Ubiquitous service access through adapted user interfaces on multiple devices

Nylander, Stina; Bylund, Markus; Wærn, Annika

doi:10.1007/s00779-004-0317-4

Cited by 22 publications

(5 citation statements)

References 12 publications

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“…The u-Business is defined as a business system applied to a diversity of fields by using Ubiquitous Computing and networks to intellectualize things, terminals, goods inducing customers' business activities in the living environment, and devices or systems constructing business processes and by connecting them with networks [11,13,14]. U-Business service is not an entirely new concept.…”

Section: Analysis On Construction Processes In the Shipbuilding Industrymentioning

confidence: 99%

A Study on User-Oriented and Intelligent Service Design in Sustainable Computing: A Case of Shipbuilding Industry Safety

Joe¹,

Chang

2017

Sustainability

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Most business services based on Ubiquitous Computing are being designed with a sole focus on the technological sector, without considering business elements. In light of this trend, this study was intended to design a user-oriented u-Business service for preventing and promptly responding to industrial disasters at shipbuilding sites using a systematic methodology. Specifically, major danger elements of disasters in need of preferential preventive and responsive measures were derived as business opportunities unfulfilled by the current process, and then a u-Business service was developed to prevent/respond to such dangers. Statistical analysis was performed on the developed services according to evaluation models, and the final u-Business service was selected based on this analysis. Resources and information systems were designed to support the chosen service.

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Section: Analysis On Construction Processes In the Shipbuilding Industrymentioning

confidence: 99%

A Study on User-Oriented and Intelligent Service Design in Sustainable Computing: A Case of Shipbuilding Industry Safety

Joe¹,

Chang

2017

Sustainability

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“…However, the proposal is intended to be used in only very limited set of internet based applications. Nylander et al [2005] provided the Ubiquitous Interactor (UBI) to address the problems of design and development that arise from services that need to be accessed from many different devices. The UBI offers a possibility to develop one device independent version of the service and then create device specific user interfaces for it.…”

Section: Related Workmentioning

confidence: 99%

Middleware based user interface migration

Salminen

Hosio

Riekki

2007

Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and the 1st International Sympo

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User interface can be seen as one of the greatest challenges in mobile computing. One promising approach to make interaction with mobile devices more efficient and pleasant is utilizing UI devices in the user's environment, such as, public displays. However, it is not clear to what extent the user is able to benefit from using external UI devices. Clearly, it also depends on the user's current task. In this paper, we present a middleware based approach that enables migration of user interface from a mobile phone to a device with better UI capabilities, such as, to a desktop computer. We quantitatively and qualitatively evaluate the benefits of such an UI migration to the user with two use cases that are common to mobile phone users; SMS or e-mail writing and establishing a phone call. The evaluation bears evidence that the method greatly increases the performance, and especially the enjoyability, compared to the mobile device's own interface when typing messages. Users prefer our approach because it provides faster and more convenient way to e.g. write a long SMS message. On the other hand for simple tasks, such as selecting a receiver when establishing a phone call or typing a very simplified message, the UI migration was found to be highly undesirable.

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“…Such need originates from the fact that traditional data sources, like logs, clickstreams, and content interactions taking place within the learning management system, only represent a small proportion of the learning activities and not the whole learning process (Pardo & Kloos, 2011). Multimodal data, in summary, can mitigate the streetlight effect, 1 by adding more street lights and expand the visible area and complete the learner's digital profile in the computer (Heckmann, 2005).…”

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confidence: 99%

From signals to knowledge: A conceptual model for multimodal learning analytics

Mitri

Schneider

Specht

et al. 2018

Computer Assisted Learning

159

100

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Multimodality in learning analytics and learning science is under the spotlight. The landscape of sensors and wearable trackers that can be used for learning support is evolving rapidly, as well as data collection and analysis methods. Multimodal data can now be collected and processed in real time at an unprecedented scale. With sensors, it is possible to capture observable events of the learning process such as learner's behaviour and the learning context. The learning process, however, consists also of latent attributes, such as the learner's cognitions or emotions. These attributes are unobservable to sensors and need to be elicited by human-driven interpretations. We conducted a literature survey of experiments using multimodal data to frame the young research field of multimodal learning analytics. The survey explored the multimodal data used in related studies (the input space) and the learning theories selected (the hypothesis space). The survey led to the formulation of the Multimodal Learning Analytics Model whose main objectives are of (O1) mapping the use of multimodal data to enhance the feedback in a learning context; (O2) showing how to combine machine learning with multimodal data; and (O3) aligning the terminology used in the field of machine learning and learning science. KEYWORDSlearning analytics, machine learning, multimodal data, multimodality, sensors, social signal processing | INTRODUCTIONWith the rise of data-driven techniques to discover insights and generate predictions from the learning process such as learning analytics, the need for 360°data about learners has grown consistently. Combining data coming from multiple sources has become a prominent necessity in learning research and has led to an increased interest in multimodality and consequently into multimodal data analysis. To clarify the concept of multimodality, we use the definition provided by Nigay and Coutaz. The term "multi" refers to "more than one", whereas the term "modal" stands both for "modality" and for "mode". The modality is the type of communication channel used by two agents to convey and acquire information that defines the data exchange.The mode is the state that determines the context in which the information is interpreted (Nigay & Coutaz, 1993). The reasons why multimodality in learning is drawing so much attention can be summarized according to four developments.First of all, multimodality is a consolidated theory. It has been subjected of investigation already for two decades in different fields including functional linguistic, conversational analysis, and social semiotics (Jewitt, Bezemer, & O'Halloran, 2016). Research in multimodal interaction investigated how different modalities interact andThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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Ubiquitous service access through adapted user interfaces on multiple devices

Cited by 22 publications

References 12 publications

A Study on User-Oriented and Intelligent Service Design in Sustainable Computing: A Case of Shipbuilding Industry Safety

A Study on User-Oriented and Intelligent Service Design in Sustainable Computing: A Case of Shipbuilding Industry Safety

Middleware based user interface migration

From signals to knowledge: A conceptual model for multimodal learning analytics

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