1. Hộ i thả o
“PHƯƠ NG PHÁP NGHIÊN CỨ U
KHOA HỌ C”
Ngườ i trình bày: Gs. TS. Bùi Tùng
Đạ i họ c Hawaii-Hoa Kỳ
Trung tâm Học liệu-Đại học Thái Nguyên, 07-08/10/2008
2. Làm nghiên cứ u khoa họ c
Gs. TS. Bui Tung
Tung Bui, PhD, Dr.rer.pol.
University of Hawaii
Matson Navigation Company Distinguished Professor of Global Business
Graduate Chair and Director of PhD Program in International Management
Phươ ng pháp luậ n về nghiên cứ u/ Dự án TTHL
Tháng 10 - 2008
52. Bí quyế t:
Có mộ t câu chuyệ n để kể
Và kể câu chuyệ n đó bằ ng mộ t cách
“khoa họ c” vớ i phươ ng pháp đượ c
chứ ng minh và nhữ ng con số khách
quan.
62. Thả o luậ n trườ ng hợ p:
Hai ví dụ về nghiên cứ u thiế t
kế
Các ví dụ kế tiế p:
Bui, Lee Các hệ thố ng hỗ trợ việ c ra quyế t đị nh, 2006
Bui, Loebbecke Các hệ thố ng hỗ trợ việ c ra quyế t đị nh,
1997
77. Tình huố ng thả o luậ n:
Hai ví dụ về nghiên cứ u thự c nghiệ m
Running examples:
Sankaran và Bui, Lee International Journal of
Instructional Psychology, 2003
Sankaran and Bui Lee International Journal of
Instructional Psychology, 2000
84. Tiế n hành nghiên cứ u (3)
Dự đoán/Phân loạ i
Running example: Bui, Sankaran, Sebastian
“A Framework for measring national e-readiness
International Journal of Electronic Business, 2003
93. Tình huố ng thả o luậ n:
Hai ví dụ về nghiên cứ u
tình huố ng và việ c sử dụ ng
nhóm nghiên cứ u trọ ng
điể m
Running examples:
Bui, Le, Jones. Mộ t nghiên cứ u tình huố ng về du lị ch điệ n
tử ở TPHCM Thunderbird International Business Review,
2006
Bui, Sebastian, Jones Hawaii 2020, 2000
109. Tình huố ng thả o luậ n:
Mộ t ví dụ về nghiên cứ u theo kinh nghiệ m
Running example:
Amblee and Bui, International Journal of Electronic Commerce, 2007
Amblee and Bui Journal of marketing, (submitted)
111. Hế t tình huố ng thả o
luậ n
Running example: Amblee & Bui
International conference on Information Systems, June,
2007
Journal of Marketing, submitted
141. Kế t thúc phầ n
“Tiế n hành nghiên cứ u”
Running example: Amblee Bui
(International conference on Information Systems,
June, 2007)
Journal of Marketing, submitted
This presentation is only an overview of research. The only way to get better at research is to do it.
In this model all design begins with Awareness of a problem . Design research is sometimes called “Improvement Research” and this designation emphasizes the problem- solving/performance-improving nature of the activity. Suggestions for a problem solution are abductively drawn from the existing knowledge/theory base for the problem area ( Pierce , 1931). An attempt at implementing an artifact according to the suggested solution is performed next. This stage is shown as Development in the diagram. Partially or fully successful implementations are then Evaluated (according to the functional specification implicit or explicit in the suggestion). Development , Evaluation and further Suggestion are frequently iteratively performed in the course of the research (design) effort. The basis of the iteration, the flow from partial completion of the cycle back to Awareness of the Problem, is indicated by the Circumscription arrow. Conclusion indicates termination of a specific design project. New knowledge production is indicated in Figure 3 by the arrows labeled Circumscription and Operation and Goal Knowledge . The Circumscription process is especially important to understanding design research because it generates understanding that could only be gained from the specific act of construction . Circumscription is a formal logical method ( McCarthy , 1980) that assumes that every fragment of knowledge is valid only in certain situations. Further, the applicability of knowledge can only be determined through the detection and analysis of contradictions – in common language, the design researcher learns or discovers when things don’t work “according to theory." This happens many times not due to a misunderstanding of the theory, but due to the necessarily incomplete nature of ANY knowledge base. The design process, when interrupted and forced back to Awareness of Problem in this way, contributes valuable constraint knowledge to the understanding of the always-incomplete-theories that abductively motivated the original design.
While both of these are tools used during research, they are not sufficient for research.
Note that econometrics is a passive science. We can only observe and hope that we the manipulations we would like will occur naturally. Or that when manipulation occur, they do so without other confounding events at the same time. Both are rare. Analytical economics is entirely created by the researcher. It attempts to capture the key environment and incentives, but may omit many important factors. Moreover the research may lack enough information about the environment of interest to effectively simplify his analysis.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
This presentation is a basic overview of research as it applies for Masters and PhD students. While the exact requirements between the two degrees is somewhat different, the basic concepts and approaches to research are not.
These don’t represent some kind of linear plan, but are rather common characteristics shared by almost all legitimate research regardless of the venue by which that research was conducted.
The concept of “important” questions is subjective and will depend on who you ask as well as the purpose of the research. For instance, PhD students have a different “bar” than Masters students owing to the requirement that their research be “original and significant.”
The first case is really an exercise in data gathering and doesn’t contribute new knowledge. The same argument holds for the second case. The third case is a mathematical statement but doesn’t address the reasons for the correlation (which might lead to new knowledge). A similar argument applies to the fourth case.
If other researchers can’t confirm your results, you may be faced with having studied an anomaly. Similarly, without a solid plan, you might have inadvertently introduced errors into the experimental design which immediately calls your results into question.
There are very few “perfect” research designs where some flaws aren’t present. That’s normal. However, these flaws must be documented as well as their possible impact on the outcome. While this won’t stop reviewers from criticizing the work, it makes it clear that you are aware of the problems and their impact upon your work.
Many of us have professional experience which can lead to possible research. Always be careful to differentiate between research and self-enlightenment. A lot of computer literature, particularly research journals such as IEEE or ACM, show good research problems and possible sources of future work. Such future work can provide a good starting point for research projects. The same groups also host professional conferences. DePaul has a student chapter of the ACM that might provide a good source of inspiration for research. Many of the faculty here at DePaul have all kinds of problems that they’re trying to solve.
When documenting the proposed research, you should be as precise as you can. You’ll probably find yourself editing and revising many times to attain the necessary level of precision and clarity.
Documenting the delimitations is just as important as documenting the intended research. In essence, the problem and delimitations describe the scope of the project. Keep the delimitations in mind as you move forward. Current delimitations might provide avenues for valuable future work.
The accurate and consistent measurement of some phenomenon is called validity and reliability respectively.
Many times the ability of a researcher to justify the importance of their research topic is directly proportional to their ability to receive funding. This basically requires good salesmanship.
There are some basic variations on this theme, but all of these areas will be covered. This format serves to crystalize your thought process and to help ensure that no critical elements of your research have been neglected.
Some journals include IEEE and ACM. Be careful of trade journals; they’re often not peer reviewed which can call the content into question in terms of its reliability and quality. The bibliography could be a Word document, Excel spreadsheet, or bibliographic database. Even if the article doesn’t directly pertain to your current project, it might provide you with ideas.
We’ll try to give some guidelines as to how to choose starting and stopping points during your research work. Please keep in mind that the following steps don’t have to be slavishly followed in the sequence in which they are presented.
The literature review is often a good source for additional ideas. This is also a good place to go in conjunction with the prior step; there’s no point in wasting good brain cells coming up with hypotheses that solve a problem that has already been adequately addressed.
Keep in mind that just because you didn’t find a solution today, doesn’t mean that one won’t show up tomorrow. This is one of the reasons that researchers are always reading and trying to keep up to date with current trends.
A statement of causality is very difficult to demonstrate because there often many other confounding factors. For an example of this, do a quick bit of reading on the hoops researchers had to go through while trying to show a causal link between smoking and certain kinds of cancer.
The choice of methodology might be governed by the kind of research being conducted. For example, the hard sciences tend to favor quantitative methodologies whereas the social sciences often gravitate toward qualitative approaches. It’s quite common for both methodologies to be used during the course of a single research project.
These are some the differences in the intent and approaches between quantitative and qualitative research. There are other significant differences in approach as well, but these are some of the highlights. Keep in mind that research design is not a simple task.