This work was motivated by the need to enable teaching educational robotics and other STEM topics in online and blended modes supported by digital tools. This need has been highlighted by the outbreak of the covid-19 pandemic. This paper presents the research findings and outcomes of a systematic effort to design, implement, and demonstrate the feasibility of preparing, creating, and applying enhanced digital educational material for educational robotics activities using augmented reality technology. The integration of augmented reality with educational robotics was identified through the Group Concept Mapping methodology, and the feedback obtained was utilized to develop a co-design instructional methodology. To demonstrate this approach a universal framework is proposed, accompanied by two augmented reality implementations employing reusable digital assets.

Online learning’s popularity has surged. However, teachers face the challenge of the lack of non-verbal communication with students, making it difficult to perceive their learning-centered affective states (LCAS), leading to missed intervention opportunities. Addressing this challenge requires a system that detects students’ LCAS from their non-verbal cues and informs teachers in an actionable way. To design such a system, it is essential to explore field experts’ needs and requirements. Therefore, we conducted design-based research focus groups with teachers to determine which LCAS they find important to know during online lectures and their preferred communication methods. The results indicated that confusion, engagement, boredom, frustration, and curiosity are the most important LCAS and that the proposed system should take into account teachers’ cognitive load and give them autonomy in the choice of content and frequency of the information. Considering the obtained feedback, a prototype of two versions was developed. The prototype was evaluated by teachers utilizing the System Usability Scale (SUS). Results indicated an average SUS score of 80.5 and 74.5 for each version, suggesting acceptable usability. These findings can guide the design and development of a system that can help teachers recognize students’ LCAS, thus improving synchronous online learning.

Abstract Virtual reality technologies in educational settings have demonstrated their potential to improve understanding, engagement, motivation and learning outcomes. However, there are multiple technical, pedagogical, and institutional challenges on the way of technology adoption in the education sector. In this group-concept-mapping study within the CloudClass project we aim at identifying the requirements for implementing a desktop VR tool (CloudClass) for education in the university context. Teachers, multimedia experts and managers from a Spanish and a Dutch university (a face-to-face and a distance learning one) were asked to complete the focus prompt “ To use/implement CloudClass in education it is required/ needed that.… ”. The generated statements were classified thematically and rated for importance and feasibility. 95 unique statements were generated and sorted statistically into 5 clusters: Evaluation, Institutional Requirements, Maintenance and Training, Student Requirements, Affordances and infrastructure. A strong correlation was identified between the importance and feasibility of the identified clusters. To ensure a sustainable implementation of a desktop VR tool like CloudClass in a university setting a holistic approach considering all identified clusters is needed. Clusters Maintenance and Training and Institutional requirements are the low-hanging fruits to invest in, as both clusters scored highest on importance and feasibility.

Training facial emotion recognition models requires large sets of data and costly annotation processes. To alleviate this problem, we developed a gamified method of acquiring annotated facial emotion data without an explicit labeling effort by humans. The game, which we named Facegame, challenges the players to imitate a displayed image of a face that portrays a particular basic emotion. Every round played by the player creates new data that consists of a set of facial features and landmarks, already annotated with the emotion label of the target facial expression. Such an approach effectively creates a robust, sustainable, and continuous machine learning training process. We evaluated Facegame with an experiment that revealed several contributions to the field of affective computing. First, the gamified data collection approach allowed us to access a rich variation of facial expressions of each basic emotion due to the natural variations in the players' facial expressions and their expressive abilities. We report improved accuracy when the collected data were used to enrich well-known in-the-wild facial emotion datasets and consecutively used for training facial emotion recognition models. Second, the natural language prescription method used by the Facegame constitutes a novel approach for interpretable explainability that can be applied to any facial emotion recog-nition model. Finally, we observed significant improvements in the facial emotion perception and expression skills of the players through repeated game play.

Over the past few years, massive online open courses (MOOCs) have been increasingly identified as technologies that could transform education, by providing free and high-quality content to anyone with an Internet connection. However, despite these potentials, MOOCs generally fail to keep their participants on board. One of the reasons for this phenomenon can lie in a lack of participants’ engagement. Social presence and sense of community (SoC) theories claim that a user in an online shared environment may feel more engaged if s/he perceives the others as ‘real persons’ and feels part of a community. Therefore, we developed our game elements with the purpose of developing social presence and SoC among MOOC users. The results of our experiment, from one side, show that our gamification design did positively impact users’ development of social presence and SoC, as well as their learning performance. From the other, data did not confirm that higher levels of social presence and SoC corresponded to higher engagement of MOOC users. These results have important implications for the field by enriching it with a more technologically enhanced approach towards implementing gamification, and by augmenting the social potentials of MOOCs.

This paper introduces the Visual Inspection Tool (VIT) which supports researchers in the annotation of multimodal data as well as the processing and exploitation for learning purposes. While most of the existing Multimodal Learning Analytics (MMLA) solutions are tailor-made for specific learning tasks and sensors, the VIT addresses the data annotation for different types of learning tasks that can be captured with a customisable set of sensors in a flexible way. The VIT supports MMLA researchers in 1) triangulating multimodal data with video recordings; 2) segmenting the multimodal data into time-intervals and adding annotations to the time-intervals; 3) downloading the annotated dataset and using it for multimodal data analysis. The VIT is a crucial component that was so far missing in the available tools for MMLA research. By filling this gap we also identified an integrated workflow that characterises current MMLA research. We call this workflow the Multimodal Learning Analytics Pipeline, a toolkit for orchestration, the use and application of various MMLA tools.

Gamification in engineering education has been applied with success in the last years. Also, Massive Open Online Courses (MOOCs) are recognized as a good strategy to enhance engineering education. Nevertheless, MOOCs have two main weaknesses: first, lack of addressing personal goals; and second, low completion rates in comparison to the number of registrations to the MOOCs. To improve learning experiences in MOOCs and to strengthen self-regulated personalized learning we propose the application of gamification in MOOCs. Our assumption is that MOOC learners will better succeed in achieving their goals if they can individually personalize and plan their learning paths through gamification. This assumption is based on the implementation intention theory which claims that people who foster their goal intentions with implementation intentions are comparatively more successful in their personal goal achievements. Based on a preliminary literature review this article presents and arguments on our research idea on how to apply gamification to enhance MOOC users' goal achievement. Besides, it introduces a new perspective on MOOC completion rates based on the user intention and a new way of measuring it via the Personal Goal Achievement Ratio (PGAR) and the Overall Goal Achievement Ratio (OGAR).

This paper reports on an iterative design process for a serious game, which aims to raise situational awareness among different stakeholders in a logistics value chain by introducing multi-user role-playing games. It does so in several phases: After introducing the field of logistics as a problem domain for an educational challenge, it firstly describes the design of an educational board game for the field of disruption handling in logistics processes. Secondly, it describes how the board game can be realized in an open-source mobile serious games platform and identifies lessons learned based on advantages and issues found. Thirdly, it derives requirements for a re-design of the mobile game and finally draws conclusions.

This paper reports on the development of WeBuild, a mobile learning game designed to engage learners difficult to reach with IT learning. The development is based on a mobile game engine for the Android smart phone that was devised to support the required multiplayer and location based services. We played and tested the mobile learning game in a training facility of the building industry. The results indicate that the learners accepted the game for the low entry barriers and were motivated to use the game in an educational context. This paper describes the WeBuild prototype and the underlying game engine. Eventually, it presents results from the game session that was carried to assess interface and gameplay usability, technical functionality and motivational aspects of the game design.

User-driven annotation of learning content allows the user to interact with it in a flexible and an intuitive manner and hence personalize the content. This interaction, in most cases, follows the "paper and pen" note-taking paradigm. Though not without its advantages, this paradigm does not scale when the courses are delivered online as web pages. These paper notes are not synchronous with the content, hence may seem out of context, they may be misplaced, and don’t make allowances for collaborative learning. In this paper we describe u-Annotate, a user-driven freeform digital ink annotation application for web e- Learning content which aims at facilitating the learner to annotate the online content with the aid of pen computing devices such as graphic tablets, etc. Learners can freely mark up the content, save the annotations for recall at a later date, as well as share these with other learners.