An Investigation Of The Relationship Between The Use Of Modern Digital Technologies, Language Learning Strategies, And Development Of Second Language Skills

Like many other areas of human knowledge, the field of language learning has undergone changes as a consequence of the application of digital technologies. Extensive exposure and anytime and anywhere access availability to data in a second or foreign language (L2) bring almost unlimited learning opportunities for digital age students, which affects their learning behaviors also known as language learning strategies (LLS). The purpose of the present study is to define preferred LLS patterns of digitally native L2 learners and to establish relationships between types of existing digital technologies, learners’ demographic characteristics, and the use of learning strategies to support the development of specific language skills and aspects. The setting for this study was made up by a medium-sized university in the northern U.S., particularly, its undergraduate student population enrolled in foreign language courses in the Department of Modern and Classical Languages and Literatures during the 2021 fall semester. They were asked to complete a survey that contained the original validated version of the Strategy Inventory for Language Learning (SILL) instrument (Oxford, 1990) and three additional sections disclosing the participants’ demographics, technology use experience, and targeted language skills and aspects. Both descriptive and inferential quantitative methods of data analysis were used in the study to elucidate the research questions. A number of analytic procedures using SPSS® Statistics software were performed to find out detailed statistic values of the research variables. Frequencies and descriptive statistics, analysis of correlations, extreme groupings t-tests to explore the relationships between the subsets of categorical variables, and factor analysis of LLS domains were implemented to identify meaningful patterns of technology use in L2 learning. Data from this study provide a view of how the Digital Natives themselves see their technology use and approaches to learning. Research conclusions based on obtained self-reported evidence allow us to make broader recommendations for changes in the L2 teaching methodology. They may also prevent instructors from making unsupported assumptions about their students\u27 mastery of educational technology, and, thereby, from neglecting to teach students the skills they need for academic success. Keywords: digital native learner, digital technology categories, language learning strategies, L2 language skill

Establishing Design Principles for Augmented Reality for Older Adults

Augmented Reality (AR) is growing rapidly and becoming a more mature and robust technology, which combines virtual information with the real environment in real-time. This becomes significant in ensuring the acceptance and success of Augmented Reality systems. With the growing number of older mobile phone users, evidence shows the possible trends associated with using AR systems to support older adults in terms of transportation, home activities, rehabilitation training and entertainment. However, there is a lack of research on a theoretical framework or AR design principles that could support designers when developing suitable AR applications for specific groups (e.g. older adults). This PhD research mainly focuses on the possibility of developing and applying AR design principles to provide various possible design alternatives in order to address the relevant AR-related issues focusing on older adults. This research firstly identified the architecture of Augmented Reality to understand the definition of AR using a range of previous AR examples. Secondly, AR design principles (version 1) were identified after describing the AR features and analysing the AR design recommendations. Thirdly, this research refined the AR design principles (version 2) by conducting two half-day focus groups with AR prototypes and related scenarios for older adults. The final version of the AR design principles (version 3) for older adults was established. These are: Instantaneous Augmentation, Layer-focus Augmentation, Modality-focus Augmentation, Accurate Augmentation and Hidden Reality. Ultimately, all of these design principles were applied to AR applications and examined in practice using two focus groups. Additionally, as part of the process of AR principle development, a number of AR issues were identified and categorised in terms of User, Device, Augmentation, Real Content, Interaction and Physical World, based on the pre-established AR architecture. These AR issues and design principles may help AR designers to explore quality design alternatives, which could potentially benefit older adults

Musiquence – Design, Implementation and Validation of a Customizable Music and Reminiscence Cognitive Stimulation Platform for People with Dementia

Dementia is a neurodegenerative disease that affects millions of individuals worldwide and is challenging to diagnose as symptoms may only perceivable decades later. The disease leads to a gradual loss of memory, learning, orientation, language, and comprehension skills, which compromises activities of daily living. Health-related costs caused by dementia will continue to increase over the next few years; between the years 2005 and 2009, an increase of 34% (from $315 to$422 billion worldwide) was observed in treating dementia-related issues. Pharmaceutical approaches have been developed to treat dementia symptoms; unfortunately, the risk of side effects is high. For this reason, nonpharmaceutical methods such as music and reminiscence therapies have gained acceptance as patients with dementia positively respond to such approaches even at later stages of the disease. Nevertheless, further research is needed to understand how music and reminiscence therapy should be used and to quantify their impact on individuals with dementia. The development of serious games has gained attention as an alternative approach to stimulate patients. However, the clinical impact that serious games have on individuals with dementia is still unclear. In this dissertation, we contribute with new knowledge regarding the usage of music and reminiscence approaches in people with dementia through a theoretical model. Based on Baddeley’s working memory model, our model aims to explain how the therapeutic properties of music and reminiscence can have a beneficial effect. To test our model, we developed a novel interactive platform called Musiquence, in which healthcare professionals can create music and reminiscence based cognitive activities to stimulate people with dementia. In this dissertation, we present the results from several studies about the usage and effects that music and reminiscence have on such a population. We performed two studies using Musiquence to study the feasibility of a novel learning method based on musical feedback to aid people with dementia during task performance in virtual reality settings. Results show that participants relied more on music-based feedback during the task performance of virtual reality activities than in other forms of feedback. Also, data suggest that the music-based feedback system can improve task performance, compensating for some dementia-related deficits. We also used Musiquence in a longitudinal one-month-long pilot study to assess its efficacy when used for a cognitive stimulation intervention in dementia patients. The results of the study are promising. The 3 participants showed improvements in terms of general cognition, quality of life, mood, and verbal fluency

Developing an Autonomous Mobile Robotic Device for Monitoring and Assisting Older People

A progressive increase of the elderly population in the world has required technological solutions capable of improving the life prospects of people suffering from senile dementias such as Alzheimer's. Socially Assistive Robotics (SAR) in the research field of elderly care is a solution that can ensure, through observation and monitoring of behaviors, their safety and improve their physical and cognitive health. A social robot can autonomously and tirelessly monitor a person daily by providing assistive tasks such as remembering to take medication and suggesting activities to keep the assisted active both physically and cognitively. However, many projects in this area have not considered the preferences, needs, personality, and cognitive profiles of older people. Moreover, other projects have developed specific robotic applications making it difficult to reuse and adapt them on other hardware devices and for other different functional contexts. This thesis presents the development of a scalable, modular, multi-tenant robotic application and its testing in real-world environments. This work is part of the UPA4SAR project ``User-centered Profiling and Adaptation for Socially Assistive Robotics''. The UPA4SAR project aimed to develop a low-cost robotic application for faster deployment among the elderly population. The architecture of the proposed robotic system is modular, robust, and scalable due to the development of functionality in microservices with event-based communication. To improve robot acceptance the functionalities, enjoyed through microservices, adapt the robot's behaviors based on the preferences and personality of the assisted person. A key part of the assistance is the monitoring of activities that are recognized through deep neural network models proposed in this work. The final experimentation of the project carried out in the homes of elderly volunteers was performed with complete autonomy of the robotic system. Daily care plans customized to the person's needs and preferences were executed. These included notification tasks to remember when to take medication, tasks to check if basic nutrition activities were accomplished, entertainment and companionship tasks with games, videos, music for cognitive and physical stimulation of the patient

Universal Communication model and evaluation with the Elderly Society

Telecommunication uses today various devices, operating systems, network technologies and applications. The multiplicity and diversity of these items are expected to increase due to the development of new technologies. As a result communication becomes a challenge. Communication is according to the World Health Organization a basic requirement for participation of elderly people in the society. In this thesis the architecture model ¿Universal Communication Model¿ (UCM) for the unified application of these items is developed and investigated. The future society will merely be 60+ and lowered physical abilities for communication need to be compensated. Two hypotheses that represent challenges of the UCM are provided and investigated: First, ¿Elderlies have difficulties in stress and ad-hoc situations to cope with ICT solutions¿ (H 1), and second ¿Elderlies have problems to reach destinations¿ (H 2). Both hypotheses are divided into sub-hypotheses without and with UCM support. Two use cases are applied to the UCM: Elderly father at home called by his daughter from her car, and disoriented grandma walking to her appointment at the medical clinic using the public transportation system. The two use cases are detailed with scenarios and corresponding prototypes. 24 tasks for elderly probands are developed and executed in a laboratory setting with 30 elderlies (including a questionnaire): Half of the tasks, namely twelve, are designed without the UCM and the other half with the application of the UCM. The time measurements to solve the tasks are evaluated using two statistical methods: The Euclidean distance and the Kullback-Leibler divergence of the measured data distributions and the corresponding Gaussian distributions are computed. The experiments demonstrate that the task execution durations were reduced by a factor of up to six due to the application of the UCM (compared to the situation without UCM). And the (qualitative) satisfaction factor of the probands increased by a factor of up to four for all tasks due to the seamless and multimodal UCM. These results show that the UCM supports communication for the elderly society in a seamless and intuitive way.Ingeniería, Industria y Construcció

Interventions to Improve Medication Management in the Aging Population: An Evidence-Based Practice Project

The overall focus of each of case scenarios are related to assessment or interventions that are related to Choosing Wisely Campaign® items 1, 2, 3, 5, 8, 10. Case scenarios were developed related to each initiative with clientele and conditions across the lifespan in various practice settings. Practice settings included school district, outpatient pediatric, primary care, skilled nursing facility, work rehabilitation, and acute care

Effects of age on smartphone and tablet usability, based on eye-movement tracking and touch-gesture interactions

The aim of this thesis is to provide an insight into the effects of user age on interactions with smartphones and tablets applications. The study considered two interaction methods to investigate the effects of user age on the usability of smartphones and tablets of different sizes: 1) eye-movements/browsing and 2) touch-gesture interactions. In eye movement studies, an eye tracker was used to trace and record users’ eye movements which were later analysed to understand the effects of age and screen-size on browsing effectiveness. Whilst in gesture interactions, an application developed for smartphones traced and recorded users’ touch-gestures data, which were later analysed to investigate the effects of age and screensize on touch-gesture performance. The motivation to conduct our studies is summarised as follows: 1) increasing number of elderly people in our society, 2) widespread use of smartphone technology across the world, 3) understanding difficulties for elderly when interacting smartphones technology, and 4) provide the existing body of literature with new understanding on the effects of ageing on smartphone usability. The work of this thesis includes five research projects conducted in two stages. Stage One included two researches used eye movement analysis to investigate the effects of user age and the influence of screen size on browsing smartphone interfaces. The first research examined the scan-paths dissimilarity of browsing smartphones applications or elderly users (60+) and younger users (20-39). The results revealed that the scan-paths dissimilarity in browsing smartphone applications was higher for elderly users (i.e., age-driven) than the younger users. The results also revealed that browsing smartphone applications were stimulus-driven rather than screen size-driven. The second study was conducted to understand the difficulties of information processing when browsing smartphone applications for elderly (60+), middle-age (40-59) and younger (20-39) users. The evaluation was performed using three different screen sizes of smartphone and tablet devices. The results revealed that processing of both local and global information on a smartphone/tablet interfaces was more difficult for elderly users than it was for the other age groups. Across all age groups, browsing on the smaller smartphone size proved to be more difficult compared to the larger screen sizes. Stage Two included three researches to investigate: the difficulties in interacting with gesture-based applications for elderly compared to younger users; and to evaluate the possibility of classifying user’s age-group based on on-screen gestures. The first research investigated the effects of user age and screen size on performing gesture swiping intuitively for four swiping directions: down, left, right, and up. The results revealed that the performance of gesture swiping was influenced by user age, screen size, as well as by the swiping orientation. The purpose of the second research was to investigate the effects of user age, screen sizes, and gesture complexity in performing accurate gestures on smartphones and tablets using gesture-based features. The results revealed that the elderly were less accurate, less efficient, slower, and exerted more pressure on the touch-screen when performing gestures than the younger users. On a small smartphone, all users were less accurate in gesture performance – more so for elderly – compared to mini-sized tablets. Also, the users, especially the elderly, were less efficient and less accurate when performing complex gestures on the small smartphone compared to the mini-tablet. The third research investigated the possibility of classifying a user’s age-group using touch gesture-based features (i.e., gesture speed, gesture accuracy, movement time, and finger pressure) on smartphones. In the third research, we provide evidence for the possibility of classifying a user’s age-group using gesture-based applications on smartphones for user-dependent and user-independent scenarios. The accuracy of age-group classification on smaller screens was higher than that on devices with larger screens due to larger screens being much easier to use for all users across both age groups. In addition, it was found that the age-group classification accuracy was higher for younger users than elderly users. This was due to the fact that some elderly users performed the gestures in the same way as the younger users do, which could be due to their longer experience in using smartphones than the typical elderly user. Overall, our results provided evidence that elderly users encounter difficulties when interacting with smartphones and tablet devices compared to younger users. Also, it was possible to classify user’s age-group based on users’ ability to perform touch-gestures on smartphones and tablets. The designers of smartphone interfaces should remove barriers that make browsing and processing local and global information on smartphones’ applications difficult. Furthermore, larger screen sizes should be considered for elderly users. Also, smartphones could include automatically customisable user interfaces to suite elderly users' abilities to accommodate their needs so that they can be equally efficient as younger users. The outcomes of this research could enhance the design of smartphones and tablets as well the applications that run on such devices, especially those that are aimed at elderly users. Such devices and applications could play an effective role in enhancing elderly peoples’ activities of daily lives