Reaching All Students

Technologies pose a great opportunity to widen the access to learning spaces and helping to reach more students in remote areas. In addition, artificial intelligence and smart devices can make teaching and learning more inclusive by reducing biases or overcoming language barriers.

The scenario “Reaching All Students” enlightens how technologies can improve accessibility and inclusiveness of learning, learning environments, and contents for marginalized children and youth and persons with disabilities, among others.

A huge barrier to effectively extending access to education is limited broadband internet coverage, especially in rural areas. Technologies such as Drone Wireless Network and 5G Mobile Network, not only educational providers benefit from stable internet access, but also learners with mobile devices will be able to learn beyond classroom walls. But even in the case of regions that may not be covered by wireless providers or with data costs that are still too elevated (as seen in some regions of South Africa), services such as Unstructured Supplementary Service Data (USSD) could help members of such communities (including parents) to be included in the system through SMS messages, prepaid callback service and mobile money transfers (e.g. to pay teacher salaries).

In classrooms with no access to the internet and/or electricity at all, an Itinerary School Station —a business model that introduces mobile solar-powered multimedia device kits into educational environments— can also help to provide access to preloaded educational content to complement the school curriculum, becoming a very useful tool for low-income communities. With a view on labor market-relevant skills, coding will offer increasingly income opportunities especially for youth and women in our partner countries. However, access to learning coding is restricted to those with the means to pay for expensive courses and the necessary time. The JavaScript-powered application Interactive Source-Code Editor eases the process of learning to program code based on short, interactive lessons that are also available in offline mode if access to the internet is limited.

Platform-based strategies such as Cloud Education and Mobile Learning, as well as solutions such as Micro-learning Platforms, will give opportunities for teachers and institutions to reach out to students and experiment with novel learning methodologies, including more participatory ones. On the other hand, technologies can not only extend the learning environment but also make it more inclusive. Following the principle of “Leave no one behind”, the application of assistive technologies can foster opportunities for migrants or people with disabilities. Especially for those learners who have language barriers, the use of a Translating Earbud could make communications more seamless, especially in the case of parents who are not fluent in the national language.

Similarly, a Talking Book such as the one developed by Amplio offers another approach to illiterate people by providing mediated exchanges that are actionable and comprehensive of dialects, making the process more organic and genuine to the student. Also, technologies such as virtual assistants, automatic speech recognition, machine translation, question answering, and automatic text summarization could enhance access and inclusiveness for students. These technologies are based on Natural language Processing (NLP), an artificial intelligence-based method that aims at the computationally understanding of human speech in text or audio format by evaluating the meaning and significance of words while completing tasks. An application example of the use of NLP is the development of an AI Therapist that engages in dialogues with users to deliver therapeutic assistance by generating health-related reminders and mental health coping mechanisms in a personalized way.

Also, by reducing and revealing biases, emerging technologies can make teaching and learning more inclusive. Technology applications such as an Algorithmic Bias Detection Tool and Collaborative Culture-Sensitive AI could identify biased judgments or uncover previously unknown biases or underlying unfairness in society. This would benefit disadvantaged groups in particular. Furthermore, collaborative algorithmic structures trained with inputs from minority communities could serve as a tool to preserve traditional cultural heritage, endangered languages, and customs. An example is Location-based Learning, a business model that serves as a cultural heritage platform that educates the local community about the current location.