This paper presents an overview of Educational Robotics (ER) in primary and pre-school education. As ER seems to be gaining popularity for its effectiveness as a learning tool, more research needs to be done in this area. Recent results from ER pilot projects advocate for the integration of ER in K-12 education curricula. On the other hand, teachers may face various difficulties in carrying out such activities due to lack of experience or knowledge in this field. Previous research has shown that ER is still an open field for exploration. Even though an increasing number of experiences are available for the use of robotic tools in early education, there is not enough empirical evidence on the features they need to present for young learners to perceive them as attractive and easy to use. In addition, the high cost of some tools may prevent educational institutions from using them systematically. To detect possible gaps in the current research, in the context of this work, 21 articles that have been published between 2011-2021 and represent ER applications and frameworks were collected and reviewed. The results of this study demonstrate that ER can be a valuable tool for supporting primary and pre-school students. However, the review supports that more research is needed on the technical features that a robotic tool must have to be successfully introduced to students of this age. Moreover, future work is needed to develop low-cost educational robotic tools so they can become more accessible to educational institutions.

During the past decade the educational data research is rapidly growing. The use of technology in education has created the need to store and manage large amounts of data that come from various sources and have different formats. Educational data can be used to benefit educational systems and the science of learning. The project "Augmented Reality Interactive Educational System" (ARETE) funded by EU Programme Horizon 2020 aims to support interactive technologies for the provision of Augmented Reality (AR) content through an open source learning management system and authoring toolkit for the broader community of users. The utilisation of educational data is vital for the efficient data management and the two relevant areas of focus in review that focus on the use of educational data to support education are the Educational Data Mining (EDM) and Learning Analytics (LA). Several studies have been published recently focusing on applications using educational data, revealing that educational data analytics is an evolving science, where researchers have explored the various use cases of applying data mining and analytics techniques on the educational domain. However, there is still a need for exploring the main objectives of applying EDM and LA techniques and defining the specific problems in the educational domain they try to resolve. The aim of this analysis is to identify studies' objective trends that recent applications are trying to achieve and to identify potential research gaps. The possible correlation between the use of particular types of techniques used by the EDM/LA applications in relation to the goals they are trying to achieve is also being presented. This paper presents the review of EDM and LA empirical studies that have been published between 2016 to 2020. To gain insight into the trend direction of the different projects, the publications are clustered based on the methods applied and the purposes those studies tried to accomplish. Studies that applied more than one technique were assigned to the method groups more than once. This paper will provide an association table of EDM/LA techniques and the objectives for which they have been used, and will serve as a model for other researchers in order to choose the method for their own specific goals. Finally, the goals that recent EDM and LA applications are approaching will be presented, which can be a source of inspiration for further research questions, by providing information on areas of educational goals that remain unexplored or have not received much attention so far.

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The current work is a proposal for Moodle administrators who aim to provide content creators and teachers with capabilities to describe in a semi-automatic way their learning resources with LOM-based metadata and make these metadata available to search service providers so that other stakeholders can easily find and retrieve them. It was composed within ARETE project to support reusability and discoverability of 3D/AR and other types of educational resources included in the project’s Moodle digital repository.Aiming on utilizing previous work on this domain, the code of two existing plugins was modified and enriched to serve the project’s needs. This paper aims to demonstrate in detail two plugins that will be utilized in ARETE’s Moodle digital repository to support the discoverability of learning resources by creating and exposing their metadata to make them available for harvesting. The content in the ARETE repository is particularly relevant to 3D/AR learning activities created through an XR authoring toolkit. Nevertheless, educational content in other formats continues to be supported by the aforementioned plugins.The integration of IEEE-LOM and OAI-PMH standards to a Moodle repository seems to be a feasible way to enhance the development of learning content by utilizing relevant already existing resources that can be easily found and retrieved. However, the difficulty of finding service providers that could support the collection of learning resource metadata and be willing to build search engines on top of them suggests the need to consider different approaches.

Augmented reality (AR) is rapidly emerging as an increasingly useful technology in educational settings. In the ARETE (Augmented Reality Interactive Educational System) H2020 project, consortium members designed and implemented an ecosystem aimed at supporting teachers in building a collaborative learning environment through the use of AR in order to improve educational experiences. In particular, one of the pilot projects aims to introduce AR into school behavior lessons for the first time, leveraging the Positive Behaviour Intervention and Support (PBIS) methodology. Specifically, in this paper we will discuss the proposed architecture within the ARETE project that incorporates AR technology into the learning process of behavior lessons to support the teaching, practice and reinforcement phases of expected behaviors. Through the combination of different technologies and systems, it is possible to create an example of a technological and innovative ecosystem designed for creating behavioral lessons in AR.