Plugins/Artfact/Library

Overview

The Mahara Library is an artefact plugin (and associated grouptype) to manage a library of publications which can be shared within a group. The artefact embeds a simple recommender system which can suggest publication that the user may choose to read based on user's recommendations and those of other users.

Installing the plugin

This documentation is based on release v1.0.0 of the plugin code which can be downloaded here: https://github.com/gnerzic/mahara-library-artefact/releases/tag/V1.0.0 This repository contains two directories; an "artefact" directory for the Library artefact plugin, and a "grouptype" directory for the LiteratureReview grouptype plugin. The structure of the grouptype and artefact plugins are provided below:

To install the plugin

• copy of the contents of literaturereview to your "mahara-hdocs"/grouptype/ directory
• copy of the the contents of library to your "mahara-hdocs"/artefact/ directory.

The plugins will register automatically in the Administrator’s Plugin Administration Screen.

Using the plugin

The library plugin is only available to ‘LiteratureReview’ groups, so either create a new group or modify an existing one to be of type ‘LiteratureReview’. (Note that the ‘LiteratureReview’ group type is exactly the same as a ‘Course’ group type). The type of the group can be set either during the group’s creation by going to the group configuration page, as shown below:

When a group is configured as a ‘LiteratureReview’ group, the library is automatically available in the group’s functional banner as a pill call ‘Library’.

If the logged in user is a group ‘tutor’ or ‘administrator’ they benefit from added functionality of being able to upload publications to the library and manage the meta-data of publications. Student users can only access publications that have already been loaded to by a ‘tutor’ or ‘administrator’, create reviews, or edit reviews they have created. More detail about the ratings that a publications has received from other users is also available through the rating volume link. The embedded recommender system makes recommendations based on similar users or based on similar publications.