Usability Issues in Advanced Distributed Learning Applications: What are the Implications for Learning?

Abstract

This paper describes the results of data collection that occurred during the alternative format session presented to the 45^th annual meeting of HFES. During the session, six participants were briefed on fuzzy logic as an alternative to regression for analyzing policy-capturing data and on usability issues associated with Advanced Distance Learning (ADL) applications. Participants then rated the extent to which usability violations impacted learning in three different ADL environments. After the conference, the validity of the regression and fuzzy models were assessed across the three ADL applications. In addition, exploratory analyses were performed in order to gain insight into the relative impact of usability principles on learning in ADL applications. Results revealed no statistically significant differences between the predictive validities of either modeling technique across the ADL applications. In addition, judgements of which usability violations had a more negative impact on learning did depend on the type of ADL application