A Multi-task Oriented Selection Strategy for Efficient Cooperation of Collocated Mobile Devices

This chapter addresses the issue of tablets acceptance for studying. An experiment was carried out to test the effects of specific studying tasks experienced by students with no previous experiences with tablets on the perceived usability and usefulness of tablets. Students had to perform a high-compatible task (i.e. navigation/reading task) and a low-compatible task (i.e. writing task) for tablets. Subjective measures of usability, usefulness and use intention were designed to be more specific to the type of task than the classical measures used in the Technology Acceptance Model approach (Davis, 1989). Participants rated their answers before and after performing the tasks with a tablet. The results showed that the perceived usability and usefulness of tablets increased after the high-compatible task while their decreased with the low-compatible task. The findings stressed the need to consider the real user experience and to use more task-oriented measures to investigate the acceptance of mobile devices for studying.

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Effects of Studying Tasks Compatibility with Tablets on Their Acceptance

Mobile Devices in Education ◽

10.4018/978-1-7998-1757-4.ch041 ◽

2020 ◽

pp. 697-720

Author(s):

Franck Amadieu ◽

Charly Pecoste ◽

Claudette Mariné ◽

Cécile van de Leemput ◽

Colin Lescarret

Keyword(s):

Technology Acceptance ◽

Mobile Devices ◽

Technology Acceptance Model ◽

User Experience ◽

Reading Task ◽

Before And After ◽

Perceived Usability ◽

Acceptance Model ◽

Task Oriented ◽

Writing Task

This chapter addresses the issue of tablets acceptance for studying. An experiment was carried out to test the effects of specific studying tasks experienced by students with no previous experiences with tablets on the perceived usability and usefulness of tablets. Students had to perform a high-compatible task (i.e. navigation/reading task) and a low-compatible task (i.e. writing task) for tablets. Subjective measures of usability, usefulness and use intention were designed to be more specific to the type of task than the classical measures used in the Technology Acceptance Model approach (Davis, 1989). Participants rated their answers before and after performing the tasks with a tablet. The results showed that the perceived usability and usefulness of tablets increased after the high-compatible task while their decreased with the low-compatible task. The findings stressed the need to consider the real user experience and to use more task-oriented measures to investigate the acceptance of mobile devices for studying.

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Setting Up Ad Hoc Computing as a Service in Mobile Ad Hoc Cloud Computing Environment

International Journal of Interdisciplinary Telecommunications and Networking ◽

10.4018/ijitn.2021010101 ◽

2021 ◽

Vol 13 (1) ◽

pp. 1-12

Author(s):

Muralidhar K. ◽

Madhavi K.

Keyword(s):

Mobile Devices ◽

Ad Hoc ◽

Attribute Selection ◽

Computation Offloading ◽

Mobile Users ◽

Selection Strategy ◽

Cloud Computing Environment ◽

Free Mobility ◽

Proposed Model ◽

Mobile Device Cloud

Despite the rapid growth in popularity and hardware capacity in mobile devices, they suffer from resource poverty, which limits their ability to meet increasing mobile users' demands. Computation offloading may give a prominent solution. But it relies on the connection to the remote cloud and may fail in situations where there is poor or no connectivity. Cloudlet was introduced to cover this problem, but mobile users miss free mobility when using cloudlets. Offloading to the cloud or cloudlet is not always the preferred solution. An alternative is to utilize the nearby mobile devices as local resource suppliers and pull their capabilities as a mobile device cloud. In this paper, the authors present such an approach known as ad hoc computing as a service (AhCaaS) model for computation offloading in an ad hoc manner by connecting to nearby mobile devices. They define a multi-attribute selection strategy to determine the optimal computation offloadee. They evaluated the proposed model, and the result shows that AhCaaS reduces execution time, battery consumption, and avoids task reassignment.

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Usability Evaluation of a Mobile Ecological Interface Design Application for Diabetes Management

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193120504901109 ◽

2005 ◽

Vol 49 (11) ◽

pp. 1042-1046 ◽

Cited By ~ 7

Author(s):

Jordanna Kwok ◽

Catherine M. Burns

Keyword(s):

Mobile Devices ◽

Interface Design ◽

Diabetes Management ◽

Usability Evaluation ◽

Task Characteristics ◽

Healthcare Applications ◽

Ecological Interface Design ◽

Ecological Interface ◽

Task Oriented ◽

Completion Times

Healthcare applications for small-screen mobile devices are becoming increasingly common for medical professionals and patients. Even so, usability issues including navigation and screen clutter remain a challenge. Ecological Interface Design (EID) was used to design a patient-oriented diabetes management display for Java-enabled mobile devices, making it one of the first mobile EID (mEID) applications. This paper presents a usability evaluation of the diabetes management application, which compares the mEID display to a modified taskbased display (mEID+Task). The mEID+Task display integrates functional task characteristics such as frequency and necessity; menu structure, item ordering, item labelling, and input scheme were varied. Results showed that normalised trial completion times were moderately faster in the mEID+Task display than in the mEID display, while no differences were observed in trial completion accuracy. Furthermore, the mEID+Task display received higher preference ratings than the mEID display alone. The findings suggest that the usability of mEID displays can be improved by incorporating a task-oriented approach.

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Apps, Apps, and More Apps

International Journal of Mobile Computing and Multimedia Communications ◽

10.4018/ijmcmc.2016010101 ◽

2016 ◽

Vol 7 (1) ◽

pp. 1-14 ◽

Cited By ~ 3

Author(s):

Matthew J. Haught ◽

Ran Wei ◽

Jack V. Karlis

Keyword(s):

Regression Analysis ◽

Mobile Phone ◽

Mobile Devices ◽

Uses And Gratifications ◽

The Internet ◽

Access To Information ◽

Regression Analyses ◽

Probability Sample ◽

Five Factors ◽

Task Oriented

This paper explores the reasons millions of people use stand-alone, task-oriented software programs designed for use on mobile devices, commonly known as “apps.” This study uses a survey with a probability sample of 576 app users. Consistent with the uses and gratifications approach, respondents were asked about their attitudes, interests, and opinions regarding apps. Theses measures were reduced to five factors. Then, regression analyses considered the factors as well as app use statistics and demographics to predict app use. The motivations of entertainment, convenience, and instrumentality are consistent with previously studied gratifications of the Internet and the mobile phone. However, the constant availability gratification for apps is unique because they provide quick access to information anytime and anywhere. Regression analysis showed these motivations predicted patterns of app use.

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The optimized selection strategy of crowdsourcing members in cloud-based design and manufacturing platform

Advances in Mechanical Engineering ◽

10.1177/1687814020903853 ◽

2020 ◽

Vol 12 (2) ◽

pp. 168781402090385

Author(s):

Jian Chen ◽

Rong Mo ◽

Suihuai Yu ◽

Dengkai Chen ◽

Jianjie Chu ◽

...

Keyword(s):

Selection Process ◽

Selection Index ◽

Medical Product ◽

Gray Relational Analysis ◽

Selection Strategy ◽

Design And Manufacturing ◽

Selection Indexes ◽

Cooperative Team ◽

Manufacturing Platform ◽

Task Oriented

Crowdsourcing services and cloud-based design and manufacturing platforms have been combined into an emerging network service model. Due to the diversity and differences of crowdsourcing members in the platform, member optimized selection process is uncertain and discrete, and it is difficult to find the most satisfying solution. In view of this, this article proposed an optimized selection strategy of crowdsourcing members to help users select reasonable crowdsourcing members to form the cooperative team with the most satisfaction. The research steps in this article are as follows. The first step is to analyze the characteristics of crowdsourcing services and crowdsourcing members in the cloud-based design and manufacturing platform. In the second step, according to the characteristics of crowdsourcing members, the evaluation index and target variables of members in the optimized process are proposed, the optimized selection system is established, and the calculation based on each target variable is given. In the third step, the decision-making model is established based on the optimized selection index system. The model decomposes the task-oriented global optimized selection indexes for crowdsourcing members into subtask-oriented local optimized selection indexes, and the gray relational analysis method is used to solve the model. Finally, the effectiveness of the proposed method is verified by taking the crowdsourcing member optimized selection process in the medical product research and development task as an example.

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