Target group Archives - EduTec Science

Oct72026 by Prof. Dr. Hendrik DrachslerNo Comments

Keynote: 5 years of Highly Informative Learning Analytics

Artificial Intelligence, Conference, Feedback, Higher Education, Keynote, Learning Analytics, Learning Design, Research Methods, School

Five years in forty minutes On 7 October 2026, Hendrik Drachsler gave a keynote at the CBIE 2026 conference in Goiana, Brazil, that tried something unusual: time travel. He compressed five years of field research, seven projects and roughly 5,750 students into one forty-minute talk. The question behind the keynote was simple: after five years of developing and testing Highly Informative Learning Analytics (HILA) in real lecture halls, what do we actually know? Not what we hoped HILA might achieve back in 2020, but what five years of our own research and data now tell us. What HILA set out to do HILA starts with a modest observation: most lecture rooms still offer very little personalisation. Learning analytics promised to change that, but its rollout in Europe stalled on four…

Oct72026 by Prof. Dr. Hendrik DrachslerNo Comments

PhD defense: Congratulations, Dr. Manuel Valle Torre!

Artificial Intelligence, Higher Education, Learning Analytics, PhD defense, School

Today, 07.10.2026 at 15:00, Manuel Valle Torre successfully defended his PhD thesis "Sequences in Data to Represent Learning Processes: What have you tried until now?" at Delft University of Technology. Hendrik Drachsler was honoured to take part as an independent member of the doctoral committee. [pdf-embedder url="https://edutec.science/wp-content/uploads/2026/10/Manuel-defense-slides.pdf"] Manuel's thesis starts with a question every programming tutor knows: "What have you tried until now?" Digital learning environments usually assess only the final product, so this question is hard for them to answer. In three phases, Manuel shows how sequences of learner actions can be used to understand learning processes and support them while they happen. He developed ELAT for analysing edX log data, reviewed the field of learning sequence analysis, and studied problem-solving in data science notebooks. He then built JELAI,…

Sep252026 by Heather WehnerNo Comments

New Pub: Implementation of AI-based Feedback and Assessment – IMPACT Project Evaluation Report

Artificial Intelligence, Feedback, Higher Education, Learning Analytics, Publication, Report

How can universities provide individual feedback and useful support systems to every student when class sizes continue to grow and learner needs become increasingly diverse? Artificial intelligence offers promising opportunities to provide personalized learning and teaching support on a larger scale. Yet as regulations regarding data protection, transparency and the responsible use of AI continue to evolve, institutions face a difficult balancing act between innovation and regulatory compliance. These issues were addressed in the IMPACT project (Implementation of AI-based Feedback and Assessment with Trusted Learning Analytics in Higher Education Institutions), which explored how AI can support students and educators throughout the academic journey. Its goal was to develop AI-based methods for the semi-automated analysis of academic texts, to allow for more effective support in learning, teaching and assessment. A key…

Aug172026 by Prof. Dr. Hendrik DrachslerNo Comments

Invited Talk at the NEES Center, Maceió, Brasil

Higher Education, Invited talk, Keynote, Keynote, Learning Analytics, Learning Design

In August, Hendrik Drachsler was invited to give a talk at the NEES research centre of the Federal University of Alagoas (UFAL) in Maceió, hosted by Prof. Dr Diego Dermeval. The lecture, "Design, Development and Evaluation of Highly Informative Learning Analytics", was organised together with the PPGI graduate programme and drew a full house of 80 participants. Hendrik's argument was straightforward. Most learning analytics is not wrong; it is just not informative enough. Counting clicks and minutes tells a teacher that something happened, not what to do about it. Moving from descriptive to truly informative analytics takes three things: indicators grounded in learning theory, a design process that includes the educators who will use the results, and a governance framework that makes the whole thing defensible. He presented the tools…

Jul312026 by Longwei CongNo Comments

[New Pub] Estimating LLM Grading Ability and Response Difficulty in Automatic Short Answer Grading via Item Response Theory

Artificial Intelligence, New Pub, School

On July 4, 2026, Longwei Cong virtually presented the paper “Estimating LLM Grading Ability and Response Difficulty in Automatic Short Answer Grading via Item Response Theory” at the ACL SIGEDU 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026). The work investigates automatic short answer grading with large language models from a psychometric perspective. Instead of relying only on aggregate evaluation metrics such as accuracy or macro-F1, the study applies Item Response Theory to jointly estimate the grading ability of individual LLMs and the difficulty of student responses. The results show that LLM graders differ not only in their overall performance, but also in their robustness when evaluating more difficult responses. In addition, highly difficult responses were found to induce systematic grading errors, including a tendency…

Jul312026 by Longwei CongNo Comments

[New Pub] Confidence Estimation in Automatic Short Answer Grading with LLMs

Artificial Intelligence, New Pub, School

On June 30, Longwei Cong presented the work “Confidence Estimation in Automatic Short Answer Grading with LLMs” at the 27th International Conference on Artificial Intelligence in Education (AIED 2026) in Seoul. The work investigates how confidence estimates can make automatic short-answer grading with large language models more reliable in practice. In addition to commonly used model-based confidence signals, it also considers uncertainty originating from the data itself. In particular, aleatoric uncertainty is estimated from the semantic heterogeneity of student responses and combined with several model-side confidence signals. The study evaluates these uncertainty estimates with a focus on practical use: whether they can support selective grading and help identify responses for which automated grading is less reliable and human review would be preferable. The paper is available via the following link:…

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…

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…

Dec182025 by Prof. Dr. Hendrik DrachslerNo Comments

New Pub: How Virtual Reality Mental Training Impacts Race Preparation in Recreational Runners

Augmented Reality, Computational Psychometrics, General education, Journal, New Pub, Publication

Can Virtual Reality Mental Training Help Recreational Runners Race Smarter? We’re glad to announce that our paper has just been published! 🎉 In this post, we share the key ideas and early findings from our newly published study exploring how virtual reality (VR) mental training—grounded in cognitive-behavioral (CB) techniques—may support long-distance recreational runners in adopting race strategies and strengthening motivation within a coaching context. What happens when cognitive-behavioral (CB) techniques like imagery and self-talk meet virtual reality (VR) in a coaching context? An exploratory study of recreational long-distance runners provides intriguing early signals. Why this study matters VR has been used in sports settings to support skill learning and performance, but it’s still relatively uncommon to see VR paired directly with cognitive-behavioral mental training—especially practical tools like imagery and self-talk…