Boosting Learning: Non-intrusive Monitoring of Student’s Efficiency

Gonçalves, Sérgio; Rodrigues, Manuel; Carneiro, Davide; Fdez-Riverola, Florentino; Nováis, Paulo

doi:10.1007/978-3-319-19632-9_10

Cited by 9 publications

(2 citation statements)

References 7 publications

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“…However, the increasing adoption of electronic devices, both in educational settings and at home, has created new opportunities to study user behavior and performance. is has allowed the development of a wide range of applications that perform tasks like monitoring progress [1] and student fatigue [2], scaffolding learners [3], recommending open educational resources [4], modeling learners [5], or predicting future performance [6,7], among many others. While some of these systems work in ways that are nonintrusive and transparent to the user, others provide direct feedback to the user or the educator [8].…”

Section: Introductionmentioning

confidence: 99%

Improving Children’s Experience on a Mobile EdTech Platform through a Recommender System

Ruiz-Iniesta

Melgar

Baldominos

et al. 2018

Mobile Information Systems

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Smile and Learn is an EdTech digital publisher that offers a smart library of close to 100 educational stories and gaming apps for mobile devices aimed at children aged 2 to 10 and their families. Given the complexity of navigating the content, a recommender system was developed. The system consists of two major components: one that generates content recommendations and another that provides explanations and recommendations relevant to parents and educators. The former was implemented as a hybrid recommender system that combines three kinds of recommendations. Among these, we introduce a collaborative filtering adapted to overcome specific limitations associated with younger users. The approach described in this work was tested on real users of the platform. The experimental results suggest that this recommendation model is suitable to suggest apps to children and increase their engagement in terms of usage time and number of games played.

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Section: Introductionmentioning

confidence: 99%

Improving Children’s Experience on a Mobile EdTech Platform through a Recommender System

Ruiz-Iniesta

Melgar

Baldominos

et al. 2018

Mobile Information Systems

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“…Teaching should be solidly grounded in the absolute understanding of how the process of learning occurs so that instructional strategies could be efficient and lead to persistent knowledge. This is especially true when learning activities involve technologies (Gonçalves, Rodrigues, Carneiro, Fdez-Riverola, & Novais, 2015). In such cases, some of the previously mentioned issues can negatively affect the acquisition of knowledge and it is necessary that the teacher engages the students, because they have other technologies and applications that they can use and this can distract them.…”

Section: Challenges Of Teachingmentioning

confidence: 99%

Attentiveness and Engagement in Learning Activities

Durães¹

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The Human being is currently under increased demand for attention, a result of a society that is moving faster. In most of the so-called developed countries, workers have nowadays increasingly busier activities. This makes them stretch their limits to find time for children, sports activities, and other. This necessary extra time is frequently obtained at the expense of shorter periods of sleep or rest. Although this effect may not be readily visible, they may have consequences at many other levels than health, including emotions, results, attention and social behavior, among others. For these reasons, school and systems of e-learning must create environments that can involve students and capture their attention and engagement. Advances in computers and wireless technologies have also had an impact on the educational system, thus generating a new approach for Ambient Intelligent Systems (AmI systems). The rapid development of these technologies combined with the access to content in a wide variety of settings, allows learners to experience new learning situations beyond the school's walls. The need for qualified people is growing exponentially, requiring limited resources allocated to education/training to be used most efficiently. Learning and elearning systems can allow some flexibility for students who have complicated schedules and obligations. However, some problems can occur: (1) relying on learning theories, it is crucial to improve the learning process and mitigate the issues

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Our Actions, Ourselves: How Unconscious Actions Become a Productivity Indicator

Rodrigues

Santos

Nováis

2018

Advances in Intelligent Systems and Computing

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Productivity always was, and still is, the main goal of organizations, that being economic, governmental, military or educational. Having the means to control, detect and monitor features that have impact on productivity is a major issue, and subject to various investigation. Considering that most of the times, if not always, unconscious actions play a very important role in the way we work, study, socialize, and even in the way we have fun, the high significance of that factors becomes very clear. Monitoring unconscious actions, selecting those of them that do play a role regarding productivity, and trying to proactively take measures to improve processes, is then the goal of this work. Specifically, we are concerned about using computers peripherals to non-intrusively monitor user´s actions. The term nonintrusively assumes greater importance, as we are concerned with unconscious actions, thus we need to strongly ensure that no entropy is derived by the way this process is done. Peripherals such as mouse, keyboard, touch screens, and possibly webcams and microphones can act as sensors, completely hidden from the user. As we use them daily, they somehow assume part of our life, and can be used to collect data that will be processed to get useful information regarding that particular user. We then can build a behavioral profile, for instance, that will provide a better insight of user´s actions. We can predict some possibly negative features, such as stress, fatigue, level of attention, for instance. If detected or predicted, they can greatly help to better manage all the information we need, in the right way. We can suggest that someone takes a coffee break, because she/he´s stressed. We can tell him/her to work/study in the morning, because the information we have collected suggests that´s the period of the day that´s more suitable to get better results, for that person. We can suggest postponing the following meeting, because the actual mood indicates that that person is more suitable to conflicts at that moment. In short, we aim to use computer peripherals and smartphones to collect data from the user, non-intrusively, aiming to detect or predict behavioral features (stress, fatigue, attention) and unconscious actions that will allow us to build a behavioral profile about the user, thus making it possible to improve productivity for instance. This is accomplished by monitoring mouse, keyboard and touch screen usage, nonintrusively, and in real time. Through the collected data, some inferences are made regarding the patterns of interaction that make it possible to detect variations regarding behavioral features and unconscious actions. With this information, we can have a detailed insight into those behavioral features, allowing us to proactively mitigate some of the potential problems that could arise. In this work a framework is proposed as a way to integrate all these features. We aim mainly to apply these concepts in learning contexts, as to improve student's outcomes.

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Boosting Learning: Non-intrusive Monitoring of Student’s Efficiency

Cited by 9 publications

References 7 publications

Improving Children’s Experience on a Mobile EdTech Platform through a Recommender System

Improving Children’s Experience on a Mobile EdTech Platform through a Recommender System

Attentiveness and Engagement in Learning Activities

Our Actions, Ourselves: How Unconscious Actions Become a Productivity Indicator

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