White labels

A white-label is a product or service created by one entity that others rebrand to make it appear as if they had made it. ARLearn games so far were only playable through the ARLearn client. This means that in order to play a game, users have to first download the ARLearn client and next install the game on this client. Admittedly, that last step is quite tedious with the current version of ARLearn. 

During the last months we have been working on a new redesigned version of ARLearn. More about this in a future blogpost. With this new version it will be possible to publish your app (in a white-label like way) to google play directly. So users do not have to install the ARLearn client anymore. 

The Elena game is an example of such a white label app. This game guides children while visiting a supermarket. The script invites kids to bake pancakes and to do the grocery shopping for this activity. While shopping, the kids are picking up some German vocabulary. This game is now available at:

As you can see, the ARLearn chrome is no longer visible. Users do not need to login with an account and can directly start playing. In addition, the content for the game is cached within the app. So after downloading a user can start playing even when not network is available.





weSPOT and data collection

Data collection is an important activity when organizing a mobile inquiry process. As an example, a microclimates inquiry - where the learner conducts a search for the sunniest place at the campus - will involve taking various measurements. A learner will as part of this inquiry process measure the temperature at various places. Mobile devices assist this process and provide an instrument to capture and manage these measurements. In addition mobiles can augment the measurement with context parameters such as time and location. This will later help the user to analyze the data.

This illustrates in a nutshell where ARLearn – a platform for mobile serious games – meets weSPOT, a European project that develops tools to support the inquiry process. The ARLearn toolkit is being used in slightly different way. Normally, authors can create game (e.g. a fieldtrip, a crisis simulation) script with the ARLearn authoring environment and have learners executing their scripts with a mobile device (i.e. the ARLearn app). Although weSPOT relies on ARLearn for mobile data collection tasks, the authoring process has been bypassed through an integration in the weSPOT inquiry workflow engine. The weSPOT workflow engine is the place where teacher create and manage the various phases in the inquiry process. This integration has been realised via the ARLearn HTTP based API. For the weSPOT user this results in a very highly coupled integration: when creating data collection tasks, they are not aware of the ARLearn integration.

For now users are executing data collection tasks via the ARLearn mobile app. Once the ARLearn app has been installed on the mobile phone, weSPOT data collection tasks will appear on the phone. As the user completes the tasks, the results appear on the weSPOT inquiry workflow engine.

Within the next month the ARLearn app will also become obsolete here. We are currently developing the Personal Inquiry Manager (PIM) that will be a replacement for the ARLearn smartphone app (in the context of wespot). The PIM app will combine the inquiry process with data collection tasks. The user will thus be able to execute existing inquiries or start a new inquiry on the mobile device and will experience a seamless integration of the data collection tasks. This illustrates how ARLearn can fully operate in service oriented architecture. Both authoring and execution of scripts are entrusted to third party applications.

New in ARLearn

You might have noticed that the ARLearn authoring tool has changed significantly over last two months. We are still working hard on making it better, but the new tool is now more or less usable. Some of the new features of this tool include:

  • Collaborative game authoring. You can now share a game with your friends and work together on the same game.
  • Oauth support. It is from now on possible to authenticate with your Facebook, Twitter, Google or LinkedIn account.

As a result of these changes, the current documentation page that is reachable through is no longer up to date. Although the concepts are still the valid, the user interface differs significantly from the current state of the tools. On you will from now on find the new ARLearn community pages. Being still "under construction" this page offers bilingual documentation. For now the information you will find here is still limited. In the next comming weeks we are planning to add a forum and an ARLearn game section, enabling to easily play an existing mobile game. 

Feature Requests

Since we published ARLearn in Google Play, we recorded almost 100 installs and more then 150 games have been created so far. Some users have requested new features which makes us of course very happy. In order to facilitate this, we started gathering these issues at one place

The ARLearn Google Code project is the place where we manage our code. Here, users can request new features or (even better) star existing issues. By starring an issue you underline its importance and indicate that you need this functionality as well. We hope that offering his voting function to the community will give us more insight in your needs.


Leren in dialoog met de omgeving

In het project Het Leren van de Toekomst gaan Pabo-studenten aan de slag met ARLearn. Rianne Tolsma en Ellen Domke van Iselinge Hogeschool leggen uit hoe ze ARLearn zullen gebruiken.


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