SWOT Analysis of innovative technologies applied to educational sector (Strengths, Weaknesses, Opportunities, and Threats)

There are some voices talking about the so called “4rth Industrial Revolution” as we have seen in several articles, books and keynotes. In 2017 some of the latest digital technologies kept on revolutionizing the education landscape and promised to be on top of the cutting-edge trends.

We have carefully selected and analysed three innovative technologies applied to educational sector in a SWOT matrix.


1. Blockchain in the educational system. Cryptoblocks on student data storage and delivery

At first, it seems a bit difficult to link blockchain technologies to education, accustomed as we were to relate it to cryptocurrencies. Nontheless, this Distributed Database is being implemented in many fields. One of the advantages of Blockchain applied to education is the possibility to bring a global digital system which would allow institutions to share validated documents and to recover academic records under will. Despite this, some issues would come by the hand of the lack of standards and the possibility of security failures.

2. AI and Machine Learning applied to education. Chatbots and automated processes

With a proper training and a good amount of data, Artificial Intelligence and Machine Learning applied to education can help analyzing student needs. Artificial Intelligence helps boosting automated processes, improving user experience and solving problems anytime. These technologies can help economizing processes and aid the teacher in some boring or repetitive tasks although they still have some problems to solve such as information leaks or programming errors. They must, first of all, gain the confidence of users, not accustomed yet to interact with bots.   

3. Learning Analytics and Big Data inside education. Student process analysis, dashboards and learning optimizing

Learning Analytics are key in the process of mapping student behavior and predicting situations such as disengagement. Educational data mining helps building adapted learning, easens the process of admissions to the HEI and facilitates student course completion. It can be also a tool for professors to adapt their teaching when necessary. On the negative side, there are dangers such as a depersonalization during the process due to automation in the data mining and a shock between the procedure and how society understands the control of big amount of behavioral data by digital automatic means.

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Desirée Gómez on Twitter
Desirée Gómez
Content curator and analyst. @eLC_UOC's Twitter Community Manager and eLC's Blog Content Specialist at the Research and Trend Analysis department of the eLearn Center at Universitat Oberta de Catalunya. Educational, innovation & technology trend detection and analysis, content curation, communication and observing tasks. University and Master Graduate on History of Art by the Universitat de Barcelona, specialised in International Relations and educational and technological observation.

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