Dear KlickerUZH community
We are happy to introduce KlickerUZH v3.4!
With this release, we are expanding the ways KlickerUZH can support you and your students before, during, and after class. A major focus is the integration of AI into everyday teaching and learning: from a course-specific chatbot for students to an assistant for lecturers, knowledge-base management, and the generation of questions from your teaching materials.
Alongside these additions, we have continued to improve familiar workflows and the overall user experience. Course duplication makes preparing a new semester easier, and numerous improvements simplify creating and managing your activities.
The AI features introduced below are beta features and currently only available at UZH. The features are being rolled out gradually within the next couple of days. You can disable the beta features in your user settings. We welcome your feedback as we continue to refine them.
Thank you to everyone who has tested new features, shared feedback, and contributed ideas from their teaching practice. If you try the new features, we would be glad to hear about your experience here in the community. Your questions, suggestions, and teaching examples help us decide what to improve next.
We wish you a successful start to the semester!
Your KlickerUZH team
Teaching Center, Department of Finance, University of Zurich
Key Highlights
Student Chatbot: Klickly (Beta)
Klickly gives students a course-specific AI companion to support their independent learning. Students can ask questions about course content and work through topics using various modes:
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Tutor: Guides students through questions with hints and prompts that encourage them to develop their own answers.
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Explainer: Provides explanations of concepts and helps students understand connections between topics.
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Quizzer: Asks questions grounded in course materials and provides formative feedback to support revision.
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Coming soon: Writing coach, …, further customizable modes
When connected to course materials, Klickly can refer students to relevant sources so they can follow up and check answers against the underlying content.
Students can also generate flashcards for their own use and open Klickly during practice quizzes to receive hints and explanations without leaving the activity.
Lecturers can create and configure their own student chatbots through a guided workflow. Publication follows a separate approval process due to the need for a gradual rollout and scaling (at least in the beginning).
In collaboration with the askUZH project and with their funding support of the Digital Charter, we can offer this feature to everyone at UZH without cost during the fall term 2026 (piloting phase), as long as only cost-efficient models are being used (e.g., GPT 5.6 Luna). For our longer-term offering of this feature, we are still looking into sustainable funding models, as AI usage generates a considerable variable cost.
Lecturer Chatbot: KlickerUZH Assistant (Beta)
The KlickerUZH Assistant supports you while working in the lecturer interface. You can use it to find existing questions and courses, ask how KlickerUZH features work, or draft questions and flashcards for a topic you want to teach.
The assistant can generate drafts of single-choice, multiple-choice, and KPRIM questions, as well as flashcards. It can also suggest explanations of why individual answer options are correct or incorrect. You review and confirm generated content before it is saved to your question library, keeping you in control of the content you create.
Knowledge-Base Management and Interactive Knowledge Graphs (Beta)
Knowledge-base management lets you organize teaching materials and make them available to supported AI features. You can upload documents, add websites, monitor processing, and connect a knowledge base to a chatbot.
We are also working towards a direct integration with Kaltura such that you can also easily add lecture podcasts. For the moment, podcasts can be added best-effort by giving us access to, e.g. your OLAT course or Kaltura channel.
Interactive knowledge graphs offer an intuitive way to explore these materials by making concepts and their relationships visible. They complement the original resources and help you explore connected topics when searching materials or generating elements.
AI Element Generation (Beta)
Create initial drafts of elements from your teaching materials. AI element generation supports single-choice, multiple-choice, KPRIM questions, and flashcards, with options for language and difficulty as well as levels of the Bloom taxonomy to cover.
Generated elements appear in a review workflow where you can inspect them and keep selected drafts in your question library. This provides a starting point for content preparation while leaving the review of correctness, wording, and suitability with you.
Course Duplication
Preparing a course for a new semester no longer requires recreating its activities individually. Course duplication lets you select which activity types to copy and adapt the course dates, with scheduled activities shifted accordingly.
Copied activities start as drafts, ready for review before publication. Participants, responses, and results remain with the original course, giving the new cohort a fresh start.
Further Improvements
Beyond the key features, v3.4 includes several improvements across KlickerUZH:
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Improved word-cloud visualization: Reworked rendering and a selectable language filter make responses easier to interpret. The filter removes common words such as “the” and “and” for the selected language and can be disabled to display all words.
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Question-library and activity-creation improvements: Clearer question cards, statuses, and actions make content easier to navigate. Guided creation and recovery of interrupted activity wizards help you continue where you left off.
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Bulk content management: For example, to archive elements and delete activities in batches. Course deletion can run in the background.
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Video embedding in elements: Add supported YouTube and Kaltura videos directly through the element editor in any content editor.
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Live-quiz usability improvements: Optional PIN protection, navigation back to answered questions, automatic local saving of responses, and resizable question and feedback areas improve the participant experience.
Use Cases
Which KlickerUZH features fit your course and teaching goals? The overview below offers a starting point, organizing teaching scenarios by their focus on interaction or engagement and their use during class or in independent learning.
With v3.4, chatbots extend these possibilities by supporting dialogue beyond the classroom. Students can ask questions, receive hints, and explore explanations while preparing for class or revising course content. Chatbots can also complement practice quizzes, helping students work through difficulties as they arise.
The different approaches can be combined throughout a course: students might prepare with a chatbot, discuss their understanding in a live quiz, and revisit key concepts through microlearning and flashcards afterwards. Your learning objectives determine which combination makes sense.
For inspiration and practical guidance, explore the KlickerUZH use cases, which describe teaching scenarios, didactic goals, and implementation examples. We welcome your experiences and ideas for applying these approaches in your own courses.
Data Privacy and Policy Updates
Our privacy policy and terms of use have been created for the initial launch of KlickerUZH v3 and not adjusted since. The introduction of AI features as well as a pronounced interest in using KlickerUZH for research projects requires further considerations. By the start of the fall term 2026, our policies will therefore be updated in collaboration with the UZH data protection office.
We are adding a direct opt-out capability for students within the account creation and profile settings to make it easy for students to opt-out of research and to allow lecturers to have a pre-filtered research export of de-identified data from students that have not opted out of this further processing. The usage of this export will be restricted to UZH-affiliates and UZH-research projects at least for now. Usage outside of UZH would most likely require a self-hosted instance of KlickerUZH under the governance of the hosting institution.
If you are a researcher potentially interested in using KlickerUZH or any of the data gathered by using it for your research, please get in touch. We are always interested in hearing about different use cases and how we can support them.
In-App Catalyst Requests and Beta Enrollment
Users outside UZH/USZ can now request Catalyst access directly within KlickerUZH and toggle beta features in your user settings. This includes the AI features described above as well as future features like learning analytics.
With enabled beta features, lecturers can create student chatbots for their courses and prepare them for publication through the guided setup. Making a chatbot available to students remains subject to the publication approval process, as we need to control the use cases made available via KlickerUZH (focusing on teaching-oriented usage).
Catalyst Updates and General Availability of all Activity Types
With the introduction of many new features including AI, the three previously Catalyst-locked activity types (i.e., practice quiz, microlearning, and group activity) move to general availability and are now available for anyone. All new features marked as beta (i.e. AI features) and upcoming features like learning analytics are available only for Catalyst users, including everyone from UZH and USZ.
Outlook
Our next steps will focus on refining these workflows through practical use and feedback, improving guidance and documentation, and expanding access as the new capabilities mature.
Release v3.5
For the next release coming soon during the fall term, we are working towards a minor release including, among others:
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New question type (QR-Code, scan a QR-code to solve the question) and “escape room” mode for quizzes (time limit, advanced only when the correct response is given)
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Native import and export capability to import elements from Excel/CSV as well as import and export to a native KlickerUZH-format (to, e.g., share with other users)
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Learning analytics in public beta
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Research export using which researchers can easily export pre-filtered and de-identified data from their courses for usage in UZH-internal research and teaching projects
Release v4.0
The release in February will mark a new major release for KlickerUZH (v4.0), with all of our piloted and beta features becoming stable and many background improvements being made as well. This includes, among others, the beta features announced above, but also the dedicated assessment mode, content sharing, and learning analytics. The release will also include new beta features such as quizzes that adapt the next question asked to the estimated skill level of the student (e.g., for skill assessment in languages).
In addition to these changes, the user experience and accessibility will be significantly revamped to make usage easier, faster, and better overall for students as well as lecturers, and the native mobile apps will be further developed as well.