Educational Data Mining plays a crucial role in identifying academically weak students of an institute and helps to develop different recommendation system for them. Students from three colleges of Assam, India were considered in our research which their records were run on deep learning using sequential neural model and adam optimization method. The paper compared other classification methods such as Artificial Immune Recognition System v2.0 and Adaboost, to find out the prediction of the results of the students. The highest classification rate was 95.34% produced by the deep learning techniques. The Precision, Recall, F-Score, Accuracy, and Kappa Statistics Performance were calculated as a statistics decisions to find the best classification methods. The dataset used in this paper was 10140 student records. Directing the student for their future plan comes from discovering the hidden patterns by using Data Mining techniques.

Abstract-The purpose of this paper is to review the most representative studies of the last decade (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) which deal with the combination of technology and music and concern individuals with Generic learning disabilities. Particularly, the areas of needs in this paper are divided to the following categories: Depression/ disruptive behavior, Down syndrome, Intellectual disabilities, Cerebral palsy and Severe/Profound disabilities. It is also underlined the important role of Information and Communication Technologies (ICTs) and digital music tools in promoting musical participation and assisting students with the pre-referred disabilities.

Navigation assistive technologies have been designed to support the mobility of people who are blind and visually impaired during independent navigation by providing sensory augmentation, spatial information and general awareness of their environment. This paper focuses on the extended Usability and User Experience (UX) evaluation of BlindRouteVision, an outdoor navigation smartphone application that tries to efficiently solve problems related to the pedestrian navigation of visually impaired people without the aid of guides. The proposed system consists of an Android application that interacts with an external high-accuracy GPS sensor tracking pedestrian mobility in real-time, a second external device specifically designed to be mounted on traffic lights for identifying traffic light status and an ultrasonic sensor for detecting near-field obstacles along the route of the blind. Moreover, during outdoor navigation, it can optionally incorporate the use of Public Means of Transport, as well as provide multiple other uses such as dialing a call and notifying the current location in case of an emergency. We present findings from a Usability and UX standpoint of our proposed system conducted in the context of a pilot study, with 30 people having varying degrees of blindness. We also received feedback for improving both the available functionality of our application and the process by which the blind users learn the features of the application. The method of the study involved using standardized questionnaires and semi-structured interviews. The evaluation took place after the participants were exposed to the system’s functionality via specialized user-centered training sessions organized around a training version of the application that involves route simulation. The results indicate an overall positive attitude from the users.

The significance of digital assistive technology in everyday life of people with disabilities has been continuously increasing during the last decade. An important example is that of the development of mobile apps which are suitably adapted for use by sensory-deprived people. We are involved in developing two such initiatives. The first offers interactive indoor navigation for blind and visually impaired persons, while the second offers deaf people a user-friendly environment for text depiction of the verbal speech, even when the articulation is defective, which is usually the case when the speaker is deaf. Despite the possible benefits of these apps, this does not necessarily signify automatic acceptance. This study aims to examine factors that may inhibit take up, in order to obviate these as much as possible. Factors contributing to the acceptance of technology may be complex, such as ‘perceived usefulness’, ‘self-efficacy’ and ‘social influence’. An exploratory study of this issue will accrue qualitative evidence from the potential users. The paper concludes by presenting recommendations for the development of a tentative modified Technology Acceptance Model that considers the special circumstances around technology use by disability cohorts, to be tested as the research continues. Keywords: Technology acceptance model, blind and visually impaired, deaf, mobile apps, qualitative analysis. Keywords: Technology Acceptance Model; blind and visually impaired; deaf; mobile apps; qualitative analysis