Challenges in context-aware mobile language learning: the MASELTOV approach

Smartphones, as highly portable networked computing devices with embedded sensors including GPS receivers, are ideal platforms to support context-aware language learning. They can enable learning when the user is en-gaged in everyday activities while out and about, complementing formal language classes. A significant challenge, however, has been the practical implementation of services that can accurately identify and make use of context, particularly location, to offer meaningful language learning recommendations to users. In this paper we review a range of approaches to identifying context to support mobile language learning. We consider how dynamically changing aspects of context may influence the quality of recommendations presented to a user. We introduce the MASELTOV project’s use of context awareness combined with a rules-based recommendation engine to present suitable learning content to recent immigrants in urban areas; a group that may benefit from contextual support and can use the city as a learning environment

Sport Psychology App lication: NCAA Coaches\u27 Preferences for a Mental Training Mobile App

This study utilized a consumer marketing approach to investigate National Collegiate Athletic Association (NCAA) head coaches\u27 preferences for a mental training mobile application (mobile map) using a conjoint market analysis. Head coaches\u27 preferences for a mental training mobile app were compared based on price, ability to track athlete use of the app, recommendation sources, the inclusion of daily functions, coaches\u27 awareness of the app being used by other teams, and the credibility of the mobile app content creators. Price and tracking athlete use were the two most important characteristics to coaches. Considering all characteristics, coaches preferred mobile apps that cost less than {dollar}200, provided comprehensive tracking of athlete use, came with an internal recommendation, included daily functions, were used by other teams, and were created by content creators who work with other successful programs. Based on market simulations, more than two-thirds of coaches would purchase a mental training mobile app with the characteristics presented in this study if given the chance. The present findings are evidence that the use of mental training at the NCAA level may rely more on the delivery method and cost of services than previously thought

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs

A Best Practice Guide for the Usage of Mobile Health Applications

The purpose of this capstone was to develop a best practice guide for the use of mobile health applications (mHealth apps) to aid in the care of chronically ill patients using an exemplar of blood pressure (BP) tracking for hypertension (HTN). Research on the use of mHealth apps is growing but a best practice guide for deployment of the apps has not yet been developed. Mobile health apps have expanded rapidly as smartphone technology captured the attention of American society. Mobile health apps have both inherent benefits and risks. The primary benefit of mHealth apps is the ability to track and display data at regular intervals during the day without resorting to paper data collection. The primary risk of mHealth apps is the possible violation of Health Insurance Portability and Accountability Act (HIPAA) laws with technology that is not yet adequately regulated by appropriate authorities. Mobile health technology on smartphones has proven to be far more useful than simply a replacement of paper data collection. Data show the use of smartphones for tracking data such as BP measurements engages patients in their treatment plans and empowers them to advocate for themselves. This empowerment adds a new dimension to the patient-provider relationship and to treatment plans, and one that providers should iv embrace. Smartphones give patients concrete actions to perform, promoting adherence to treatment plans and activities that foster long-term health. Although smartphone technology is mature and widespread, the healthcare community had not fully exploited it in an effort to combat chronic illnesses. This capstone focused on the development of a best practice guide for the usage of mHealth apps in an effort to facilitate deployment of mHealth apps in clinical settings. It was meant to serve as a practical best practice guide for healthcare providers to understand the capabilities of mHealth apps in the effort to reduce the effects of chronic illnesses in the United States and the benefits and risks associated with the use of mHealth apps. It was also meant to serve as a “How-To” book for the deployment of mHealth apps to patients with chronic illnesses