Visible to the public Biblio

Filters: Author is Shrivastava, Gulshan  [Clear All Filters]
2022-06-14
Qureshi, Hifza, Sagar, Anil Kumar, Astya, Rani, Shrivastava, Gulshan.  2021.  Big Data Analytics for Smart Education. 2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA). :650–658.
The existing education system, which incorporates school assessments, has some flaws. Conventional teaching methods give students no immediate feedback, also make teachers to spend hours grading repetitive assignments, and aren't very constructive in showing students how to improve in their academics, and also fail to take advantage of digital opportunities that can improve learning outcomes. In addition, since a single teacher has to manage a class of students, it gets difficult to focus on each and every student in the class. Furthermore, with the help of a management system for better learning, educational organizations can now implement administrative analytics and execute new business intelligence using big data. This data visualization aids in the evaluation of teaching, management, and study success metrics. In this paper, there is put forward a discussion on how Data Mining and Data Analytics can help make the experience of learning and teaching both, easier and accountable. There will also be discussion on how the education organization has undergone numerous challenges in terms of effective and efficient teachings, student-performance. In addition development, and inadequate data storage, processing, and analysis will also be discussed. The research implements Python programming language on big education data. In addition, the research adopted an exploratory research design to identify the complexities and requirements of big data in the education field.