Prospects of a mathematical theory of human behavior in complex man-machine systems tasks

A hierarchy of human activities is derived by analyzing automobile driving in general terms. A structural description leads to a block diagram and a time-sharing computer analogy. The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in actual complex tasks. Other mathematical tools so far not often applied to man machine systems are also discussed. The mathematical descriptions at least briefly considered here include utility, estimation, control, queueing, and fuzzy set theory as well as artificial intelligence techniques. Some thoughts are given as to how these methods might be integrated and how further work might be pursued

Investigating attributes affecting the performance of WBI users

This is the post-print version of the final paper published in Computers and Education. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Numerous research studies have explored the effect of hypermedia on learners' performance using Web Based Instruction (WBI). A learner's performance is determined by their varying skills and abilities as well as various differences such as gender, cognitive style and prior knowledge. In this paper, we investigate how differences between individuals influenced learner's performance using a hypermedia system to accommodate an individual's preferences. The effect of learning performance is investigated to explore relationships between measurement attributes including gain scores (post-test minus pre-test), number of pages visited in a WBI program, and time spent on such pages. A data mining approach was used to analyze the results by comparing two clustering algorithms (K-Means and Hierarchical) with two different numbers of clusters. Individual differences had a significant impact on learner behavior in our WBI program. Additionally, we found that the relationship between attributes that measure performance played an influential role in exploring performance level; the relationship between such attributes induced rules in measuring level of a learners' performance

How Supervisors Influence Performance: A Multilevel Study of Coaching and Group Management in Technology-Mediated Services

This multilevel study examines the role of supervisors in improving employee performance through the use of coaching and group management practices. It examines the individual and synergistic effects of these management practices. The research subjects are call center agents in highly standardized jobs, and the organizational context is one in which calls, or task assignments, are randomly distributed via automated technology, providing a quasi-experimental approach in a real-world context. Results show that the amount of coaching that an employee received each month predicted objective performance improvements over time. Moreover, workers exhibited higher performance where their supervisor emphasized group assignments and group incentives and where technology was more automated. Finally, the positive relationship between coaching and performance was stronger where supervisors made greater use of group incentives, where technology was less automated, and where technological changes were less frequent. Implications and potential limitations of the present study are discussed

Investigation of the use of navigation tools in web-based learning: A data mining approach

Web-based learning is widespread in educational settings. The popularity of Web-based learning is in great measure because of its flexibility. Multiple navigation tools provided some of this flexibility. Different navigation tools offer different functions. Therefore, it is important to understand how the navigation tools are used by learners with different backgrounds, knowledge, and skills. This article presents two empirical studies in which data-mining approaches were used to analyze learners' navigation behavior. The results indicate that prior knowledge and subject content are two potential factors influencing the use of navigation tools. In addition, the lack of appropriate use of navigation tools may adversely influence learning performance. The results have been integrated into a model that can help designers develop Web-based learning programs and other Web-based applications that can be tailored to learners' needs