Looking at the Future of Cognitive Technology in Education

Artificial intelligence (AI), cognitive technology, and machine learning are becoming increasingly intertwined in the classroom and online learning environment as products like IBM Watson Element aim to make personalized learning attainable and functional. A recent article published by IBM presented some interesting and compelling uses of IBM’s Watson artificial intelligence supercomputer to assist teachers and professors, as well as design and prescribe adaptive learning tracks for students, in addition to other innovative uses in and out of the classroom. Watson is a supercomputer-based question answering system which can answer questions in natural language. Watson’s use in the educational technology market is promising as it brings the potential to reach new populations of learners due to its ability to interact with users in natural language.

Natural Language and Dialogue

Cognitive technologies like Watson will be able to power new types of instructional devices and delivery methods such as Intelligent Tutoring, where systems use cognitive technology and natural language processing (NLP) to engage learners through dialogue. However, full extent of these technologies won’t be contained by the traditional and non-traditional classrooms. As segments of the employment population find themselves structurally unemployed, cognitive technologies can be used to create focused, yet realistically usable training courses in order to teach new skills and expand the workforce.

In one example provided in IBM’s article, a computer science professor at Georgia Tech used an AI powered teaching assistant powered by Watson to handle more basic student inquiries. Due to its highly convincing natural language programming, students did not realize they were interacting with a machine. In another example, the same teaching assistant bot software was used in a graduate course to similar results. With Watson handling housekeeping questions such as “when is the first discussion post due?” and “how long does the presentation need to be?”, professors are able to devote more energy to higher-level tasks while students still receive personal attention.

The Institution of Data

Artificial Intelligence and machine learning can play a major role in designing personalized curricula for students due to the amount of data being collected by teachers and learning management systems. Educational data analysis software such as IBM Watson Element allow instructors to record data and information about students’ performance, mastery, interests, attendance, and learning experiences which is then stored in the cloud and seamlessly shared across the entire institution. This sort of technology lets instructors collaborate and plan on how to approach particular trouble areas. Eventually, the software will be able to use the data collected and suggest individualized lesson plans or strategies for helping students master concepts. While the software is mainly used currently in the K–12 environment, its potential for use in Higher-Ed is noteworthy.

IBM Watson Element Demo

Moving Forward

One aspect of this new segment of computer technology which is currently entering the Higher-Ed community is intelligent tutoring. Pearson, a prominent educational resource publisher, recently announced a global education alliance intended to avail the advantages of cognitive technology to students using Pearson’s digital learning products. Using much of the same technology mentioned previously, the IBM Watson-Pearson collaboration aims to employ data analysis, adaptive learning systems, and on-demand tutoring (made possible by natural language programming) to empower students and professors alike.

All of these advancements and changes are not without potential pitfalls and challenges. Information sharing, especially sensitive information such as grades and personal identification numbers, must be handled properly and securely. The large amount of data being collected and analyzed needs to be used to improve student learning outcomes, not to identify underperforming schools, programs, or instructors. Technological oversaturation is a large concern for developing brains in the K–12 environment. As with any new field of science and technology, these sorts of considerations must be dealt with carefully and strategically as new software continues to enter the education market.

IBM’s Watson has already been successfully tested and utilized at a rather basic level in the college classroom as an automated teaching assistant. However, the developers and instructors alike have ambitious and exciting plans for the future of integration between educational technology and artificial intelligence, cognitive technology, and machine learning. As these technologies become increasingly ubiquitous, a paradigm of personalized, individualized learning become real possibilities.

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