How to capitalise on mobility, proximity and motion analytics to support formal and informal education?

© 2017, CEUR-WS. All rights reserved. Learning Analytics and similar data-intensive approaches aimed at understanding and/or supporting learning have mostly focused on the analysis of students' data automatically captured by personal computers or, more recently, mobile devices. Thus, most student behavioural data are limited to the interactions between students and particular learning applications. However, learning can also occur beyond these interface interactions, for instance while students interact face-to-face with other students or their teachers. Alternatively, some learning tasks may require students to interact with non-digital physical tools, to use the physical space, or to learn in different ways that cannot be mediated by traditional user interfaces (e.g. motor and/or audio learning). The key questions here are: why are we neglecting these kinds of learning activities? How can we provide automated support or feedback to students during these activities? Can we find useful patterns of activity in these physical settings as we have been doing with computer-mediated settings? This position paper is aimed at motivating discussion through a series of questions that can justify the importance of designing technological innovations for physical learning settings where mobility, proximity and motion are tracked, just as digital interactions have been so far

Responsible research and innovation in science education: insights from evaluating the impact of using digital media and arts-based methods on RRI values

The European Commission policy approach of Responsible Research and Innovation (RRI) is gaining momentum in European research planning and development as a strategy to align scientific and technological progress with socially desirable and acceptable ends. One of the RRI agendas is science education, aiming to foster future generations' acquisition of skills and values needed to engage in society responsibly. To this end, it is argued that RRI-based science education can benefit from more interdisciplinary methods such as those based on arts and digital technologies. However, the evidence existing on the impact of science education activities using digital media and arts-based methods on RRI values remains underexplored. This article comparatively reviews previous evidence on the evaluation of these activities, from primary to higher education, to examine whether and how RRI-related learning outcomes are evaluated and how these activities impact on students' learning. Forty academic publications were selected and its content analysed according to five RRI values: creative and critical thinking, engagement, inclusiveness, gender equality and integration of ethical issues. When evaluating the impact of digital and arts-based methods in science education activities, creative and critical thinking, engagement and partly inclusiveness are the RRI values mainly addressed. In contrast, gender equality and ethics integration are neglected. Digital-based methods seem to be more focused on students' questioning and inquiry skills, whereas those using arts often examine imagination, curiosity and autonomy. Differences in the evaluation focus between studies on digital media and those on arts partly explain differences in their impact on RRI values, but also result in non-documented outcomes and undermine their potential. Further developments in interdisciplinary approaches to science education following the RRI policy agenda should reinforce the design of the activities as well as procedural aspects of the evaluation research

Proceedings of the Sempre MET2018: Researching Music, Education, Technology

MET 2018 Researching Music - Education - Technology (MET2018) 26–27 March 2018 Following the great success of its inaugural conference held by the University of Hull in 2010, MET2014, and MET2016 at IOE London, this fourth two-day conference (#sempreMET) was hosted by the Department of culture, Communication & Media, IOE, University College London, at the University of London’s iconic Senate House. Although the 'musicking' humanity has been reliant on technology from the very beginning of its musical journey, we cannot deny that, nowadays, technology changes, develops, and its role is being redefined at a dramatically greater rate. This sempre conference aimed to celebrate technology's challenging role(s) and provide a platform for critical discourse and the presentation of scholarly work in the broader fields of digital technologies in: music composition and creation music performance music production (recording, studio work, archival and/or communication of music) diverse musical genres (e.g. popular, classical, world, etc.) creativity/ies real world praxial contexts (e.g. classroom, studio, etc.) assessment of musical development and/or assessment of performance computational musicology music and Big Data (a special call for chapters for an edited OUP VOLUME will be posted soon) the music industry special educational contexts/needs The conference provided opportunities for colleagues to present and discuss ideas in a friendly and supportive environment, as well as to provide a meeting point for academics, scholars, teachers, and practitioners who were seeking to form connections and synergies with participants from around the world

Imaging and visualization at the University of Missouri--Columbia

"The following group of faculty helped prepare this document for MU’s Cyberinfrastructure (CI) Council as part of the 2016 updates to MU’s CI Plan. ... Bimal Balakrishnan, Tommi White, Teresa Lever, David Larsen, Kannappan Palaniappan, Filiz Bunyak, and Chi-Ren ShyuThe document includes a long-term vision for a Show-Me Center for Imaging and Visualization (see page 7). For consistency, with the other parts of the CI Plan, one and three year objectives are provided. This document is designed to help update the CI Plan, and help advance the growing momentum for a imaging and visualization center to support faculty and students from a wide-variety of discipline, and advance a variety of innovative collaborations.Imaging and Visualization and the University of Missouri (MU) -- Return on Proposed Investment -- Imaging and Visualization Needs and Recommendations -- Cross connections with other areas of emphasis in the MU Cyberinfrastructure Plan -- One Year Objectives -- Three to Five Year Objectives -- The Big Picture: the Show-Me Center for Imaging and Visualization. Physical Space ; Where to Start and Why ; Visualization Related ; Infrastructure needed at MU ; Computation, Data Storage and Networking needs ; Management, Staffing, Training and Support ; Needed expertise -- Appendix A: Faculty Perspectives on the Importance of Visualization on Research and Teaching at MU -- Appendix B: Comparable Imaging Facilities -- Appendix C: Visualization Centers at Major Research Universities

Experimental Studies in Learning Technology and Child–Computer Interaction

This book is about the ways in which experiments can be employed in the context of research on learning technologies and child–computer interaction (CCI). It is directed at researchers, supporting them to employ experimental studies while increasing their quality and rigor. The book provides a complete and comprehensive description on how to design, implement, and report experiments, with a focus on and examples from CCI and learning technology research. The topics covered include an introduction to CCI and learning technologies as interdisciplinary fields of research, how to design educational interfaces and visualizations that support experimental studies, the advantages and disadvantages of a variety of experiments, methodological decisions in designing and conducting experiments (e.g. devising hypotheses and selecting measures), and the reporting of results. As well, a brief introduction on how contemporary advances in data science, artificial intelligence, and sensor data have impacted learning technology and CCI research is presented. The book details three important issues that a learning technology and CCI researcher needs to be aware of: the importance of the context, ethical considerations, and working with children. The motivation behind and emphasis of this book is helping prospective CCI and learning technology researchers (a) to evaluate the circumstances that favor (or do not favor) the use of experiments, (b) to make the necessary methodological decisions about the type and features of the experiment, (c) to design the necessary “artifacts” (e.g., prototype systems, interfaces, materials, and procedures), (d) to operationalize and conduct experimental procedures to minimize potential bias, and (e) to report the results of their studies for successful dissemination in top-tier venues (such as journals and conferences). This book is an open access publication

Smart School Multimodal Dataset and Challenges

As part of a research project aiming to explore the notion of ‘smart school’ (especially for STEM education) in Estonia, we are developing classrooms and schools that incorporate data gathering not only from digital traces, but also physical ones (through a variety of sensors). This workshop contribution describes briefly the setting and our initial efforts in setting up a classroom that is able to generate such a multimodal dataset. The paper also describes some of the most important challenges that we are facing as we setup the project and attempt to build up such dataset, focusing on the specifics of doing it in an everyday, authentic school setting. We believe these challenges provide a nice sample of those that the multimodal learning analytics (MMLA) community will have to face as it transitions from an emergent to a mainstream community of research and practice

Econometrics meets sentiment : an overview of methodology and applications

The advent of massive amounts of textual, audio, and visual data has spurred the development of econometric methodology to transform qualitative sentiment data into quantitative sentiment variables, and to use those variables in an econometric analysis of the relationships between sentiment and other variables. We survey this emerging research field and refer to it as sentometrics, which is a portmanteau of sentiment and econometrics. We provide a synthesis of the relevant methodological approaches, illustrate with empirical results, and discuss useful software