Attention Metadata Management: Tracking the use of Learning Objects
through Attention.XML


Jehad Najjar, Michael Meire and Erik Duval
Computer Science Department, K.U.Leuven
Celestijnenlaan 200 A, B-3001 Leuven, Belgium
{Jehad.Najjar, Michael.Meire, Erik.Duval}@cs.kuleuven.be


Abstract: In this paper, we introduce a framework for automatic collection and management of
attention metadata. This framework enables keeping track of the learning objects that people
use, how they use them, the time they spend with them, etc. By sharing their attention metadata
with others, the framework can alert them on other learning objects they might be interested in.
Our framework tracks user interactions with the different tools they use and then publishes that
data in the open attention.XML format. The produced source can be accessed by different tools
and users.


1. Introduction

In order to create a feedback loop that enables learning from the way people actually use new technologies
and tools for learning, it is essential to track the behavior of users and learners (Duval & Hodgins, 2003).
The release of the new attention.xml specification (Attention.XML, 2004) inspired us to examine the
possibilities of using that specification to track usage of learning objects. In this paper, we introduce our framework
for tracking and publishing attention given to learning objects and for notifying the user about objects that she might
be interested in.
The paper is structured as follows: in section 2, the attention.XML specification is briefly presented. In
section 3, we introduce the Attention Metadata Management (AMM) framework that we are developing. Related
work is briefly presented in section 4. Finally, a conclusion and some comments on future work are provided in
section 5.

2. Attention Metadata Standard: Attention.XML

Attention.XML is an open specification for tracking, prioritizing and sharing what people are reading,
looking at or listening to. In this way, it helps to keep track of and, more importantly, share information on the
“attention” users give to web pages, news feeds and blogs they read (Attention.XML, 2004):

• What feeds, blogs and sites the user read.
• When they were added to the feed/blog list.
• How long the user spent on it.
• The last time a user read a feed/blog/pages.
• What links in the post/item/page the user clicked on.
• The user’s rating for those items.

Figure 1 shows the Attention.XML schema used to record the attention metadata. Attention metadata
records users’ attention to the different blogs, feeds and sites they use and to their sub posts, items and pages.

Figure 1: Attention.XML schema Figure 2: Simple XOXO fragment

Technically, attention.XML is an XML file that uses the XOXO hierarchical outline format
(http://developers.technorati.com/wiki/XOXO) (see figure 2). That file contains an outline of feeds, blogs and sites,
where each feed itself is an outline, and each post is also an outline under the feed. In this study we intend to use the
same approach that is used to track and share attention to feeds and blogs, to track and share attention to learning
objects.

3. Attention Metadata Management for Learning (AMM)


Figure 3: The AMM framework that tracks and publishes attention of learning object users

Figure 3 presents the AMM framework that we are developing, in order to track, publish and share
attention to learning objects.
Users may interact with a wide variety of tools that make use of learning objects:
• Learning Object Repositories (LORs): Users may interact with a LOR (such as MERLOT, EdNa,
ARIADNE and SMETE) to introduce or search relevant learning objects.
• Learning Management systems (LMSs): Teachers may interact with an LMS (such as Blackboard,
Moodle, and WebCT) to manage objects of their courses. Students also can use an LMS to access
those objects.
• Internet Browsers: Users may download their relevant learning objects from the appropriate LOR
and then open and read it (learn it) in another application like web browsers.
• Messaging Systems: users may also chat about a learning object using a messaging system.
• Email Clients: users may send or receive learning objects or information about them by email
messages or RSS feeds.
• Audio and Video Players: users may use an audio or video player to learn.
• Other tools, such as MSWord and Powerpoint.