Offering a Proper E-learning model for Islamic Azad University of Roudsar and Amlash (IAURA)

One of the opportunities that apply Technology an information technology at university is utilization of E-learning. For this reason various models have been suggested for e-learning technologies. In this paper for developing e-learning at IAURA, we analyzed and offered a new model of E-learning as for their requirements and essential offered models (Interactive model, Blended model, Virtual model).In this paper three models were compared. Thus, based on TAM model and utilization of AHP method we weighted these models by Expert Choice Software base on two views as easy and essential of use .E-learning easy of use at IAURA was completed by analyzing and prioritizing models based on implementation requirements and e-learning essential of use at IAURA was completed by analysis of scale of information technology projects at higher education .then we used SAW model for combination of results and interactive model was offered with highest weight. For testing this model in higher education we start many researches and then designed a questionnaire with fifty seven questions for easy of use and essential utilization of interactive model. In this study questionnaire was completed and responded by directors groups, active researchers and experts in e-learning area. After collecting responses, responses were sent to university. Also in this study we used SPSS software for analyzing and finally was determined that education requirements are most important factors in easy of use in interactive model at IAURA. In end of study we exhibited many suggestions for implementation of offered model

When Good Fit is Bad: The Dynamics of Perceived Fit

In the “quest” (Delone and McLean 1992) for reliable and practical measures of IS success, a growing stream of research has argued that a key predictor of performance impacts is user evaluations of fit between task requirements and characteristics of the system or technology (Goodhue and Thompson 1995; Vessey and Galletta 1991; Jarvenpaa 1989; Goodhue 1988). The argument is that a better fit produces better performance — good fit is desirable. It has also been argued that users are quite capable of reliably evaluating fit (Goodhue 1995). While both intuitively and empirically there is some support for these notions, evidence presented in this research suggests that users can misperceive their fit with technology. Furthermore, it is argued that such misperceptions of fit can inhibit learning and productivity with technology (generativity), and at the extreme may lead to catastrophic decision making by users (Weick 1990). The basis for these arguments draws on work in ecological psychology, cognitive science, and organizational theory to identify four types of fit, and focuses particularly on the process dynamics of how fit emerges from user-technology interactions

Making and Unfinishedness: Designing Toolkits for Negotiation

The diffusion and democratisation of computing technologies and physical prototyping systems has supported the rise of Do-It-Yourself culture. In the context of design innovation, this shift has undoubtedly blurred the lines between the roles of amateur and professional. Crowdsourcing platforms providing easily accessible, lightweight services to promote and fund ideas for new products can potentially radically compress the timescale from new concept generation to market. However, questions are emerging around these adjustments in the roles of amateur and professional, and to what extend individual makers and their communities can participate in, and benefit from, this new landscape. This paper will examine this situation using the framing of a “toolkit design and development” approach. We discuss the toolkit approach by drawing on the work of a current cross-European, interdisciplinary, collaborative project that is developing a technology toolkit to enable creation of locally based DIY networking systems

OVERVIEW OF RESEARCHES ON THE INFLUENTIAL FACTORS OF M-GOVERNMENT'S ADOPTION

Willingness of targeted users to adopt government mobile services is a determinant for the success of m-government, and as such, requires the interest of researchers who are focused on m-government research. Understanding the factors influencing the end-users to adopt government mobile services is very important for the government to find ways to encourage the use of these services by targeted users, so that investment in adopting mobile technologies for government services can be profitable and safe. Although, some researches to measure citizens' perceptions of m-government have been conducted recently, the anticipation and explanation of m-government use to provide full understanding of the adoption of m-Government requires further investigation. For all those who would like to study the factors influencing the adoption of m-Government, it is essential to know about the work done so far by researchers and scholars of this field and to learn the theoretical and methodological approaches used in relevant researches. In attempt to provide such an overview, many research studies in the field of User Acceptance and adoption of m-Government services have been analysed in this research. A summary table reflects the studies conducted by 19 different authors in identifying factors that may influence the adoption of m-Government, by summarizing them from a selective list of articles published between the years 2011-2017.  Article visualizations

Gesture recognition with application in music arrangement

This thesis studies the interaction with music synthesis systems using hand gestures. Traditionally users of such systems were limited to input devices such as buttons, pedals, faders, and joysticks. The use of gestures allows the user to interact with the system in a more intuitive way. Without the constraint of input devices, the user can simultaneously control more elements within the music composition, thus increasing the level of the system's responsiveness to the musician's creative thoughts. A working system of this concept is implemented, employing computer vision and machine intelligence techniques to recognise the user's gestures.Dissertation (MSc)--University of Pretoria, 2006.Computer ScienceMScunrestricte