Νικόλαος Τσέλιος

Christos Katsanos, Michalis Xenos, Nikolaos Tselios

The Keystroke Level Model (KLM) and Fitts Law constitute core teaching subjects in most HCI courses, as well as many courses on software design and evaluation. The KLM Form Analyzer (KLM_FA) has been introduced as a practitioner s tool to facilitate web form design and evaluation, based on these established HCI predictive models. It was also hypothesized that KLMFA can also be used for educational purposes, since it provides step by step tracing of the KLM modeling for any web form filling task, according to various interaction strategies or users characteristics. In our previous work, we found that KLM-FA supports teaching and learning of HCI modeling in the context of distance education. This paper reports a study investigating the learning effectiveness of KLM-FA in the context of campus-based higher education. Students of a software quality course completed a knowledge test after the lecture- based instruction (pre-test condition) and after being involved in a KLMFA mediated learning activity (post-test condition). They also provided posttest ratings for their educational experience and the tool s usability. Results showed that KLM-FA can significantly improve learning of the HCI modeling. In addition, participating students rated their perceived educational experience as very satisfactory and the perceived usability of KLM-FA as good to excellent.

Nikolaos Tselios, Manolis Maragoudakis

A device which contains number of symbol input keys, where the number of available keys is less than the number of symbols of an alphabet of any given language, screen, and dynamic reordering table of the symbols which are mapped onto those keys, according to a disambiguation method based on the previously entered symbols. The device incorporates a previously entered keystrokes tracking mechanism, and the key selected by the user detector, as well as a mechanism to select the dynamic symbol reordering mapped onto this key according to the information contained to the reordering table. The reordering table occurs from a disambiguation method which reorders the symbol appearance. The reordering information occurs from Bayesian Belief network construction and training from text corpora of the specific language.

Adrian Stoica, Nikolaos Tselios, Christos Fidas

This paper is concerned with the design and implementation of an innovative user support system in the frame of an open educational environment. The environment adapted is ModelsCreator (MC), an educational system supporting learning through modelling activities. The pupils typical interaction with the system was modelled us-ing Bayesian Belief Networks (BBN). This model has been used in ModelsCreator to build an adaptive help system providing the most useful guidelines according to the current state of interaction. A brief description of the system and an overview of application of Bayesian techniques to educational systems is presented together with discussion about the process of building of the Bayesian Network derived from actual student interaction data. A preliminary evaluation of the developed prototype indicates that the proposed approach produces systems with promising performance.

Anastasia Revythi, Nikolaos Tselios

This study examines the acceptance of technology and behavioral intention to use learning management systems (LMS). In specific, the aim of this research is to examine whether students ultimately accept and use educational learning systems such as e-class and the impact of behavioral intention on their decision to use them. An extended version of technology acceptance model has been proposed and used by employing the System Usability Scale to measure perceived ease of use. 345 university students participated in the study and the data analysis was based on partial least squares method. The results were confirmed in most of the research hypotheses. In particular, social norm, system access and self-efficacy significantly affect behavioral intention to use. As a result, it is suggested that e-learning developers and stakeholders should focus on these factors to increase acceptance and effectiveness of learning management systems.