Application potentials and challenges of artificial intelligence in education
Background and central aspects of the topic
In the future, artificial intelligence (AI) will likely play a much more vital role in the field of education, among other fields. Thus, in the context of the COVID 19 pandemic, teaching has shifted to digital platforms. For example, pupils and students are now working with personalised recommendation systems and AI-based learning apps. It is to be expected that AI will gain importance in the future not only as a subject of education in the school, tertiary and vocational sectors, but also as an educational medium.
At the learner level, possible applications include e. g. the support of a (digitally organised) learning process by means of evaluating available data (learning and data analytics). By collecting data on the learning progress (process data from digital learning platforms, but also data obtained by means of special sensors such as eye-tracking glasses), it is possible to provide hints with regard to strengths and weaknesses in knowledge acquisition or to offer the respective appropriate learning content. Moreover, intelligent tools for creating augmented or virtual realities (AR/VR) can provide a learning experience that is not subject to the limitations of analogue learning (e. g. in scientific experiments or simulations). For teachers, AI systems offer manifold possibilities to adapt the teaching of content and learning of competences more closely to the respective learning group and to individual learners, for example if the (automated) evaluation of the collected data reveals a need for support. At the institutional level, the data obtained can be used to prospectively assess learners' chances of success and, if necessary, to provide appropriate support.
So far, in Germany, AI in education is still in the early stages of development and implementation – both with regard to AI systems developed specifically for education and to the use of generic AI applications (e. g. language processing) in educational contexts. Furthermore, legal, pedagogical as well as ethical questions about the collection and use of learners' data and the risks of applying AI in learning processes still remain widely unanswered.
Objectives and approach
The tangible effects of AI applications on learners, teaching-learning processes or their organisation can only be analysed when a larger number of application examples is available and the results of current and future research projects have been evaluated.
This is why it has to be examined first – by way of a monitoring study – which education-related AI applications currently exist or are in development in Germany. In addition, the state of knowledge regarding the application potentials and challenges of AI applications in education as well as regarding possible opportunities for improving educational processes shall be evaluated and summarised in the form of a synopsis. Based on interviews with experts (from the fields of AI and education), a roadmap of expected developments should then be drawn up and possible impacts should be identified. For a concentrated analysis, we chose to focus on the area of vocational education and training.
In October 2021, an expert report was commissioned to review the status of research, development and application of AI in education, which is to evaluate the international academic debate with the help of a literature analysis, among other things. In addition to an overview of the various fields of application and systems, the aim is also to identify the potential, but also possible obstacles, and to gain insights into the significance of ethical guidelines and funding programmes. A second commissioned report will focus on the situation in Germany and, by means of web/desk research and surveys, will ascertain which AI-supported applications are already being used in the various areas of education, what expectations and fears are associated with them and what potential exists specifically in the area of competence-oriented learning in vocational education and training.
Publication on the topic
Themenkurzprofil Nr. 41
Learning Analytics – Potenzial von KI-Systemen für Lehrende und Lernende.