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Experiences in Teaching and Mentoring Interdisciplinary Graduate Students of Diversified Backgrounds

Abstract

The interdisciplinary master's degree program in Computational Science and Engineering (CSE) at North Carolina A&T State University, Greensboro, NC is now more than 3 years old, and provides graduate education in several computational areas and the associated primary field disciplines. The CSE program since its inception has presently graduated more than 12 students who are currently placed in several major industries. Our CSE graduate program offers an interdisciplinary curriculum combining computational core areas along with various domain areas. The students enrolled in the program begin with diversified backgrounds (prior undergraduate studies in various fields such as engineering, physical sciences, life sciences, mathematics, business, etc), and are required to take four core courses relevant to CSE for their graduation in the areas of applied probability and statistics, comprehensive numerical analysis, Data structures and parallel programming, computational and scientific visualization irrespective of their prior background. The preparation level for the diversified group of students in these courses depends on their undergraduate major. This poses significant challenges to graduate faculty teaching these courses and mentoring these students with diversified backgrounds.

Our experiences and observations with the course content and structure, teaching methods, evaluation and student performances in these courses with diversified graduate students and their mentoring for the past 3 years are presented. The performances of the students in these core courses are correlated to their background and analyzed. Our experiences indicate students with a lesser preparation level seem to get geared quickly via peer guidance from the stronger students. In several cases, the performances were not related to an individual’s prior background, but on their motivation and willingness to strive and succeed. The experiences indicate that the students can benefit well with additional short training courses at the beginning of their graduate study. Though challenging, the positive outcome of such interdisciplinary education is that the graduates are able to technically understand and communicate effectively across disciplines in complex problem areas where such interdisciplinary interactions are not only critical, but are required in the current market place and global economy. This is reflected in the career placement of graduates in areas that generally would not have been possible based solely on their undergraduate field.

Introduction

The new paradigm in graduate studies is interdisciplinary programs that meet the technical needs of the current practices in the field and industry. Modeling and simulation built upon computational science and engineering has now become the third key solution methodology in not only engineering and physical sciences but also in other areas such as biology and economics that are generally considered to be non-computational fields. The interdisciplinary master's degree program in Computational Science and Engineering (CSE) at North Carolina A&T State University is now more than 3 years old, and provides graduate education in several computational areas and the associated primary field disciplines. The CSE program since its

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Mohan, R., & Kelkar, V., & Kelkar, A. (2008, June), Experiences In Teaching And Mentoring Interdisciplinary Graduate Students Of Diversified Backgrounds Paper presented at 2008 Annual Conference & Exposition, Pittsburgh, Pennsylvania. 10.18260/1-2--4475