To benefit from most of the current digital educational technologies, learners are required to sit down and look closely at a computer monitor or smart device screen for hours, which can have side effects on learners’ health and lifestyle. As an attempt to address this, we developed MathKinetics, an application designed to support the practice of cognitive skills such as arithmetic while engaging in physical activity by integrating the principles of Multimodal Learning, Life Kinetik, and Gamification. MathKinetics is a variant of an endless running game where users control an avatar through their body posture and dodge obstacles. At the same time, they pick up arithmetic problems whose answers need to be verbalized. In this paper, we present an exploratory evaluation of MathKinetics and its user experience. We conducted user tests with 20 participants. Results from our tests indicate that MathKinetics is a fun way to practice arithmetic skills and train executive cognitive functions such as task switching.

When reading long and complex texts, students may disengage and miss out on relevant content. In order to prevent disengaged behavior or to counteract it by means of an intervention, it is ideally detected an early stage. In this paper, we present a method for early disengagement detection that relies only on the classification of scrolling data. The presented method transforms scrolling data into a time series representation, where each point of the series represents the vertical position of the viewport in the text document. This time series representation is then classified using time series classification algorithms. We evaluated the method on a dataset of 565 university students reading eight different texts. We compared the algorithm performance with different time series lengths, data sampling strategies, the texts that make up the training data, and classification algorithms. The method can classify disengagement early with up to 70% accuracy. However, we also observe differences in the performance depending on which of the texts are included in the training dataset. We discuss our results and propose several possible improvements to enhance the method.

In recent years, Learning Analytics (LA) has become a very heterogeneous research field due to the diversity in the data generated by the Learning Management Systems (LMS) as well as the researchers in a variety of disciplines, who analyze this data from a range of perspectives. In this paper, we present the evaluation of a LA tool that helps course designers, teachers, students and educational researchers to make informed decisions about the selection of learning activities and LA indicators for their course design or LA dashboard. The aim of this paper is to present Open Learning Analytics Indicator Repository (OpenLAIR) and provide a first evaluation with key stakeholders (N=41). Moreover, it presents the results of the prevalence of indicators that have been used over the past ten years in LA. Our results show that OpenLAIR can support course designers in designing LA-based learning activities and courses. Furthermore, we found a significant difference between the relevance and usage of LA indicators between educators and learners. The top rated LA indicators by researchers and educators were not perceived as equally important from students' perspectives.

In order to obtain a holistic perspective on learning, technical infrastructure at an institutional level can be advantageous for Learning Analytics (LA). If personal data is collected and processed in such infrastructure, legal requirements are of crucial importance. Recent studies have examined various aspects of LA infrastructure, such as ethical trade-offs and stakeholder needs. However, strategies for designing technical LA infrastructure at the institutional level and strategies for dealing with data protection regulations have been lacking so far, although they are crucial for the adoption of LA in Europe. The purpose of this paper is to examine three research questions: (RQ1) which strategies are currently used to design LA infrastructure; (RQ2) how data protection and privacy affect the design of LA infrastructure; and (RQ3) how could technical measures support the adoption of LA. These research questions were investigated by conducting eleven interviews with LA infrastructure developers representing eight different higher education institutions and ten different infrastructures. According to RQ1, the paper first examines the domain specificity of LA infrastructure and the four design strategies used. The paper also examines, according to RQ2, the interviewees’ awareness of data protection, the conflict with users’ consent, and the data subject rights. Finally, the paper presents, in line with RQ3, the results of the strategies in dealing with trust, stakeholder expectations, and engagement. Researchers and infrastructure developers can use and adopt these findings to improve their strategies for developing technical LA infrastructure with regard to data protection, privacy, and trust.

We report the results of a study that investigated the usage of a consumer-grade smartwatch for associative media learning. In a study with 29 participants, we investigated the effects of learning the Morse code alphabet purely visual versus learning with an associated vibration pattern. Our results show a trend that participants who received the vibration stimulus in addition to the visual stimulus learned faster and retained more knowledge than the group who learned using only the visualization, as measured by two post-tests one and three days after the learning took place.

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.

The increasing accessibility of sensors allows the study and development of multimodal learning tools that create opportunities for learners to practice while receiving feedback. One of the potential learning scenarios addressed by these learning applications is the development of public speaking skills. First applications and studies showed promising empirical results in laboratory conditions. In this article we present a study where we explored the use of a multimodal learning application called the Presentation Trainer, supporting learners with a real public speaking task in the classroom. The results of this study help to understand the challenges and implications of testing such a system in a real-world learning setting, and show the actual impact compared to the use in laboratory conditions.

The acquisition of knowledge is a key aspect for learners. However, in moments of stress the cognitive capacities of learners decrease considerably, making it very difficult for learners to get access and use their already acquired knowledge. Therefore we developed The Booth, a prototypical toolkit designed to support learners to prepare for key situations that are foreseen to be stressful. It guides the learner through a series of lectures helping them to gain personal power, and become in touch with their sincere-self. This paper presents the prototype, including the description of its technical aspects and the theory behind its lectures.

The increasing accessibility of sensors has made it possible to create instructional tools able to present immediate feedback to their users. In order to study how this type of instruction can have an effect on learning, we created the Presentation Trainer : a prototype designed to help users to develop their nonverbal communication skills for public speaking. In this paper we present our work in progress on the Presentation Trainer , which includes two user studies. The studies showed that participants would gladly use the Presentation Trainer to prepare for oral presentations, and pointed out to some considerations required for the design of tools able to effectively support a complex learning task through immediate feedback.

The paper presents the evolution of Presentation Trainer, a prototypical sensor-based toolkit that works as a public speaking instructor. It tracks the learner’s body posture, movements and voice in order to provide instructional feedback on nonverbal communication skills. Based on our design-based research the current version of the Presentation Trainer is able to provide the learner with the type of feedback that it considers to be appropriate according to the learner’s performance; it includes haptic feedback helping to reduce the learner’s cognitive load.

The Presentation Trainer is a multimodal tool designed to support the practice of public speaking skills, by giving the user real-time feedback about different aspects of her nonverbal communication. It tracks the user's voice and body to interpret her current performance. Based on this performance the Presentation Trainer selects the type of intervention that will be presented as feedback to the user. This feedback mechanism has been designed taking in consideration the results from previous studies that show how difficult it is for learners to perceive and correctly interpret real-time feedback while practicing their speeches. In this paper we present the user experience evaluation of participants who used the Presentation Trainer to practice for an elevator pitch, showing that the feedback provided by the Presentation Trainer has a significant influence on learning.