Download and Try OnTask:
OnTask has been implemented and trialled in several higher institutions. These trials have provided detailed information about the most relevant functionality, technical requirements to include it as part of current institutional ecosystems, and user requirements to be adopted by instructors and students.
The difference we found in educational institutions and stakeholders has guided the project to produce three versions of the tool implemented with different underlying technologies. Although the overall functionality is the same and we try to keep both versions synchronised, you may find slight differences between them. The versions are: OnTask (NodeJS), OnTask (Django) and OnTask (ReactJS Django)
If you download and install OnTask, we would like to know about your experience through the Project Forum
For all three of the tools, you have the possibility of downloading the code and installing your own instance, or using a demo server (with limited functionality in terms of sending emails).
OnTask (NodeJS) |
OnTask (Django) |
| Platform implemented using NodeJS.
The technical requirements are: – Redis v2.8 or later – Node.js v6.10 or late – Mysql or MariaDB – Python v2. – Ruby v2.2.6 or later
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Platform implemented using Django.
The technical requirements are: – Python v3. – Redis v2.8 or later – Django – Postgreslq 9.6 or later – Pandas – Additional Django libraries (see documentation)
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| Repository:
https://github.com/Argsen/OnTask
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Repository:
https://github.com/abelardopardo/ontask_b
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| Demo Server:
(Please request access by emailing project lead Abelardo Pardo) https://demo.ontasklearning.org
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For members of any Australian University with access to AAF, log in directly to flip.ee.usyd.edu.au/ontask using your university credentials. You will automatically be upgraded to ‘instructor’ role after 15 minutes.
Otherwise, try our Demo Server (please request access by emailing project lead Abelardo Pardo) https://demo2.ontasklearning.org
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| Documentation:
Main Features: – Uses MySQL to store internal data – API to manipulate matrix value – Documentation to integrate with LTI – Import/export functionality – Schedule execution of actions
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Documentation:
Main Features: – Uses Pandas for data manipulation – API for basic operations over workflows and matrix (load, merge) through regular or Token Authentication – Import/export functionality – Send email provided a snapshot of the workflow for reproducible results – Preview of actions and emails – Fast matrix visualisation using AJAX – Documentation to integrate with LTI – Schedule execution of actions -Integrates with Canvas Email
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| Demonstration Video:
You can watch a video here |
OnTask (ReactJS Django) |
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| Platform implemented using React JS (frontend) and Django (backend)
The technical requirements are: – npn (Node JS Package Manager) – Python v3 – Django – RDS supported by Django (eg MySQL, Postgresql, SQLite) – Mongo DB -Pandas -Additional Django libraries (see readme)
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| Repository:
https://github.com/moocunsw/ontask2_UNSW
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| For members of any Australian University with access to AAF, log in directly to flip.ee.usyd.edu.au/ontask using your university credentials. You will automatically be upgraded to ‘instructor’ role after 15 minutes.
Otherwise try our Demo Server (please request access by emailing Lorenzo Vigentini) |
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| Documentation:
Main Features: -Decouped frontend and backend (takes advantage of modern Javascript based frontend framework) -NoSQL database support (allows users to flexibly create datasets from multiple datasources on the fly, with support for:
-Abstracts the creation of complex “SQL-like” joins, such that the user does not require technical knowledge of these concepts. -Scheduling functionality for
-Data snapshots and audit trails that enable the comprehensive drill-down of workflow action triggers -Data visualisations that are embeddable in workflow actions -Support for AAF and LTI authentication
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We would like to get feedback from your experience. Please drop us a note at our Project Forum
