A comparative study of an assistive e-learning interface among students with and without visual and hearing impairments.

PURPOSE: Using a human-computer interaction (HCI) approach, the present study proposes a new e-learning interface with interactional features for use by students with varying visual and hearing needs. MATERIALS AND METHOD: Prototypes of these new features have been presented through several screens, including an interaction panel that allows for Button voice, Tab voice, Text voice, and sign language. The interactive features were evaluated by teachers and tested by students with and without visual and hearing impairments. Evaluation of the interface was conducted using a mixed methods design; student satisfaction with the features was measured quantitatively, while teacher perspectives regarding practical issues with implementation were explored through qualitative interviews. RESULTS: The results indicate a high level of satisfaction towards the new interactional features in the suggested user interface among all students regardless of visual and hearing ability. CONCLUSION: The teachers involved in the study expressed the need for comprehensive cooperation from academic organisations through provision of required support, including technical, financial, and human resources.IMPLICATIONS FOR REHABILITATIONThe existing e-learning systems in higher educational organizations revealed the need to develop and implement instructional communication features based on technological components to support visual-and hearing-impaired students.The implementation of the accessible e-learning system is an important strategical approach to enhance flexible access to learning contents for all students who are unable to attend a traditional mode of learning.This type of accessible e-learning system, along with teachers' support, is needed to develop a more comprehensive understanding of the self-management of the student's learning process; giving students the opportunity to study according to their individual abilities, schedules and locations.The integration of appropriate visual and hearing assistive technology (AT) and its related applications, embedded within the educational technology infrastructure, are important resources to enhance the educational outcomes for visual- and hearingimpaired students.

Development of a techno-humanist model for e-health adoption of innovative technology.

BACKGROUND AND PURPOSE: After investing billions of dollars in an integrated Electronic Medical Records (physicians) and Personal Health Records (patients) system to allow both parties to manage and communicate through e-health innovative technologies, Canada is still making slow adoption progress. In an attempt to bridge the human and technological perspectives by developing and testing a holistic model, this study purports to predict patients' behavioral intentions to use e-health applications. METHODS: An interdisciplinary approach labelled as a techno-humanism model (THM) is testing twelve constructs identified from the technological, sociological, psychological, and organizational research literature and deemed to have a significant effect upon and positive relationship with patients' e-health applications adoption. Subjects were Canadians recruited in a mall-intercept mode from a region representing a demographically diverse population, including rural and urban residents. The SmartPLS measurement tool was used to evaluate the reliability and validity of study constructs. The twelve constructs were separately tested with quantitative data such as factor analysis, single, multiple, and hierarchical multiple regression. RESULTS: The hierarchical multiple regression analysis process led us to formulate four models, each hinged on a combination of interdisciplinary variables. Model 1 consisted of the technological predictors and explained 62.3% (p < .001) of variance in the behavioral intention to use e-health. Model 2 added the sociological predictors to the equation and explained 72.3% (p < .001) of variance. Model 3 added the psychological predictors to Model 2 and explained 72.8% (p < .001). Finally, Model 4 included all twelve predictors and explained 73% (p < .001) of variance in the behavioral intention to use e-health applications. CONCLUSIONS: One of the greatest barriers to applying e-health records in Canada resides in the lack of coordination among stakeholders. The present study implies that healthcare policy makers must consider the twelve variables with their findings and implications as a whole. The techno-humanist model (THM) we are proposing is a more holistic and continuous approach. It pushes back to a breakdown of the various technological, sociological, psychological, and managerial factors and stakeholders that are at the root cause of behavioral intentions to use e-health, as opposed to merely observing behavioral outcomes at the end of the "assembly line". Active participation and coordination of all stakeholders is a key feature.