Open Source 4 you
“Everything should be as simple as possible, but not simpler.” – Albert Einstein
Hyperchalk is a self-hosted collaborative online whiteboard software. Similar to commercial solutions like Miro or Flinga, this software provides users with collaborative boards which they can use to draw, write or sketch together.
However, unlike commercial solutions, Hyperchalk allows for collecting rich log data, which can be used to study the behaviour of its users and to allow Learning Analytics and studies on computer-supported collaborative learning. Moreover, Hyperchalk comes with a built-in replay mode which allows watching how users behave in its spaces.
It supports the LTI1.3 standard, which enables seamless integration with learning management systems such as Moodle, Blackboard or Canvas. It was developed with data privacy in mind and allows for the easy anonymization of user data. Hyperchalk is open source and was released under the GPLv2 license.
You can try out Hyperchalk here: https://hyperchalk.edutec.science/demodemodemodemodemodemo/
Menzel, L., Gombert, S., Di Mitri, D., & Drachsler, H. (2022). Superpowers in the Classroom: Hyperchalk is an Online Whiteboard for Learning Analytics Data Collection. In Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. EC-TEL 2022. Lecture Notes in Computer Science, vol 13450. Springer International Publishing. https://doi.org/10.1007/978-3-031-16290-9_37
- Schneider, J., Di Mitri, D., Limbu, B., & Drachsler, H. (2018, September). Multimodal learning hub: A tool for capturing customizable multimodal learning experiences. In European Conference on Technology Enhanced Learning (pp. 45-58). Springer, Cham.
- Schneider, J., Börner, D., Van Rosmalen, P., & Specht, M. (2015, November). Presentation trainer, your public speaking multimodal coach. In Proceedings of the 2015 ACM on International Conference on Multimodal Interaction (pp. 539-546). acm.
- Schneider, J., Börner, D., Van Rosmalen, P., & Specht, M. (2016). Can you help me with my pitch? Studying a tool for real-time automated feedback. IEEE Transactions on Learning Technologies, 9(4), 318-327.
- Schneider, J., Börner, D., Van Rosmalen, P., & Specht, M. (2017). Presentation Trainer: what experts and computers can tell about your nonverbal communication. Journal of computer assisted learning, 33(2), 164-177.
- Schneider, J., Börner, D., Van Rosmalen, P., & Specht, M. (2016, September). Enhancing public speaking skills-an evaluation of the Presentation Trainer in the wild. In European Conference on Technology Enhanced Learning (pp. 263-276). Springer, Cham.
- Schneider, J., Börner, D., Van Rosmalen, P., & Specht, M. (2017, June). Do You Know What Your Nonverbal Behavior Communicates?–Studying a Self-reflection Module for the Presentation Trainer. In International Conference on Immersive Learning (pp. 93-106). Springer, Cham.
Github:https://github.com/CanIALugRoamOn/VRPT Literature:Schneider, J., Romano, G., & Drachsler, H. (2019). Beyond Reality—Extending a Presentation Trainer with an Immersive VR Module. Sensors, 19(16), 3457.
- Schneider, J., Börner, D., van Rosmalen, P., & Specht, M. (2018). Do you Want to be a Superhero? Boosting Emotional States with the Booth. Journal of Universal Computer Science, 24(2), 85-107.
- Di Mitri, D., Schneider, J., Trebing, K., Sopka, S., Specht, M., & Drachsler, H. (2020). Real-Time Multimodal Feedback with the CPR Tutor. In I. I. Bittencourt, M. Cukurova, & K. Muldner (Eds.), Artificial Intelligence in Education (AIED’2020) (pp. 141–152). Cham, Switzerland: Springer, Cham. https://doi.org/10.1007/978-3-030-52237-7_12
- Di Mitri D., Schneider J., Specht M., Drachsler H. (2019) Read Between the Lines: An Annotation Tool for Multimodal Data for Learning. In Proceedings of the 9th International Conference on Learning Analytics & Knowledge - LAK19 (pp. 51–60). New York, NY, USA: ACM. DOI: 10.1145/3303772.3303776
- Di Mitri, Daniele; Asyraaf Mat Sanusi, Khaleel; Trebing, Kevin; Bromuri, Stefano (2020) MOBIUS: Smart Mobility Tracking with Smartphone Sensors. Proceedings of the EAI conference S-Cube
- Asks the learner for the progress on their tasks
- Asks them for the reasons that affected their learning
- George-Petru Ciordas-Hertel, Schneider, J., Ternier, S., Drachsler, H., (2020). Adopting Trust in Learning Analytics Infrastructure: A Structured Literature Review. Journal of Universal Computer Science, Vol. 25, No. 13, pp. 1668-1686.
OpenLAIR is a system whose frontend consists of a dashboard. This dashboard provides an interface that filters out the list of indicators and their metrics based on learning design activity. The information presented by the OpenLAIR is the result of a literature review, where we harvested and analyzed learning analytics papers from the last ten years (2011-2020) and extracted from them learning design and learning analytics activities, learning analytics indicators and metrics. The tool is based on the framework below.
The reference framework is based on LD and LA elements. In LD and LA, it starts with a learning objective, wherein LD the objective can be a learning event or can lead to a learning event. Then it leads to learning activities. In LD, to fulfill a learning activity, a learning task is required whether the support (such as learning materials) is needed or not, which leads to learning outcomes. In LA, learning activities in a learning environment lead to the generation of log data that forms metrics, and metrics help create indicators for LADs. The learning outcome in LD can be shown or presented via LA indicator(s) for selected LD-LA activities.
OpenLAIR dashboard contains learning events, learning activities, indicators, and metrics. Where Learning Event is a learning or teaching event that occurs during a learner’s activity or a teacher’s activity. Leclercq and Poumay identified eight learning events: create, explore, practice, imitate, receive, debate, meta-learn, and experiment. In order to interact with OpenLAIR it is recommended to take a tour that it provides by clicking on start tour in the top right corner.
To access OpenLAIR use the following link: OpenLAIR
LiteratureGeorge-Petru Ciordas-Hertel et al. (2021). Mobile Sensing with Smart Wearables of the Physical Context of Distance Learning Students to Consider Its Effects on Learning. Sensors 21, 19 (oct 2021), 6649. https://doi.org/10.3390/s21196649
If you are interested in the projects that triggered the development of our products navigate to the research projects page.