How do you sleep? Using off the shelf wrist wearables to estimate sleep quality, sleepiness level, chronotype and sleep regularity indicators

This piece of research is situated in the domain of multi-modal analytics. New commercial off the shelf wearables, such as smartwatches or wristbands, are becoming popular and increasingly used for fitness and wellness in a new trend known as the quantified-self movement. The sensors included in these devices (e.g. accelerometer, heart rate) in conjunction with data analytics algorithms are used to provide information such as steps walked, calories consumed, etc. The main goal of this piece of research is to check if new wearable technologies could be used to estimate sleep indicators in an automatic way. The available medical literature proposes several sleep-related features and methods to calculate them involving direct user observation, interviews or specific medical instrumentation. Off the shelf wearable vendors also provide some sleep indicators, such as the sleep duration, the number of awakes or the time to fall asleep. Taking as a reference the results and methods described in the medical literature and the data available in commercial off the shelf wearables, we propose new sleep indicators offering a greater interpretative value: sleep quality, sleepiness level, chronotype. The results obtained after initial experiments demonstrate the feasibility of this approach to be applied in real contexts. Eventually, we plan to apply these solutions to support educational scenarios related to self-regulated learning and teaching support.Agencia Estatal de Investigación | Ref. TIN2016-80515-RXunta de Galicia | Ref. GRC2013-006Universidade de Vig

An xAPI application profile to monitor self-regulated learning strategies

Self-regulated learning (SRL) is being promoted and adopted increasingly due to the needs of current education, student centered and focused on competence development. One of the main components of SRL is learners' self-monitoring, which eventually contributes to a better performance. Monitoring is also important for teachers, as it enables them to know to what extent their learners are doing well and progressing properly. At the same time, the use of technology for learning is now common and facilitates monitoring. Nevertheless, the available software still offers poor support from the SRL point of view, especially, for SRL monitoring. This clashes with the growth of learning analytics and educational data mining. The main issue is the wide variety of SRL actions that need to be captured, commonly performed in different tools, and the need to integrate them to support the development of analytics and data mining developments, making imperative the search of interoperable solutions. This paper focuses on the standardization of SRL traces to enable data collection from multiple sources and data analysis with the goal of easing the monitoring process for teachers and learners. First, the paper analyzes current monitoring software and its limitations for SRL. Then, after a brief analysis of available standards on this area, an application profile for the eXperience API specification is proposed to enable the interoperable recording of the SRL traces. The paper describes the process followed to create the profile, from the analysis to the final implementation, including the selection of the interactions that represent relevant SRL actions, the selection of vocabularies to record them and a case study.Xunta de Galicia | Ref. ED431B 2017/67Xunta de Galicia | Ref. ED431D 2017/1

Engineering modular web-based education systems to support EML units of learning

Educational Modeling Languages (EMLs) have been proposed to support the modeling of units of learning enabling the description of different pedagogical approaches. Eventually, such models are intended to support the operation of appropriate computer systems, controlling and managing the corresponding units of learning. This paper considers EMLs involving a set of independent perspectives. Our purpose is to use this set of perspectives to facilitate the development of Web-based education systems that are able to support the execution of EML models. As a result, we obtain a modular architecture where different pedagogical approaches can be supported.Education for the 21 st century - impact of ICT and Digital Resources ConferenceRed de Universidades con Carreras en Informática (RedUNCI

Evaluation of commercial-off-the-shelf wrist wearables to estimate stress on students

Wearable commercial-off-the-shelf (COTS) devices have become popular during the last years to monitor sports activities, primarily among young people. These devices include sensors to gather data on physiological signals such as heart rate, skin temperature or galvanic skin response. By applying data analytics techniques to these kinds of signals, it is possible to obtain estimations of higher-level aspects of human behavior. In the literature, there are several works describing the use of physiological data collected using clinical devices to obtain information on sleep patterns or stress. However, it is still an open question whether data captured using COTS wrist wearables is sufficient to characterize the learners' psychological state in educational settings. This paper discusses a protocol to evaluate stress estimation from data obtained using COTS wrist wearables. The protocol is carried out in two phases. The first stage consists of a controlled laboratory experiment, where a mobile app is used to induce different stress levels in a student by means of a relaxing video, a Stroop Color and Word test, a Paced Auditory Serial Addition test, and a hyperventilation test. The second phase is carried out in the classroom, where stress is analyzed while performing several academic activities, namely attending to theoretical lectures, doing exercises and other individual activities, and taking short tests and exams. In both cases, both quantitative data obtained from COTS wrist wearables and qualitative data gathered by means of questionnaires are considered. This protocol involves a simple and consistent method with a stress induction app and questionnaires, requiring a limited participation of support staff.Agencia Estatal de Investigación | Ref. TIN2016-80515-

Study of stress detection and proposal of stress-related features using commercial-off-the-shelf wrist wearables

This paper discusses the possibility of detecting personal stress making use of popular wearable devices available in the market. Different instruments found in the literature to measure stress-related features are reviewed, distinguishing between subjective tests and mechanisms supported by the analysis of physiological signals from clinical devices. Taking them as a reference, a solution to estimate stress based on the use of commercial-off-the-shelf wrist wearables and machine learning techniques is described. A mobile app was developed to induce stress in a uniform and systematic way. The app implements well-known stress inducers, such as the Paced Auditory Serial Addition Test, the Stroop Color-Word Interference Test, and a hyperventilation activity. Wearables are used to collect physiological data used to train classifiers that provide estimations on personal stress levels. The solution has been validated in an experiment involving 19 subjects, offering an average accuracy and F-measures close to 0.99 in an individual model and an accuracy and F-measure close to 0.85 in a global 2-level classifier model. Stress can be a worrying problem in different scenarios, such as in educational settings. Thus, the last part of the paper describes the proposal of a set of stress related indicators aimed to support the management of stress over time in such settings.Agencia Estatal de Investigación | Ref. TIN2016-80515-RUniversidade de Vig

III Workshop sobre Recursos Educativos Abiertos. Los Recursos Educativos Abiertos como Eje de la Innovación Educativa

[ES]Esta tercera edición del workshop sobre Recursos Educativos Abiertos en el ámbito latinoamericano se ha planteado entorno al concepto de innovación educativa, tratando de buscar las relaciones y oportunidades que se presentan entre ambos dominios. Tras las dos primeras ediciones realizadas en Brasil en los años 2012 y 2015 esta edición tiene lugar en Salamanca, España. En este evento se han seleccionado 10 ponencias de los siguientes países: Argentina, Bolivia, Brasil, España, Portugal y Uruguay.Este workshop ha sido posible gracias a la colaboración de la la Red 513RT0471 de CYTED RIURE (Red Iberoamericana para la Usabilidad de Recursos Educativos, www.riure.net)

Sustainability of Open Educational Resources: the eCity case

[EN]The promotion of Open Educational Resources (OER) as reusable tools for teachers and students is highly relevant but the nature of the income model requires specific strategies to maintain and update those resources. eCity is a city simulation game that supports a Problem Based Learning (PBL) pedagogical methodology in secondary schools and, at the same time, fosters the interest of students in following an Engineering career. The game is freely available through online stores and the generated interest (about 100.000 downloads so far) has raised the need to discuss and adopt a sustainability strategy for the maintenance of the game and the development of new versions. This article presents possible alternatives for that strategy

Sustainability of Open Educational Resources: the eCity case

[EN]The promotion of Open Educational Resources (OER) as reusable tools for teachers and students is highly relevant but the nature of the income model requires specific strategies to maintain and update those resources. eCity is a city simulation game that supports a Problem Based Learning (PBL) pedagogical methodology in secondary schools and, at the same time, fosters the interest of students in following an Engineering career. The game is freely available through online stores and the generated interest (about 100.000 downloads so far) has raised the need to discuss and adopt a sustainability strategy for the maintenance of the game and the development of new versions. This article presents possible alternatives for that strategy

Profiling students’ self-regulation with learning analytics: a proof of concept

The ability to regulate one's own learning processes is a key factor in educational scenarios. Self-regulation skills notably affect students' ef cacy when studying and academic performance, for better orworse. However, neither students or instructors generally have proper understanding of what self-regulated learning is, the impact that it has or how to assess it. This paper has the purpose of showing how learning analytics can be used in order to generate simple metrics related to several areas of students' selfregulation, in the context of a rst-year university course. These metrics are based on data obtained from a learning management system, complemented by more speci c assessment-related data and direct answers to self-regulated learning questionnaires. As the end result, simple self-regulation pro les are obtained for each student, which can be used to identify strengths and weaknesses and, potentially, help struggling students to improve their learning habits.Xunta de Galicia | Ref. ED431B 2020/3

Monitoring students’ self-regulation as a basis for an early warning system

Among the elements that determine a student’s academic success, their ability to regulate their own learning processes is an important, yet typically underrated factor. It is possible for students to improve their self-regulated learning skills, even at university levels. However, they are often unaware of their own behavior. Moreover, instructors are usually not prepared to assess students’ self-regulation. This paper presents a learning analytics solution which focuses on rating selfregulation skills, separated in several different categories, using activity and performance data from a LMS, as well as self-reported student data via questionnaires. It is implemented as an early warning system, offering the possibility of detecting students whose poor SRL profile puts them at risk of academic underperformance. As of the date of this writing, this is still a work in progress, and is being tested in the context of a first year college engineering course