Abstract: The use of digital media is increasingly being promoted in school teaching. Since this aspect changes the interaction between teachers and pupils, this research is concerned with the development of a prototype of a mobile application for Android and iOS, in which different learning applications for language acquisition are offered on the basis of learning analytical measurements provided by experts in the field. By logging and collecting interactions of the user, it is possible to create a variety of statistical evaluations and thus respond to the needs and weaknesses of students. For the evaluation of the application, a user experience test was carried out, whereby the child-friendly operation of the application was tested. Due to the very positive feedback, the design was found to be good and can therefore be further developed.
Reference: Friedl, Markus, Ebner, Markus, Ebner, Martin (2020) Mobile Learning Applications for Android und iOS for German Language Acquisition based on Learning Analytics Measurements. International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI). 2(1). pp. 4-13
Due to recent technological advancements, artificial intelligence (AI) has received increased attention and has been adopted to many sectors and fields, thus, producing a profound impact. Given the rapid advancement of AI, it is expected that AI will continue to develop, integrate deeper and in many different sectors. Although the application of AI in the educational sector has been the subject of research for more than 30 years, a renewed and enforced interest in AI in education can be documented through the themes of scientific conferences, workshops and research papers, as well as how the Edtech industry is increasing efforts to integrate AI in educational applications. Indeed, this development is not unexpected considering that AI is associated with potentials of more personalized, adaptive and inclusive learning, and with empowered teachers and advanced learning environments. This Special Issue aims at highlighting contemporary research that covers AI in education. We are looking forward to receive both theoretical and empirical papers that provide readers with a better understanding of the theoretical discussions that are currently taking place, the empirical studies that are conducted, and the AI applications and systems that are developed