Towards Automatic Competence Assignment of Learning Objects

Ricardo Kawase presenting @ECTEL2012. (picture taken by Maren Scheffel)

Competence-annotations assist learners to retrieve and better understand the level of skills required to comprehend learning objects. However, the process of annotating learning objects with competence levels is a very time consuming task; ideally, this task should be performed by experts on the subjects of the educational resources. Due to this, most educational resources available online do not enclose competence information. In this paper, we present a method to tackle the problem of automatically assigning an educational resource with competence topics. To solve this problem, we exploit information extracted from external repositories available on the Web, which lead us to a domain independent approach. Results show that automatically assigned competences are coherent and may be applied to automatically enhance learning objects metadata.

Ricardo Kawase, Peter Brusilovsky and Mikhail Fominykh. (picture taken by Maren Scheffel)

Venue: ECTEL2012

Authors: Ricardo Kawase, Patrick Siehndel, Bernardo Pereira Nunes, Marco Fisichella and Wolfgang Nejdl

PDF: kawase-ectel2012

Hyperlink of Men

Ricardo Kawase presenting @LAWEB2012

Hand-made hyperlinks are increasingly outnumbered by automatically generated links, which are usually based on text similarity or some sort of  recommendation algorithm. In this paper we explore the current linking and appreciation of automatically generated links. To what extent do they prevail on the Web, in what forms do they appear, and do users think those generated links are just as good as human-created links? To answer these questions we first propose a model for extracting contextual information of a hyperlink. Second, we developed a hyperlink ranker to assigned relevance to each existing human generated link. With the outcomes of the hyperlink ranker, together with another two recommendation strategies, we performed a user study with over 100 participants. Results indicate that automated links are “good enough”, and even preferred in
some user contexts. Still, they do not provide the deeper knowledge as expressed by human authors.

Venue: LAWEB2012

Authors: Ricardo Kawase, Patrick Siehndel, Eelco Herder and Wolfgang Nejdl

PDF:  kawase-laweb2012

Unsupervised Auto-tagging for Learning Object Enrichment

Ricardo Kawase presenting @ECTEL2011

An online presence is gradually becoming an essential part of every learning institute. As such, a large portion of learning material is becoming available online. Incongruently, it is still a challenge for authors and publishers to guarantee accessibility, support effective retrieval and the consumption of learning objects. One reason for this is that non-annotated learning objects pose a major problem with respect to their accessibility. Non-annotated objects not only prevent learners from finding new information; but also hinder a system’s ability to recommend useful resources. To address this problem, commonly known as the cold-start problem, we automatically annotate specific learning resources using a state-of-the-art automatic tag annotation method: α-TaggingLDA, which is based on the Latent Dirichlet Allocation probabilistic topic model. We performed a user evaluation with 115 participants to measure the usability and effectiveness of α-TaggingLDA in a collaborative learning environment. The results show that automatically generated tags were preferred 35% more than the original authors’ annotations. Further, they were 17.7% more relevant in terms of recall for users. The implications of these results is that automatic tagging can facilitate effective information access to relevant learning objects.

Venue: ECTEL2011

Authors:  Ernesto Diaz-Aviles, Marco Fisichella, Ricardo Kawase, Wolfgang Nejdl, Avaré Stewart

Award: ECTEL2011 Best Paper

PDF:  diaz-ectel2011

A Comparison of Paper-Based and Online Annotations in the Workplace

Example of annotations in research papers.

While reading documents, people commonly make annotations: they underline or highlight text and write comments in the margin. Making annotations during reading activities has been shown to be an efficient method for aiding understanding and interpretation. In this paper we present a comparison of paper-based and online annotations in the workplace. Online annotations were collected in a laboratory study, making use of the Web-based annotation tool SpreadCrumbs. A field study was out to gather paper-based annotations. The results validate the benefits of Web annotations. A comparison of the online annotations with paper-based annotations provides several insights in user needs for enhanced online annotation tools, from which design guidelines can be drawn.

Venue: ECTEL2009

Authors:  Ricardo Kawase, Eelco Herder, Wolfgang Nejdl

PDF: kawase-ectel209