We are honored to have been recognized by the Gesellschaft für Pädagogik, Information und Medien e.V. (GPI) as one of the most outstanding educational media for work, training, school, culture and leisure. The award not only recognizes the years of development of our micro-learning app, but also proves the quality and impact of the continuous and sustainable learning experience with chunkx! A big thank you also to the National Anti-Doping Agency, which has proven with the COMMON AGAINST DOPING Academy on chunkx how successfully a sustainable learning culture can be established.
Enclosed you can now find the German version of the press release.
chunkx wins in the category "Digital didactic media products
Berlin, Germany – the micro-learning app chunkx was honored on June 23 at this year’s Comenius Award ceremony in Berlin by the Gesellschaft für Pädagogik, Information und Medien e.V. (GPI) as one of the most outstanding educational media for work, training, school, culture and leisure.
The demand and also the market for digital educational media are growing continuously. However, only a fraction can meet the pedagogical, didactic and technical criteria and establish a sustainable digital educational medium. With the Comenius-EduMedia Award, GPI has therefore made it its task to test and award digital educational media according to the criteria mentioned. For more than 26 years, the awards have been presented in the categories Digital Didactic Media Products, General Digital Media Products, Teaching and Learning Management Systems, and Computer Games with Competence Enhancing Potential.
This year, over 200 manufacturers, publishers, projects and authors from 8 European countries applied and underwent the manufacturer-neutral quality check.
The Comenius EduMedia Award underlines the didactic quality achieved by the National Anti-Doping Agency together with chunkx and confirms the growing demand for digital solutions for adaptive and continuous learning.
chunkx convinces with innovative approaches for sustainable learning
To move from static to adaptive learning paths and make invested learning time as effective as possible, chunkx follows the micro-learning approach. Individual learning units are packed into small chunks in order to be more “digestible” for the learner. Instead of listening to an extensive course or video/audio once, content is equalized and repeated over longer periods of time. The resulting moments of reflection promote the sustainability of the learning process and enable a deeper anchoring than so-called “bulimic learning” can.
Adaptivity for knowledge-based learning content
In chunkx, learning content isselectedbased on users . Specially developed algorithms not only repeat the microlearning units, but also select them dynamically based on the knowledge level of the individual users. This selection can be constantly readjusted. Because with every action of the learner, the app also continues to learn and improve the selection.
Self-determined and connecting learning
In chunkx, learners decide for themselves how long and intensive they want their learning unit to be. You can use the “Start all your channels” button to learn more than one topic. At the touch of a button, chunkx then selects the most suitable microlearning unit from all subscribed topics and based on the individual learning history. As a result, topics no longer compete for the attention of users, but instead connect and reinforce each other. In addition, the existing learning content is enriched by further relevant information such as published articles, studies or podcasts in the form of postings .
Simple and AI-based content creation
To actively contribute to a new continuous and sustainable learning culture, chunkx offers AI-based content creation. With the click of a button, chunkx users can upload content, have microlearning units created automatically, and start learning. This not only involves all learning parties in extending learning courses, but also lets them share knowledge with others in the easiest way.
chunkx is an adaptive micro-learning app for web, iOS and Android. It focuses on sustainable learning transfer through smart algorithms, artificial intelligence and user-based content selection. chunkx uses Natural Language Processing for user-based recommendations and the automatic creation of interactive microlearning units. The chunkx user app and chunkx creator authoring tool provide authors and users with the optimal support for ongoing content creation and learning engagement. chunkx is a product of chunkx B.V. and was founded in 2018. The EdTech start-up is based at the High Tech Campus Eindhoven, Netherlands, and in Düsseldorf, Germany.
We are very happy to introduce you to our new partner and investor LUMO Labs! LUMO Labs brings many years of experience in the AI field as well as a global network. Their focus on impact-driven startups makes them the ideal partner for us, and they share chunkx’s vision of designing adaptive and continuous learning experiences for everyone. We look forward to working with you!
Enclosed you will find the German version of the official press release.
chunkx becomes part of the LUMO Labs family
Eindhoven, The Netherlands – Learning is often seen as something static and one-time, completed by the attainment of a diploma or certificate. But today’s fast-paced and ever-changing world requires a continuous learning approach that goes beyond certificates and degrees. LUMO Labs, through its investment fund LUMO Fund II, invests in chunkx, a German-Dutch startup that uses artificial intelligence to make learning more relevant and effective in the digital age.
chunkx is an AI-powered micro-learning app that creates a curated and personalized learning experience through adaptive content selection. The platform selects appropriate microlearning units based on the needs of each user and in the future will offer automatic generation of new content to enable the continuous development of users.
Founder and CEO Florian Stieler’s vision is that every person with a smartphone and chunkx technology will be empowered to connect their countless learning experiences, create their lifelong learning feed, and continuously evolve in an ever-changing world.
chunkx is aimed at both companies and educational institutions such as universities. The National Anti-Doping Agency Germany (NADA) is one of the first customers on board. chunkx allows them to transform their traditional e-learning course into an adaptive learning experience. After only three months, more than 6,000 athletes in Germany have already attended the academy.
“We strongly believe that learning is a continuous process that doesn’t stop at the end of a lecture or the last page of an eLearning course,” Stieler said. “With chunkx, we enable users to continue the learning journey. LUMO Labs is the perfect partner for us in this; a partner that shares our vision, brings a strong tech focus and supports us in internationalizing our business.”
“The scalable and accessible idea of the chunkx platform provides equal access to continuous education for people around the world. The innovative focus and customized content creation ensures the relevance and quality of each individual’s learning journey,” said Andy Lürling, founder of LUMO Labs.
“We see great potential in chunkx’s approach to learning and development.”
Lürling and co-founder Sven Bakkes said LUMO Labs is investing because chunkx’s business plan is based on sustainable engagement and connectivity. People cannot immediately transfer everything they have learned to their everyday work. With chunkx, any learning activity can be extended to ensure knowledge transfer.
At the push of a button, the most suitable microlearning unit is selected from all subscribed topics and based on the individual learning history. Just as LinkedIn or Twitter connects us to any number of sources, chunkx connects users to learning content, making it possible to learn even when time is short.
“Both chunkx’s technology and impact goals are central to our investment strategy,” said Bakkes. “We are very excited to welcome this incredibly promising edtech team to our portfolio.”
The investment from LUMO Labs will enable chunkx to continue its pioneering work in AI-based learning content generation and prepare for further growth as a company with lasting impact, he added.
About LUMO Labs
Based at the High Tech Campus Eindhoven, LUMO Labs creates opportunities for impact-driven software and smart hardware startups. The current LUMO Fund II is a multi-stage and impact-driven capital fund (pre-seed up to and including Series A). The Fund includes a two-year venture builder program to help its portfolio companies achieve financial success as well as social reach and impact.
LUMO Labs funds startups that pursue at least one of the following three United Nations Sustainable Development Goals (SDGs): sustainable cities and communities, good health and well-being, and quality education. Investment focus areas include artificial intelligence/data, blockchain, internet of things, robotics and drones, and virtual / augmented reality.
LUMO Labs advocates for self-determination and traceable ownership of data, as well as transparency and traceability of technologies.
chunkx is an adaptive micro-learning app for web, iOS and Android. It relies on sustainable learning transfer through smart algorithms, artificial intelligence and user-based content selection. chunkx uses Natural Language Processing for user-based recommendations and the automatic creation of interactive microlearning units. The chunkx user app and chunkx creator authoring tool provide authors and users with the optimal support for ongoing content creation and learning engagement. chunkx is a product of chunkx B.V. and was founded in 2018. The EdTech start-up is based at the High Tech Campus Eindhoven, Netherlands, and in Düsseldorf, Germany.
Certainty Based Marking (CBM), or more conveniently, Confidence Based Marking (CBM), fascinated me while I was studying education. Therefore, it was only a matter of time when this super useful concept would also find its way into our app chunkx. This much in advance: CBM and adaptive learning are a great fit. In this article, I’ll explain what’s behind it and what role it plays in our learning app.
What is Certainty Based Marking?
In chunkx, microlearning content is often supplemented by interactive learning tasks. This allows us to learn more about the individual user’s knowledge and non-knowledge and to prioritize and, if necessary, repeat content accordingly. Learning tasks in the form of single choice or multiple choice tasks, however, have the disadvantage that simple guesses are quickly made here. That’s where we come to CBM:
Certainty Based Marking (CBM) asks users not only to answer an objective question, but also how certain they are that their answer is correct. Our scoring system particularly rewards not only selecting the correct answer, but also being maximally confident in doing so. Certainty Based Marking encourages reflection on how sound one’s knowledge and skills really are.
How is CBM used in chunkx?
chunkx is a micro-learning app that adaptively selects learning content. Adaptive means individual and suitable per user. I bet you already realize that Certainty Based Marking makes a lot of sense in this context. How often did your teachers used to ask you how sure you were about an answer? I hope so on a regular basis, because the assessment of this helps to better classify one’s own level of knowledge.
We, meaning our algorithms in the app, use this classification to help decide which content to display next that is appropriate for the user.
Must Certainty Based Marking always be used in chunkx?
Authors use the chunkx creator to create channels and micro-learning content. CBM can be used here for all content with closed tasks. Quite optional as a checkbox that can be quickly turned on and off. By default, it is enabled because we are convinced of the concept and the user experience is significantly improved both in terms of response and more appropriate content selection.
Adaptive learning with chunkx
With chunkx, we offer you a tool to expand both new and existing measures in a targeted manner. chunkx is aimed at both companies and educational institutions, such as universities or schools. In addition to closed instances, chunkx offers a public area. Academies such as those offered by Gemeinsam-gegen-Doping, the Lehmbruck Museum and other educational institutions are offered here.
Are you not yet a customer or do you have questions about Certainty Based Marking or other topics in chunkx? Then contact us for a personal presentation and let’s talk about the possibilities together. We look forward to hearing from you!
Adaptive learning and content sorting: Putting learning content in a meaningful order is one of the most basic tasks in creating digital learning content. In our authoring tool chunkx creator, we have recently started to offer our authors the possibility to either give a topic a fixed order or to let our algorithm choose the content according to the order. of the learner profile, i.e., to be selected adaptively. A fixed sequence is suitable, for example, when a topic is presented for the first time. Adaptive assignment, on the other hand, is more suitable when learning content is to be selected to complement training.
In this article, we explain why the settings option is so helpful, what the advantages and disadvantages of the two variants are, and describe in more detail how adaptive learning works in chunkx.
Structuring of learning content
Learning videos, web-based trainings, webinars or trainings: the content in each of these units has been put into an order that makes sense from her/his point of view by a trainer or author. In the best case, this is preceded by a definition of the learning objectives: What should the participants have learned after the measure?
Once the learning objectives are available, the learning time and format must be defined. Both aspects are cost drivers, so decisions are not made solely according to didactic parameters, but also according to economic ones.
Now we finally come to the structuring of the content: How do you give the participants the necessary context? Do you first describe a topic on an abstract level and then give an example, or vice versa? When are good times for exercises and discussions? As you can see, it is not possible to describe a one-size-fits-all approach, as all factors have to be taken into account: Learning objectives, formats, premises, time, budget, the type of content, its complexity, etc.
Experienced didacticians have already noticed which factor we have not yet listed: The participants.
Participants:inside are the most heterogeneous factor
As if it were not complicated enough, we develop our learning activities for a varying number of individual participants. Some learn best inductively, that is, first by concrete examples and then by theory. For others it’s the other way around, they want to understand the theory before they get to the examples.
Participants bring different levels of prior knowledge with them. While some first have to carefully understand the context and gain basic knowledge, others are already ten steps further and are impatiently waiting for the content that is exciting for them to finally follow.
In addition, there are other factors, such as the communication between the participants, the speed of learning or hierarchical behaviors that require different approaches.
In classroom trainings and webinars there are usually between 5 and 30 participants. But learning videos and web-based trainings are often created for several thousand participants. That’s why we developed chunkx to enable adaptive learning automatically and without any effort on the part of the author – whether for five or several thousand users.
Learning in chunkx – this is how it works
In chunkx, content is broken down into learning tasks as the smallest possible interactive formats. Learning tasks have the advantage that they not only stimulate memory, association and learning processes, but also make productive use of the user’s time: If I can already do something, it will only take me a few seconds to complete it. If I can’t do something yet, I deal with it more intensively. The tasks always contain all the necessary learning content, integrate images and videos, or refer in the feedback to sources that describe the content in even more detail – such as a web-based training or a blog article.
The learning tasks are also supplemented by a timeline on which users can receive pre-programmed or manually sent messages from authors. In turn, they learn how many users have responded to their posts and what is more and less interesting to them.
By combining a micro-learning format with data that reflects the interests and knowledge of users, our algorithm creates individual learning paths across any number of topics. Quite automatically and without complex programming, the strengths of the users are given less priority than the weaknesses and learning content is continuously repeated according to the respective user difficulty.
Sorting instead of adaptive allocation
Let’s imagine a channel with 40 learning tasks. Adaptive allocation means that task #39 is shown first to one user, task #1 to another, or task #20 to yet another user. In order to provide users with a fixed order, authors can change the channel in chunkx from adaptive to sorted at any time. As a result, new content from the channel is presented in exactly the order the author deems most appropriate. The emphasis here is on “new” content. Because repetitions are always used in chunkx according to. of the learner’s individual data, i.e., adaptively assigned.
Adaptive vs. sorted – which is the better choice when?
Let’s think back to the complexity of sorting learning content described at the beginning. Here, chunkx offers authors the chance to exploit the possibilities of digital solutions and to rely on the support of our algorithm when it comes to the user-specific selection of learning content. In the following scenarios, this makes especially much sense:
1. supplementation of learning measures
With chunkx, trainings, webinars, webbased trainings can be easily extended. When the above measures end, content can be repeated and reinforced via chunkx. And since repetitions should be based on the individual level of knowledge and not on a fixed order that applies to everyone, the “adaptive” setting is the best choice here.
2. many equivalent contents
Sometimes topics consist of many knowledge units that do not so much build on each other, but stand neutrally next to each other. This can be the case of legal and regulatory content, but also when you want learners to apply learned knowledge to new contexts through a variety of application scenarios. Here, too, we believe that the “adaptive” setting is the best way to efficiently present users with the content that is relevant to them.
3. particularly heterogeneous target groups
The larger and more diverse the target users are, the more difficult it is to define a successful fixed sequence of learning content. Of course, it is also possible to prepare channels for different target groups differently in chunkx – e.g. a separate variant only for executives – but even after such a division, the participants are still too different, then a content selection makes sense according to the “chunkx” concept. We write “possibly” deliberately, because here the advantages described below for the “sorted” setting must be weighed carefully against those described above.
The “sorted” setting offers authors other possibilities and advantages, especially in the following situations:
1. new contents
If chunkx is not used subsequently to another measure, but presents content as a learning unit to users for the first time, a predefined structure of the content is suitable. In this case, too, the learning time of the individual user:s is used more productively than in other learning formats, because familiar content costs them little time and unfamiliar content is repeated selectively. The fixed sorting applies only to “new” content that users have not yet edited.
2. strong narrative
At its best, learning content should inspire and engage us. And we believe that you can do this even with the most supposedly boring topic. In adaptive micro-learning, we face the particular challenge of ensuring that we chop up content as much as possible so that we can, in turn, arrange it in a flexible and user-specific way. However, this also means that successful scenarios, pictorial descriptions, emotionalizing narratives can only be built up within a single micro-unit, since we do not know for sure what users have already processed and what not. Sorting learning content can overcome this hurdle. You can now be sure that the thread within the topic is maintained and you know exactly that all user:in step by step through the same texts, images, videos and exercises wander.
Sorted vs. adaptive – the authors decide
In our authoring tool chunkx creator, authors decide which setting suits their channel. Helpful tips help with the selection and it is also possible to change the setting again after go-live: If a channel is put online with the setting “adaptive” and you realize after a short time that a sorting would be more suitable after all, this can be adjusted immediately. The order of the content can also be changed and readjusted at any time.