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Abstract number: 011-0445
Abstract title: PhD students: supervision and success
Harm-Jan Steenhuis
Eastern Washington University
668 N. Riverpoint Blvd., Suite A
Spokane, WA99202-2677, USA
+1-509-358-2210
Erik J. de Bruijn
University of Twente
PO Box 217
7500 AE Enschede, The Netherlands
+31-53-489-3531
POMS 20th Annual Conference
Orlando, Florida U.S.A.
May 1 to May 4, 2009
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PhD students: supervision and success
Harm-Jan Steenhuis and Erik J. de Bruijn
Much of the extensive literature on the scholarship of teaching and learning is aimed at
primary and secondary education compared with tertiary education. Within this last
literature stream the main focus is more on undergraduate studies then on the masters
level. Research on teaching and learning aimed at PhD level programs is hard to find.
The aim of this paper is to explore the factors that influence successful completion of
PhD programs. This is based on a European PhD program, covers 15 years of experience
including 23 PhD students who have successfully completed the program, 6 who have
abandoned the program, and 7 who are currently enrolled in the program. It examines 1)
the goals of the PhD program, 2) the degree of success of success of PhD students, and 3)
an exploration of the factors that influence success such as the type of supervision,
student characteristics and environmental characteristics.
1. Introduction
Since Boyer’s (1990) book on scholarship which introduces the scholarship of teaching,
teaching and learning has received considerable academic attention. Numerous studies
have been conducted that have examined a wide range of variables and their influence on
effective student learning. Some studies focus on the student and student characteristics
such as their ability to think formally (Hudak and Anderson, 1990), whether they are first
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generation or not (Collier and Morgan, 2008), personality characteristics (Chamorro-
Premuzic, Furnham and Lewis, 2007; Whittingham, 2006), how they learn and learning
styles (Entwistle and Tait, 1990; Felder and Spurlin, 2005; Loo, 2002; Sternberg and
Grigorenko, 1995; Sternberg and Grigorenko, 1997; Tait and Entwistle, 1996),
attendance and engagement (Billington, 2008; Bryson and Hand, 2007; Durden and Ellis,
1995; Handelsman, Briggs, Sullivan and Towler, 2005; Koppenhaver, 2006) or more
generally what they do in classrooms and how this affects learning (Biggs, 1999).
Other studies are focus on the instruction side such as the type of instruction and
course design (Flamm, Hoffman, Delgadillo and Ewing, 2008; Mukherjee, 2002;
Samuelowicz and Bain, 2001; Trigwell, Prosser and Waterhouse, 1999), how grading is
done (Kulick and Wright, 2008), and for example the impact of team-based competition
(Umble, Umble and Artz, 2008).
Research has also appeared on specific teaching methods such as for example the
use and effectiveness of online quizzes (Brothen and Wambach, 2001, Grimstad and
Grabe, 2004; Kibble, 2007; Maki and Maki, 2001), the use of clickers in the classroom
(Beatty, 2004; Carnaghan and Webb, 2007; Martyn, 2007; Steenhuis, Grinder, de Bruijn,
2009; Yourstone, Kraye and Albaum, 2008) or the use of peer-mentors (Fox and
Stevenson, 2006; Libarkin and Mencke, 2001; McGee, 2001; Rubin and Hebert, 1998;
Tien, Roth and Kampmeier, 2002).
Most of the studies mentioned above are aimed at the undergraduate level or in a
few cases they are oriented on the Masters level. During our work with (international)
PhD students we have experienced numerous challenges. The purpose of this paper is to
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identify the main challenges with ‘teaching’ PhD students and to explore the underlying
factors.
2. Doctoral education
Research on doctoral education is very limited. The main goal of this paper is to look at
how doctoral students ‘should’ be taught and guided in such a way that they successfully
complete their thesis. This relates to effectiveness of instruction or in other words the
effectiveness of supervision. It also relates to the effectiveness of learning or in other
words how PhD students are learning and what they are doing during their doctoral
education. The literature contains a number of books that give students advice on how to
approach the process of the doctoral program, in particular the writing of the dissertation,
see for example (Bloomberg and Volpe, 2008; Bolker, 1998; Sternberg, 1981). With
more emphasis on independent learning at the doctoral level, these books that provide
advice to students do not come as a surprise. However, they assume that students, once
they read these books, understand the material and are capable of applying it. The
literature covered in the introduction shows that not all students are successful in
undergraduate courses and that this depends upon a wide variety of factors which likely
holds true for PhD students as well.
On the side of the instructor, i.e. the doctoral student supervisor, there is limited
advice on how to supervise. Some of it what is available is similar to the literature that is
available to students. That is, it is practical in nature and for example oriented on how to
help students write the dissertation, see (Caffarrella, 1997; Kamlar and Thomson, 2006).
Again, similar to the student side of things, this assumes that the instructor can follow the
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advice when supervising the doctoral student. It also assumes that the student has the
skills and capabilities to conduct quality PhD research and that it is only a matter of
writing the findings down.
Finishing a doctoral program is more complicated. For example, Smallwood
(2004) suggests that the attrition rate for PhD programs is 40 to 50 percent. This indicates
that in many instances students are not capable, or willing, to finish their doctoral
education. In looking at variables that predict doctoral degree completion (in economics),
Grove and Wu (2007) found that foreign applicants, those with high quantitative and
verbal Graduate Record Examination (GRE) scores, and those with a letter of reference
from a top economist or an active researcher were significantly more likely to complete a
PhD. The prestige of the undergraduate institutions did not strongly predict PhD
completion. Grove, Dutkowsky and Grodner (2007) distinguish three stages in the PhD
program: a theory comprehensive exam, a field comprehensive exam, and completion.
They found that students who pass comprehensive exams have high verbal and
quantitative GRE scores, have a Masters degree, and had a strong prior background in
economics. For the completion, i.e. research phase, strong research motivation and math
preparation were required. Although these findings are insightful, they don’t explain why
these variables predict the outcome of achieving a PhD, or in other words, how it is
connected with the PhD program. For example, it can be hypothesized that quantitative
skills are important because some of the work done during the PhD research requires
these skills but this is not clear, nor is it obvious that people who do not have adequate
skills at the beginning of the program will not be able to catch-up.
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Leshem (2007) describes a tutoring program related to doctoral research. In this
case, she found that most doctoral candidates struggled as they sought to progress from
descriptive to conceptual perspectives on research. May candidates displayed
misunderstandings of the research functions for conceptual frameworks. The article
provides an example that shows a type of comprehension that is necessary for PhD
students and how a particular program has worked on ‘teaching’ doctoral students this
skill. What is missing is why students are having difficulties with conceptual frameworks
and whether certain student characteristics such as for example a high GRE are predictors
for understanding and working with conceptual frameworks. Burton and Wang (2005),
examined whether verbal and quantitative GRE scores and undergraduate grade point
average predict outcomes of graduate school. Outcome measures considered were:
cumulative grade point average, mastery of the discipline, professional productivity, and
communication skills. The latter three were based upon faculty ratings. They found that
GRE scores were positively related to these outcome measures indicating that GRE
scores can be a good tool to include when looking at who is allowed to enter the program.
Again, what this doesn’t show is whether high GRE scores for example mean that PhD
students have better ability to develop conceptual frameworks. A related issue is whether
students need to have skills at the beginning of the PhD program which are then used
during the program compared to learning additional things during the program with the
help of a supervisor. One example is that the measurement of ‘mastery of the discipline’
included a factor ‘ability to structure, analyze, and evaluate problems’. This is measured
at the end of the PhD program but maybe the student already had this ability at the start
(although not measured by the GRE). Another example; if a student has a lower GRE
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score, is it possible that this student can still complete the program? And, if so, does this
require more supervision? More time? Etc. Nilsson and Anderson (2004) find that for
Applied Psychology programs, international students have additional challenges due to
cultural and language differences. The supervisor also plays a role in helping with those
differences. Deuchar (2008) extends the view on PhD supervision. Deuchar (2008)
argues that there are four different supervision styles (laisser-faire, pastoral, directorial
and contractual) and that there is an increasing pressure for a directorial style assuming
that students need support in managing the project but not themselves. Sinclair (2004)
also discusses the issue of supervision. He finds that among other things, ‘hands off’
approaches tend to be associated with slow and non-completion. This may partly be so
because PhD students tend to lack in one or more qualities such as for example
independence and confidence, or the ability to construct and sustain a logical argument
(Sinclair, 2004: 27).
In order to get more insight into how doctoral students ‘should’ be supervised or
what influences their success, this paper will explore a particular PhD program to
determine the challenges with supervision, underlying causes and the influence of
supervision.
3. The educational environment and context
The program under study is a PhD program at a Dutch university that could be classified
as a Research I extensive university in the Carnegie Classification, i.e. extensive research
is conducted and PhD degrees are granted at this university. One of the key requirements
for being granted the PhD degree in the Netherlands is that the candidate shows the
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capability to do independent research. Although programs vary by university and by
discipline, the typical Dutch PhD ‘program’ is differently oriented than in for example
the U.S. The program is officially four years for full time students and does not contain
formal course work but instead has more emphasis on the field research. Comprehensive
theory or field tests such as mentioned by Grove, Dutkowsky and Grodner (2007) are not
included. The All But Dissertation (ABD) stage is also not part of the program.
The program that is considered for this paper is oriented on PhD research projects
in the area of International Management/International Operations (IM/IO). The program
started in 1990 So far, 23 PhD students have successfully completed the program, six
have abandoned the program, and seven are currently enrolled in the program at various
stages of completion. Most PhD students are international students from developing
countries with an emphasis on Indonesia. Entry requirements are that the student has a
Masters degree from a respectable institute. There is no formal check on English
language skills, but this aspect is taken into account on an individual basis by the
proposed supervisor.
Three types of PhD candidates can be distinguished. First, internally funded,
known in the Netherlands as AIOs which can be loosely translated as assistants in
training. In this case they occupy full-time salaried research positions (with a possibility
of spending up to 10% of their time on other activities such as teaching). Second, there
are externally funded positions through a type of research grant. These are known in the
Netherlands as OIOs which can be loosely translated as researchers in training. These are
also paid positions. In these instances the PhD candidates typically are involved in the
grant proposal either by developing it themselves or by working with a faculty member.
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Third, PhD candidates can enroll as a student, i.e. they pay tuition and are not employed
by the university. In general these students are supported by a company in which they are
employed but they may also be ‘general’ students who privately pay for their PhD
education. To avoid confusion, the term candidates will be used in the remainder of this
paper when all three categories are involved. The terms AIO, OIO and PhD student will
be used if the groups are considered separately.
The typical PhD process in the IM/IO program follows three phases. In the first
phase, which should roughly last one year for full-time PhD candidates, the candidate
prepares the research, i.e. conducts a literature review and develops the research design.
In the case of internally funded candidates, i.e. AIOs, the department has already
completed preliminary work in order to get the position funded but the candidate has to
make him/herself familiar with this work and extend the preliminary work. Sometimes a
more or less formal evaluation takes place after the first year to determine whether the
PhD candidate has made sufficient progress. This leads to a decision to continue or
abandon the program. This practice has not been consistent. In the second and third year,
the actual field study takes place. For international candidates this usually occurs in their
home country. Studies have typically followed a case study design where in-depth data
gathering takes place and where in particular differences between business practices in
developing countries are compared with practices and theories from industrially
developed countries. During the fourth and last year, the PhD candidate works on writing
the dissertation. The program is completed with two final steps. First, the draft
dissertation is sent to a committee consisting of internal and external members. These
members are essentially asked one question: is the dissertation of sufficient scientific
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quality to warrant the PhD degree? In other words, at this point it is not a matter of a
dialogue with committee to rephrase text as is more typical in for example the U.S. If the
dissertation is deemed of sufficient quality then the defense occurs where the candidate is
questioned by the committee members for a specific length of time (45 minutes) in a
public session. If successful then the PhD degree awarding ceremony immediately
follows this public defense officially ending the PhD program.
Experiences with the PhD candidates show a mix of outcomes where the intensity
of supervision varies among candidates and the success of candidates varies as well.
Furthermore, a high level of supervision and guidance has not always led to a better
quality of the dissertation. In the following section, exploratory analysis will be
conducted to start analyzing this situation and to look for underlying factors.
4. Exploration of the PhD process
In order to facilitate our thinking about the successfulness of the PhD process a basic
operations viewpoint is taken, i.e. there is an input (the PhD candidate), there is a
transformation process, i.e. the program including training and research, and there is an
output, i.e. a PhD graduate.
Figure 1: PhD process
Candidate characteristics
Transformation process
characteristics
Output characteristics
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4.1 Input characteristics
As found by Grove and Wu (2007) and Grove, Dutkowsky and Grodner (2007), some
candidate characteristics are more likely to lead to successful completion of the PhD
program. Essentially, this means that these candidate characteristics are more likely to
lead to the successful completion of the different activities that take place during the
transformation process (4.3). The different types of activities such as doing theory tests
versus doing a field study such as interviewing may require different skills. Table 1
provides background information on the PhD candidates that finished the program or are
currently enrolled.
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Table 1: PhD candidate characteristics
Country of
origin
Previous degree Time between previous
degree completion and
starting PhD program
Type of position
Indonesia: 10
Netherlands: 3
Tanzania: 3
China: 2
Libya 2
Pakistan: 2
Sudan: 2
Japan: 1
Palestine: 1
South Africa: 1
South Korea: 1
Taiwan: 1
Thailand: 1
MBA: 15
MSc. in Industrial
Engineering &
Management: 11
MSc. in Economics: 2
MSC. in Aeronautics: 1
1 year: 7
2 years: 6
3-5 years:13
6-10 years: 3
11 years or more: 1
Average: 4.5
AIO: 8
OIO: 9
Student with
company
support: 8
Student without
company
support: 4
4.2 Output
The two key requirements for completing the PhD program, i.e. outputs for an individual
candidate, are that the dissertation needs to be of sufficient quality and that the candidate
should show the ability to conduct independent research. In addition, it is also possible to
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take a broader viewpoint and look at the program overall such as how many candidates
complete the program, i.e. program effectiveness, and how long it took them to complete
the program, i.e. program efficiency. Ultimately, the committee members evaluate the
scientific quality of the dissertation and independence of the candidate. Although the
compositions of the committees are variable, in general the scientific evaluation can be
deemed fairly consistent due to peer contacts. The assessment of a PhD candidate’s
independence relies perhaps more on the internal committee members. It can be
measured by looking at, among other things, the frequency of the supervision contacts.
As these contacts are recorded, for example in e-mail exchanges or minutes of meetings
(including the issues concerned), a fairly sound judgment can be made. Table 2 shows
how quickly the 23 candidates finished the program.
Table 2: Time to complete
Full time students 3 years: 1
4 years: 13
5 years: 6
6 years: 1
Part time students 5 years: 1
9 years: 1
Insufficient skills were not a main reason for candidates to drop out of the program. The
main reason for not completing the research was their inability to combine part time
research with a (demanding) job. A second factor was health related reasons and a third
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factor was the inability to raise continued financial support, e.g. when the project was
started only support for limited time was secured, and now follow up could not be found.
4.3 Transformation process
The transformation process relates to activities that the candidates have to do and learn
during their time in the PhD program that will eventually lead to the two output
characteristics i.e. scientific quality and independent working. This process can be
described in three phases with a preliminary phase as identified earlier. Each of these
phases places different demands on the PhD candidate.
Figure 2: Phases in the PhD process
The preliminary phase is where initial ideas for the research are formed. This may or may
not include the PhD candidate. For example in the case of AIO positions, the department
does these initial investigations. The end of this phase is when a proposal to do research
on a topic is approved.
The preparation phase is a phase in which the PhD candidate works on developing
a more detailed research design. This requires that the candidate conducts a literature
review, i.e. find and read literature, on the substantive area under research as well as on
methodology. It also requires that the candidate comprehends the substantive literature
and can develop a conceptual model or framework and that he/she comprehends the
Preliminary phase
Field study Dissertation writing and
defense
Preparation
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methodology and apply it by developing the research questions and approach to do the
field-study such as for example the development of a case study protocol. This frequently
requires that the candidate can work on the substantive area and on methodology
simultaneously. This phase ends when the research design is approved.
The second phase is the field study. This means that the design as developed in
the first phase is now being implemented by contacting companies. Once companies are
contacted data collection needs to take place through interviews, documents and
observations. Each of these requires that the candidate receives cooperation from the
companies and can collect the required information such as for example conduct an
appropriate interview. In case studies, frequently data collection and analysis take place
simultaneously and the candidate needs to be able to draw conclusions and direct what
type of data to collect next based on previous findings. This phase ends when all case
studies are completed and reports for each case study are written. This phase in particular
requires that the candidate has good personal skills, has self-confidence to contact
companies and discuss issues with frequently high ranking managers, has analytical skills,
writing skills, and is attuned to the emerging issues in the cases.
In the last phase, the data is brought together and the dissertation is completed.
This phase ends with the public defense. This phase in particular requires that the
candidate can oversee a large complex document (typically several hundred pages), can
align the different cases and present them in similar ways, and be aware of
inconsistencies. Of course it requires written and to a lesser degree verbal communication
skills as well.
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5. Challenges and supervision
Our experiences over the years indicate that the main challenges encountered with the
supervision of PhD candidates are related to the following PhD candidate characteristics:
• Insufficient independent development of a sound conceptual model/framework that is
sufficiently based on previous research (literature). This relates to the PhD
candidates’ analytic and synthesis skills to use the existing theoretical base, i.e.
literature, and combine this in a conceptual framework. Or, in other words, the ability
to develop an overview of the main variables, their relationship and find what has
previously been reported on those variables and how these relationships were
previously measured and what types of assumptions were made in those
measurements and what that means for the candidates research. This can also be
viewed as critical thinking skills. We find that if PhD candidates do not possess these
skills when they enter the PhD program, then these students will require more
supervision and guidance. However, even with a lot of supervision and guidance,
these skills are very slow to develop. If for example an article is discussed in-depth to
point out the assumptions and to discuss the implications, then in many instances this
is not transferred by the PhD candidate to the next article that is being read. In other
words, the same issues keep coming up in the supervising process.
• Lack of scientific rigor both in the set up as in the execution of the research work.
This relates to the ability to ‘think scientifically’. In particular, this relates to the
ability to develop appropriate research questions and in particular operationalizations
for these research questions, i.e. the design of the measurement, as well as conducting
the actual measurement such as by asking the right questions in an interview and/or
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following up with the right questions in case open interview questions are being used.
This, again has something to do with critical thinking but also with being able to think
logically and being able to ‘read between the lines’.
As an example of the latter, Yin (1994) is often used by the PhD candidates in
explaining the case study research design. In some cases, PhD students will have
contacts with one particular company and therefore have at the outset the explicit
plan to do research in only one company. Yin (1994) compares case studies with
experiments. In other words, you do an experiment (case study) to find out how
certain concepts are related to each other or how they influence each other. As
with an experiment, doing this once isn’t enough. In order to gain confidence in
the findings you want to replicate findings and this can be done by either doing an
experiment (case study) where you have a similar set up so that you would expect
similar findings, or by doing an experiment (case study) where you have specific
differences in the set up so that you would expect specific different findings. So,
the overall goal is to normally conduct multiple cases. Yin (1994: 38) explains
that single case studies can also be sufficient. He gives three reasons. First, if it is
a critical case. This is the situation when a well formulated theory with clear
propositions and circumstances etc. that can serve to test the theory with all of its
conditions, or in other words, a full-fledged test of something with all of its
comprehensive conditions in place. A second reason is if it is an extreme or
unique case, or in other words an outlier which extends thinking on the more
extreme situations. A third reason is if it is a revelatory case, or in other words
when something can be investigated that has not been available before. In each of
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these three situations, the underlying mechanism of experiments still holds true
but they are in a way ‘exceptions’. In the first case it is a comprehensive
experiment covering many aspects to kind of be able to draw ‘final’ conclusions.
In the second case, it is an experiment of an extreme situation where the
boundaries are tested. In the third case, it is an experiment in a new area. What we
sometimes find with in particular the PhD students who come in with the idea of
doing research in one company is that they will refer to Yin’s third reason (1994:
40) “This situation exists when an investigator has an opportunity to observe and
analyze a phenomenon previously inaccessible to scientific investigation”. They
argue that their particular company was previously not accessible and therefore
this third reason applies. However, this argument misses the scientific thinking
that underlies the thinking about cases and the analogy with experiments. That
particular company may not have been studied before but similar companies with
similar conditions may have been studied before and scientific theories may
already exist that explain these situations and therefore there would be no need to
do the case study (in that case it is possible to develop broader theories and then
use the first argument, critical case, but this possibility typically does not occur to
this type of PhD student).
These challenges may occur due to insufficient previous education and/or a lack of
language skills. We find that supervising and guidance can ‘fix’ the situation, i.e.
discussions are held so that the situation gets addressed, but the underlying causes
(lack of scientific thinking or lack of comprehension) are not taken away and will
show up again, i.e. it requires constant attention from supervisors.
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• Another challenge that occurs is that some PhD candidates have limited skills in
‘translating’ what they find in the literature to the real life industry situations. This
may occur more frequently with candidates who have limited work experience and
have difficulty with envisioning how what they read applies or occurs in real life
industry situations. This problem occurs in the first phase of the PhD process but
often once the candidates start their field study they ‘see the light’. For supervision
this means two things. On the one hand, during the first phase it means explaining to
PhD candidates how companies work to give the PhD candidate some deeper sense of
the literature. On the other hand, it also relates to when a candidate gets confronted
with the field. For example, it is possible to do a small exploratory study so that the
PhD candidate gets a sense of industry and companies but if this exploration is very
short, it might not help much.
• The flipside of the previous difficulty is an inability to apply/maintain scientific rigor
in the fieldwork or in other words to ‘translate’ the methodology literature into the
industry situation. This problem is more often faced by PhD students who have had
long working experience and know and understand how companies function but now
have to apply scientific standards.
For example, based upon their years of experience, they may ‘know’ that a
concept relates to or influences another concept. However, from a scientific
standpoint, the issue is: how do you know? And, related to that, how do you
measure this? And, how do you know that this measure is correct? In industry
there is no time to always delve into this level of detail and specificity but it is at
the core of scientific research.
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From a supervisor perspective, this often means that much time is devoted in the
guidance on discussions related to operationalization of concepts and the research
design, i.e. the first phase. However, it then sometimes is challenging as well for the
PhD candidates to maintain this level of rigor while they are doing their field study.
This is especially the case because in field study situations respondents or informants
have a tendency to point out new things or highlight what they find interesting which
isn’t necessarily the same as what the study is trying to achieve. It then becomes a
challenge to stick to a case study protocol with its questions and to stick to the
specific operationalizations. In some instances we have found that the data that was
collected in the field did not match with the initial research design. Most of the time
this then resulted in adjustments in the last phase of the PhD process to realign the
research design with collected data.
• Some PhD candidates are struggling due to insufficient skills in multitasking. This is
especially prevalent in the first phase of the research which requires a constant
circling between the substantive literature and the methodology literature and fine-
tuning the research design. Although it is possible to survive the first phase without
much multitasking, it makes this phase last longer because the student gains
understanding on the connection of methodology and substantive area at a much
slower pace.
• Lastly, one observation is that a number of PhD candidates have shown problem
avoiding behavior when theoretical or practical obstacles are encountered.
As an example, we may have a meeting with a PhD candidate to discuss the
research design. In this meeting, some of the problems of the design may be
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pointed out. For example, it may appear that the logic and arguments for the
specific operationalization of a concept is too weak or that the literature used for
developing this operationalization contains assumptions that were not taken into
consideration by the PhD candidate. The point of the meeting, from the
supervising standpoint, is that the PhD candidate becomes aware of the pros and
cons and the message is in this case is often that the PhD candidate has to delve a
little deeper. In other words, the candidate is on the right track, but needs to be
more careful in how things are worded or how conclusions are drawn. What we
find is that instead of fixing the situation and delving deeper some PhD candidates
will drop the entire line of thinking. Eventually, this almost never works because
when they take another route, the same issues usually pop-up. Consequently, this
type of behavior from PhD candidates slows their progress.
The challenge from a supervisory standpoint is that on the one hand PhD candidates have
to work independently and therefore should be given the freedom to adjust research
design and variables and relationships that they find interesting to research. On the other
hand, continuous switching of research topics or angles leads to a perpetual process
without end. At some point therefore the supervisor has to end this cycle, ‘freeze’ the
research design and ‘force’ the PhD candidate to delve into the details. When this
decision is made depends upon the circumstances, the candidate etc. The supervision
style difference between ‘laisser-faire’ and ‘directorial’ (Deuchar, 2008) or ‘hands-on’
versus ‘hands-off’ (Sinclair, 2004) plays a role as well and obviously affects the speed
with which PhD candidates go through the process.
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6. Conclusions
In this paper an exploratory analysis of the PhD process has been provided. Although
literature on teaching and learning exists, the number of studies on PhD education is very
limited. To organize our thinking we used a basic input-transformation-output model in
which the transformation process was divided into a preliminary phase followed by three
distinct phases. These phases apply in a particular PhD program in International
Management/International Operations in the Netherlands which may not be
representative to all PhD programs and is different from typical U.S. PhD programs
which have formal course work as part of the requirements.
Our analysis shows that the demand placed on PhD candidates are different in the
three different phases of the PhD process. Some of the main challenges with the PhD
process are identified and the influence of supervision has been discussed in the context
of the time it takes to complete the PhD as well as whether problems appear systemic or
not (supervision might ‘fix’ a particular issue but not remove the underlying cause).
Based on the experiences and success of the indicated research population we reach the
following conclusions:
The intensity of the supervision is inverse related to the quality of the research
and the time required for completion. That means, the highest quality dissertations
require the least supervision. Students who score relatively high on ability to analyze,
synthesize and evaluate and reflect do better. Students who are weak in these areas can
reach some improved performance by extensive guidance, but a number of the required
skills are hardly influenced by the supervision process. This means that the overall
quality result, i.e. dissertation quality, remains weak. Furthermore, since the IM/IO PhD
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program had an established nominal time but not a fixed time termination point, the weak
scoring students who are persistent were able to complete the process but they required
considerable overruns of the nominal time.
Similar conclusions are reached for the relationship between time to completion
and time required for supervision. Those students that need the longest time also required
the most supervision. An exception for this is the category of PhD students who have
extensive business experience. In general these PhD students require extremely long
completion times. However, they shun from supervision, as they hold the opinion that
they do not need it. This is incorrect, but they implicitly accept the long PhD completion
time.
Dissertations of the highest quality are achieved by students who are intrinsically
motivated by the subject, rather than being motivated because they simply want to obtain
the PhD degree.
Although to be admitted to the PhD program the PhD candidate needs a master
degree from a respected institute of learning, there are significant differences in the
attention given to methodological research aspects in the different degrees. Student who
graduate from institutes with less emphasis on those aspects, tend to have great
difficulties to close the gap. This is especially the case because the IM/IO PhD program
did (does) not have the facilities to compensate for this as it was (is) implicitly assumed
that the students already possess these skills.
The ability to apply multitasking shortens the completion times considerably.
24
References
Beatty, I. (2004), ‘Transforming student learning with classroom communication
systems’, Educause Research Bulletin, vol. 3, no. 3, pp. 2-13. Available at
http:www.educause.edu/ir/library/pdf/ERB0403.pdf.
Biggs, J. (1999), ‘What the student does: teaching for enhanced learning’, Higher
Education Research & Development, vol. 18, no. 1, pp. 57-75.
Billington, P.J. (2008), ‘Impact of student attendance on course grades’, Journal of
American Academy of Business, vol. 12, no. 2, pp. 256-262.
Bloomberg, L.D. and Volpe, M. (2008), Completing your qualitative dissertation: a
roadmap from beginning to end, Sage Publications, Thousand Oaks, CA.
Bolker, J. (1998), Writing your dissertation in fifteen minutes a day, A guide to starting,
revising, and finishing your doctoral thesis, Henry Holt and Company, New York.
Boyer, E.L. (1990), Scholarship reconsidered, Priorities of the professoriate, The
Carnegie Foundation for the Advancement of Teaching, New York.
Brothen, T. and Wambach, C. (2001), ‘Effective student use of computerized quizzes’,
Teaching of Psychology, vol. 28, no. 4, pp. 292-294.
Bryson, C. and Hand, L. (2007), ‘The role of engagement in inspiring teaching and
learning’, Innovations in Education and Teaching International, vol. 44, no. 4, pp.
349-360.
Burton, N.W. and Wang, M.M. (2005), Predicting long-term success in graduate school:
a collaborative validity study, GRE Board Report No. 99-14R, Educational Testing
Service, Princeton (NJ).
25
Caffarrella, R.S. (1997), Teaching doctoral students writing: negotiating the borders
between the world of practice and doctoral study, University Council for Educational
Administration, Columbus (OH).
Carnaghan, C. and Webb, A. (2007), ‘Investigating the effects of group response systems
on student satisfaction, learning and engagement in accounting education’, Issues in
Accounting Education, vol. 22, no. 3, pp. 391-409.
Chamorro-Premuzic, T., Furnham, A. and Lewis, M. (2007), ‘Personality and approaches
to learning predict preference for different teaching methods’, Learning and
Individual Differences, vol. 17, pp. 241-250.
Collier, P.J. and Morgan, D.L. (2008), ‘ “Is that paper really due today?”: differences in
first-generation and traditional college students’ understandings of faculty
expectations’, Higher Education, Vol. 55, pp. 425-446.
Deuchar, R. (2008), ‘Facilitator, director or critical friend?: contradiction and congruence
in doctoral supervision styles’, Teaching in Higher Education, vol. 13, no. 4, pp. 489-
500.
Durden, G.C. and Ellis, L.V. (1995), ‘The effects of attendance on student learning in
principles of economics’, The American Economic Review, vol. 85, no. 2, pp. 343-
346.
Entwistle, N. and Tait, H. (1990), ‘Approaches to learning, evaluations of teaching, and
preferences for contrasting academic environments’, Higher Education, vol. 19, no. 2,
169-194.
26
Flamm, P., Hoffman, J.J., Delgadillo, F. and Ewing, B.T. (2008), ‘A hybrid approach for
teaching introduction to operations management’, International Journal of
Information and Operations Management Education, vol. 2, no. 3, pp. 255-274.
Felder, R.M. and Spurlin, J. (2005), ‘Applications, reliability and validity of the index of
learning styles’, International Journal of Engineering Education, vol. 21, no. 1, pp.
103-112.
Fox, A. and Stevenson, L. (2006), ‘Exploring the effectiveness of peer mentoring of
accounting and finance students in higher education’, Accounting Education: an
international journal, vol. 15, no. 2, pp. 189-202.
Grimstad, K. and Grabe, M. (2004), ‘Are online study questions beneficial?’, Teaching of
Psychology, vol. 31, no. 2, pp. 143-146.
Grove, W.A., Dutkowsky, D.H. and Grodner, A. (2007), ‘Survive then thrive:
determinants of success in the economics Ph.D. program’, Economic Inquiry, vol. 45,
no. 4, pp. 864-871.
Grove, W.A. and Wu, S. (2007), ‘The search for economics talent: doctoral completion
and research productivity’, American Economic Review, vol. 97, no. 2, pp. 506-511.
Handelsman, M.M., Briggs, W.L., Sullivan, N. and Towler, A. (2005), ‘A measure of
college student course engagement’, The Journal of Educational Research, vol. 98,
no. 31, pp. 184-191.
Hudak, M.A. and Anderson, D.E. (1990), ‘Formal operations and learning style predict
success in statistics and computer science courses’, Teaching in Psychology, vol. 17,
No. 4, pp. 231-234.
27
Kamler, B. and Thomson, P. (2006), Helping doctoral students write, Pedagogies for
supervision, Routhledge, New York.
Kibble, J. (2007), ‘Use of unsupervised online quizzes as formative assessment in a
medical physiology course: effects of incentives on student participation and
performance’, Advances in Physiology Education, vol. 31, pp. 253-260.
Koppenhaver, G.D. (2006), ‘Absent and accounted for: absenteeism and cooperative
learning’, Decision Sciences Journal of Innovative Education, vol. 4, no. 1, pp. 29-49.
Kulick, G. and Wright, R. (2008), ‘The impact of grading on the curve: a simulation
analysis’, International Journal for the Scholarship of Teaching and Learning, vol. 2,
no. 2.
Leshem, S. (2007), ‘Thinking about conceptual frameworks in a research community of
practice: a case of a doctoral programme’, Innovations in Education and Teaching
International, vol. 44, no. 3, pp. 287-299.
Libarkin, J.C. and Mencke, R. (2001), ‘Students teaching students, Peer training in
undergraduate education’, Journal of College Science Teaching, vol. 31, no. 4, pp.
235-239.
Loo, R. (2002), ‘The distribution of learning styles and types for hard an soft business
majors’, Educational Psychology, vol. 22, no. 3, pp. 349-360.
Maki, W.S. and Maki, R.H. (2001), ‘Mastery quizzes on the web: results from a web-
based introductory psychology course’, Behavior Research Methods, Instruments &
Computers, vol. 33, no. 2, pp. 212-216.
Martyn, M. (2007), ‘Clickers in the classroom: an active learning approach’, Educause
Quarterly, vol. 30, no. 1, pp. 71-74.
28
McGee, C.D. (2001), ‘Calming fears and building confidence: a mentoring process that
works’, Mentoring & Tutoring, vol. 9, no. 3, pp. 201-209.
Mukherjee, A. (2002), ‘Improving student understanding of operations management
techniques through a rolling reinforcement strategy’, Journal of Education for
Business, July-August, pp. 308-312.
Nilsson, J.E. and Anderson, M.Z. (2004), ‘Supervising international students: the role of
acculturation, role ambiguity, and multicultural discussions’, Professional
Psychology: Research and Practice, vol. 35, no. 3, pp. 306-312.
Rubin, L. and Hebert, C. (1998), ‘Model for active learning, Collaborative peer teaching’,
College Teaching, vol. 46, no. 1, pp. 26-30.
Samuelowicz, K. and Bain, J.D. (2001), ‘Revisiting academics’ beliefs about teaching
and learning’, Higher Education, vol. 41, no. 3, pp. 299-325.
Sinclair, M. (2004), The pedagogy of ‘good’ PhD supervision: a national cross-
disciplinary investigation of PhD supervision, Commonwealth of Australia, Canberra.
Smallwood, S. (2004), ‘Doctor dropout’, The Chronicle of Higher Education, Vol. 50, no.
19, pp. A-10.
Steenhuis, H.J., Grinder, B. and de Bruijn, E.J. (2009), ‘Measuring student learning over
time with clickers in an introductory operations management course’, International
Journal of Information and Operations Management, Forthcoming.
Sternberg, D. (1981), How to complete and survive a doctoral dissertation, St. Martin’s
Press, New York.
Sternberg, R.J. and Grigorenko, E.L. (1995), ‘Styles of thinking in the school’, European
Journal for High Ability, vol. 6, pp. 201-219.
29
Sternberg, R.J. and Grigorenko, E.L. (1997), ‘Are cognitive styles still in style?’,
American Psychologist, vol. 52, no. 7, pp. 700-712.
Tait, H. and Entwistle, N. (1996), ‘Identifying students at risk through ineffective study
strategies’, Higher Education, vol. 31, no. 1, pp. 97-116.
Tien, L.T., Roth, V. and Kampmeier, J.A. (2002), ‘Implementation of a peer-led team
learning instructional approach in an undergraduate organic chemistry course’,
Journal of Research in Science Teaching, vol. 39, no. 7, pp. 606-632.
Trigwell, K., Prosser, M. and Waterhouse, F. (1999), ‘Relations between teachers’
approaches to teaching and students’ approaches to learning’, Higher Education, vol.
37, pp. 57-70.
Umble, E.J., Umble, M. and Artz, K. (2008), ‘Enhancing undergraduates’ capabilities
through team-based competitions: the Edward Jones challenge’, Decision Sciences
Journal of Innovative Education, Vol. 6, No. 1, pp. 1-27.
Whittingham, K.L. (2006), ‘Impact of personality on academic performance of MBA
students: qualitative versus quantitative courses’, Decision Sciences Journal of
Innovative Education, Vol. 4, No. 2, pp. 175-190.
Yin, R.K. (1994), Case study research: design and methods, second edition, Sage
Publications, Thousand Oaks (CA).
Yourstone, S.A., Kraye, H.S. and Albaum, G. (2008), ‘Classroom questioning with
immediate electronic response: do clickers improve learning?’, Decision Sciences
Journal of Innovative Education, vol. 6, no. 1, pp. 75-88.
