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IBM Watson Industry Cognitive Education Methods

Authors: M, Rajeshwari; K, Krishna Prasad;

IBM Watson Industry Cognitive Education Methods

Abstract

Data analytics converts bulk of data into insights for business, healthcare, insurance and education. An upcoming development in IBM’s data analytic approach towards education is cognitive learning systems. Human being and machine can communicate each other by the technologies that use Natural Language processing and Machine Language together in action. Presently, many students struggle for their education without any goals. In this sense, cognitive systems should improve student education and results with a customized perception of their learning. IBM has recently pointed his service on education by its supercomputer or computing technology, IBM Watson. Such systems can provide an expert assistant to all varies of professionals in their respective fields. It is also being used widely to assess student performance and to help educators in the classroom develop more constructive instructional practices for their students. It helps the teacher to collect attendance, marks detail and to analyse the individual student’s interest based on his result. This industrial analysis will explain the power of data analytics in classroom by the teachers to assess the student’s personal behaviour and the way it is used as a tool by the teachers to determine student’s interest in finding the better career. Based on individual student outcome, Watson using AI will find solutions to improve quality and policy of education. Here AI technology gives tools to the teachers they need to be most effective and help learners perform at the top of their abilities like tutors, childhood vocabulary development and personalizes content for students based on mastery. Data Digital services and apps are used on learning and they help in the learning experience. This study will help to understand the way different technologies working together in predictive analytics and to prepare a report on admission, number of attendances, student dropout rate, their result analysis and their future. This study will analyse the success rate of personalised education of student using cognitive learning skills.

Keywords

Machine Learning, AI, Learning, IBM Watson, Cognitive Systems, Natural Language Processing

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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