1. What is OnTask

OnTask is a platform offering instructors and educational designers the capacity to use data to personalize the learner experience.

Learning is complex, highly situated, and requires interacting with peers, instructors, resources, platforms, etc. This complexity can be alleviated providing learners with the right support actions such as feedback, recommendations, discussions, etc. However, all these actions become increasingly complex when the number of learners grows. The larger the number of learners, the more difficult is for instructors to provide adequate support. Typical solutions include providing generic resources or sending announcements that are only relevant to a subset of the audience.

Learning platforms now generate a wealth of data when activities are mediated by technology. This data can be used to help instructors and designers understand the learner experience and provide a truly personalized experience. The reason why this is not is happening in current platforms is because establishing the connection between data and learner support actions is challenging to implement. This is the focus of OnTask: provide instructors and designers with a platform to easily connect existing data produced in learning environments with highly personalized student support actions.

The existing data is uploaded and stored in a table so that instructors and designers can create a set of simple rules to personalize the content of a web document or a survey. Different learners see different parts of the document depending on the created rules. This document can be sent as an email or made available to each learner. The following picture shows the high level structure of the platform.


The rest of the document is divided into the following blocks:


This block covers the technical details to download, install and configure the tool. It requires technological expertise and access to the adequate computing facilities (a virtual machine, a server, or similar). The main audience of this part is system administrators and advanced users that want to use the tool within their institution or for their own use.

Using the tool

This block explains how to use OnTask in the context of alearning experience, how to load data, manipulate the table and create the personalized actions. The audience for this part is teachers and designers that need to personalize the interactions they have with learners in a platform offering some data sources.

Use scenarios

A set of concrete scenarios describing situations in which OnTask is used to deliver learner support actions.


This block contains a a step by step tutorial on how to use OnTask from the instructor’s point of view.

Advanced features

This block presents more advanced functionality such an application programming interface (API) that allows other platforms to upload data to OnTask.

1.1. Research

There are several platforms that implement similar functionality or follow a similar approach. OnTask has been implemented with numerous ideas initially present in the Student Relationship Engagement System (SRES) and subsequent versions. The common idea among them is the positive impact that personalized communication may have when supporting learners. There are a few scientific publications that document the ideas and processes that inspired the creation of OnTask:

  • Pardo, A., Bartimote-Aufflick, K., Buckingham Shum, S., Dawson, S., Gao, J., Gašević , D., … Vigentini, L. (2018). OnTask: Delivering Data-Informed Personalized Learning Support Actions. Journal of Learning Analytics, 5(3), 235-249.

  • Pardo, A., Jovanović, J., Dawson, S., Gašević, D., & Mirriahi, N. (2018). Using Learning Analytics to Scale the Provision of Personalised Feedback. British Journal of Educational Technology. doi:10.1111/bjet.12592

  • Liu, D. Y.-T., Taylor, C. E., Bridgeman, A. J., Bartimote-Aufflick, K., & Pardo, A. (2016). Empowering instructors through customizable collection and analyses of actionable information Workshop on Learning Analytics for Curriculum and Program Quality Improvement (pp. 3). Edinburgh, UK.

  • Liu, D. Y. T., Bartimote-Aufflick, K., Pardo, A., & Bridgeman, A. J. (2017). Data-driven Personalization of Student Learning Support in Higher Education. In A. Peña-Ayala (Ed.), Learning analytics: Fundaments, applications, and trends: A view of the current state of the art: Springer. doi:10.1007/978-3-319-52977-6_5

1.2. License

The OnTask software is open source and available under the MIT License.