This paper attempts an analysis of some current trends and future developments in computer science, education, and educational technology. Based on these trends, two possible future predictions of AIED are presented in the form of a utopian vision and a dystopian vision. A comparison of these two visions leads to seven challenges that AIED might have to face in the future: intercultural and global dimensions, practical impact, privacy, interaction methods, collaboration at scale, effectiveness in multiple domains, and the role of AIED in educational technology. The paper discusses these challenges and the associated risks and opportunities.

Generative artificial intelligence (AI) (GenAI) has emerged as a transformative force in various fields, and its potential impact on education is particularly profound. This chapter presents the development trends of “GenAI in Education” by exploring the technical background, diverse applications, and multifaceted challenges associated with its adoption in education. The chapter briefly introduces the technical background of GenAI, particularly the development of large language models (LLMs) such as ChatGPT & Co. It provides key concepts, models, and recent technological advances. The chapter then navigates through the various applications of GenAI or LLMs in education, examining their impact on different levels of education, including school, university, and vocational training. The chapter will highlight how GenAI is reshaping the educational landscape through real-world examples and case studies, from personalized learning experiences to content creation and assessment. It also discusses various technical, ethical, and organizational/educational challenges to using technology in education.

A large number of refugees need to learn a new language in order to transition to, or settle in, a new country. Most refugees have access to smartphones with which they can access mobile language learning tools. However, refugees in different stages of their journeys have different language learning needs. Identifying the unique needs of refugees is essential to design language learning tools that support their language learning activities. Through a two-part participatory design study, we identify and compare the tacit and latent language learning needs of two different groups of Syrian refugees: a group in transition in Lebanon, and a group settling in Germany. The Syrian refugees we worked with in Lebanon are studying English to transition to another country with better living conditions. On the other hand, the Syrian refugees we worked with in Germany are trying to learn German to better integrate into German society. Our results show overlapping needs and specific needs for the two groups of refugees. We present our findings and discuss the opportunities and challenges for designing language learning tools to support the language learning activities of refugees.