Artificial intelligence to measure collaborative capacity of students

Artificial intelligence to measure the collaborative capacity of students
e-learning.

Tecnalia works on the development of semantic descriptors applied to collaboration indicators on e-learning platforms.

E-learning platforms are becoming particularly relevant now that training is a key factor for people, and both companies and universities or training centres are aware that they are going to be an essential training pillar in the future, thanks to their flexibility, dispersion and adaptation to the different study rates of students. One of the key aspects is the potential of collaborative learning between students; the ability to resolve a problem between several people, divide and spread out the work and learn from it, has a clear advantage over individual learning.

It is essential to be able to measure the degree of of each student, and have transferable metrics and indicators so that any e-learning platform can monitor the degree of collaboration of its . In this way, this platform can generate recommendations to encourage collaboration between its members, or correct inappropriate trends in a process.

Artificial Intelligence techniques are used to obtain this data and hence generate the opportune recommendations: Machine Learning and Data Mining, which provide metrics and indicators that are transferable to any e-learning programme, through semantic techniques that can be used on any platform for adaptive and recommendation purposes.


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Provided by Elhuyar Fundazioa
Citation: Artificial intelligence to measure collaborative capacity of students (2013, October 22) retrieved 23 July 2019 from https://phys.org/news/2013-10-artificial-intelligence-collaborative-capacity-students.html
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