Recent meta-analysis and literature reviews support that adaptive learning systems are components of effective instruction. These exciting results are motivating researchers to explore new technologies that provide relevant students' information to promote a better-personalized experience for students to achieve better learning outcomes in technology-enhanced learning environments. A new trend is related to the studies that use brain-imaging techniques to provide relevant students' information for educational systems, aiming to enable an enhanced personalized experience. Some of these studies are making use of artificial intelligence to provide real-time monitoring of students' cognitive phenomena supplied by brain-imaging techniques such as electroencephalography and functional magnetic resonance imaging. Therefore, considering the relevance of the application of artificial intelligence in studies that use brain-imaging techniques combined with technology-enhanced learning environments and the lack of a current understanding of how these techniques have been used in this context, we present a systematic literature review (SLR) that aims to explore which artificial intelligence algorithms have been adopted, what are their purposes in studies that apply brain-imaging techniques in educational technologies and which were the results reported in these studies related to the use of artificial intelligence algorithms. The systematic literature review was conducted according to the recommendation of a well-accepted guideline to perform a rigorous review of the current literature. The search was conducted in seven academic databases in January 2020 and resulted in a total of 6089 studies that was reduced to 20 studies for the final analysis.

People with disabilities living in Brazil face great difficulties in the tasks of daily life mainly due to the lack of accessibility in public spaces, products and services. In this context, we noticed a lack of a computing tool that embraces both people with visual and hearing impairment. This work presents TATU -- a mobile application for both Android and iOS platforms aimed at supporting people with visual or hearing impairment to enjoy Brazilian tourist attractions, including both open-air and indoor spaces. TATU application has an adaptive interface exclusively designed for each of the impairment user profiles, it can work on guided tour mode by indoor navigation using BLE beacons and outdoor navigation using GPS. Our solution was evaluated by three experiments, one of which was carried out with blind volunteers and TATU application obtained satisfactory results for both spacious attractions with the lowest density of collection items and for the smallest spaces.