Influence Of Mobile Technologies Research Articles

Influence of mobile technology and smart classroom environment on learning engagement

To expand the application of mobile technology and smart classroom environment in education, and explore their influence on learning engagement, this paper, based on the Situated Cognition Theory, took 296 sophomores from six universities in China as the research objects and investigated the relationship between mobile technology, smart classroom environment, and learning engagement. The findings show that: (1) in the mobile technology and smart classroom environment, the frequency of learning by mobile devices in class, the frequency of learning by mobile devices after class, the duration of learning by mobile devices in class, the duration of learning by mobile devices after class, the hardware environment, software resources, and technology acceptance have positive effects on learning engagement; (2) mobile technology and smart classroom environment can better mobilize learners’ interest and initiative in learning and increase learners’ engagement in learning; (3) mobile technology and smart classroom environment can greatly improve college learners’ behavioural engagement, emotional engagement, and cognitive engagement respectively. This study helps turn the learners’ external learning needs into their internal learning motivation, thus enhancing their learning engagement.

851-P: Sleep and Quality of Life in Adolescents with Type 1 or Type 2 Diabetes

Poor sleep due to the influence of mobile technology and hectic schedules is common in adolescents and may affect overall diabetes management. The purpose of this study was to examine associations between sleep quality and perceptions of physical health, emotional well-being, self, family support, friendships and life satisfaction in adolescents with diabetes. Seventy-six adolescents with either T1D (n = 49; 25 males) or T2D (n= 27) completed a self-report global measure of sleep quality using a 5-point scale with higher values representing more sleep difficulty and measures of quality of life based upon subscales from well-validated and reliable instruments. These included the Kiddo KINDL® and the Diabetes Quality of Life Instrument for Youth with higher values on a 5-point scale indicating more positive perceptions of quality of life and life satisfaction. Hemoglobin A1c% (HbA1c) was obtained using the Abbott IMx® assay method. Adolescents with T2D were significantly older (15.2±2.0 vs. 14.0±1.4 years), had higher body mass index z-scores (2.0±0.6 vs. 0.6±0.9) and less duration of diabetes (2.0±1.8 vs. 5.5±3.2 years) (P < 0.01). There were no group differences in median scores for sleep quality or mean HbA1c (8.1±2.4 vs. 8.8±1.8) and no association between HbA1c and sleep quality. Using Spearman rho correlational analyses, there were significant associations between sleep quality and perceptions of physical health (rho = -.44), self (rho = -.19), family (rho = -.20), friends (rho = -.23) and life satisfaction (rho = -.25), P <0.05). Significant associations were stronger in those with T1D, ranging from rho = -.36 to -.64, including emotional well-being, likely due to the larger sample size for those with T1D. Results indicate those with greater sleep difficulty had lower quality of life. Greater emphasis on overall sleep quality and personal health and relationships are needed in future research and the clinical management of diabetes in adolescents. Disclosure M.S. Faulkner: None. Funding National Institutes of Health (R01NR07719)

Mobile Health Technology Evaluation

Globally, the advancement of mobile technology and the growing number of mobile phone users has promoted the boom in mobile health services. The influence of mobile technology has, in fact, made healthcare delivery more accessible, affordable and effective today. Consumers are thus increasingly using mobile devices as health service delivery aids across various countries. However, questions remain as to how consumer traits like personal innovativeness and self-efficacy, financial costs related to the service delivery and demographics like age and gender may affect the usage and adoption of mobile health services, especially for emerging economies like Bangladesh. Conceptual model of the study identifies self-efficacy, facilitating conditions, effort expectancy and performance expectancy to be significant constructs that influences users' overall perceptions of mobile health services, along with moderating effects of both age and gender upon the selected factors. Finally, the study highlights managerial implications, future research directions and limitations.

Seven Fears and the Science of How Mobile Technologies May Be Influencing Adolescents in the Digital Age

Close to 90% of U.S. adolescents now own or have access to a mobile phone, and they are using them frequently. Adolescents send and receive an average of over 60 text messages per day from their devices, and over 90% of adolescents now access the Internet from a mobile device at least occasionally. Many adults are asking how this constant connectivity is influencing adolescents’ development. In this article, we examine seven commonly voiced fears about the influence of mobile technologies on adolescents’ safety (e.g., cyberbullying and online solicitation), social development (e.g., peer relationships, parent–child relationships, and identity development), cognitive performance, and sleep. Three sets of findings emerge. First, with some notable exceptions (e.g., sleep disruption and new tools for bullying), most online behaviors and threats to well-being are mirrored in the offline world, such that offline factors predict negative online experiences and effects. Second, the effects of mobile technologies are not uniform, in that benefits appear to be conferred for some adolescents (e.g., skill building among shy adolescents), whereas risk is exacerbated among others (e.g., worsening existing mental health problems). Third, experimental and quasi-experimental studies that go beyond a reliance on self-reported information are required to understand how, for whom, and under what conditions adolescents’ interactions with mobile technologies influence their still developing social relationships, brains, and bodies.

Digital inclusion and social inclusion: a tale of two cities

This paper presents results of a recent research project that focuses on the influence of mobile technologies on social exclusion. It investigates the impact of two distinct approaches by local government to providing access to local support and services. Aug City advocated a bottom-up infrastructure-based model with non-state involvement after the technology was embedded. Conversely, Mobile City used a centrally planned model where the state acted as service custodians through teams of visiting officers and a mobile office. A case study approach was utilized focusing on two urban area of the UK, that adopted contrasting initiatives for implementing mobile information and communication technologies (MICT) to provide access to local government support and services. Activity Theory was used to provide a theoretical and analytical framework. A range of pre-existing information needs and barriers were revealed, but in some cases the technology itself presented a barrier. Issues with literacy, technology skills and in some cases the socioemotional condition of some of the socially excluded combined with the complexity of their information needs fundamentally undermines the direct access model for this section of the community. There are implications for social policy and practice. It is important to understand and address existing information needs and barriers (such as literacy and IT literacy, and social-emotional issues), ahead of new MICT initiatives to ensure the fullest chance of success and benefit for targeted communities and individuals.

Opinions from teachers in the Fresno area of Central California regarding the influence of mobile technology on their students’ learning

Opinions from teachers in the Fresno area of Central California regarding the influence of mobile technology on their students’ learning