Cognition and Technology: Effectiveness of intelligent tutoring systems for software training

This study addresses the potential of using an intelligent tutoring system (ITS) to tutor on off-the-shelf (OTS) software. ITSs have been successfully used to tutor on a variety of learning domains, but there has been little research comparing ITS-based training on an OTS application with traditional software training approaches such as books or interactive software simulations. The work presented here includes procedures and results for Paint.NET training and evaluation using three methods: book-based, interactive simulation, and an ITS. It is reported that there were some associations between the training method and training experiences. Book-based training exhibited higher scores on both task performance and system usability perception, while better times were recorded for the simulation approach. Concept acquisition score was not found to significantly correlate with training method, however. Additionally, it was found that interactions between training mode and spatial ability or general self-efficacy (GSE) significantly affected system usability perception. It was also learned that within ITS high computer self-efficacy (CSE) learners outperformed these with low CSE on task performance measure. Similar findings were reported for simulation group where high-spatial learners recorded better training times than low-spatial learners. Overall, results indicated that four individual characteristics to succeed indicators explored in this study significantly correlated with total training time and system usability measures. It is concluded that if an ITS is to be a tutor on OTS application then further refinements are needed

Active Learning via a Sample Database: The Case of Microsoft\u27s Adventure Works

This paper describes the use and benefits of Microsoft’s Adventure Works (AW) database to teach advanced database skills in a hands-on, realistic environment. Database management and querying skills are a key element of a robust information systems curriculum, and active learning is an important way to develop these skills. To facilitate active learning and produce a compelling narrative, the data structure and content of a useful pedagogically-oriented database should be realistic and lifelike. It should contain data that accurately depicts the business processes, functions, and entities of a realistic organization, structured in a way that demonstrates best practices in database design. Most database textbooks include sample databases, but these are often small and sparse of data. By contrast, Microsoft’s AW database presents a robust, realistic, and comprehensive framework for many important educational objectives in an IS curriculum. This paper introduces the AW business case and database, and illustrates several pedagogical uses in an undergraduate CIS program

Effectiveness and User Experience of Augmented and Mixed Reality for Procedural Task Training

Use of augmented reality (AR) and mixed reality (MR) technologies for training is increasing, due in part to opportunities for increased immersion, safer training, and reduced costs. However, AR/MR training effectiveness and user experience, particularly for head-mounted displays (HMDs), is not well understood. The purpose of this study is to investigate user perceptions and retention of AR/MR training delivered through a HMD for a procedural task. This two-part study utilized a within-subjects experimental design with 30 participants to determine how instruction method (paper vs. AR vs. MR) and time of procedure recall (immediate vs. post-test vs. retention) influenced completion time, perceived task difficulty, perceived confidence in successfully completing the task, workload, user experience, and trainee reactions. Results indicate differences between instruction methods for user experience and preference, with significantly higher user experience ratings for MR and lower preference rankings for AR. Findings also show decreased performance, increased perceived task difficulty, and decreased confidence as time since training increased, with no significant differences in these measures between instruction methods. Completion times and workload were also found to be comparable between instruction methods. This work provides insight into objective and subjective differences between paper-, AR-, and MR-based training experiences, which can be used to determine which type of training is best suited for a particular use case. Recommendations for appropriately matching training modalities and scenarios, as well as for how to successfully design AR/MR training experiences, are discussed

Inferring Intent from Interaction with Visualization

Today\u27s state-of-the-art analysis tools combine the human visual system and domain knowledge, with the machine\u27s computational power. The human performs the reasoning, deduction, hypothesis generation, and judgment. The entire burden of learning from the data usually rests squarely on the human user\u27s shoulders. This model, while successful in simple scenarios, is neither scalable nor generalizable. In this thesis, we propose a system that integrates advancements from artificial intelligence within a visualization system to detect the user\u27s goals. At a high level, we use hidden unobservable states to represent goals/intentions of users. We automatically infer these goals from passive observations of the user\u27s actions (e.g., mouse clicks), thereby allowing accurate predictions of future clicks. We evaluate this technique with a crime map and demonstrate that, depending on the type of task, users\u27 clicks appear in our prediction set 79\% -- 97\% of the time. Further analysis shows that we can achieve high prediction accuracy after only a short period (typically after three clicks). Altogether, we show that passive observations of interaction data can reveal valuable information about users\u27 high-level goals, laying the foundation for next-generation visual analytics systems that can automatically learn users\u27 intentions and support the analysis process proactively

Investigating The Impact of Interaction Design on the Delivery of Online Pharmaceutical Courses: Adapting Online Course Graphic Design for Improved Content Retention

In recent years, the use of online courses has emerged as a way to quickly and easily deliver content to large numbers of trainees. In writing these courses, pharmaceutical course developers often use traditional instructional design models and techniques to design course content for online learning. But is this truly enough? Interaction design principles and practices can also be incorporated to increase the quality of learning by improving learner comprehension and retention. Using pharmaceutical content and learners, this research investigated how interaction design impacts online learning by measuring the effect of applying different graphical user interfaces. The results were surprising, as the data showed no significant improvement in retention rates between graphical treatments. However, the incorporation of graphics did slightly improve overall course satisfaction