Artificial Intelligence Archives

Jul242026 by Heather WehnerNo Comments

New Pub: The Dependency Dilemma of Machine Learning Aids

Artificial Intelligence, Journal, New Pub

AI and machine-learning decision aids can be a great support for employees and help them improve their work performance. An overreliance on algorithmic recommendations, on the other hand, may result in a long-term reduction of the employees’ ability to develop and maintain their own decision-making skills. This could be especially problematic when such AI and machine-learning decision aids are not available. Instead of overly relying on such AI-based recommendations, organizations should train their employees to continue developing their critical thinking and decision-making skills. Hendrik Drachsler and his research partners address this problematic dependency on AI tools and the conflict of interests in the workplace in their newly published article “The Dependency Dilemma: How Machine Learning Decision Aids can Undermine Skill Growth”. Using a controlled experiment, the authors found that participants…

Jul162026 by Heather WehnerNo Comments

New Pub: Recommendations for Higher Education in the Age of Generative AI

Artificial Intelligence, Higher Education, Publication, Report

Generative AI cannot be treated as just another digital tool that has come along. As it becomes more and more embedded in higher education, universities face the challenge of responsibly navigating the many challenges and opportunities that generative AI brings with it. One central guiding principal for institutions and stakeholders engaged with generative AI is intellectual sovereignty, which the German Science and Humanities Council (Wissenschaftsrat, WR) highlights in its newly published position paper, which was presented in a digital press release on 06.07.2026. Intellectual sovereignty refers to the ability to think independently, exercise critical judgment and maintain autonomy in the creation and evaluation of knowledge. Rather than relying uncritically on AI-generated outputs, this concept encourages students, educators and institutions to actively question, assess and contextualize information. By placing intellectual sovereignty…

Jun252026 by Prof. Dr. Hendrik DrachslerNo Comments

Keynote: From Experiment to Infrastructure: Reflections on AI in Higher Education

Academy, Artificial Intelligence, Conference, Higher Education, Keynote, Keynote

Today, Hendrik Drachsler gave a keynote at the VHB annual Conference in Bamberg, speaking to an audience of over 33 AI project leaders from higher education institutions in Germany. The topic was "From Experiment to Infrastructure: Scaling, Evaluation, and Governance of AI Systems in Higher Education," reflecting his thinking on various grassroots projects and how to scale them across the whole university. The gap between performance and learning Hendrik opened with a provocation: Is AI the new calculator? Both technologies automate cognitive processes, both faced early scepticism, and both promised efficiency gains. But the analogy breaks down quickly. A calculator takes over arithmetic, not problem-solving. AI takes over the formulation, analysis, and argument. That is a qualitative difference, and it demands a different institutional / governance response. Mixed results on…

Jun102026 by Heather WehnerNo Comments

New Pub: Competent Usage of AI and Digital Technology in Education

Artificial Intelligence, New Pub, Publication

[caption id="attachment_8403" align="alignright" width="300"] Modified TPACK model as Level 2 of the AIEDTEC-CDM. Note. TPK = technological pedagogical knowledge (TPK), TCK = technological content knowledge, PCK = pedagogical content knowledge, TPCK = technological pedagogical content knowledge.[/caption] How can teachers and learners use AI and digital technology competently, critically and safely in education? Simply using AI tools and digital technology in educational settings does not necessarily mean that learners will profit from these tools. Some tools may have a positive effect on learning, while others may not. A newly published paper addresses this issue and formulates a theoretical framework for the “Competence to Use Artificial Intelligence and Digital Technology in Educational Processes” (AIEDTEC competence). Combining insights from psychology and computer science, it aims to provide a theoretical definition of the competent…

May122026 by Prof. Dr. Hendrik DrachslerNo Comments

How AI Systems Impact Mathematics Achievement in Rural Areas

Artificial Intelligence, PhD defense, School

On Friday, May 8, 2026, Rashmi Khazanchi successfully defended her doctoral dissertation, "Artificial Intelligence in Education: Impact of AI-Based Systems on Mathematics Achievement," at the Open Universiteit in Heerlen. The defense was supervised by Prof. Dr. Hendrik Drachsler, who holds a guest professorship at the Open Universiteit, alongside co-promotor Prof. Dr. Daniele Di Mitri (German University of Digital Sciences). The Research Question Khazanchi's work addresses a pressing challenge in education: whether AI-based learning systems can help close the mathematics achievement gap for students from socioeconomically disadvantaged backgrounds. Her research focused on students in a rural school district in South Georgia, USA — a setting often characterized by limited resources and a shortage of qualified teachers. What Was Studied The school implemented two AI-based systems to support struggling learners: ALEKS, an…

Dec42025 by Heather WehnerNo Comments

New Collaborative Research Center [in:just]

Artificial Intelligence, Project

We are excited to announce that we will be part of the newly launched Collaborative Research Centre [in:just]. This center is special as it will be the first such center in the field of educational sciences and will focus on justice and participation in the educational system. Its goal is to study why inequality in Germany’s educational system continues to exist and what factors contribute to this. The spokespersons are Prof. Merle Hummrich and Prof. Vera Moser, both of whom work in the Department of Educational Sciences at Goethe University. The first phase of the Collaborative Research Centre [in:just] will be funded by the German Research Foundation (DFG) from 2026 – 2029. A team of 31 researchers from fields such as education, sociology, philosophy, political science, law, geography and computer…

Dec22025 by Heather WehnerNo Comments

Moving Education Towards Didactical Intelligence

Artificial Intelligence, Event, Invited talk, Learning Analytics

ChatGPT and other GenAI tools are said to be good for learning. But does their usage really empower learners, or does it overwhelm them instead? Studies from Highly- Informative Learning Analytics (HILA) programs show how complex the effects of such AI-tools can be. While dashboards can potentially improve students’ learning outcomes, AI feedback can sometimes be helpful and sometimes be demotivating for students, depending on their feedback literacy. In a recent presentation at IWM Lectures Hendrik Drachsler argues that we need more research into Didactical Intelligence – a framework for understanding when, how and for whom AI and Learning Analytics truly improves learning and when not. Technology alone doesn’t guarantee better outcomes; its success depends on thoughtful integration into pedagogy. He therefore presented the Highly-Informative Learning Analytics research platform. This…

Nov282025 by Heather WehnerNo Comments

Exploring the Future of Digital Teaching at #EduNext25

Artificial Intelligence, Conference, Event, Higher Education

On 26.11.2025 our team had the privilege of participating in #EduNext25, a full-day conference dedicated to the future of digitalization and AI in higher education. Hosted by studiumdigitale at Goethe University Frankfurt, the event brought together educators, researchers and innovators from across Hessen and beyond to discuss how technology can transform teaching and learning. The opening remarks by Prof. Dr. Viera Pirker, Minister TimonGremmels and Prof. Dr. Hendrik Drachsler set the tone: digitalization and AI are not just trends, they are essential tools for shaping the academic experience of tomorrow. One highlight was the EduConnect session, where universities from the HessenHub network and the QuiS program showcased their latest projects and approaches to digital learning. Another highlight was the panel discussion on strategic alliances for future teaching. Experts from various…

Sep172025 by Heather WehnerNo Comments

New Pub: Design, Development and Evaluation of HILA

Artificial Intelligence, Keynote, Learning Analytics, Publication

How can AI-supported learning analytics be integrated into educational processes in a significant way? How can they be designed, tested and further developed to effectively improve teaching and learning practices? These questions were addressed by Hendrik Drachsler in his keynote at the Learning AID 2024 in Bochum, which has recently been published in the conference proceeding “Learning Analytics, Artificial Intelligence und Data Mining in der Hochschulbildung”. In his keynote, Hendrik stresses the importance of content-specific applications that address genuine educational needs and are supported by empirical evidence demonstrating their effectiveness. The key to fostering adaptive and sustainable learning experiences is to understand and accommodate learners’ individual needs. Hendrik argues that technological progress alone is not sufficient to improve education. His ongoing research shows that AI-supported learning analytics can only bring…

Jun122025 by Heather WehnerNo Comments

New Pub: Tracking students’ progression in developing understanding of energy using AI technologies

Artificial Intelligence, Journal, Publication, School

[caption id="attachment_7553" align="alignright" width="400"] Instructional unit, with pre- and post-test, as well as lesson-set-level assessment[/caption] In physics education, some students fail to have the foundational knowledge of energy concepts needed to engage in societal debates on climate change and energy transformation. A newly published study highlights the potential of AI to identify students with different learning trajectories and to help bridge the knowledge gaps. The researchers used a digital workbook designed to teach energy concepts to collect detailed interaction data from over 500 students. After applying exclusion criteria, data from 172 students were analyzed to identify their productive and unproductive learning curves. [caption id="attachment_7554" align="alignleft" width="400"] Example single choice pretest item[/caption] By using machine learning, specifically random forest models, and natural language processing (NLP), the researchers were able to classify…