Toward an Adaptive and Adaptable Architecture to Support Ubiquitous Learning Activities

Zbick, Janosch; Vogel, Bahtijar; Jansen, Marc; Milrad, Marcelo

doi:10.1007/978-3-319-26518-6_8

Cited by 5 publications

(5 citation statements)

References 38 publications

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“…Additionally, the mobile tools allow researchers and teachers to mark critical incidents, and to time stamp the different stages of the learners' project. The tool is developed on the basis of modern web technologies, which run across different platforms (Zbick, Vogel, Spikol, Jansen, & Milrad, 2016).…”

Section: Mobile Toolsmentioning

confidence: 99%

Supervised machine learning in multimodal learning analytics for estimating success in project‐based learning

Spikol

Ruffaldi

Dabisias

et al. 2018

Computer Assisted Learning

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138

107

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Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates the use of diverse sensors, including computer vision, user‐generated content, and data from the learning objects (physical computing components), to record high‐fidelity synchronised multimodal recordings of small groups of learners interacting. We processed and extracted different aspects of the students' interactions to answer the following question: Which features of student group work are good predictors of team success in open‐ended tasks with physical computing? To answer this question, we have explored different supervised machine learning approaches (traditional and deep learning techniques) to analyse the data coming from multiple sources. The results illustrate that state‐of‐the‐art computational techniques can be used to generate insights into the "black box" of learning in students' project‐based activities. The features identified from the analysis show that distance between learners' hands and faces is a strong predictor of students' artefact quality, which can indicate the value of student collaboration. Our research shows that new and promising approaches such as neural networks, and more traditional regression approaches can both be used to classify multimodal learning analytics data, and both have advantages and disadvantages depending on the research questions and contexts being investigated. The work presented here is a significant contribution towards developing techniques to automatically identify the key aspects of students success in project‐based learning environments, and to ultimately help teachers provide appropriate and timely support to students in these fundamental aspects.

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Section: Mobile Toolsmentioning

confidence: 99%

Supervised machine learning in multimodal learning analytics for estimating success in project‐based learning

Spikol

Ruffaldi

Dabisias

et al. 2018

Computer Assisted Learning

Self Cite

138

107

View full text Add to dashboard Cite

show abstract

“…Surveyed approaches have proposed a range of dimensions, which intersect and differ on multiple levels. It can be concluded that the domain of application (Zbick et al, 2016), the tools and infrastructure of the learning (Hwang, 2013), and the reliance on technical or pedagogical foundations for the learning (Macchia and Brézillon, 2021), are all factors that influence t he a doption o f a c ertain dimension, or set of dimensions, over the other ones.…”

Section: Profile-based Context Dimensionsmentioning

confidence: 99%

“…The l ack o f s tandards f or d escribing t he c ontext f actors a nd dimensions is not a new challenge. This issue has been addressed in Verbert et al (2012), and it seems to remain unsolved till now in the state-of-the-art, despite several attempts to propose generalizable schemes of the context dimensions, such as in the work of Zbick et al (2016), Moebert et al (2016), andLi (2016). One of the solutions that were proposed for this challenge, is to adopt a semantic-web-based approach for defining standardized vocabularies for context factors and dimensions.…”

Section: Observation 2: Context Dimensions As Domain-specific or Stan...mentioning

confidence: 99%

Context based learning: a survey of contextual indicators for personalized and adaptive learning recommendations – a pedagogical and technical perspective

Abu-Rasheed,

Weber,

Fathi

2023

Front. Educ.

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Learning personalization has proven its effectiveness in enhancing learner performance. Therefore, modern digital learning platforms have been increasingly depending on recommendation systems to offer learners personalized suggestions of learning materials. Learners can utilize those recommendations to acquire certain skills for the labor market or for their formal education. Personalization can be based on several factors, such as personal preference, social connections or learning context. In an educational environment, the learning context plays an important role in generating sound recommendations, which not only fulfill the preferences of the learner, but also correspond to the pedagogical goals of the learning process. This is because a learning context describes the actual situation of the learner at the moment of requesting a learning recommendation. It provides information about the learner’s current state of knowledge, goal orientation, motivation, needs, available time, and other factors that reflect their status and may influence how learning recommendations are perceived and utilized. Context-aware recommender systems have the potential to reflect the logic that a learning expert may follow in recommending materials to students with respect to their status and needs. During the last decade, several approaches have emerged in the literature to define the learning context and the factors that may capture it. Those approaches led to different definitions of contextualized learner-profiles. In this paper, we review the state-of-the-art approaches for defining a user’s learning-context. We provide an overview of the definitions available, as well as the different factors that are considered when defining a context. Moreover, we further investigate the links between those factors and their pedagogical foundations in learning theories. We aim to provide a comprehensive understanding of contextualized learning from both pedagogical and technical points of view. By combining those two viewpoints, we aim to bridge a gap between both domains, in terms of contextualizing learning recommendations.

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“…Technology tends to develop quickly over time. This is especially true for digital ubiquitous technology, constantly evolving at a rapid pace (Zbick, Vogel, Spikol, Jansen, & Milrad, 2016). Teachers face challenges adapting to these changes when constructing sequences of learning tasks (Luckin et al, 2016).…”

Section: Inseparable Sequences Of Environmental Knowledgementioning

confidence: 99%

A Framework for the Analysis of Personal Learning Networks

Fair

2021

Research in Networked Learning

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This paper introduces Fast Food da Politica (FFDP) as a case study of a learning network designed to promote social action in a developing country. Our focus is on exploring FFDP design elements, such as those related to tools, tasks and social organization, and the connections between these elements and valued learning activity. FFDP cleverly (re)purposes popular (board) games as pedagogical tools, which are then customised for the teaching and learning of the mechanisms and functioning of Brazilian political structures. FFDP has taken their political games to game-playing sessions across the country in varied venues -including schools, government organisations, and open sessions at market-street events and public protests. Their games are shared as open learning resources through blueprints and manuals that explain the many ways a game can be played, and which are easily downloadable through their website. FFDP also encourages game users (educators and learners) to come up with and share their own game-playing ideas for reuse. As a result, FFDP has built a repository of games that is constantly evolving, as new ways of using their open resources are captured and packaged for sharing and reuse by others. As a not-for-profit organisation, FFDP has been successfully relying on social media and crowdsourced funding to survive. In this paper, we draw on the ACAD Wireframe to explore the alignment of this network's design elements at the micro and meso levels, focusing on the ways FFDP combines a strategic educational vision deeply grounded on action for social change, with a curriculum that emphasizes gaming elements and promotes the physicality of materials in learning. At the micro level, the case study examines how the quality of materials support the development of educational innovation, while at the meso level this organization, driven by young women, is buildingup a learning network for social action, empowering children, youth and adults to learn about the mechanisms of politics and their civil rights, within the Brazilian context. Overall, this paper offers an inspiring example of a productive learning network in action, where participation and co-creation are fostered through connections between a network of people, ideas, digital and material elements. KeywordsOpen education; design for learning; games in education help people learn and teach deeper critical thinking of political matters, and in so doing, to empower learners to take hold of their own future.

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Toward an Adaptive and Adaptable Architecture to Support Ubiquitous Learning Activities

Cited by 5 publications

References 38 publications

Supervised machine learning in multimodal learning analytics for estimating success in project‐based learning

Supervised machine learning in multimodal learning analytics for estimating success in project‐based learning

Context based learning: a survey of contextual indicators for personalized and adaptive learning recommendations – a pedagogical and technical perspective

A Framework for the Analysis of Personal Learning Networks

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