Use of Artificial Intelligence for Mobile Teacher Training in Africa

ID: 54347 Type: Brief Paper
  1. Thierry Karsenti, University of Montreal, Canada

Thursday, June 27 2:55 PM-3:15 PM Location: Oud West View on map

Presider: Arash Issaee, University of Vienna, Austria

Abstract: With its 46.3% poverty rate, Niger is one of the poorest nations on earth. In addition, of all the African countries, Niger has the fewest teachers as well as the highest percentage of unqualified teachers (83%). Like other developing countries, a key education issue in Niger is the need to improve initial and continuing teacher training programs. Accordingly, Niger, like many other countries, is seeking new ways to train teachers, and uses of ICT for education will play a leading role in this effort. However, many educators are insufficiently trained to teach. The ambitious UTIFEN project is an innovative response to these substantial challenges. Moreover, it contributes significantly to the renewal of teaching practices for both practicing and future teachers in Niger. UTIFEN also enables imaginative uses of artificial intelligence (AI) and technology that are adapted to Nigerien realities. This intelligent, flexible online training platform allows all teachers to train at their own pace. UTIFEN is aligned with the principles of personalized, adaptive learning (a simple form of artificial intelligence adapted to mobile learning), and its effectiveness has been repeatedly demonstrated in large-scale distance learning programs. UTIFEN is based on a simple premise: users’ responses are taken into account in order to better construct the learning experience throughout the process.


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