Supporting Training of Expertise with Wearable Technologies: The WEKIT Reference Framework

Authors: Bibeg Limbu, Mikhail Fominykh, Roland Klemke, Marcus Specht and Fridolin Wild
Type: Book chapter
SourceMobile and Ubiquitous Learning
Publisher: Springer, Singapore
Date: 18 November, 2017
Linkhttps://link.springer.com/chapter/10.1007/978-981-10-6144-8_10

Abstract: In this chapter, we present a conceptual reference framework for designing augmented reality applications for supporting training. The framework leverages the capabilities of modern augmented reality and wearable technology for capturing the expert’s performance in order to support expertise development. It has been designed in the context of Wearable Experience for Knowledge Intensive Training (WEKIT) project which intends to deliver a novel technological platform for industrial training. The framework identifies the state-of-the-art augmented reality training methods, which we term as “transfer mechanisms” from an extensive literature review. Transfer mechanisms exploit the educational affordances of augmented reality and wearable technology to capture the expert performance and train the trainees. The framework itself is based upon Merrienboer’s 4C/ID model which is suitable for training complex skills. The 4C/ID model encapsulates major elements of apprenticeship models which is a primary method of training in industries. The framework complements the 4C/ID model with expert performance data captured with help of wearable technology which is then exploited in the model to provide a novel training approach for efficiently and effectively mastering the skills required. In this chapter, we will give a brief overview of our current progress in developing this framework.

Affordances for Capturing and Re-enacting Expert Performance with Wearables

Authors: Will Guest, Fridolin Wild, Alla Vovk, Mikhail Fominykh, Bibeg Limbu, Roland Klemke, Puneet Sharma, Jaakko Karjalainen, Carl Smith, Jazz Rasool, Soyeb Aswat, Kaj Helin, Daniele Di Mitri and Jan Schneider
Type: Conference proceedings
Source: 12th European Conference on Technology Enhanced Learning (ECTEL 2017)
Publisher: Springer, Cham
Date: 05 September, 2017
Linkhttps://link.springer.com/chapter/10.1007%2F978-3-319-66610-5_34

Abstract: The WEKIT.one prototype is a platform for immersive procedural training with wearable sensors and Augmented Reality. Focusing on capture and re-enactment of human expertise, this work looks at the unique affordances of suitable hard- and software technologies. The practical challenges of interpreting expertise, using suitable sensors for its capture and specifying the means to describe and display to the novice are of central significance here. We link affordances with hardware devices, discussing their alternatives, including Microsoft Hololens, Thalmic Labs MYO, Alex Posture sensor, MyndPlay EEG headband, and a heart rate sensor. Following the selection of sensors, we describe integration and communication requirements for the prototype. We close with thoughts on the wider possibilities for implementation and next steps.

Community Learning Analytics with Industry 4.0 and Wearable Sensor Data

Authors: István Koren and Ralf Klamma
Type: Conference proceedings
Source: Third International Conference of the Immersive Learning Research Network (iLRN 2017)
Publisher: Springer, Cham
Date: 26 June, 2017
Linkhttps://link.springer.com/chapter/10.1007%2F978-3-319-60633-0_12

Abstract: Learning analytics in formal learning contexts is often restricted to collect and analyze data from students following curricula through a learning management system. In informal learning, however, a deep understanding of learners and entities interacting with each other is needed. The practice of exploring these interactions is known as community learning analytics. Mobile devices, wearables and interconnected Industry 4.0 production machines equipped with a multitude of sensors collecting vast amounts of data are ideal candidates to capture the goals and activities of informal learning settings. What is missing is a methodological approach to collect, manage, analyze and exploit data coming from such an interconnected network of artifacts. In this paper, we present a concept and prototypical implementation of a framework that is able to gather, transform and visualize data coming from Industry 4.0 and wearable sensors and actuators. Our collaborative Web-based visual analytics platform is highly embeddable and extensible on various levels. Its open source availability fosters research on community learning analytics on a broad level.

Technology Acceptance of Augmented Reality and Wearable Technologies

Authors: Fridolin Wild, Roland Klemke, Paul Lefrere, Mikhail Fominykh, Timo Kuula
Type: Conference proceedings
Source: Third International Conference of the Immersive Learning Research Network (iLRN 2017)
Publisher: Springer, Cham
Date: 26 June, 2017
Linkhttps://link.springer.com/chapter/10.1007/978-3-319-60633-0_11

Abstract: Augmented Reality and Wearables are the recent media and computing technologies, similar, but different from established technologies, even mobile computing and virtual reality. Numerous proposals for measuring technology acceptance exist, but have not been applied, nor fine-tuned to such new technology so far. Within this contribution, we enhance these existing instruments with the special needs required for measuring technology acceptance of Augmented Reality and Wearable Technologies and we validate the new instrument with participants from three pilot areas in industry, namely aviation, medicine, and space. Findings of such baseline indicate that respondents in these pilot areas generally enjoy and look forward to using these technologies, for being intuitive and easy to learn to use. The respondents currently do not receive much support, but like working with them without feeling addicted. The technologies are still seen as forerunner tools, with some fear of problems of integration with existing systems or vendor-lock. Privacy and security aspects surprisingly seem not to matter, possibly overshadowed by expected productivity increase, increase in precision, and better feedback on task completion. More participants have experience with AR than not, but only few on a regular basis.

Do You Know What Your Nonverbal Behavior Communicates? – Studying a Self-reflection Module for the Presentation Trainer

Authors: Jan Schneider, Dirk Börner, Peter van Rosmalen and Marcus Specht
Type: Conference proceedings
Source: the Third International Conference of the Immersive Learning Research Network (iLRN 2017)
Publisher: Springer, Cham
Date: 26 June, 2017
Linkhttps://link.springer.com/chapter/10.1007%2F978-3-319-60633-0_8

Abstract: In recent years, research on multimodal sensor-based technologies has produced different prototypes designed to support the development of public skills. These prototypes are able to analyze the nonverbal communication of learners and provide them with feedback, in cases where human feedback is not available. One of these prototypes is called the Presentation Trainer (PT). Experts in public speaking claim that ultimately there is not such thing as the right way to do a presentation. They pointed out that it would be useful for tools such as the PT to present learners with the opportunity to become aware of their own nonverbal communication. Following this suggestion we developed a self-reflection module for the PT. In this study we conducted user tests exploring the use of this module. Results from these tests showed that participants perceived that the self-reflection module helped them to reflect about their performance, and point out research paths to further investigate the influence of self-reflection in the learners’ performance.

Bridging the Skills Gap of Workers in Industry 4.0 by Human Performance Augmentation Tools: Challenges and Roadmap

Authors: Eric Ras, Fridolin Wild, Christoph Stahl and Alexandre Baudet
Type: Conference proceedings
Source: 10th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2017)
Publisher: ACM New York, NY, USA
Date: 21 June, 2017
Linkhttps://dl.acm.org/citation.cfm?doid=3056540.3076192

Abstract: Industry 4.0 is a coordinated push for automation in Smart Factories and other Cyber-Physical Systems (CPS). The increasing complexity of frequently changing production environments challenges shop floor workers to perform well. The tasks they work on are getting less routine and ask for continuous knowledge and skills development. For example, the skills portfolio of workers likely requires improved higher-order thinking and decision-making skills. A wide range of research and development efforts already today sets focus on different areas of workplace learning, including performance appraisals, pedagogy and education, technology, and business economics. Bridging the skills gap, however, requires novel user-facing technologies — such as Augmented Reality (AR) and wearables — for human performance augmentation to improve efficiency and effectiveness of staff delivered through live guidance. AR branches out beyond mobile apps with 3D-object superimposition for marketing purposes to rather complex use cases delivered by a rapidly growing innovation ecosystem of hard- and software providers collaborating closely with R&D organisations. This paper provides a first shared vision on how AR can tackle four different challenges related to handling complexity in a CPS environment: develop intelligent assistance systems for learning and performance assessment at the workplace, adapt job profiles accordingly, and last but not least to address also the issue of work-life balance. The paper concludes with an outline of a research roadmap.

Preparing research projects for sustainable software engineering in society

Authors: Dominik Renzel, István Koren, Ralf Klamma and Matthias Jarke
Type: Conference proceedings
Source: 39th International Conference on Software Engineering: Software Engineering in Society Track
Publisher: IEEE Press Piscataway, NJ, USA
Date: 20 May, 2017
Linkhttps://dl.acm.org/citation.cfm?id=3103222

Abstract: With the pervasive need for digitization in modern information society, publicly funded research projects increasingly focus on engineering digital approaches to manage societal processes. Such projects inherently face the challenge of establishing a sustainable software engineering culture. A major challenge thereby is that project consortia need to establish a distributed developer community that effectively and resource-efficiently aligns development efforts with the goals and needs of complex societal constellations beyond project lifetime. In this paper we extract empirical evidence from longitudinal studies in two large-scale research projects to outline typical challenges in such problem contexts and to develop an open source software engineering methodology for research projects, including supportive infrastructure and social instruments of community building and awareness. We thus contribute a comprehensive strategy preparing collaborative research projects for sustainable societal software engineering.

WEKIT – Wearable Experience for Knowledge Intensive Training

Authors: Kaj Helin, Mikhail Fominykh and Carlo Vizzi
Type: Poster in conference proceedings
Source: the Euro VR Conference
Publisher: Euro VR, online
Date: 22 November, 2016
Linkhttps://www.eurovr-association.org/conference2016/program/posters

Abstract: This poster introduces European commission funded H2020 project called WEKIT – Wearable Experience for Knowledge Intensive Training. This three-year project has left two years and it will produce a WEKIT platform which exploits Augment training in situ with live expert guidance, a tacit learning experience and a re-enactment of the expert, in knowledge-intensive environments. Project has three industrial cases: (1) Aircraft maintenance: exploiting Augmented Reality and Wearable Technology for inspections, decisions making and safety (2) Healthcare: exploiting Augmented Reality for improving innovation in technology and responsibility in healthcare applications for medical imaging; and (3) Space: exploiting Augmented Reality and Wearable Technology for astronauts training and for supporting the assembly integration and test of payloads and sub-systems. The WEKIT platform will be tested together with end-users with iterative development loops.

Wearable Experience: New Educational Media for Knowledge Intensive Training

Author: Mikhail Fominykh
Type: Invited speech publication
Source: EdMedia: World Conference on Educational Media and Technology
Publisher: AACE, USA
Date: 29 June 2016
Linkhttps://www.academicexperts.org/conf/edmedia/2016/papers/49527/

Abstract: Wearable computing and augmented reality are disruptive technologies. They fundamentally change the way we educate and train people to a master level of performance. With advanced sensors we can capture experience as it emerges. For example, a trainee can receive live guidance in the form of semi-transparent 3D hands that appear at the right place spatially and are operated by a remote expert using sensor data. Captured guidance provides reference to scale, allowing repeated access to the information asynchronously at the right time and in the right place where it is most urgently needed. Expert guidance can be captured with wearable sensors and later re-enacted by trainees with augmented reality creating a believable illusion of a master-apprentice knowledge sharing. The captured experience therefore represents a new type of educational media that has properties of carrying both explicit and tacit knowledge. This new media helps to convert experience to knowledge and enable learning by bringing closer the theoretical knowledge and immediate experience, which are traditionally separated. Tailored content of captured experience can be presented with augmented reality using intuitive and immersive user interfaces. This can have a positive impact on mental processing and memorization, not only adding scaffolds for high performance, but also acting as a safety net preventing potential problems sensed in the environment. Learning how to master a complex task usually involves reflecting on your own performance, looking back at your behavior and comparing it to that of others. The goal of this new training methodology is to enable the full cycle of immersive experience observing an expert, training with and without guidance, and observing own performance.

Learning analytics for workplace and professional learning

Authors: Tobias Ley, Ralf Klamma, Stefanie Lindstaedt and Fridolin Wild
Type: Conference proceedings
Source: the Sixth International Conference on Learning Analytics & Knowledge
Publisher: ACM New York, NY, USA
Date: 25 April 2016
Linkhttps://dl.acm.org/citation.cfm?id=2883860

Abstract: Recognizing the need for addressing the rather fragmented character of research in this field, we have held a workshop on learning analytics for workplace and professional learning at the Learning Analytics and Knowledge (LAK) Conference. The workshop has taken a broad perspective, encompassing approaches from a number of previous traditions, such as adaptive learning, professional online communities, workplace learning and performance analytics. Being co-located with the LAK conference has provided an ideal venue for addressing common challenges and for benefiting from the strong research on learning analytics in other sectors that LAK has established. Learning Analytics for Workplace and Professional Learning is now on the research agenda of several ongoing EU projects, and therefore a number of follow-up activities are planned for strengthening integration in this emerging field.