Running head: PHILOSOPHY OF CHANGE IN HIGHER

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Running head: PHILOSOPHY OF CHANGE IN HIGHER EDUCATION
Personal Philosophy of Change in Higher Education
Eric J. Teske
Bowling Green State University
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Greater Than the Sum of Its Parts
Before delving into my personal beliefs about change in higher education, a brief
synopsis of the characteristics of such institutions will serve as a useful foundation. I want to
highlight several of the emergent features of higher education that are distinct from
organizational structures in business. First, Kezar’s outline of distinctive features of higher
education is useful in assessing appropriate models of the change process, and helps to highlight
the emergent features to which I am referring. Of the 13 items she identifies, the unique culture
of the academy, institutional status, values-driven environment, loosely coupled structure, goal
ambiguity, and image are of particular interest (Kezar, 2001). All of these features of the
organized environment of higher education influence the unique culture of each individual
institution.
The implications are fascinating! Kezar describes each of these features in somewhat
cerebral terms, familiar to the fields of psychology and neurology. “Loose coupling is a cognitive
response to an environment of constant change,” where institutions’ norms are tied to the
identities of their constituent human members (Kezar, 2001, p. 70). Organizations have their own
belief systems, and internally conflicting goals that are subject to interpretation and expression at
the individual level.
Finally, and all the more baffling, institutions of higher education appear to generate a
sort of self-awareness through the collective image and identity of their members. Greater than
the sum of individual notions bottled up inside the craniums of the members themselves, these
constructs give life to the organization. Demers raises the controversial question: “Is there such a
thing as organizational cognition” (2007, p. 129)? As an alternative to the view of organizational
knowledge (the aggregate of individual cognition), I am tempted to say that the view of a
cognition being greater than the sum of individual cognitions is not just an illusion. Just as the
thought process of a mob is different than the thoughts of an individual, I believe that
organizations at a collective level take on new cognitive characteristics. Furthermore, I am of the
opinion that a system of human effort that resembles a self-aware and uniquely identifying entity
should be handled with the benefit of a social-cognitive understanding.
Implications for My View of Change
Institutions of higher education do not need to take on anthropomorphic characteristics
for us to realize that their cultures, identities, and values resemble a metaphoric life based out of
the communal beliefs and projections of their members. This is where the metaphor must end,
however, because my philosophy of institutional change does not go so far as to suggest these
“organisms” of higher education should develop and change through a life cycle. An organism is
an individual, and an individual is motivated by survival and reproduction. This is where the life
cycle model (which I will go into no further detail here) falls short. The life cycle assumes the
motives and survivability of an individual entity, whereas institutions are comprised of distinct
individuals with deeply held beliefs, attitudes, and values of their own. Kezar agrees, and states
that “higher education institutions would seem to be best interpreted through cultural, socialcognition, and political models” (2001, p. 77). Therefore my change philosophy can be
understood through cultural models, with an emphasis on behavior changes at the individual and
unit level (social-cognition), and with a small but respectable mention of the political influences
that are more prevalent in higher education than in other organized systems.
Ultimately, culture change is going to be the driving force that changes an institution in a
sustainable way. Burke writes, “you don’t change culture by trying to change culture” (2011, p.
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24). Although culture is really the target of change efforts, because it is going to provide both the
strong tide of change and the following support of attitudes, values, and beliefs, it is too big a
beast to tackle head on. In fact, if approached precariously, the beast may just turn on you in
spite of your good intentions. So we need to think smaller. If culture can operationally be defined
as “the way we do things here,” then behaviors describe what we are doing.
Changes in behavior affect changes in attitudes and beliefs, which extend into pockets of culture
that comprise the overall identity and “feel” of a university. But how do these behaviors change?
Members within organizations, and by virtue the organizations themselves, acquire new
behaviors through the aptly-named behavioral learning approach. Behavioral learning is a
routine-based approach that produces change through experimentation (i.e. trial and error), and
where successful routines are reinforced (Demers, 2007). These replications result in incremental
changes of an evolutionary type, over a longer period of time, and are typically first-order
changes that “consist of alterations or modifications in existing system characteristics” (Burke,
2011, p. 144). The replication of successful routines reminds me of the theory of memetics put
forth by British evolutionary biologist Richard Dawkins, in which memes are the fundamental
replicator units of cultural transmission (Dawkins, 2006). In his first publication on memes in
1976, Dawkins writes:
“Just as genes propagate themselves in the gene pool by leaping from body to body via
sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain
to brain via a process which, in the broad sense, can be called imitation. If a scientist
hears, or reads about, a good idea, he passes it on to his colleagues and students. He
mentions it in his articles and his lectures. If the idea catches on, it can be said to
propagate itself, spreading from brain to brain” (Dawkins, 2006).
Although meme theory, or memetics, seems to be grounded in the cognitive approach typical of
the 1980’s, in which frames of thought, perspectives, and ideas alone were thought to be
transmitted; Dawkins’ emphasis of imitation in his theory is an interesting addition. Viewing
memes as a base unit for routine transition could be a unifying factor for cross-level learning,
and is a possible linkage between cognitive and behavioral learning overlooked by Demers
(2007). Regardless of whether or not fundamental units of cognitive-behavioral transmission
exist, I believe that “good” routines are replicated and imitated between individuals within an
organization. Further, I believe that when changes in routines occur “simultaneously at various
collective levels” within an organization, it is capable of learning (Burke, 2011, p. 79). Burke
continues:
“Although it is absolutely necessary to be clear at the outset of a change effort about the
desired values and about the modified culture that is the goal, we do not concentrate on
the culture per se, but on the behaviors that will gradually influence the culture in the
desired direction” (2011, p. 25).
This statement concisely describes my views on the underlying ingredients of cultural change,
and also provides an excellent segue into the role of teleological planning in the change process.
Borrowing from Demers’ description of “Era 3” change, I believe that the view of change as
lacking a clear beginning and end is proving to be accurate (2007, p. 115).
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We humans are very good at recognizing patterns, and compartmentalizing the world
around us into smaller units in order to make sense of them. Our concept of time is an excellent
example of this ability. A surprisingly poignant article on Wikipedia describes time as “the
temporal position of events with respect to the transitory present [that] is continually changing;
events happen, then are located further and further in the past” (n.d.). Although we understand
time to describe continual change, we choose to segment time into digestible units. These
artificial units are an illusion of segmentation, and so are periods of change and stability within
an organization. So, if change is ongoing, and “turmoil and unpredictability are here to stay,”
(Demers, 2007, p. 116) then what is the role of intentional planning? This question will be
addressed in the section on application and leadership below.
Before going into a description of applied practice, I must refer back to my description of
institutional change through political models. “The political nature of higher education can be
seen within the many subgroups that work autonomously, yet depend on one another for power
and influence” (Kezar, 2001, p. 66). This power-driven political nature derives from the
characteristics of multiple power and authority structures, organized anarchical decision making,
shared governance, and divided professional and administrative values (Kezar, 2001). The
political approach that compliments my understanding of change in higher education is a model
of incrementalism utilizing a multilevel (top-down and bottom-up) process (Demers, 2007).
Pettigrew’s places central importance on power in his political change process, and describes
change resulting from processes of competition between interest groups that stick to their
insoluble rationalities (As cited in Demers, 2007, p. 103). This description seems to place
political change into a dialectical model of opposing forces resulting in incremental change over
time. While this is a fairly useful description, a more complex image of political change emerges
in the context of culture, and both “front stage” and “back stage” uses of power must be
considered (Demers, 2007, p. 104). While the intricacies of power structures in a political model
can seem overwhelming and obtrusive to organizational change, these aspects can be absorbed
into the social-cognition models of change through the inclusion of organizational self-discovery.
Application: Leadership and Actions that Guide Change
Considering the scope of literature on change, I believe I have at least adequately
described where my philosophical view of change is grounded. Based on characteristics of
higher education, the most appropriate guiding theories of change involve culture, which is too
large to be controlled overtly. Instead, the application of behavioral learning to alter routines
provides access to attitudes and beliefs that can be influenced to affect values, which then
produce incremental change at the cultural level. So, with what we know of the unpredictable,
multifaceted, and downright stubborn nature of institutions, how can one attempt to guide or
intentionally change systems in higher education?
Demers suggests that “change is not something that is done to the organization by
visionary managers; rather, it is something that the organization does itself, in which all members
are involved” (Demers, 2007, p. 116). Again, this view grounds the pace and direction of change
with the members themselves in a behavioral-cultural model. So, as discussed previously, the
route to changes in culture come from changes in behavior, and ultimately specific routines
themselves. Performance feedback rules govern the assessment of experiential learning systems
(Demers, 2007, p. 123). If an instrumental leader can manipulate the evaluation of routines by
setting parameters for what is considered successful, then the leader can guide (not control) the
evolutionary growth in one direction over another.
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This attempt at top-down teleological change using evolutionary methods based out of
the reinforcement of certain routines (possibly memes) over others leads me to the creation of an
elaborate metaphor to describe my philosophy of change in practice. I envision a dog breeder
using selective combinations of characteristics (based in genes) in an attempt to guide nature in
the desired direction. While the dog breeder has no power to simply create a desired breed of
dog out of thin air, he is able to choose which heritable and repeatable traits to encourage and
which to weed out. In this way, strategic redirection incrementally over long periods of time can
produce intentional change that may be more directed and timely than if the change had been left
up to the random combinations of genes through normal reproduction. If the breeder wanted to
create a larger dog, for example, his selection and reinforcement of characteristics should be
largely informed by an image of his desired outcome; in this case an emphasis on gradual
increase in size. With this image in mind, the breeder could attempt to approximate the
characteristics over generations, and gradually shape the appearance of the dog, resulting in a
dramatically different animal than before; an apparent revolutionary change that was actually
brought about through incremental processes.
Bringing it back to higher education, if I wanted to act as a dog breeder to initiate change,
I would first need to understand the initial characteristics of the organization. To do this, I would
spend a lot of time listening, rather than attempting to direct change preemptively. Furthermore, I
would consult with my directors at various levels within the organization to learn about the
different behaviors and cultures between different offices. All of these fact-finding activities are
means of self-assessment, which Kezar describes as part of laying the groundwork for change
(2001). Next, after I know the characteristics of the initial breed, I should want to develop an end
goal to work towards. In higher education this involves revising the mission, objectives, and
vision of the university.
With these two endpoints, I would be able to plot a course for shaping the organism to
match the desired state. This is easier said than done, but luckily I have an advantage that goes
beyond the selective breeding metaphor. While the breeder may only control the reinforcement
of traits, he does not directly convince the genes to combine in a particular fashion. On the other
hand, in an institutional setting, I would have the ability to combine my planning and assessment
with the use of stories, symbolism, and a vision of institutional identity. In other words, I have
the ability to speak directly to my transformative units: The individuals whose behavior I am
attempting to guide. In this way, I would hopefully bring about beneficial changes in a more
active and intentional way. Continual assessment is important for evaluating the progress of the
change. The metaphor of genetic recombination is again useful in describing the underlying
chaos of change. In the case of genetics, the rearrangement of DNA can produce new observable
traits while also creating unseen combinations that may cause problems in later generations. So
too the chaos of changing routines at numerous levels within an institution simultaneously might
lead to several observable and agreeable changes, while at the same time creating new and
challenging patterns that must be resolved at a later time. To help manage the headaches,
understand that endpoints of change are an illusion. While I don’t know many runners who
would enter a race if they knew it would last the rest of their lives, and that the finish line would
constantly change, it’s nice to know that the pursuit itself is a worthy goal.
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References
Burke, W. W. (2011). Organization change: Theory and practice (3rd ed.). Thousand Oaks, CA:
Sage Publications.
Dawkins, R. (2006). The Selfish Gene: 30th Anniversary Edition. Oxford University Press, New
York. Retrieved from http://www.macroevolution.narod.ru/gene/gene30.htm
Demers, C. (2007). Organizational change theories: A synthesis. Thousand Oaks, CA: Sage
Publications.
Kezar, A. J. (2001). Understanding and facilitating organizational change in the 21st century:
Recent research and conceptualizations. In ASHE-ERIC Higher Education Report: Vol.
28(4). San Francisco, CA: Jossey-Bass.
Time. (n.d.). In Wikipedia. Retrieved December 1, 2011, from http://en.wikipedia.org/wiki/Time
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