CCLI: Model Eliciting Activities: Experiments and Mixed Methods to Assess Student Learning – Part II

As part of a seven university CCLI* Type 3 collaborative effort focused on models and modeling, we have extended the model eliciting activity (MEA) construct to upper division engineering programs. Originally developed and validated by mathematics education researchers, MEAs were found to have significant value as an educational tool. In particular, our overall goal has been to use this construct as a means for enhancing engineering students‟ problem solving and modeling skills as well as their conceptual understanding of certain engineering topics. Specifically,we have pursued two main research avenues: MEAs as teaching tools and MEAs as learning assessment tools. This paper summarizes our results for these two research thrusts as we enter our fourth project year. Particular emphasis is placed on our mixed measurements for student learning and achievement, and an examination of the relative conceptual gain for a series of MEA experiments, including those where a comparison group was available

DEVELOPING METHODS TO SOLVE THE WORKFORCE ASSIGNMENT PROBLEM CONSIDERING WORKER HETEROGENEITY AND LEARNING AND FORGETTINGDEVELOPING METHODS TO SOLVE THE WORKFORCE ASSIGNMENT PROBLEM CONSIDERING WORKER HETEROGENEITY AND LEARNING AND FORGETTING

In this research we study how the assignment of a fully cross-trained workforce organized on a serial production line affect throughput. We focus on two serial production environments: dynamic worksharing on a production line, similar to bucket brigade systems and a fixed assignment serial-production line where workers work on a specific task during a given time period. For the dynamic assignment environment we concentrated on the impact of different assignment approaches and policies on the overall system performance. First, we studied two worker two station lines when incomplete dominance is possible as well as the effects of duplicating tooling at these lines. One focus of this research was to optimally solve the dynamic worksharing assignment problem and determine exact percentages of work performed by each worker under the assumptions presented. We developed a mixed integer programming formulation for n workers and m stations that models one-cycle balanced line behavior where workers exchange parts at exactly one position. This formulation is extended to incorporate multiple production lines. We also developed a two-cycle formulation that models a condition when workers exchange parts at exactly two positions in a periodic manner. We also determined throughput levels when workers productivity changes over time due to workers' learning and forgetting characteristics.A fixed worker assignment system considers a serial production setting in which work is passed from station to station with intermediate buffers between stations. We considered two models. The first model assumes that workers perform tasks based on their steady-state productivity rate. The second model assumes that workers' productivity rates vary based on their learning and forgetting characteristics. Heuristic methods were developed and implemented to solve these two models and to determine optimal throughput levels and optimal worker assignments. We were also able to demonstrate the importance of introducing learning and forgetting into these types of worker assignment problems. A final focus of this research was the comparison of the dynamic worksharing and fixed worker assignment environments

A Solution Approach to the Daily Dockworker Planning Problem at a Port Container Terminal

This study focused on vital resources at port container terminals such as quay cranes and dockworkers. We studied the impact of incorporating the dockworker assignment problem (DWAP) into the quay crane assignment problem (QCAP). The aim of this study was to formulate and solve an integrated model for QCAP and DWAP, with the objective of minimizing the total costs of dockworkers, by optimizing workers’ assignment, so that the ships’ costs due to the time spent in the port are not increased. We proposed an integrated solution approach to the studied problem. Our proposed model has been validated on an adequate number of instances based on the real data. Obtained solutions were compared with the solutions obtained by the traditional sequential approach. It was demonstrated that, for all solved instances, our proposed integrated approach resulted in a reduction in the total costs of dockworkers. The major contribution of this study is that this is the first time that these two problems were modeled together. The obtained results show significant savings in the overall costs