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

Annotation Tool for Enhancing E-Learning Courses

One of the most popular forms of learning is through reading and for years we have used hard copy documents as the main material to learn. With
the advent of the Internet and the fast development of new technologies, new tools have been developed to assist the learning process. However,
reading is still the main learning method that is an individual activity. In this paper we propose a highlighting tool that enables the reading
and learning process to become a collaborative and shared activity. In other words, the highlighting tool supports the so-called active-reading,
a well-known and efficient means of learning. The highlighting tool brings to the digital environment the same metaphor of the traditional
highlight marker and puts it in a social context. It enables users to emphasize certain portions of digital learning objects. Furthermore, it
provides students, tutors, course coordinators and educational institutions new possibilities in the teaching and learning process. In this work
we expose the first quantitative and qualitative results regarding the use of the highlight tool by over 750 students through 8 weeks of
courses.

Venue: ICWL2012

Authors:  Bernardo Pereira Nunes, Ricardo Kawase, Stefan Dietze, Gilda Helena Bernardino de Campos and Wolfgang Nejdl

Boosting Retrieval of Digital Spoken Content

Every day, the Internet expands as millions of new multimedia objects are uploaded in the form of audio, video and images. While traditional text-based content is indexed by search engines, this indexing cannot be applied to audio and video objects, resulting in a plethora of multimedia content that is inaccessible to a majority of online users. To address this issue, we introduce a technique of automatic, semantically enhanced, description generation for multimedia content. The objective is to facilitate indexing and retrieval of the objects with the help of traditional search engines. Essentially, the technique generates static Web pages automatically, which describe the content of the digital audio and video objects. These descriptions are then organized in such a way as to facilitate locating corresponding audio and video segments. The technique employs a combination of Web services and concurrently provides description translation and semantic enhancement. Thorough analysis of the click-data, comparing accesses to the digital content before and after automatic description generation, suggests a significant increase in the number of retrieval items. This outcome, however is not limited to the terms of visibility, but in supporting multilingual access, additionally decreases the number of language barriers.

Venue: KES (Selecte Papers) 2012

Authors:  Bernardo Pereira Nunes, Alexander Mera, Marco A. Casanova and Ricardo Kawase

PDF: nunes-kes(selected)2012

Automatically generating multilingual, semantically enhanced, descriptions of digital audio and video objects on the Web

Every day, millions of new images, videos and audios are uploaded to the web. However, unlike text-based content, audio and video objects cannot be indexed by search engines. Thus, much valuable multimedia content stay unreachable for a great majority of online users. To overcome this problem we introduce a technique that automatically generates semantically enhanced descriptions of audio and video objects. The goal is to facilitate indexing and retrieval of the objects with the help of traditional search engines. Basically, the technique automatically generates static Web pages that describe the content of the digital audio and video objects, organized in such a way as to facilitate locating segments of the audio or video that correspond to the descriptions. The technique is a mashup of Web services that also provides translation of the descriptions and semantic enhancement. We thoroughly analyzed the click-data comparing accesses to the digital content before and after the automatic generation of the descriptions. The outcomes suggest that the technique significantly improve the retrieval of items, not only in terms of visibility, but also brings down language barriers, by supporting multilingual access.

Venue: KES2012

Authors:  Bernardo Pereira Nunes, Alexander Mera, Marco A. Casanova and Ricardo Kawase

PDF: nunes-kes2012

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