile game-based learning of mathematics. It also suggests technology and proposes a general model which enables researchers to access anonymized data, teachers to keep track of student progress, and students to keep track of their own progress relative to other students, all at the same time. A microblogging social network service is integrated in the system in a way that enables sending messages without additional authentication and thus facilitates dynamics of the system. The proposed model enables mining of anonymized data streams originating from both the game and the social network. In this paper the model is used for the analysis of concepts which students most often publish, and for the analysis of their correlation with other activities within the system. Social network posts are analysed with the aim to detect students capable of taking advanced classes which cover more complex areas than the regular curriculum.
STEM education forms a basis for an innovation-based society, and Mathematics is, besides being an integral part of STEM, also a prerequisite for success in mastering remaining STEM constituents. With the aim of early detection of gifted students, who would be able to follow advanced forms of teaching and be successful in STEM, this paper analyses cognitive predispositions of students gifted for Mathematics and the differences in their ways of solving problem tasks in the computer game for learning primary school Mathematics. Additionally, the paper analyses success related to finishing different levels of the game.
The paper gives an overview of the state of the art methods and technologies in the field of stream data mining with applications in the Internet of Things systems for supporting fruit cold chain logistics. As the number of sensors used in on-line monitoring of the process is large, the amount of time series data is increasing rapidly. It is challenging to process such data in order to discover patterns, trends and outliers as a consequence of fluctuations of certain process parameters. In particular, the paper discusses methods for mining stream data collected in fruit cold chain aiming at real time control of fruit quality. A model of the centralized IoT system and the part responsible for monitoring fluctuations of temperature, humidity, and concentration of gases is proposed.
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