BackgroundBangladesh is declared as Digital Bangladesh however medical students are least acquainted with the necessary ICT knowledge in the context of medical education. We have conducted a survey to know about Digital Equipment Ownership, therefore, carried out a self-reported assessment of knowledge and Utilization of ICT in relation to educational and clinical development.Materials and MethodsA cross-sectional, multi-centered questionnaire survey was conducted among the medical students during the period of October 2019.Result & DiscussionsIn total 467 medical students responded to the questionnaire in which 92% of the students owned a Google android smart phone and accessed the internet on their devices. 69% student has (1-5) medical related apps in their device and drug formulary apps most commonly used 43%. 59% of students have gained their present computer knowledge by via self-learning. For study work with fellow student, 90% student preferred Facebook group, Whats app and Viber. While there was a range of variation in the usage of non-academic search engines 72% Google and no usages were found for more dedicated academic services such as PubMed and Medscape. According to 74% of students, inadequate integration of ICT knowledge into their syllabus culminated in insufficient future professional skills. All students were keen for a Basic ICT learning program at the beginning of their medical courses.ConclusionThe study revealed that to prepare medical students for using ICT in their academic work adequately, introducing ICT training at the initial stage of the undergraduate program and designing the curriculum to develop a multiplicity of skills is essential in addition to an integrated teaching method.
The internet can broadly be divided into three parts: surface, deep and dark among which the latter offers anonymity to its users and hosts [1]. Deep Web refers to an encrypted network that is not detected on search engine like Google etc. Users must use Tor to visit sites on the dark web [2]. Ninety six percent of the web is considered as deep web because it is hidden. It is like an iceberg, in that, people can just see a small portion above the surface, while the largest part is hidden under the sea [3, 4, and 5]. Basic methods of graph theory and data mining, that deals with social networks analysis can be comprehensively used to understand and learn Deep Web and detect cyber threats [6]. Since the internet is rapidly evolving and it is nearly impossible to censor the deep web, there is a need to develop standard mechanism and tools to monitor it. In this proposed study, our focus will be to develop standard research mechanism to understand the Deep Web which will support the researchers, academicians and law enforcement agencies to strengthen the social stability and ensure peace locally & globally.
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