A QFD Framework for Curriculum Planning
Colin O. Benjamin,  Miriam Watkins & Mirza Murtaza
Florida A & M University, Tallahassee Florida 32307
Abstract
This paper proposes a  three-phase QFD  framework  for  curriculum planning  in  academia and illustrates its application  via a case study of planning an integrated Engineering for Business curriculum.  A Course Planning Matrix which prioritizes the  teaching methodologies best suited to deliver critical competencies is integrated with a Course Design Matrix which identifies and prioritizes  the engineering  tools and techniques to be incorporated into the curriculum.  A  Course Implementation Matrix is introduced in the final phase of this curriculum planning methodology  to assign the engineering tools and  techniques to specific Engineering for Business courses.  The robustness of the Course Implementation phase of this planning  methodology  is confirmed via sensitivity analysis and extensions of this structured, collaborative approach to planning are suggested.
1.  Introduction
Continuous improvement (CI) is vitally important in academia to maintain a high quality of service to  "customers" - the students, faculty, and industry stakeholders.  Proposals for curriculum enhancements  should be examined and teaching methodologies carefully scrutinized to ensure that they are well suited to deliver the critical competencies and course content needed by students. Relevant analytical tools  and techniques must be identified and incorporated into the curriculum.  Appropriate courses must be developed to deliver the desired curriculum.  Quality Function Deployment (QFD) [1], a planning and design tool traditionally employed to facilitate integrated product development, can be modified to provide a flexible, integrated planning framework for curriculum planning.In this paper, we propose a framework using QFD to provide a systematic approach to curriculum planning  in academia and describe a case study from Florida A & M University to illustrate the application of this approach.
2. Quality Function Deployment
Quality Function Deployment (QFD) [1] first developed and applied by the Japanese in the early 1970's  helps multi-functional teams identify and prioritize customer requirements and relate these needs to corresponding product or service characteristics.  Over the years, QFD has attracted attention from a wide range of progressive industrial organizations in the USA including Ford Motor Co
mpany, General Motors, Rockwell International, AT&T, DEC, Hewlett-Packard, and Polaroid [6] and has been used mainly in the area of product development and improvement. Recently, QFD has been used to facilitate planning in areas such as planning process improvement projects [2], planning for technology transfer on information technology projects [3], business planning in small companies [4], manufacturing strategic planning [5], and strategic planning for service improvement projects [6].  QFD is best implemented as a multi-phase process as this approach offers the greatest potential for realizing significant benefits.  Here a series of matrices link relationships and provide a graphical summary of the process. However, several QFD projects limit implementation to the first two phases thus limiting the positive impact of this technique.
Recently, we have seen several attempts to utilize QFD to provide a structured approach for planning in academia in areas such as developing laboratories for CIM [10], revising mechanical engineering curriculum [11], research planning [12], course design [13], planning enhancements to computer laboratories [14], and improving the quality of teaching [15].  These applications all confirm the potential of QFD to facilitate effective communication, timely information transformation, and efficient resource utilization. In the following section, we describe a case study in which QFD provides a framework for integrating engineering concepts into a business curriculum.
3.  A Case Study
3.1 The Course Planning Process
The School of Business and Industry (SBI) at Florida A & M University (FAMU) is developing a suite of Engineering for Business courses for integration into its business curriculum. Among the benefits envisaged to be reaped by the students are an increased awareness of engineering and technology fundamentals, improved teamwork skills, and enhanced analytical and logical thinking. To realize these benefits, careful attention must be given to curriculum planning to maintain the quality and effectiveness of this very innovative program.  We propose that planning for this curriculum development proceed in the following phases:
♦Phase #1:  Course Planning - which prioritizes the  teaching methodologies best suited to deliver critical competencies;
♦Phase #2: Course Design - which identifies and prioritizes  the engineering  tools and techniques to be incorporated into the curriculum;
♦Phase #3: Course Implementation - which assigns the preferred engineering tools and  techniques to specific Engineering for Business courses.
In this paper we describe Phase #3: Course Implementation, the final phase of the integrated three-phase QFD methodology proposed for curriculum planning in academia.
3.2.  Course Implementation
The steps adopted in this phase of the QFD process for curriculum planning were as follows:
Step #1- Define the customer: In this case, the customers were the students enrolled in SBI’s innovative program.
Step #2-Identify the relevant Engineering Tools and Techniques for incorporation in the program and establish the relative importance of these tools and techniques - the WHATs:  These engineering tools and techniques were determined via faculty collaboration in the previous phase of the QFD process, the Course Design  phase, and weights derived  to reflect their relative importance.
Step #3- Identify Engineering for Business courses that are candidates for implementation–the HOWs. Following a brainstorming session among  our Engineering faculty, the following four courses were proposed:♦Fundamental Engineering Concepts
♦Management Engineering I
♦Management Engineering II
♦Managemernt of Technology
Step #4- Map the HOWs into the WHATs
The planning team mapped the HOWs into the WHATs by assigning ratings on a 1-3-9 scale (1 – weak; 3 – medium; 9– strong;) to indicate the relationship between each HOW and WHAT.  Several heuristics  were employed to facilitate aggregation of the mappings of individual team members while enabling a balanced allocation of tools and techniques to proposed courses.
Step #5 - Develop a House of Quality
Our team constructed a spreadsheet-based model to facilitate computation of the row and column totals and the ranking of the courses under consideration. The QFD chart is shown as Figure 1.
3.2 Analysis Of Results
Examination of the results summarized in the QFD chart in Figure 1 reveals the following:
Engineering Tools and Techniquesspring framework表达式assign
The weights assigned to the Engineering Tools and Techniques approximated a symmetrical distribution with 5 of the 17 tools (29.4%) receiving the median weight of 3 on a five-point weighting scale.  The results indicated that the greatest importance should be assigned to those engineering tools and techniques which have a strong team orientation. e.g. Project Management and Quality Function Deployment.  These received  a weight of  5 on a five-point weighting scale.  The least importance was accorded those which required considerable mathematical manipulation (e.g. Risk Analysis, Value Engineering, and Mathematical Programming).  These received a weight of 1.
Engineering for Business Courses
The scores obtained by the four courses examined ranged from a low of 22.75% to a high of 25.9 %.  This narrow range suggests that all four courses were of approximately equal significance in satisfying the School's curriculum objectives. These results can in part be attributed to the consensus-building heuristics used for aggregating individual preferences during the mapping process. Equal contributions could therefore be expected from faculty charged with the responsibility for delivering these courses.  This would afford curriculum planners considerable flexibility in developing an integrated Engineering  for Business curriculum.
3.3 Sensitivity Analysis
Sensitivity tests were conducted to ascertain the impact of variations in the weights assigned to the Engineering Tools and Techniques  (the WHATS) and the rating scale used to map the HOWs into the WHATs on the relative importance of the HOWs, the Engineering  for Business Courses.  Four scenarios were investigated.  Scenario 1 used the weights obtained from the Course Design phase and a rating scale of 1-3-9 to map the HOWs into the WHATs.    In Scenario 2, all WHATs were assigned a weight of three (average importance) on a five point scale.  In Scenario 3, all weights adopted in Scenario 1 were reduced by 30%.  In the final case, Scenario 4, the weights of the WHATs were similar to those obtained in Scenario 1.  However, a 1-3-5 rating scale was used (1 - weak; 3 - medium; 5 - strong;)
The results of the sensitivity analysis are summarized in Table 1.  These show the relative importance of each of the proposed courses in achieving the overall curricular objectives.  These results suggest that the proposed planning framework is very robust.  Significant changes in the input planning data  have little impact on the relative scores of  the HOWs.  However, there is some minor shifting in the ranking of the HOWs.  Scenario #2 which assigns equal weights to the WHATs  and  Scenario #4 which uses a 1-3-5 rating scale both produce significant changes in the ranking of the HOWs.
4. Conclusion
QFD has proven to be an effective tool in managing product/service development in manufacturing industry, in software development, in service industries, and in academia.  It can provide a powerful framework for enhancing effective communication, defining clear and accurate tasks, and achieving effective resource utilization.  This makes the technique attractive for adoption as a planning tool to enhance any group decision-making process.  In this application in academia, QFD provided a flexible framework to support an integrated, robust curriculum planning process.  Its effectiveness can be enhanced through the use of groupware to facilitate consensus building and timely decision-making. The QFD process can also be expanded to provide a structured approach for assessing the outcomes of these curriculum  changes.
Acknowledgements
The authors would like to thank the Engineering Faculty in the School of Business and Industry, Florida A & M University for their collaboration on this project.
5.  References
1.  Bossert, J. L., Quality Function Deployment: A Practitioner's Approach.  ASQC Quality Press, Milwaukee, Wisconsin, 1991.
2. Benjamin, C.O., Y. Khawaja, S. Pattanapanchai, & H. Siriwardane,  "A Modified QFD Planning Framework for Process Inprovement Projects", Proceedings, 47th International IIE Conference, St. Paul/Minnesota, MN, May 18-23, '96, pp.35-39
3. Khawaja, Y. & C. O. Benjamin,  "A  QFD Framework for Effective Transfer of AM/FM/GIS Information Technologies to Small Communities", URISA (Journal of the Urban and Regional Information Systems Assoc)., Vol. 8, No. 1, Spring  '96, pp. 37-50.
4. Ferrell, S.F. and W.G. Ferrell, "Using Quality Function Deployment in Business Planning at a Small Appraisal Firm", Appraisal Journal, Vol. 62, No. 3, July 1994, pp. 382-390.
5. Crowe, T. J. and C.C. Cheng, "Using Quality Function Deployment in Manufacturing Strategic Planning", International Journal of Operations and Production Management, Vol. 16, No. 4, April 1996, pp. 35-48.
6.  Schubert, M. A., "Quality Function Deployment: A Comprehensive Tool for Planning and Development", IEEE Proc. Natl. Aerospace and Electronics Conf., Vol. 4, 1989, pp. 1498-1503.
7.  Zultner, R. E., "Software Quality Function. Deployment", ASQC Ann. Quality Cong. Trans., Vol. 43, 1989, pp. 558-563.
8.  Maddux, G., R. Amos, A. Wyskido, "Organizations can apply QFD as a Strategic Planning Tool", Industrial Engineering, September 1991, PP. 33-37.
9. Panitz, B, “Evolving Paths”, ASEE Prism, October 1996, pp. 22-28.
10. Benjamin, C.O., S. Pattanapanchai,  & L. Monplaisir, "QFD - A  Strategic Planning Framework for CIM Laboratories", Proceedings, 1994 ASEE Annual Conference, Alberta, Canada, June 1994.
11. Ermer, D.S.,"Using QFD Becomes an Educational Experience for Students and Faculty", Quality Progress, May 1995, pp. 131-136.
12. Chen, C.L & S.F. Bullington, "Development of a strategic plan for an academic Department through the use of Quality Function Deployment", Computers and Industrial Engineering, Vol. 25, Nos. 1-4, 1993, Vol. 25, Nos 1-4, pp. 49-52.
13. Burgar, P., “Applying QFD to Course Design in Higher Education", Annual Quality Transactions, 1994.
14. Benjamin, C.O., R. Lynch & A. Mitchell, “A Methodology for Planning Enhancements to Computer Laboratories in Academia”, Proceedings, ASEE Southeastern Conference, Marietta, Georgia, April 199
7, pp. 211-218.
15.  Lam, K. K &  X. Zhao,  "An Application of Quality Function Deployment to improve the Quality of Teaching", International Journal of Quality and Reliability Management, Vol. 15, No. 4-5, April-May 1998, pp 389 (25).
Scenario #1    Base Case
Original Data      Scenario #2
Equal Weights
of 3
Scenario #3
Weights Decreased
by 20%
Scenario #4
Rating Scale
(1-3-5)
Relative Importance Relative Importance Relative Importance Relative Importance Factor
Number
Description (%)Rank%Rank%Rank%Rank
1Fundamental Engineering
Concepts
25.901=25.371=37.001=84.002
2Management Engineering I25.42323.88436.31394.001 3Management Engineering II25.901=25.371=37.001=72.004 4Management of Technology22.78425.371=32.55475.003 Table 1: Summary Results of Sensitivity Analysis
The WHATs                          The HOWs:  Proposed Courses
Engineering Tools Fundamental Management Management Management Importance Row                And Engineering Engineering I Engineering II of Technology1-little; Total        Techniques Concepts5-great;
1Computer Aided Design311210 2Facilities Planning193339 3Value Engineering313 4Quality Control33318 5Ergonomics3412 6Simulation Modeling931339 7Multi-Criteria Decision Models3933354 8Mathematical Programming313 9Scheduling33212 10Network Analysis9436 11Expert Systems122 12Artificial Neural Networks9436 13Fuzzy Logic20 14Quality Function Deployment33530 15Project Management393575 16Risk Analysis39112 17Computer Programming93336 Absolute Score10810610895417
Percentage25.9025.4225.9022.78100
Rank1=31=4
Rating Scale:  1 - Weak  3 - Medium9 - Strong
Figure 1:QFD Chart for Course Implementation
COLIN O. BENJAMIN
MIRIAM WATKINS
Miriam Watkins is an Assistant Professor in  the School of Business and Industry at Florida A & M University.  She received her MBA from the School of Business & Industry, Florida A & M University and has had several industry internships. Her current research interests include Leadership Developm
ent and Team Building. MIRZA MURTAZA
Mirza Murtaza is an Assistant Professor in the School of Business and Industry at Florida A & M University.  He obtained a PhD in Industrial Engineering from the University of Houston and has taught at Prairie View College. His current research interests lie in the areas of Artificial Intelligence Applications to Decision-making, Telecommunications and Information Systems.

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