A critical review of 13 years of mobile game-based learning

With the increasing popularity of smartphones and tablets, game-based learning (GBL) is undergoing a rapid shift to mobile platforms. This transformation is driven by mobility, wireless interfaces, and built-in sensors that these smart devices offer in order to enable blended and context-sensitive mobile learning (m-Learning) activities. Thus, m-Learning is becoming more independent and ubiquitous (u-Learning). In order to identify and analyze the main trends and the future challenging issues involved in designing mGBL learning strategies, as well as to bring to the foreground important issues pertaining to mobile and context-aware ubiquitous GBL, the work at hand conducts a comprehensive survey of this particular area. Specifically, it introduces and applies a six-dimensional framework consisted of Spatio-temporal, Collaboration/Social, Session, Personalization, Data security & privacy, and Pedagogy, with the aim of scrutinizing the contributions in the field of mGBL published from 2004 to 2016. It was found that the transition to mGBL presents several difficulties, and therefore cannot be conceived as a simple and quick modification of existing GBL solutions. In this respect, this work is anticipated to foster the development of well-designed solutions that are intensive not only in their technological aspect, but in pedagogical qualities as well.     

Real vs virtual physics experiments: comparison of learning outcomes among fifth grade primary school students. A case on the concept of frictional force

This paper compares students’ conceptual understanding of a standard physics law, i.e. frictional force, following the execution of real vs virtual experiments. The research sample was made up of 110 fifth grade students attending a primary school in the city of Ioannina, Northwestern Greece who were randomly assigned to either the control group (55 students) or the experimental group (55 students). The control group carried out experiments with real world objects, while the experimental group used Interactive Physics simulation software. Data was collected by administering to both groups identical pre and post tests, before and after the experiments respectively and which contained six questions each. The SOLO taxonomy model was used to evaluate student answers and the findings reveal that both experimentation methods are equally effective in the conceptual understanding of frictional force.     

Multi-technique comparative analysis of machine learning algorithms for improving the prediction of teams’ performance

Education and Information Technologies - Working in groups is an important collaboration activity in the educational context, where a variety of factors can influence the prediction of the...