Pages: pp. 144-144
Welcome to our third issue of the IEEE Transactions on Learning Technologies (TLT), which includes five papers exploring advanced technologies for technology-enhanced learning and how they support new forms of education.
Lecture recording has become mainstream in many e-learning scenarios and is relatively easy to use at universities. Recording and storing lectures is, however, only the first step; the second, equally important, step is finding the right video or video sequence again after some time. Stephan Repp and his colleagues from the University of Potsdam in Germany discuss an innovative solution for indexing and browsing lecture videos, based on state-of-the-art speech transcription algorithms. Detecting topical chains helps to identify appropriate video sequences for these topics and browsing allows for easy access to different parts of the lecture.
In addition to recording what lecturers do, learning can also benefit from recording student ideas and results. Chee-Kit Looi from Singapore and two colleagues from Taiwan explore the use of Group Scribbles as an innovative tool to collaboratively generate, collect, and aggregate ideas through a shared space. In contrast to a conventional lecturing approach, they use the Jigsaw cooperative learning method, encouraging active student involvement and interaction. Their paper investigates how students interact with others during group discussion using this tool and how Group Scribbles influences and improves their brainstorming and discussion process with promising results.
Barry Hayes and John V. Ringwood, from Ireland, address an issue relevant for assessment in distance learning programs: how to make sure that the student who takes the exam is the one who registered for the program. The system presented is designed to be used in conjunction with a graduate program in electronic engineering and provides a verification accuracy of better than 90 percent with minimization of false negatives based on telephone speech.
Last, but not least, the remaining two papers focus on software aspects. Freya H. Lin and Timothy K. Shih, from Taiwan, describe a debugging mechanism for IMS sequencing. Their solution is based on the Petri net model and detects sequencing traps, helping the content designer to avoid specifying incorrect learning paths. In addition to presenting the underlying model and trap detection mechanism, the paper describes its implementation in a SCORM 2004-compliant authoring tool.
Juan M. Dodero from Cadiz, Spain, and Ernie Ghiglione from Sidney, Australia, describe a Representational State Transfer (ReST) architectural style of accessing learning services and constituent resources, as well as a methodology to guide the design of learning service access. The method is applied to integrating wiki services in a learning environment.
We again hope that you enjoy this issue and are looking forward to receiving your submissions, both to regular issues as well as to our special issues, whose calls for papers have been announced on the TLT website!
Wolfgang Nejdl, Editor-in-Chief
Peter Brusilovsky, Associate Editor-in-Chief