The following paper presents the evaluation of an artificially intelligent assistant system (DIAS) with a service-oriented chatbot as a central communication element. The conversational AI (Artificial Intelligence) is supposed to increase information transparency in higher education environments and thus support students, teachers, and administrative staff. The exploratory study had two objectives: first, we intended to find out about the usability and utility of the DIAS chatbot using the CUQ (Chatbot Usability Questionnaire) score and benchmark the results against other conversational agents. Secondly, we were interested in possible effects among the different variables of interest, which could contribute to further theory development of chatbots in education. The results show that the DIAS chatbot scored above average, and can support students in finding relevant information, particularly if they use the assistant frequently. Positive aspects included the intuitive use, a welcoming persona (expressed in design & language) and easy navigation. The negative feedback showed potential for improvement particularly in content quality and handling dialogue mistakes, which is a general shortcoming of conversational AI at this development stage. The results can be used as a guidance for future research and theory building. However, they must be considered carefully due to several study limitations.

In a current research project at the Ansbach University of Applied Science, an AI-based quiz function was created to serve as a voluntary student-oriented support offer to determine their learning progress in their respective courses by means of conducting self-assessment quizzes. The application takes lecture scripts as input and applies a question generation model to create questions that students can answer. In order to evaluate the given answers, another language model is involved to perform Natural Language Inference (NLI). Users can engage with the system via a graphical user interface currently provided via a web app. To assess preliminary feasibility and perception of the model prototype, a qualitative focus group discussion following a semi-structured interview guideline prepared by the research team according to similar studies in the education field (Sek et al. 2012) was conducted with five participants. A transcript of the discussion was prepared and analyzed using the qualitative content analysis method according to Kuckartz. Overall, the quiz function was well received by the participants of the focus group. However, the prototype still has potential when it comes to generating meaningful questions and transparently assigning categories to the given answers. Furthermore, the quiz parameters should be individually adjustable by users. In the following paper, the development of the service is illustrated by outlining the considerations for the application design and the training procedure of the language models. Afterwards, the design of the qualitative focus group is described including the presentation of the results.

Artificial Intelligence (AI) is drastically transforming the world around us. Rather than replacing humans, hybrid intelligence combines human and machine intelligence to leverage each of their individual strengths. We summarize different requirements and approaches identified to achieve hybrid intelligence and focus on conversational AI to build a cognitive agent that supports knowledge management within an organization. The agent automatically extracts knowledge from artifacts provided or published by the us- ers. In addition, the knowledge base steadily grows while the agent talks to the users and the users provide feedback and the system is continuously learning to extract new types of entities and relations to answer more questions based on the knowledge graph and to access other sources of information. The first types of entities and relations extracted already support users in finding colleagues with relevant skills or inter- ests. Based on information provided by the agent, collaboration among employees and, thus, knowledge sharing and transfer is encouraged. The collaboration between the cognitive agent as an AI artifact and employees combined with a system that learns and adapts while in use stressing explainability and trust in its answers entails a step towards hybrid intelligence.

Digital technologies have become increasingly important for educational institutions since the Covid-19 pandemic. In this paper, we present an artificially intelligent assistant system that supports students and prospective students on different levels. In addition to an AI-based chatbot as the central communication element, the virtual guidance system includes planning, study analysis, and motivation applications. To evaluate how the assistant can best address students’ needs, a qualitative focus group study with eight current students was conducted in April 2022, involving first a user testing of the chatbot prototype and second an assessment of different concept sketches for the planner and motivator applications. Results from the user testing of the chatbot suggest the importance of a vivid persona and appealing design, accurate, guided, direct answering, and optional push messaging. In the second part concerning planner and motivator, the students expressed the wish to integrate predominantly functions, which help to prepare on time for exams and ideally bundle the applications on one platform to avoid switching between different platforms. Furthermore, participants voiced privacy concerns, as well as an increase in distraction and competitive pressure through gamification. The findings were used to further develop and refine the digital assistant before launch. They give detailed insight into why and how integrated, digital assistants can be successful in educational settings and can be used for future research in the emerging research field of AI in teaching and learning.

A successful study requires an efficient study organization. Not all students succeed in this, especially in distance learning scenarios. In the DIAS project, a digital intelligent assistant for studying and teaching is to be developed. The AI-based assistant will accompany students, motivate them and enable them to better organize and successfully complete their studies. It serves as a planner, communicator, analyzer and motivator. The assistant is being developed in close cooperation with all stakeholders and tested as a model in two degree courses at the University of Applied Sciences Ansbach. An app and an information terminal are to be implemented as exemplary output channels at Ansbach University of Applied Sciences.

In a current research project at a German university, a digital study assistant based on conversational AI is being developed. In this research project, four main application areas of the digital assistant are planned: communicator, for answering questions, conversation, and mentoring; a planner, for performing time and task management and course planning; a motivator, for actively managing learning success with gamification elements; and an analyzer, for processing necessary information about the student's study progress. In order to identify different application examples and possibilities for these four areas of the digital study assistant, the aim of this paper is to conduct a literature review. In addition to application examples and possibilities, implementation goals and the improvement of study results through such applications were researched.