Teaching Statistics to Adult Learners 1 Teaching Statistics to Mid-Career Adult Learner Graduate Students in Public Administration and Public Health Programs A Modified Innovative Paradigm By Michael W. Popejoy, M.B.A., Ph.D., M.P.H., M.S. Fellow, Royal Society for Public Health (UK) Adjunct Professor of Public Health Department of Health Promotion and Disease Prevention Robert Stempel School of Public Health and Social Work Florida International University Miami, Florida, USA And Associate Graduate Faculty MSA Program in Research Administration Clinical Research Administration Global Campus Central Michigan University Mt. Pleasant, Michigan USA Charlotte, North Carolina, USA May 2013 Abstract This paper presented to the Roundtable Discussion Session at the Annual Great Lakes Conference on Teaching and Learning at Central Michigan University in Mt. Pleasant, Michigan reports the results of an experimental course developed to teach a modified statistics course to a small cohort of
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Teaching Statistics Without Mathematics An Innovation Approach to Public Administration Education
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Teaching Statistics to Adult Learners 1
Teaching Statistics to Mid-Career Adult Learner Graduate Students in Public Administration and Public Health Programs
A Modified Innovative Paradigm
By
Michael W. Popejoy, M.B.A., Ph.D., M.P.H., M.S.Fellow, Royal Society for Public Health (UK)
Adjunct Professor of Public HealthDepartment of Health Promotion and Disease PreventionRobert Stempel School of Public Health and Social Work
Florida International UniversityMiami, Florida, USA
And
Associate Graduate FacultyMSA Program in Research Administration
Clinical Research AdministrationGlobal Campus
Central Michigan UniversityMt. Pleasant, Michigan USA
Charlotte, North Carolina, USAMay 2013
Abstract
This paper presented to the Roundtable Discussion Session at the Annual Great Lakes
Conference on Teaching and Learning at Central Michigan University in Mt. Pleasant,
Michigan reports the results of an experimental course developed to teach a modified
statistics course to a small cohort of adult (mature) graduate students in public
administration. These students were mid-careerists in administrative or management
positions in the public sector with an average of 15 to 20 years of experience each. The
theme of the course, and this paper, is on whether or not statistics can be taught
successfully with minimal mathematical applications while emphasizing statistical
Teaching Statistics to Adult Learners 2
analysis interpretation leading to better informed administrative and managerial decisions
in public sector organizations. The limited sampling frame notwithstanding, the cohort
reported a high degree of satisfaction with the modified course, and reflected their belief
that the modified course would help them understand statistical data and knowledge
related specifically to understanding statistical analysis. Further, the students reported
that in the years spent in their careers, none had been mandated to undertake on-the-job
studies requiring them to perform statistical analysis themselves; rather they saw
themselves as consumers of statistical reports and needed more exposure in how to read
and interpret them. An untested frame is whether or not students retained knowledge
longer when the course was presented with minimal mathematical formulas and formula
problem solving. However, despite the potential controversy, a change in curriculum
content and teaching methodology is recommended due to the desired end result which is
to provide mid-career administrators with immediate information that can support
decisions and learning that could endure over time. This new approach supports the
primacy of practice over theory as it may relate to specific cohorts of students—the adult
learner in mid-career management and administrative positions in the public sector who
generally are not considering doctorate studies.
Introduction
Statistics can arrive in two sets of clothes: one is applied mathematics and the other as
applied information for decision makers. For the mathematician/statistician, it is all about
the process (statistical analysis) of arriving at an answer based on collected raw data and
application of appropriate statistical analysis procedures based on currently accepted
statistical theory. For the decision maker, it is more about using the end product of
Teaching Statistics to Adult Learners 3
statistical analysis, the output of the process, to arrive at a satisfying outcome—a well
grounded decision based on the best evidence.
In pedagogy, one has to close the gap between what the statistician does and what the
decision maker needs. If the decision maker has confidence in the work of the statistical
analyst, then the painful details of the “theoretically correct” process is not needed, and
indeed, may not be well understood anyway; and, the analytical details may complicate
further an already complex decision. The decision maker needs an answer to the raw
quantitative data collected, and a clearly understandable interpretation in order to inform
the decision. Although, once data is collected and analyzed appropriately, even the
interpretation may be left up to the decision maker if people in those positions are well
prepared to understand and interpret statistical output.
For instance, an SPSS (Statistical Program for the Social Sciences) output page(s)
with graphics should be enough information for the decision maker to interpret how the
raw data was handled and what decisions may be reliably made from the analysis. How
much is it necessary for the decision maker to know what data was collected, how it was
collected, how it was analyzed if he/she knows how to interpret the output and has
confidence in the skill of the analyst in developing the study plan? Does the decision
maker need to be well grounded in the mathematical formulae underlying the computer
printouts? Further, the decision maker can partner with the statistician in assisting with
what outcomes are desired in terms of the input data needed. Indeed, in many statistics
textbooks, the authors often advise students confronted with complex statistical tasks to
consult with a statistician first before proceeding with a research plan (Neill, 2008;
Rosner, 2006; Tabachnick and Fidell, 2001).
Teaching Statistics to Adult Learners 4
In the training of adult, mid-career, administrative graduate students, who are most
often already well established in their careers as public decision makers, the faculty focus
may be too often on the process, and too seldom on how the results of the process will be
utilized. Indeed, the training and background of the faculty teaching statistics may be the
determining factor in how graduate courses are taught—applied mathematics statisticians
will most likely focus on process (equations and the mathematics process), whereas the
applied decision maker will most likely focus on interpretation of the analytical outputs
allowing the computer program to crunch the numbers based on the data collected by the
analyst (Hawk and Shaw, 2007 citing Merriam and Caffarella, 1999; Noddings, 1998).
Hawk and Shaw (2007) write, “We believe that most faculty in higher education
initially adopt a teaching style that merges (1) the ways they prefer to learn and (2)
approaches to teaching they saw as effective for their own learning in higher education
programs” (p.1). Consequently, Hawk and Shaw propose that the faculty either are
unfamiliar with learning style methods or are uncomfortable experimenting with learning
styles other than their own preference because it “takes them out of their own comfort
zone” (p.1).
It is possible that the mathematical processes are continuing to be taught both in the
classroom and in the textbooks mainly because the current generation of textbook writers
and university faculty learned statistics themselves prior to the development of
sophisticated computer programs that do all the hard, time consuming computational
work. Teachers may teach the way they were taught (the old school) rather than adapting
their pedagogy to the new demands of modern administrative managers, and the tools that
are now available as desktop decision support systems.
Teaching Statistics to Adult Learners 5
The question of the pedagogical approach in the curriculum may focus on whether it is
critical or how important it is to the quality of the decision that the decision maker must
comprehend the exquisitely complex mathematical processes when in reality it is the
outcome of the decision that is most important to the decision maker in public
administration (and public health). Are we emphasizing the wrong things for the wrong
audience based on what that particular audience may need? Are we emphasizing the
wrong things based on how today’s teachers were taught by yesterday’s teachers?
Another issue of consideration in graduate education is how long, once learned, will
the detailed statistical analytical (mathematical formula based) processes be retained by
decision makers who are not normally expected to perform the analysis themselves as
part of their daily responsibilities? “Use it or lose it” is the old adage about retention.
Would it be more probable that decision makers, who are not analysts working daily with
the numerical aspects of analyses; retain more of some ideas of interpretation longer than
they would the mathematical processes that they do not use and have not seen since
sweating out the required graduate course?
This paper shows that exposing a modified statistics curriculum of applied statistics
utilizing minimal mathematics to a graduate class for public administrators, through an
informal survey, it was revealed that 100 percent of the students were mid-career to upper
level decision makers (managers/administrators) in their public organizations who used
statistical information frequently but were never expected to do the analysis themselves.
Some of these student objections may be based on math phobia or simply inadequate
mathematics background; however, the more significant objections seem to come from
adult learners who simply do not believe in wasting time learning techniques, processes,
Teaching Statistics to Adult Learners 6
or theories that are of not an immediate benefit to their educational goals based on their
occupational requirements. When the focus of the course is directly related to the above,
adult student acceptance of the course rises significantly; as does faculty evaluations.
So, are we teaching the wrong things to the wrong groups under the guise of requiring
“tools” courses for academic programs designed for public administrators? This paper
adds some modest support to a curriculum reevaluation of how statistics are presented to
decision makers as compared to how they would be presented to students planning on
becoming statistical analysts.
One aspect of how these courses are presented that is not being considered in this
paper is the probable fact that some courses are held out to be “gatekeeper” courses that
in a sense serve to wash out students who cannot gain sufficient knowledge of the
material (such as mathematics) to make a passing grade in a required course for the
degree. This particular feature of a graduate program then lies with faculty preferences
and prejudices, not pedagogical methodology best serving theory.
Pedagogy on Adult Education
It is important to distinguish between teaching methodology that works well for young
people (with virtually no professional managerial or administrative work experience from
which to draw upon) and what works well for the adult learner who is returning to school
for advanced education or continuing education directly related to career retention and/or
advancement. Most adult learners are either changing careers or are expecting to advance
in careers that they already have attained a certain level – usually the mid-career level.
Teaching Statistics to Adult Learners 7
Most of these adult learners are already successful and are interested in earning the
highest grades in courses they feel offer relevant work-related and/or life-related content.
They are less interested in theory or theory building foundations that are at best only
remotely related to their goals for returning to school. The rigors of theory take a back
seat to applied concepts. The exception, of course, may be the adult learner in a doctoral
program. The very nature of a doctoral program is designed to be grounded in theory,
advance theory through original research, push new paradigms, and learn research design
and analytical techniques to prepare the student for careers in research and/or academia.
However, the far majority of masters’ students are not potentially future professors or
researchers—they are being trained as decision makers in the applied sense and they need
information they can use tomorrow at work. Consequently, all course work for these
students needs to focus on adapting the theoretical foundations of any subject into an
applied context that adult students can relate to and use in their current and/or future
careers. But, how many professors can claim directly related work experience in the
fields they teach?
The expectations these adult students bring to the classroom are quite different than
that experienced in teaching younger students. Some of these differences may be
attributed to generational differences, and others may be more related to the stage in their
careers, and what they are seeking in terms of new knowledge that would be directly
related to their immediate work environments. Adult students want to get results from the
substantial investment in time (from both family and work) and money that they make to
return to school, usually for a graduate degree in management or administration (MBA,
MHA, MPA, MPH, MSN in administration, etc.).
Teaching Statistics to Adult Learners 8
This is possibly why at the University of Phoenix, courses are called workshops, and
professors are called facilitators, and the facilitators, although required to hold doctorates,
are also required to have significant occupational experience in any field they teach so
that the workshop discussions can be focused to a limited degree on theory that is broadly
applied to practice more intensely rather than what is often the opposite approach taken at
a research university.
There is little pretense in formal adult education that the adult student is interested in
studying, in depth, why something works the way it does, rather, they simply want to
know how to apply what works in their immediate work environments. So, the role of the
facilitator is to facilitate that application of theory to practice in concert with the adult
student-participants in the workshop.
In teaching statistics to adult learners, they may well ask “why do I need to do the
mathematics when I have a computer that will crunch the numbers and provide me with
output that then I can make a decision?” Further, “why can’t I just ask my staff
statistician to work out the details and send me a bullet report that I can be trained to
understand?” Traditional statistics teachers may counter that it is better and safer to know
the theory behind a process than just being an “operator.”
Unhappily for traditional statistics teachers is that the adult learner is less interested in
how to do statistics than in what statistics can do for them. Many statistics textbooks
today recognize the ease of doing the computations with computers, yet insist that
everyone should learn the basics by working out the formulas by hand so that they can
gain a “deeper” understanding of statistical analysis (Neil, 2008). This deeper level of
understanding is not what is being demanded by today’s adult learner who is seeking an
Teaching Statistics to Adult Learners 9
expedient application of any technique being taught. They then perceive whether or not it
is worth their investment in time and money to take the course and this is based on what
is in it for them—immediately. Tabachnick and Fidell (2001) argue in an earlier edition
of their textbook, Using Multivariate Statistics that you can be taught to skillfully drive a
car without necessarily knowing all that is going on under the hood.
This approach to teaching and learning is also the same when teaching in a research
university’s off campus compressed time format graduate degree programs such as
Central Michigan University’s College of Extended Learning which offers an MPA
degree among others. These specialized programs that are restricted to adult learners
attract the same adult learner with the same goals and motivations as does the
nontraditional graduate degree programs such as those offered at the University of
Phoenix and Strayer University; among a host of others.
As more universities are beginning to offer off campus programs and online programs
(due to excessive demand from students and due to the attractiveness of these programs
financially to universities competing for enrollment) attracting a different student than the
more traditional on campus programs tend to attract; the curriculum, and the faculty who
choose to teach in these new formats must face some challenges in modifying the
curriculum content, pedagogical approach and methodology to meet the demands and
goals of this new category of student.
These same students, who will likely be reluctant to invest their time and money in a
degree program that does not meet their needs, even if the program does meet the needs
of other types of students; and by the way, specifically meets the needs of faculty who are
entrenched in teaching the way they were taught. Further, it is unlikely that the traditional
Teaching Statistics to Adult Learners 10
faculty will be satisfied with negative student evaluations of their teaching, and of their
course content, when they continue to fail to understand and adapt to this new category of
student.
If we need to question a change in how courses are delivered, based on student
demand, we need only ask why University of Phoenix alone enrolls 345,000 students
(Wasley, The Chronicle of Higher Education, August 8, 2008. p.A1). And, Central
Michigan University’s College of Extended Learning is a significant cash cow for the
university as is most all adult learning programs are to their parent universities. Indeed,
some adult learner programs, such as the graduate programs (MBA, MHA, MBA/MHA,
and MSL) at Pfeiffer University in Charlotte, North Carolina, subsidize their parent
institution offering traditional degree programs to such an extent that the parent campus
would cease to exist quickly without the adult degree programs student enrollment
revenues (personal communication, Dr. Joel Vikers, Dean Inis Gibbs, 2007).
The annual budget at Pfeiffer University absolutely depends on sufficient enrollment
of adult learners in their Adult Studies Program (undergraduate) and their Graduate
Program, not the enrollment on main campus (where the traditional undergraduate
students attend) (personal communication, Dean Inis Gibbs, 2007).
So, given the financial imperatives created by this new student demand, and given the
faculty evaluations from students, it is important that curriculum content changes and
changes in how courses are taught are going to be increasingly necessary for university
programs to remain competitive, indeed in some cases to survive. And, given the
decreasing levels of financial support from both state and Federal sources, it is even more
Teaching Statistics to Adult Learners 11
important for the traditional research universities to seek out the adult learner student
base and strive to meet their unique needs.
The pedagogical or teaching methodology changes being suggested in this paper can
be applied to the entire curriculum in general, but specifically, this paper concentrates on
how statistics is being taught, or how it should be taught, to contemporary adult learner
graduate students today.
Students learn in different ways which forces faculty in higher education to reevaluate
any assumptions that all students learn the same way and that the faculty member’s own
preferences and prejudices for learning are broad enough to facilitate the learning needs
of most or all the students in a course. In order to achieve more effective learning, faculty
must embrace the attitude of expanding their learning activities to accommodate a wider
field of adult learning styles (Hawk and Shah, 2007, p.2).
In the Kolb Experiential Learning Model (2005), learners are segmented by learning
preference and then Kolb designs learning activities to accommodate the different
personalities. The segments are (1) divergers who have strong imaginative ability, are
good at seeing things from different perspectives, are creative, and work well with
people; (2) assimilators who have abilities to create theoretical models, prefer inductive
reasoning, and would rather deal with abstract ideas; (3) convergers have a strong
practical orientation, are generally deductive in their thinking, and tend to be
unemotional; (4) accommodators like doing things, are risk takers, are in the here and
now, and solve problems intuitively.
A second, but related learning model is the Gregorc Learning/Teaching Style Model
that defines learning style as “distinctive and observable behaviors that provide clues
Teaching Statistics to Adult Learners 12
about the mediation abilities of individuals and how their minds relate to the world and,
therefore, how they learn” (Gregorc, 1979, p.19).
Gregorc claims that individuals have natural predispositions for learning along four
bipolar, continuous mind qualities that function as mediators as individuals learn from
and act upon their environments (adult, mature, administrators/managers). These mind
qualities are abstract and concrete perception, sequential and random ordering, deductive
and inductive reasoning, and separative and associative relationships. The Gregorc Style
Delineator (GSD) provides metrics on how individuals measure up to these four
dimensions. The GSD is commercially available (www.gregorc.com) and can be self-
administered, self-scored and self-interpreted.
Both of these learning/teaching models are only two of many models currently in
vogue in educational research, however, it is imperative that higher education faculty in
all disciplines and in all course delivery methods, who normally are not in the field of
educational research, should be aware of and increase their adaptability in teaching based
on these models. It gets back to the thesis of teaching the right things to the right
audience in the right manner to ensure both learning and student satisfaction with the
educational experience into which the student has invested time and money.
The conclusion in educational research is that no one instrument or model can capture
all the learning styles in one neat package. It does require higher education faculty to
rethink their pedagogical processes based on the student audience that is presented at the
time. It should be easy to conclude that undergraduate students, masters’ students, and
doctoral students should all be approached differently since each category has different
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