A Community of Practice Approach to Integrating Professional Skills Training with Graduate Thesis Research

Background. It is well recognized that current graduate education is too narrowly focused on thesis research. Graduate students have a strong desire to gain skills for their future career success beyond thesis research. This obvious gap in professional skill training in current graduate study also leads to the common student perception that professional skills beyond academic knowledge should only be gained after completion of thesis research. Purpose. A new program is being developed to rigorously integrate professional skills training with thesis research. The approach is to establish learning communities of Graduates for Advancing Professional Skills (GAPS) to incorporate project management skill training from industry into academic research. The GAPS program seeks to address two fundamental education research questions: How can project management skill training be integrated with thesis research in graduate education? What is the role/value of learning communities in enhancing the training and retention of professional skills and the effectiveness of thesis research? Our proposed solution is that graduate student learning communities engaging in a blended online and classroom approach will promote learning of professional skills such as project and time management in thesis research activities. The purpose of this session is to establish the connection between project management and thesis research, and demonstrate the beginning progress of the GAPS program towards. Methodology/approach. The following progress is being made to establish GAPS learning communities through which to teach and practice professional skills. A website has been developed to introduce the program, recruit participants, provide information on the online modules, and survey results of participants’ current levels of knowledge and skills related to project management. A new course, “Introduction of Project Management for Thesis Research”, has been added to the course catalog and open to enrollment for students from different majors. In addition, learning modules including project charter, scheduling, communication, teamwork, critical path method, and lean concept are developed. Case studies and examples have been developed to help students learn how to utilize project management skills in their thesis research. Conclusions. The concept of integrating professional skills training with thesis research through learning communities has been demonstrated. There are multiple advantages of this approach, including efficient utilization of the current resources, and faculty buy-in. Preliminary data from the first cohort are being collected and analyzed to identify students’ needs, benefits of the program, and areas of improvement for future cohort iterations. Implications. The GAPS program will improve professional skill training for graduate students through communities of practice. This new learning model has the potential to fundamentally change the culture of graduate education. We believe the method demonstrated here can be broadly applied to different engineering majors, and even broadly to all thesis research

2008 Author Recognition Bibliography

https://scholarworks.gvsu.edu/authorrecognition/1006/thumbnail.jp

A change-point detection and clustering method in the recurrent-event context

Change-point detection in the context of recurrent-event is a valuable analysis tool for the identification of the intensity rate changes. It has been an interesting topic in many fields, such as medical studies, travel safety analysis, etc. If subgroups exist, clustering can be incorporated into the change-point detection to improve the quality of the results. This paper develops a new algorithm named Recurrent-K-means to detect the change-points of the intensity rates and identify clusters of objects with recurrent events. It also proposes a test-based method to perform a heuristic search in determining the number of underlying clusters. In this study, the objects are assumed to fall in several clusters while the objects in the same cluster share identical change-points. The event count for an object is assumed to be a non-homogeneous Poisson process with a piecewise-constant intensity function. The methodology estimates the change-point as well as the intensity rates before and after the change-point for each cluster. The methodology establishes a clustering analysis based on K-means algorithm but enhances the procedure to be model based. The simulation study shows that the methodology performs well in parameter estimation and determination of the number of clusters in different scenarios. The methodology is applied to the UK coal mining disaster data to show its possible role in shaping government regulations and improving coal industry safety

Parametric estimation of change-points for actual event data in recurrent events models

Time to event data have long been important in many applied fields. Many models and analysis methods have been developed for this type of data in which each sample unit experiences at most a single end-of-life event. In contrast, many applications involve repeated events, where a subject or sampling unit experiences more than one event. There is growing interest in the analysis of recurrent events data, also called repeated events and recurrence data. This type of data arises in many fields. For example, the repair history of manufactured items can be modeled as recurrent events. In medical studies, the times of recurrent disease episodes in patients can also be modeled as recurrent events. In this paper we focus on medical applications (e.g. seizures, heart attacks, cancerous tumors, etc.). However, our proposed methodologies can be applied to other areas as well. For analyzing recurrence data, the first and perhaps most important step is to model the expected number of events, and sometimes this can be facilitated by modeling the cumulative intensity function or its derivative, the intensity rate function. One particular recurrent events scenario involves patients experiencing events according to a common intensity rate, and then a treatment may be applied. Assuming the treatment to be effective, the patients would be expected to follow a different intensity rate after receiving the treatment. Further, the treatment might be effective for a limited amount of time, so that a third rate would govern arrivals of the recurrent events after the effects of the treatment wore out. In this paper we model the intensity rate for such scenarios. In particular we allow models for the intensity rate, post-treatment, to be piecewise constant. Two estimators of the location of this change are proposed. Properties of the estimators are discussed. An example is studied for illustrative purposes.