KI im Hochschulkontext: Forschung, Praxis und Campus-Management

Governing AI Prompts at the Institutional Level: New Paper by TraiNex at EDULearn 2026

Claudia

How can a university ensure that AI tools are used reliably, pedagogically meaningfully, and consistently — even by staff without prompt expertise? This question was at the heart of a paper presented by researchers from Trainings-Online GmbH and TH OWL at the 18th international EDULearn Conference in July 2026 in Palma.

Conference poster: Prompt Governance in Higher Education (EDULearn 2026)
Conference poster from EDULearn 2026 — click to enlarge

The paper “Prompt Governance in Higher Education: Curated Prompt Libraries for Reliable AI Assistance” introduces a curated prompt library as a governance approach — directly integrated into a campus management system. Rather than leaving AI usage to chance, universities can centrally manage prompts, control target audiences, and monitor usage.

The system distinguishes five prompt types: from freely editable prompts to database-based queries to agent-driven workflows that autonomously conduct literature searches in external databases. Embedded in a campus chat assistant, the system identifies the user’s intent and automatically selects suitable prompts — including contextual enrichment from module handbooks and course schedules.

The approach demonstrates: reliable AI in higher education does not require complex infrastructure — it requires smart integration into existing systems like TraiNex.

→ Read the full paper on ResearchGate

Intellectual Sovereignty: What Germany’s Science Council Demands – and What We’re Already Building

Claudia

On July 6, 2026, Germany’s Wissenschaftsrat (Science Council) published its recommendations “Intellectual Sovereignty: Recommendations for Higher Education in Times of Generative AI” — nine concrete calls to action for universities, faculty, students, federal states, and the national government. Reading through them, one thought kept recurring: this is exactly what we’re building with TraiNex and SMARTA.

Intellectual Sovereignty and Generative AI – Wissenschaftsrat Recommendations 2026
Intellectual Sovereignty vs. Generative AI — click to enlarge

What the Science Council is calling for

“Critical thinking cannot be delegated to an AI,” says Council chair Wolfgang Wick. This isn’t technophobia — it’s precision. It defines what AI should do, and what it must not. The Science Council calls on universities to build AI competencies while also anchoring AI-free zones in curricula. Assessment formats should be rethought, universities preserved as social learning environments. And: sovereign AI infrastructures should be developed that work across institutions and are financed on a long-term basis.

Not as much AI as possible — but the right AI

Not as much AI as possible, but AI deployed deliberately — with the right context, for faculty, students, and university administration. For us, this means advancing context engineering: the intelligent connection of AI to each individual user’s current situation. Automatic consideration of academic records, curricula, exam regulations, timetables, and today’s lecture content. To achieve this, we connect generative AI with our algorithmic intelligence, directed by agents.

Context Engineering as the answer

An AI that automatically considers a student’s academic standing, their curriculum, their exam regulations, and today’s lecture content is not an uncontrolled black box — it’s a precise tool with a defined context. That is the core of SMARTA: not generative AI that simply responds, but AI that draws the right context from the campus management system. Study progress, curricula, exam regulations, timetables, today’s lecture notes — all of this defines the frame within which the AI operates.

Conclusion

The Science Council has set an important framework. For universities that want to deploy AI deliberately — with control, context, and competence — TraiNex shows what that looks like in practice.

→ Full press release by the Wissenschaftsrat

Can AI Understand Emotions? Empirical Quality Assessment of Sentiment Analysis in the SMARTA Project

Claudia

Can an AI reliably detect whether a student is frustrated, motivated, or indifferent? This question was at the heart of our empirical study, presented at the EDULEARN25 conference in Palma de Mallorca in July 2025.

Sentiment Analysis Poster – SMARTA Project EDULEARN 2025
Sentiment Analysis: AI vs. Human — click to enlarge

Sentiment analysis as a core component of SMARTA

In the SMARTA project, we develop AI-powered chatbots that support students with motivation, learning organization, and personal challenges. For the chatbots to respond empathetically to procrastination, social pressure, or frustration, they need to accurately detect the emotional tone of conversations. That is where automated sentiment analysis comes in.

What the study examined

In a comparative study, sentiment classifications by linguistic experts, students, and various GPT models (including GPT-3.5 and newer versions) were analysed. Quality metrics included accuracy, precision, recall, and confusion matrices.

Result: GPT more reliable than expected

Even older models like GPT-3.5 recognise sentiment with high reliability. Deviations occur primarily in neutral statements — an area where human assessments also diverge. This led us to propose the Human-AI-Gap-Benchmark: AI performance should be measured relative to human error rates, not against a zero-error ideal.

Legal context: EU AI Act

Sentiment analysis remains a black-box process with limited explainability. We assessed the method for compliance with the EU AI Act. Our solution: sentiment results are stored anonymously, and the chat history is deleted immediately after each conversation ends. In the SMARTA project, sentiment analysis is deployed as a trusted module.

→ Full paper on ResearchGate

Official Seal for Research Excellence and Innovation Competence 🏅🤖✨

admin

Proud to share that our AI activities have been recognized with the official Seal of Innovation Competence. The BSFZ seal is awarded on behalf of the Federal Ministry of Research, Technology and Space by the Certification Office for Research Allowance (BSFZ).

This recognition confirms that our AI projects are not only innovative and future-oriented, but also comply with the high standards set by the research funding program. It is an official acknowledgment of our research excellence and our contributions to technological progress in Germany.

A key aspect being honored is our approach of “combining generative AI with higher education context data to create a new functional level of personalized educational assistance.” While some of this remains a vision under development, it is already becoming tangible through our projects. In other words: we connect state-of-the-art AI technologies with the real needs of study and campus management — today and tomorrow.

For us, the seal is both recognition and motivation to continue: bringing AI into higher education in a practical, responsible, and impactful way.

SMARTA Explained: How Chatbots Like Alix, Robyn & Dr. Melly Revolutionize Studying with AI

admin

Discover how the SMARTA project is reshaping higher education through AI-powered study coaching. Based on the academic article “SMARTA – Chatbots as Individual Study Coaches for Tackling the Two Sigma Problem,” this animated explainer introduces three intelligent chatbots — Alix, Robyn, and Dr. Melly — and how they support students in motivation, reflection, and learning. These AI companions bring the benefits of one-on-one tutoring to everyday study life — scalable, personal, and always available. Dive into the future of education and see how the SMARTA approach bridges the gap between psychological insight and AI innovation.

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