Basic Terms

The context of the AISOP-web-app usage is that of a course at learning institution which typically has fixed students and fixed contents. A course can contain multiple courses or modules.

• AISOP Web-app: The nodeJS server that interfaces with the portfolio-composing system.
• Portfolio: the content written by a student in order to represent his or her progress, learning and knowledge using a textual and graphical form. Generally expressed in HTML, can be embedded in various web-pages.
• Course-contents: The set of slides, their annotations, the videos and handouts that normally read by students and teachers.
• Analysis: The set of programmes that recognize and measure the contents of a portfolio. Often also the name of the resulting interactive presentation (which can feature summaries or enriched portfolio views).
• Composition Platform: A space where the portfolio is written. Normally a web-space. In AISOP we have focussed on the classical e-portfol;io composition platform Mahara (a PHP server).

1) Data Preparation

1.1: Make a Concept Map

Employing tools such as CMapTools, create a graphical concept map that represents the topics of the course. This concept map can be familiar with the teachers and learners of this course as a way to show the paths through the content.

From the concept map, extract a .cxl file which carries the same information and will be presented on the web-page.

From the concept map, also extract a hierarchy of topics, assuming there is more than (approx) 10 topics in the map. The hierarchy should be a text file with a label per line and the label indented to the right in case of children relation as in the following example:

Algorithmization
    Flow Charts
    Programming
        Programming Paradigm
            Imperative Programming....

1.2: Extract Text of the Course Content

In order for the topic recognition to work, a model needs to be trained that will recognize the words used by the students to denote a part or another of the course. This allows to create relations between the concepts of the course and the paragraphs of the portfolio and offer these in the interactive dashboards. The training is the result of annotating fragments of texts which, first, need to be extracted from their media, be them PDF files, PowerPoint slides, scanned texts or student works. These texts will not be shared so that even protected material or even personal-information carrying texts can be used.

Practically:

• Assemble the documents

1.3: Annotate Text Fragments

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2) Deployment

2.1 Train a Recognition Model

...

2.2 Create a Pipeline

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2.3 Create a Seminar and Import Content

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2.4 Interface with the composition platform

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3) Usage

3.1 Invite Users

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3.2 Verify Imports and Analyses

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3.3 Observe Usage and Reflect on Quality

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3.4 Gather Enhancements

... on the web-app, on the creation process, and on the course