Gender Differences in User Satisfaction of Mobile Touch Screen Interfaces: University Students’ Service Sites

2018 ◽  
Vol 15 (06) ◽  
pp. 1950003
Author(s):  
Ayman N. Alkhaldi ◽  
Ahmed Al-Sa’di
Keyword(s):  
User Interfaces ◽  
User Satisfaction ◽  
Quantitative Research ◽  
Service Providers ◽  
Rapid Development ◽  
Mobile User ◽  
Learning System ◽  
Mobile Service ◽  
Online Help ◽  
Future Work

The rapid development of mobile user interfaces for students’ websites and the constant utilization of such interfaces by students have witnessed a significant upsurge in growth. However, mobile service providers may lack valuable feedback on user satisfaction, particularly for Arabic users, because the sites are designed and implemented without students’ participation. This paper empirically investigates the user satisfaction of a mobile banner system for the University of Ha’il in Saudi Arabia. Users’ satisfaction was evaluated across six scales: overall reactions, screens, terminology and system information, learning, system capabilities, and technical manuals and online help. A quantitative research method was utilized, involving a questionnaire survey of 235 students. We found that female students have significant concerns about user satisfaction. The paper proposes theoretical and practical implications for future work.

Generating Personalized Navigation Learning Path Based on Knowledge Map

2014 ◽  
Vol 4 (2) ◽  
pp. 1-17
Author(s):  
Xiang Jun Huang ◽  
Chao Zhang ◽  
Qing Hua Zheng
Keyword(s):  
User Satisfaction ◽  
Information Overload ◽  
Rapid Development ◽  
Learning System ◽  
Knowledge Map ◽  
Learning Efficiency ◽  
Learning Path ◽  
Learning Instruction ◽  
E Learning ◽  
On Line

With a rapid development of Internet, E-Learning is becoming a new learning mode. E-Learning is not limited by time and space. It also has a large number of on-line learning resource. However, it has many disadvantages for students, such as information overload, disorientation, low learning efficiency, low user satisfaction and so on. Our aim is to improve learning efficiency and user satisfaction by overcoming information overload and disorientation of E-Learning system. This paper proposes an algorithm by combining Spreading-Activation Theory and techniques of classifying and sorting knowledge. The algorithm can generate a near optimal navigation learning path(NLP) based on a student's target knowledge unit(TKU) and knowledge map(KM) which it belongs to. NLP provides students an appropriate learning instruction to effectively eliminate disorientation during the process when they are learning interested knowledge units. The essential tasks of the algorithm is to filter redundant information and sort candidate knowledge units. So its realization process can be divided into three phrases: first, generating candidate complement map to overcome information overload. Because the candidate complement map only contains essential candidate knowledge units and learning dependencies among them to master TKU. Second, constructing learning features to discrete the candidate complement map to implement techniques of sorting knowledge conveniently. Final, sorting candidate knowledge units to get an appropriate NLP by using a Secondary Sort Strategy(SSS). The experimental results have shown that our method is sound for improving learning efficiency and users' satisfaction.

Comparison of context-aware predictive modeling approaches

2015 ◽  
Vol 11 (3) ◽  
pp. 323-346 ◽  
Author(s):  
Tapio Soikkeli
Keyword(s):  
Service Providers ◽  
User Behavior ◽  
Real Life ◽  
Initial Step ◽  
Mobile User ◽  
Mobile Service ◽  
Contextual Data ◽  
Content Type ◽  
Electronic Service ◽  
Behavior Models

Purpose – The aim of this paper is to empirically examine how to best incorporate such contextual data, such as location or the semantic place of mobile users, into mobile user behavior models. Acquiring such data has become technically easier than ever. The proper utilization of these data leads, hypothetically, to better understanding of mobile user behavior and, consequently, to enhanced mobile services. Design/methodology/approach – The paper systematically compares, under multiple experimental settings, the predictive performances of models built with three different approaches (pre-filtering, contextual modeling and post-filtering) used for incorporating contextual data into user behavior models. The comparisons focus on by which approach additional semantic place information can be best utilized for making the most accurate inferences on mobile user behavior. Real-life smartphone usage data are utilized in the analysis. Findings – The results demonstrate that none of the considered approaches uniformly dominate the others across all experimental settings. However, they show circumstance specific differences that need to be aligned with practical use cases for the best performance. Practical implications – Identifying the most suitable approaches for utilizing the semantic place (and other contextual) data is an important practical problem for electronic service providers, whose offerings are increasingly moving to the mobile domain and thus need to respond to the demands of mobility. Originality/value – The paper constitutes an initial step toward understanding and systematically evaluating different approaches for incorporating semantic place data into modeling mobile user behavior. Practitioners in the mobile service domain can apply the initial results and academics build upon them with more diverse experimental settings.

scholarly journals EFFECT OF LEARNING USING MATHEMATICA SOFTWARE TOWARD MATHEMATICAL ABSTRACTION ABILITY, MOTIVATION, AND INDEPENDENCE OF STUDENTS IN ANALYTIC GEOMETRY

2019 ◽  
Vol 8 (2) ◽  
pp. 219 ◽  
Author(s):  
Yanuar Hery Murtianto ◽  
Sutrisno Sutrisno ◽  
Nizaruddin Nizaruddin ◽  
Muhtarom Muhtarom
Keyword(s):  
Quantitative Research ◽  
Rapid Development ◽  
Learning System ◽  
Advanced Technology ◽  
Analytic Geometry ◽  
Mathematical Abstraction ◽  
Quasi Experimental ◽  
Research Findings ◽  
Independent Variable ◽  
Mathematica Software

Rapid development of technology for the past two decades has greatly influenced mathematic learning system. Mathematica software is one of the most advanced technology that helps learn math especially in Geometry. Therefore this research aims at investigating the effectiveness of analytic geometry learning by using Mathematica software on the mathematical abstraction ability, motivation, and independence of students. This research is a quantitative research with quasi-experimental method. The independent variable is learning media, meanwhile the dependent variables are students’ mathematical abstraction ability, motivation, and independence in learning. The population in this research was the third semester students of mathematics education program and the sample was selected using cluster random sampling. The samples of this research consisted of two distinct classes, with one class as the experimental class was treated using Mathematica software and the other is the control class was treated without using it. Data analyzed using multivariate, particularly Hotelling’s T2 test. The research findings indicated that learning using Mathematica software resulted in better mathematical abstraction ability, motivation, and independence of students, than that conventional learning in analytic geometry subject.

The Effect of Service Quality on Customers' Satisfaction in Mobile Phone Services in the UAE

2020 ◽  
Vol 8 (1) ◽  
pp. 75-94
Author(s):  
Emad Yusuf Masoud
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Mobile Phone ◽  
Service Providers ◽  
Mobile Service ◽  
Behavioural Difference ◽  
Mobile Industry ◽  
Quality Dimensions ◽  
Service Quality Dimensions ◽  
Network Quality

This study aims to determine the dimensions of mobile service quality and to examine their effect on customer satisfaction in UAE mobile phone service providers while also investigating the behavioural differences between mobile phone customers with prepaid and postpaid subscriptions. A combination of the SERVPERF model has been adopted as the main framework for analyzing service quality. A structured questionnaire instrument was designed for data collection. The present study concentrates on the level of customers’ satisfaction for leading service providers in the UAE mobile industry. Etisalat and Du were chosen for this study. A sample of (452) mobile phone users in Abu Dhabi city was selected at random using convenience-sampling. We found a positive effect of both functional and technical service quality (network quality) on customers’ satisfaction. Functional and technical dimensions were good predictors of customer satisfaction and confirmed the multidimensional nature of service quality. Also, the service quality dimensions; reliability, assurances, and responsiveness are found to be significant predictors of customer satisfaction. Behavioural difference between mobile phone customers is also significant in predicting customer satisfaction for postpaid subscribers. However, only reliability and network quality are significant predictors of customer satisfaction for prepaid subscribers. The model developed in this study provides marketers and researchers with a diagnostic tool to assess service quality from the perspectives of customers to meet the customer’s expectations and ensure customer satisfaction.

scholarly journals A recommendation and risk classification system for connecting rough sleepers to essential outreach services

Data & Policy ◽  
2021 ◽  
Vol 3 ◽  
Author(s):  
Harrison Wilde ◽  
Lucia L. Chen ◽  
Austin Nguyen ◽  
Zoe Kimpel ◽  
Joshua Sidgwick ◽  
...  
Keyword(s):  
Service Providers ◽  
Modern Society ◽  
Learning System ◽  
Extreme Weather Events ◽  
Resource Limitations ◽  
Modeling Process ◽  
The People ◽  
Weather Events ◽  
Outreach Services ◽  
Data Driven Approach

Abstract Rough sleeping is a chronic experience faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link (HL), a UK-based charity, in developing a data-driven approach to better connect people sleeping rough on the streets with outreach service providers. HL's platform has grown exponentially in recent years, leading to thousands of alerts per day during extreme weather events; this overwhelms the volunteer-based system they currently rely upon for the processing of alerts. In order to solve this problem, we propose a human-centered machine learning system to augment the volunteers' efforts by prioritizing alerts based on the likelihood of making a successful connection with a rough sleeper. This addresses capacity and resource limitations whilst allowing HL to quickly, effectively, and equitably process all of the alerts that they receive. Initial evaluation using historical data shows that our approach increases the rate at which rough sleepers are found following a referral by at least 15% based on labeled data, implying a greater overall increase when the alerts with unknown outcomes are considered, and suggesting the benefit in a trial taking place over a longer period to assess the models in practice. The discussion and modeling process is done with careful considerations of ethics, transparency, and explainability due to the sensitive nature of the data involved and the vulnerability of the people that are affected.

Measuring the Efficacy of a Pilot Public Health Intervention for Engaging Communities of Puerto Rico to Rapidly Write Hurricane Protection Plans

2020 ◽  
pp. 1-10
Author(s):  
Mark E. Keim ◽  
Laura A. Runnels ◽  
Alexander P. Lovallo ◽  
Margarita Pagan Medina ◽  
Eduardo Roman Rosa ◽  
...  
Keyword(s):  
Public Health ◽  
Puerto Rico ◽  
User Satisfaction ◽  
National Guard ◽  
Rapid Development ◽  
Public Health Intervention ◽  
Health Intervention ◽  
Project Work ◽  
Community Members ◽  
Community Based

Abstract Objective: The efficacy is measured for a public health intervention related to community-based planning for population protection measures (PPMs; ie, shelter-in-place and evacuation). Design: This is a mixed (qualitative and quantitative) prospective study of intervention efficacy, measured in terms of usability related to effectiveness, efficiency, satisfaction, and degree of community engagement. Setting: Two municipalities in the Commonwealth of Puerto Rico are included. Participants: Community members consisting of individuals; traditional leaders; federal, territorial, and municipal emergency managers; municipal mayors; National Guard; territorial departments of education, health, housing, public works, and transportation; health care; police; Emergency Medical Services; faith-based organizations; nongovernmental organizations (NGOs); and the private sector. Intervention: The intervention included four community convenings: one for risk communication; two for plan-writing; and one tabletop exercise (TTX). This study analyzed data collected from the project work plan; participant rosters; participant surveys; workshop outputs; and focus group interviews. Main Outcome Measures: Efficacy was measured in terms of ISO 9241-11, an international standard for usability that includes effectiveness, efficiency, user satisfaction, and “freedom from risk” among users. Degree of engagement was considered an indicator of “freedom from risk,” measurable through workshop attendance. Results: Two separate communities drafted and exercised ~60-page-long population protection plans, each within 14.5 hours. Plan-writing workshops completed 100% of plan objectives and activities. Efficiency rates were nearly the same in both communities. Interviews and surveys indicated high degrees of community satisfaction. Engagement was consistent among community members and variable among governmental officials. Conclusions: Frontline communities have successfully demonstrated the ability to understand the environmental health hazards in their own community; rapidly write consensus-based plans for PPMs; participate in an objective-based TTX; and perform these activities in a bi-lingual setting. This intervention appears to be efficacious for public use in the rapid development of community-based PPMs.

scholarly journals IoT Cloud Security Review

2021 ◽  
Vol 54 (4) ◽  
pp. 1-36
Author(s):  
Fei Chen ◽  
Duming Luo ◽  
Tao Xiang ◽  
Ping Chen ◽  
Junfeng Fan ◽  
...  
Keyword(s):  
Case Studies ◽  
Service Providers ◽  
Risk Mitigation ◽  
Rapid Development ◽  
Security Analysis ◽  
Cloud Security ◽  
Future Research ◽  
Security Risk ◽  
Research Attention ◽  
Cloud Systems

Recent years have seen the rapid development and integration of the Internet of Things (IoT) and cloud computing. The market is providing various consumer-oriented smart IoT devices; the mainstream cloud service providers are building their software stacks to support IoT services. With this emerging trend even growing, the security of such smart IoT cloud systems has drawn much research attention in recent years. To better understand the emerging consumer-oriented smart IoT cloud systems for practical engineers and new researchers, this article presents a review of the most recent research efforts on existing, real, already deployed consumer-oriented IoT cloud applications in the past five years using typical case studies. Specifically, we first present a general model for the IoT cloud ecosystem. Then, using the model, we review and summarize recent, representative research works on emerging smart IoT cloud system security using 10 detailed case studies, with the aim that the case studies together provide insights into the insecurity of current emerging IoT cloud systems. We further present a systematic approach to conduct a security analysis for IoT cloud systems. Based on the proposed security analysis approach, we review and suggest potential security risk mitigation methods to protect IoT cloud systems. We also discuss future research challenges for the IoT cloud security area.

scholarly journals Understanding Visual Saliency in Mobile User Interfaces

2020 ◽  
Author(s):  
Luis A. Leiva ◽  
Yunfei Xue ◽  
Avya Bansal ◽  
Hamed R. Tavakoli ◽  
Tuðçe Köroðlu ◽  
...  
Keyword(s):  
User Interfaces ◽  
Visual Saliency ◽  
Mobile User

A framework for programmatically designing user interfaces in JavaScript

2015 ◽  
Vol 11 (3) ◽  
pp. 254-269
Author(s):  
Henry Larkin
Keyword(s):  
User Interface ◽  
User Interfaces ◽  
Design Methodology ◽  
Rapid Development ◽  
Program Code ◽  
Web Based ◽  
Content Type ◽  
Mobile Web ◽  
Mobile Interfaces ◽  
New Framework

Purpose – The purpose of this paper is to investigate the feasibility of creating a declarative user interface language suitable for rapid prototyping of mobile and Web apps. Moreover, this paper presents a new framework for creating responsive user interfaces using JavaScript. Design/methodology/approach – Very little existing research has been done in JavaScript-specific declarative user interface (UI) languages for mobile Web apps. This paper introduces a new framework, along with several case studies that create modern responsive designs programmatically. Findings – The fully implemented prototype verifies the feasibility of a JavaScript-based declarative user interface library. This paper demonstrates that existing solutions are unwieldy and cumbersome to dynamically create and adjust nodes within a visual syntax of program code. Originality/value – This paper presents the Guix.js platform, a declarative UI library for rapid development of Web-based mobile interfaces in JavaScript.

scholarly journals Adaptive Reservation of Network Resources According to Video Classification Scenes

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1949
Author(s):  
Lukas Sevcik ◽  
Miroslav Voznak
Keyword(s):  
User Satisfaction ◽  
Quality Evaluation ◽  
Spatial Information ◽  
Service Providers ◽  
Video Quality ◽  
Subjective Assessment ◽  
Video Sequences ◽  
Network Resources ◽  
Proposed Model

Video quality evaluation needs a combined approach that includes subjective and objective metrics, testing, and monitoring of the network. This paper deals with the novel approach of mapping quality of service (QoS) to quality of experience (QoE) using QoE metrics to determine user satisfaction limits, and applying QoS tools to provide the minimum QoE expected by users. Our aim was to connect objective estimations of video quality with the subjective estimations. A comprehensive tool for the estimation of the subjective evaluation is proposed. This new idea is based on the evaluation and marking of video sequences using the sentinel flag derived from spatial information (SI) and temporal information (TI) in individual video frames. The authors of this paper created a video database for quality evaluation, and derived SI and TI from each video sequence for classifying the scenes. Video scenes from the database were evaluated by objective and subjective assessment. Based on the results, a new model for prediction of subjective quality is defined and presented in this paper. This quality is predicted using an artificial neural network based on the objective evaluation and the type of video sequences defined by qualitative parameters such as resolution, compression standard, and bitstream. Furthermore, the authors created an optimum mapping function to define the threshold for the variable bitrate setting based on the flag in the video, determining the type of scene in the proposed model. This function allows one to allocate a bitrate dynamically for a particular segment of the scene and maintains the desired quality. Our proposed model can help video service providers with the increasing the comfort of the end users. The variable bitstream ensures consistent video quality and customer satisfaction, while network resources are used effectively. The proposed model can also predict the appropriate bitrate based on the required quality of video sequences, defined using either objective or subjective assessment.

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