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Contribution: A semester-long, open-ended design project was implemented to promote intellectual development of first-year students while reinforcing event-driven/procedural programming principles. This paper describes this approach, and an evaluation strategy using Perry's model for intellectual development. The results show that students can reach the relativism stage of Perry's model in their first year of studies. Background: Students must move beyond a dualistic worldview to be engineers. Felder and Brent provided a list of recommendations to promote this type of intellectual development in students; active learning strategies strongly align with these recommendations. While active learning is common in programming courses (sometimes taking the form of project-based learning), they are typically tightly controlled by the instructor, and limited in scope (both in time and complexity), potentially reducing their impact on students. Intended Outcomes: This course and term-long project provided students a supportive environment in which to develop their decision-making skills, and promoted their intellectual development through Perry's stages related to software design. Application Design: Aligned with Felder and Brent's recommendations and Kuh's High Impact Practices, a course was built to: 1) teach students procedural programming, with 2) a focus on software design and open-ended problem solving, while maintaining 3) a supportive environment for skill acquisition. Findings: A mixed methods study showed the majority of students align themselves with the relativism stage of intellectual development at the end of the course. This study also illuminated the decision-making processes of teams of students in a first-year software design course.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.05.010 Byline: Gary W. Black (a), Kenneth N. McKay (b), Thomas E. Morton (c) Keywords: Scheduling; Aversion Dynamics; Adaptive heuristics; Risk mitigation heuristics Abstract: Empirical studies have shown that human schedulers use special procedures to deal with troublesome jobs that are perceived to disrupt manufacturing or that will take substantially longer than the industrial engineering standards. These troublesome jobs present a risk to the manufacturing process and to the schedule robustness. One strategy is to delay them whenever possible and to allow other work to overtake. The Aversion Dynamics concept is used to include this type of logic in scheduling heuristics such that a trade-off analysis of penalties occurs in light of the expected performance results. This is accomplished by altering processing time estimates to achieve a form of 'safety time' for risky jobs. This paper conducts a large empirical study within the single-machine static arrival environment to demonstrate that the concept of special sequencing based on job risk is significant and that robust strategies can be developed. Author Affiliation: (a) School of Business, University of Southern Indiana, 8600 University Boulevard, Evansville, IN 47712, USA (b) Department of Management Sciences, University of Waterloo, Waterloo, ont, N2L 3G1, Canada (c) Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, PA 15213, USA Article History: Received 22 September 2003; Accepted 13 May 2005

Eliyahu M. Goldratt The North River Press Publishing Corporation, Great Barrington, MA, 1997. ISBN 0-88427-153-6 This is a business novel that focuses Goldratt's Theory of Constraints on project management. Throughout [...]

Production schedules released to the shop floor have two important functions: allocating shop resources to different jobs to optimize some measure of shop performance and serving as a basis for planning external activities such as material procurement, preventive maintenance and delivery of orders to customers. Schedule modification may delay or render infeasible the execution of external activities planned on the basis of the predictive schedule. Thus it is of interest to develop predictive schedules that can absorb disruptions without affecting planned external activities while maintaining high shop performance. We present a predictable scheduling approach, that inserts additional idle time into the schedule to absorb the impacts of breakdowns. The effects of disruptions on planned support activities are measured by the deviations of job completion times in the realized schedule from those in the predictive schedule. We apply our approach to minimizing total tardiness on a single machine with stochastic machine failures. We then extend the procedure to consider the case where job processing times are affected by machine breakdowns, and provide specialized rescheduling heuristics. Extensive computational experiments show that this approach provides high predictability with minor sacrifices in shop performance. [ABSTRACT FROM AUTHOR]