Manajemen | Fakultas Ekonomi Universitas Maritim Raja Ali Haji joeb.84.2.96-100
Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
The Impact of Learning Structure on Students'
Readiness for Self-Directed Learning
Linda Dynan , Tom Cate & Kenneth Rhee
To cite this article: Linda Dynan , Tom Cate & Kenneth Rhee (2008) The Impact of Learning
Structure on Students' Readiness for Self-Directed Learning, Journal of Education for Business,
84:2, 96-100, DOI: 10.3200/JOEB.84.2.96-100
To link to this article: http://dx.doi.org/10.3200/JOEB.84.2.96-100
Published online: 07 Aug 2010.
Submit your article to this journal
Article views: 340
View related articles
Citing articles: 25 View citing articles
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=vjeb20
Download by: [Universitas Maritim Raja Ali Haji]
Date: 11 January 2016, At: 22:46
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
TheImpactofLearningStructureon
Students’ReadinessforSelf-Directed
Learning
LINDADYNAN
TOMCATE
KENNETHRHEE
NORTHERNKENTUCKYUNIVERSITY
HIGHLANDHEIGHTS,KENTUCKY
ABSTRACT. Self-directedlearning
(SDL)skillsarethebasisoflifelonglearning.Theauthorspresentfindingsfroma
classroomexperimenttoassessacquisition
oftheskillofSDLunderstructuredand
unstructuredlearningenvironments.The
authorsfoundthatstructurematchenhances
SDLskillsandthatcoursesdesignedto
enhancestudents’readinessforSDLcando
so.However,themajorityofthestudentsin
thisstudy,whowerelikelytobesimilarto
otherstudentsatpublicuniversitiesinmetropolitanareas,enteredthecourseunpreparedforSDL.Thestructuredenvironment,
inwhichstudentsmodelgoodlearning
skills,providedamoresuitableenvironmentforimprovingstudentreadinessfor
SDLformorestudents.Theauthorsmake
recommendationsforthedevelopmentof
SDLacrossthecollegecurriculum.
Keywords:learningenvironment,selfdirectedlearning,structure
Copyright©2008HeldrefPublications
96
JournalofEducationforBusiness
A
titsbest,teachingaimstoachieve
at least two essential goals for
students:to(a)increaseknowledgewith
respect to particular content and (b)
develop skills that will serve students
well,evenbeyondthecontentofaspecific course. We present findings from
a classroom experiment designed to
assessstudentperformancewithrespect
to the second goal of skill acquisition,
specifically the skill of self-directed
learning(SDL).
According to Knowles (1975), SDL
“is a process in which individuals take
the initiative, with or without the help
of others, in diagnosing their learning
needs,formulatinglearninggoals,identifying human and material resources,
choosing and implementing appropriate learning strategies, and evaluating
learningoutcomes”(p.18).Theskillof
SDL, if successfully acquired, equips
students with the ability to be lifelong
learners.Thecontributionofthepresent
studyistotestwhetherhavingstudents
pattern their skills after their professors’skills(structured)orpracticetheir
own (unstructured) self-directed skills
improves readiness to engage in SDL.
Ananswertothisquestionwillenhance
the ability of educators to produce
graduates capable of lifelong learning.
Although many other factors, such as
emotional maturity (Chickering, 1969;
Keegan,1982;Perry,1970),areimportant in enhancing student readiness to
engageinSDL,thosearenotthefocus
ofthisstudy.
In this classroom experiment, we
assess whether upper division students
achieve measurably better self-direction skills in a structured or unstructuredlearningenvironment.Weaskthis
question to better understand whether
students at this educational level in a
public university’s college of business
can perform with intellectual independence and self-direction. This study is
motivated by an earlier one by Dynan
and Cate (2005) in which the authors
examined whether regular structured
writingassignmentsinaclassofmixed
majors that did not use a formal textbookimprovedperformance.Theresults
suggestedthatwritingdoesmatter,asit
significantly improves student test performance.Thisfindingistrueevenafter
control for variation in student major
(Dynan&Cate).
To the extent to which faculty are
concernedwithstudentsmasteringcontent,thestructuredwritingassignments
appeareffective.However,totheextent
thatfacultyareconcernedwithteaching
independenceandself-direction—skills
essentialinaglobaleconomyundergoing significant structural change that
requires an increasingly flexible and
continuously educated workforce—this
method of instruction may be less
appropriate for instilling skills (Dynan
&Cate,2005).
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
In the present study, we used a pretest and posttest experimental design to
understandhowlearningstructureaffects
skill enhancement. How different learning structures affect readiness for SDL
is measured by the pretest and posttest
change in student scores on a survey
instrument designed to measure student
readiness for SDL. We used the pretest survey scores to determine whether
matching the students’ initial readiness
toself-directwiththeirlearningstructure
affectstheiracquisitionofthatskill.
The importance of understanding
SDLinthisstudentpopulationisunderscored by the increasing prevalence of
onlinelearningforuniversitywork,nondegree training, and skill enhancement
intendedtoretoolworkersreentering—
or transitioning in—the labor market.
Forstudentstobenefitfromthistypeof
course,theyshouldpossessatleastsome
minimallevelofreadinessforSDL.
and explain why one is better than
another. Although all of these skills
neednotbewelldevelopedsimultaneously, reasoning skills must advance
to at least the level of application for
the student to engage in independent
lifelong learning that achieves goals
beyond self-improvement projects or
leisureactivities.
TheabilitytoengageinSDLisaskill
that is necessary for lifelong learning.
Withthisskill,onthebasisofBloom’s
(1956)study,weproposedthatstudents
will be able to do the following: (a)
ask an appropriate question to guide
theirinquiry;(b)identifytheappropriate
resources and tools necessary; (c) use
the tools and resources, with appropriateadjustmentsandmodificationsbased
on their specific needs, to satisfactorily
answertheinitialquestion;and(d)questiontheassumptionsandideasthatcreatedthequestioninstep(a).
PREVIOUSRESEARCH
PatterningorPractice?SelfDirectedLearningExperiments
EssentialSkills
Preparing students with the skills
necessary for independent and
lifelong learning is a challenge with
which teachers have struggled (Candy,
1991). Learning requires that internal
resources—thatis,theabilitytoreason,
read, or cipher (Confessore & Confessore, 1992)—be well developed. However, this limited set of skills produces
only the most basic learning. In the
language of Bloom’s (1956) taxonomy,whichdefinedahierarchicalsetof
learning skills, the student with these
skillsacquiresknowledge(anabilityto
define basic concepts) and comprehension(theabilitytodefinebasicconcepts
tosomeoneelse).
However,moreadvancedreasoning,
as presented in Bloom’s (1956) taxonomy, is essential to engage in SDL.
Thesehigherorderreasoningskillsare
(a)application,theabilitytoapplythe
basic concepts to real-world problems
or situations; (b) analysis, the ability
torecognizeandexplainmajorunderlying assumptions; (c) synthesis, the
ability to build simple models based
on principles; and (d) evaluation, the
ability to compare and contrast the
costs and benefits of simple models
During the 1960s and 1970s,
researchers(e.g.,Hiemstra,1975;Johnstone & Rivera, 1965; Penland, 1979;
Tough,1979)documentedtheextentof
adultinvolvementinSDLprojects.Two
other lines of inquiry have contributed
to our understanding of adult involvementinSDL.Thefirstistheclassroom
experimentationapproachusedbyHall
and Steele (1971) and McCauley and
McClelland (2004). The second is the
curriculum development and implementationapproachassociatedwiththe
Adult Education Guided Independent
Study program at Columbia University’s Teachers College (Bauer, 1985)
andtheGuidedSelf-DirectedLearning
Strategies atAlverno College (Thompson&Wulff,2004).
The aforementioned studies had at
least two problems. First, the studies
did not focus on the analysis of the
learning aspect of adult involvement
in SDL projects. Second, they did not
examinetheextenttowhichprofessors
qua role models of SDL principles in
actionaffectedstudentlearning.
Guglielmino (1977) addressed the
first problem. As part of her doctoral
dissertation, Guglielmino developed
the Self-Directed Learning Readiness
Survey (SDLRS) instrument consisting of 58 items to which participants
responded using a 5-point Likert-type
scalerangingfrom1(Almostnevertrue
ofme;Ihardlyeverfeelthisway)to5
(Almostalwaystrueofme;therearevery
few times when I don’t feel this way).
Studies have evaluated the statistical
reliability of the instrument (Delahaye
& Choy, 2000; Guglielmino & Klatt,
1993;Reio&Davis,2005).Onestudy
(Brookfield, 1985) concluded that the
SDLRSissuitedtomeasuringthereadinessforSDLofadultswhohaveaverage or above-average levels of formal
education and rely on books and periodicalsforinformation.
Forthesecondproblem,Grow(1991),
notingthatamismatchbetweenstudents’
levelsofself-directionandteachingstyle
could reduce student learning, argued
thatgoodteachingrequiredamixtureof
different teaching styles and advocated
theadoptionofamorehumanisticteachingstyle.Inthepresentstudytheauthors
extended Grow’s mismatch hypothesis to the structure of the classroom’s
learningenvironment.
MoreVersusLessStructure
Intheunpublishedexplanatorymaterialsthatcomewiththescoredtests,Guglielmino(1977)claimedthataperson’s
scorecanbechanged:“Mostpersonswith
low or average levels of self-directed
learning readiness can increase their
readinesswithawarenessandpractice”
(6467A). High scores are desirable
becausehighscoresareassociatedwith
better performance in jobs that involve
problemsolving,creativity,andchange
(Guglielmino & Klatt, 1993). In the
general population, the average SDL
readiness score is 214, whereas in a
sampleofsuccessfulentrepreneurs,the
meanwas248(SD=25.59[Guglielmino&Klatt]).
According to Guglielmino & Klatt
(1993), high scorers prefer SDL.Averagescorerssucceedinmoreindependent
situationsbutarenotfullycomfortable
withidentifyingtheirlearningneedsor
planningandimplementingtheirlearning. Low scorers, on the other hand,
prefer structured learning options. In
thepresentstudy,wetestedoutcomesin
therelationbetweenstructureandscore,
November/December2008
97
not the relation between preferences
about the environment and score. The
hypothesesthatwetestedfollow:
Hypothesis1(H1):Astructuredenvironment will improve students’ preparedness for SDL to a greater extent
thandoesanunstructuredenvironment.
H2: Students’ scores on the SDLRS
will show greater improvement when
the learning structure matches the students’ initial scores. By matching, we
mean that high scorers will improve
more in an unstructured environment
andtheconverse.
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
METHOD
Data from eight sections of the
course, The International Context of
Business,withanenrollmentofapproximately 250 students, were collected.
Four sections in the spring of 2006
wereconductedinastructuredlearning
environment.Foursectionsinthefallof
2006wereconductedinanunstructured
learningenvironment.
In the structured learning environment,studentswereaskedspecificquestions related to their work each week.
They were given explicit and detailed
instructions for completing each of
their assignments and semester projects.Ability for students to self-define
their work was intentionally limited.
In this method the authors tested the
hypothesis that students would learn
how to develop learning projects by
continual modeling of their professors’
lineofinquiry.
In the unstructured environment,
students were afforded much greater
opportunity to shape their work, both
in the weekly assignments and for the
semester-long project. The weekly
assignmentswereopenquestionsbased
on an unpublished syllabus that asked
the students to address the following
(Locke,2005):
1.Ideas and arguments in the readings
that the student found important,
interesting,orstimulating.
2.Questions,concerns,ordisagreements
the student has with claims or ideas
presentedintheassignedmaterial.
3.Connectionsamongthematerial,lectures, and experiences the class has
exploredforthiscourse.
98
JournalofEducationforBusiness
Thestudentsweregivenanopportunitytodefinetheirresearchprojectson
the basis of a choice of five different
readings.Inthisenvironment,students
were given the practical opportunity
to define and implement work of their
owndesign.
Skills’ outcome variables were collected using the SDL Readiness Scale,
developed by Guglielmino (1977), at
thebeginningandendofthesemesterin
eachsectionofthecourse.Theanalysis
coveredthechangeinthescores,importanceoflearningstructureonimproving
thesescores,theimportanceofstudents’
initial readiness to self-direct, and the
environmentinwhichtheyareplacedfor
thedevelopmentofSDL.Thescoresare
numeric,butinterpretedwithinrangesof
readinesstolearnasfollows:Ascoreof
58–176indicateslowreadiness;ascore
of 177–201 indicates below-average
readiness;ascoreof202–226indicates
average readiness; a score of 227–251
indicates above-average readiness; and
ascoreof252–290indicateshighreadiness. In repeated samples, Guglielmino
and associates found an adult mean
readinessof214(SD=25.59).
The impacts of the students’ initial
SDL readiness scores, the environment
(structuredorunstructured),andtheinitial score’s match to the environment
on skill enhancement were assessed.
Students with low, below-average, and
average readiness to self-direct were
said to match if the environment was
structured.Above-averagereadinessand
high readiness to self-direct matched
to the unstructured environment. An
alternative grouping that changed the
classification of an average score from
matchingtothestructuredenvironment
to unstructured environment was also
tested.Althoughtheresultswererobust
(the results retained direction and significance) for this alternative, they lost
somemagnitude.
Control variables that we thought
affectedperformancewerecollectedby
surveysintheclasses.Otherexplanatory
variablesincludedindicatorvariablesfor
thelearningstructure,thematchbetween
initialreadinessscoreandstructure,day
oreveningclass,andprofessor.
The hypotheses were tested by
difference-in-meansandmultipleregressionanalyses.
RESULTS
Wereceivedapprovalfromaninstitutionalreviewboard(IRB)forthepresent
study. The IRB required that participation be voluntary. The students were
accordingly informed that they were
to be the participants of a study. Both
semesters achieved 100% participation.
However, outliers (students who had
changes in their SDL readiness scores
greater than 1 standard deviation [SD
= 26 points]) were removed from the
sample. The spring sample contained
8 outliers (8.3%), and the fall semester had 14 outliers (10.9%). In part,
this arrangement controlled for student
responsebiasfromeitherstudentshopingtoimpresstheirprofessororstudents
perhapshopingtosabotagetheirprofessor. The usable response rate for the
spring of 2006 was 66% = 88/133 and
forthefallof2006was76%=97/128.
Table1presentsthemeanvaluesfor
the dependent and independent variables included in the analysis for the
structured and unstructured samples.
The results of difference-in-means (or
sampleproportions)testsacrossthetwo
samplesarealsopresented.
Thecharacteristicsofthespringand
fall sections of the course are similar. However, several significant differences should be noted. First—and
most important—the share of students
that do match to the environment in
which they undertake the course is
much greater in the structured semester.Itisinterestingthatthemajorityof
students(59%inthespringand61%in
the fall) are not ready for independent
learningatthebeginningofthesemester. Second, the fall semester had far
fewernightstudentsthandidthespring
semester. This difference was because
of scheduling demands in the department. There was also some variation
in the mix of student major across the
semesters. With these few exceptions,
the student populations were roughly
similar across semesters. The preponderance of students in both semesters
wasseniors.However,imminentgraduationdistractionsaffectbothsemesters
because graduations take place in the
springandthefall.
In each semester, we estimated
the difference-in-means tests of the
TABLE1.DifferenceinMeansorSampleProportions
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
Variable
Final
Pretestscore
Posttestscore
Change
Negativechange
Actualmatch
Night
Male
Age
Gradepointaverage
Numberofdependents
Hourspaidwork
Yearsincollege
Informationsystems
Accounting
Economics/finance
Management
Businessadministration
Marketing
Senior
Instructor1
Structured
(n=88)
Unstructured
(n=97)
Difference
80.32
222.82
225.70
2.89
0.38
0.57
0.49
0.55
25.10
3.12
0.38
27.11
5.40
0.09
0.19
0.19
0.13
0.13
0.27
0.94
0.44
79.56
216.71
221.57
4.86
0.29
0.39
0.27
0.51
24.85
3.15
0.37
28.67
5.37
0.07
0.22
0.08
0.27
0.14
0.22
0.93
0.44
0.97
5.23
3.50
–1.73
0.07
0.19*
0.21*
0.04
0.04
–0.04
–0.03
–1.99
–0.02
0.01
–0.02
0.11**
–0.13**
–0.02
0.06
0.02
–0.01
*
p
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
The Impact of Learning Structure on Students'
Readiness for Self-Directed Learning
Linda Dynan , Tom Cate & Kenneth Rhee
To cite this article: Linda Dynan , Tom Cate & Kenneth Rhee (2008) The Impact of Learning
Structure on Students' Readiness for Self-Directed Learning, Journal of Education for Business,
84:2, 96-100, DOI: 10.3200/JOEB.84.2.96-100
To link to this article: http://dx.doi.org/10.3200/JOEB.84.2.96-100
Published online: 07 Aug 2010.
Submit your article to this journal
Article views: 340
View related articles
Citing articles: 25 View citing articles
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=vjeb20
Download by: [Universitas Maritim Raja Ali Haji]
Date: 11 January 2016, At: 22:46
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
TheImpactofLearningStructureon
Students’ReadinessforSelf-Directed
Learning
LINDADYNAN
TOMCATE
KENNETHRHEE
NORTHERNKENTUCKYUNIVERSITY
HIGHLANDHEIGHTS,KENTUCKY
ABSTRACT. Self-directedlearning
(SDL)skillsarethebasisoflifelonglearning.Theauthorspresentfindingsfroma
classroomexperimenttoassessacquisition
oftheskillofSDLunderstructuredand
unstructuredlearningenvironments.The
authorsfoundthatstructurematchenhances
SDLskillsandthatcoursesdesignedto
enhancestudents’readinessforSDLcando
so.However,themajorityofthestudentsin
thisstudy,whowerelikelytobesimilarto
otherstudentsatpublicuniversitiesinmetropolitanareas,enteredthecourseunpreparedforSDL.Thestructuredenvironment,
inwhichstudentsmodelgoodlearning
skills,providedamoresuitableenvironmentforimprovingstudentreadinessfor
SDLformorestudents.Theauthorsmake
recommendationsforthedevelopmentof
SDLacrossthecollegecurriculum.
Keywords:learningenvironment,selfdirectedlearning,structure
Copyright©2008HeldrefPublications
96
JournalofEducationforBusiness
A
titsbest,teachingaimstoachieve
at least two essential goals for
students:to(a)increaseknowledgewith
respect to particular content and (b)
develop skills that will serve students
well,evenbeyondthecontentofaspecific course. We present findings from
a classroom experiment designed to
assessstudentperformancewithrespect
to the second goal of skill acquisition,
specifically the skill of self-directed
learning(SDL).
According to Knowles (1975), SDL
“is a process in which individuals take
the initiative, with or without the help
of others, in diagnosing their learning
needs,formulatinglearninggoals,identifying human and material resources,
choosing and implementing appropriate learning strategies, and evaluating
learningoutcomes”(p.18).Theskillof
SDL, if successfully acquired, equips
students with the ability to be lifelong
learners.Thecontributionofthepresent
studyistotestwhetherhavingstudents
pattern their skills after their professors’skills(structured)orpracticetheir
own (unstructured) self-directed skills
improves readiness to engage in SDL.
Ananswertothisquestionwillenhance
the ability of educators to produce
graduates capable of lifelong learning.
Although many other factors, such as
emotional maturity (Chickering, 1969;
Keegan,1982;Perry,1970),areimportant in enhancing student readiness to
engageinSDL,thosearenotthefocus
ofthisstudy.
In this classroom experiment, we
assess whether upper division students
achieve measurably better self-direction skills in a structured or unstructuredlearningenvironment.Weaskthis
question to better understand whether
students at this educational level in a
public university’s college of business
can perform with intellectual independence and self-direction. This study is
motivated by an earlier one by Dynan
and Cate (2005) in which the authors
examined whether regular structured
writingassignmentsinaclassofmixed
majors that did not use a formal textbookimprovedperformance.Theresults
suggestedthatwritingdoesmatter,asit
significantly improves student test performance.Thisfindingistrueevenafter
control for variation in student major
(Dynan&Cate).
To the extent to which faculty are
concernedwithstudentsmasteringcontent,thestructuredwritingassignments
appeareffective.However,totheextent
thatfacultyareconcernedwithteaching
independenceandself-direction—skills
essentialinaglobaleconomyundergoing significant structural change that
requires an increasingly flexible and
continuously educated workforce—this
method of instruction may be less
appropriate for instilling skills (Dynan
&Cate,2005).
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
In the present study, we used a pretest and posttest experimental design to
understandhowlearningstructureaffects
skill enhancement. How different learning structures affect readiness for SDL
is measured by the pretest and posttest
change in student scores on a survey
instrument designed to measure student
readiness for SDL. We used the pretest survey scores to determine whether
matching the students’ initial readiness
toself-directwiththeirlearningstructure
affectstheiracquisitionofthatskill.
The importance of understanding
SDLinthisstudentpopulationisunderscored by the increasing prevalence of
onlinelearningforuniversitywork,nondegree training, and skill enhancement
intendedtoretoolworkersreentering—
or transitioning in—the labor market.
Forstudentstobenefitfromthistypeof
course,theyshouldpossessatleastsome
minimallevelofreadinessforSDL.
and explain why one is better than
another. Although all of these skills
neednotbewelldevelopedsimultaneously, reasoning skills must advance
to at least the level of application for
the student to engage in independent
lifelong learning that achieves goals
beyond self-improvement projects or
leisureactivities.
TheabilitytoengageinSDLisaskill
that is necessary for lifelong learning.
Withthisskill,onthebasisofBloom’s
(1956)study,weproposedthatstudents
will be able to do the following: (a)
ask an appropriate question to guide
theirinquiry;(b)identifytheappropriate
resources and tools necessary; (c) use
the tools and resources, with appropriateadjustmentsandmodificationsbased
on their specific needs, to satisfactorily
answertheinitialquestion;and(d)questiontheassumptionsandideasthatcreatedthequestioninstep(a).
PREVIOUSRESEARCH
PatterningorPractice?SelfDirectedLearningExperiments
EssentialSkills
Preparing students with the skills
necessary for independent and
lifelong learning is a challenge with
which teachers have struggled (Candy,
1991). Learning requires that internal
resources—thatis,theabilitytoreason,
read, or cipher (Confessore & Confessore, 1992)—be well developed. However, this limited set of skills produces
only the most basic learning. In the
language of Bloom’s (1956) taxonomy,whichdefinedahierarchicalsetof
learning skills, the student with these
skillsacquiresknowledge(anabilityto
define basic concepts) and comprehension(theabilitytodefinebasicconcepts
tosomeoneelse).
However,moreadvancedreasoning,
as presented in Bloom’s (1956) taxonomy, is essential to engage in SDL.
Thesehigherorderreasoningskillsare
(a)application,theabilitytoapplythe
basic concepts to real-world problems
or situations; (b) analysis, the ability
torecognizeandexplainmajorunderlying assumptions; (c) synthesis, the
ability to build simple models based
on principles; and (d) evaluation, the
ability to compare and contrast the
costs and benefits of simple models
During the 1960s and 1970s,
researchers(e.g.,Hiemstra,1975;Johnstone & Rivera, 1965; Penland, 1979;
Tough,1979)documentedtheextentof
adultinvolvementinSDLprojects.Two
other lines of inquiry have contributed
to our understanding of adult involvementinSDL.Thefirstistheclassroom
experimentationapproachusedbyHall
and Steele (1971) and McCauley and
McClelland (2004). The second is the
curriculum development and implementationapproachassociatedwiththe
Adult Education Guided Independent
Study program at Columbia University’s Teachers College (Bauer, 1985)
andtheGuidedSelf-DirectedLearning
Strategies atAlverno College (Thompson&Wulff,2004).
The aforementioned studies had at
least two problems. First, the studies
did not focus on the analysis of the
learning aspect of adult involvement
in SDL projects. Second, they did not
examinetheextenttowhichprofessors
qua role models of SDL principles in
actionaffectedstudentlearning.
Guglielmino (1977) addressed the
first problem. As part of her doctoral
dissertation, Guglielmino developed
the Self-Directed Learning Readiness
Survey (SDLRS) instrument consisting of 58 items to which participants
responded using a 5-point Likert-type
scalerangingfrom1(Almostnevertrue
ofme;Ihardlyeverfeelthisway)to5
(Almostalwaystrueofme;therearevery
few times when I don’t feel this way).
Studies have evaluated the statistical
reliability of the instrument (Delahaye
& Choy, 2000; Guglielmino & Klatt,
1993;Reio&Davis,2005).Onestudy
(Brookfield, 1985) concluded that the
SDLRSissuitedtomeasuringthereadinessforSDLofadultswhohaveaverage or above-average levels of formal
education and rely on books and periodicalsforinformation.
Forthesecondproblem,Grow(1991),
notingthatamismatchbetweenstudents’
levelsofself-directionandteachingstyle
could reduce student learning, argued
thatgoodteachingrequiredamixtureof
different teaching styles and advocated
theadoptionofamorehumanisticteachingstyle.Inthepresentstudytheauthors
extended Grow’s mismatch hypothesis to the structure of the classroom’s
learningenvironment.
MoreVersusLessStructure
Intheunpublishedexplanatorymaterialsthatcomewiththescoredtests,Guglielmino(1977)claimedthataperson’s
scorecanbechanged:“Mostpersonswith
low or average levels of self-directed
learning readiness can increase their
readinesswithawarenessandpractice”
(6467A). High scores are desirable
becausehighscoresareassociatedwith
better performance in jobs that involve
problemsolving,creativity,andchange
(Guglielmino & Klatt, 1993). In the
general population, the average SDL
readiness score is 214, whereas in a
sampleofsuccessfulentrepreneurs,the
meanwas248(SD=25.59[Guglielmino&Klatt]).
According to Guglielmino & Klatt
(1993), high scorers prefer SDL.Averagescorerssucceedinmoreindependent
situationsbutarenotfullycomfortable
withidentifyingtheirlearningneedsor
planningandimplementingtheirlearning. Low scorers, on the other hand,
prefer structured learning options. In
thepresentstudy,wetestedoutcomesin
therelationbetweenstructureandscore,
November/December2008
97
not the relation between preferences
about the environment and score. The
hypothesesthatwetestedfollow:
Hypothesis1(H1):Astructuredenvironment will improve students’ preparedness for SDL to a greater extent
thandoesanunstructuredenvironment.
H2: Students’ scores on the SDLRS
will show greater improvement when
the learning structure matches the students’ initial scores. By matching, we
mean that high scorers will improve
more in an unstructured environment
andtheconverse.
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
METHOD
Data from eight sections of the
course, The International Context of
Business,withanenrollmentofapproximately 250 students, were collected.
Four sections in the spring of 2006
wereconductedinastructuredlearning
environment.Foursectionsinthefallof
2006wereconductedinanunstructured
learningenvironment.
In the structured learning environment,studentswereaskedspecificquestions related to their work each week.
They were given explicit and detailed
instructions for completing each of
their assignments and semester projects.Ability for students to self-define
their work was intentionally limited.
In this method the authors tested the
hypothesis that students would learn
how to develop learning projects by
continual modeling of their professors’
lineofinquiry.
In the unstructured environment,
students were afforded much greater
opportunity to shape their work, both
in the weekly assignments and for the
semester-long project. The weekly
assignmentswereopenquestionsbased
on an unpublished syllabus that asked
the students to address the following
(Locke,2005):
1.Ideas and arguments in the readings
that the student found important,
interesting,orstimulating.
2.Questions,concerns,ordisagreements
the student has with claims or ideas
presentedintheassignedmaterial.
3.Connectionsamongthematerial,lectures, and experiences the class has
exploredforthiscourse.
98
JournalofEducationforBusiness
Thestudentsweregivenanopportunitytodefinetheirresearchprojectson
the basis of a choice of five different
readings.Inthisenvironment,students
were given the practical opportunity
to define and implement work of their
owndesign.
Skills’ outcome variables were collected using the SDL Readiness Scale,
developed by Guglielmino (1977), at
thebeginningandendofthesemesterin
eachsectionofthecourse.Theanalysis
coveredthechangeinthescores,importanceoflearningstructureonimproving
thesescores,theimportanceofstudents’
initial readiness to self-direct, and the
environmentinwhichtheyareplacedfor
thedevelopmentofSDL.Thescoresare
numeric,butinterpretedwithinrangesof
readinesstolearnasfollows:Ascoreof
58–176indicateslowreadiness;ascore
of 177–201 indicates below-average
readiness;ascoreof202–226indicates
average readiness; a score of 227–251
indicates above-average readiness; and
ascoreof252–290indicateshighreadiness. In repeated samples, Guglielmino
and associates found an adult mean
readinessof214(SD=25.59).
The impacts of the students’ initial
SDL readiness scores, the environment
(structuredorunstructured),andtheinitial score’s match to the environment
on skill enhancement were assessed.
Students with low, below-average, and
average readiness to self-direct were
said to match if the environment was
structured.Above-averagereadinessand
high readiness to self-direct matched
to the unstructured environment. An
alternative grouping that changed the
classification of an average score from
matchingtothestructuredenvironment
to unstructured environment was also
tested.Althoughtheresultswererobust
(the results retained direction and significance) for this alternative, they lost
somemagnitude.
Control variables that we thought
affectedperformancewerecollectedby
surveysintheclasses.Otherexplanatory
variablesincludedindicatorvariablesfor
thelearningstructure,thematchbetween
initialreadinessscoreandstructure,day
oreveningclass,andprofessor.
The hypotheses were tested by
difference-in-meansandmultipleregressionanalyses.
RESULTS
Wereceivedapprovalfromaninstitutionalreviewboard(IRB)forthepresent
study. The IRB required that participation be voluntary. The students were
accordingly informed that they were
to be the participants of a study. Both
semesters achieved 100% participation.
However, outliers (students who had
changes in their SDL readiness scores
greater than 1 standard deviation [SD
= 26 points]) were removed from the
sample. The spring sample contained
8 outliers (8.3%), and the fall semester had 14 outliers (10.9%). In part,
this arrangement controlled for student
responsebiasfromeitherstudentshopingtoimpresstheirprofessororstudents
perhapshopingtosabotagetheirprofessor. The usable response rate for the
spring of 2006 was 66% = 88/133 and
forthefallof2006was76%=97/128.
Table1presentsthemeanvaluesfor
the dependent and independent variables included in the analysis for the
structured and unstructured samples.
The results of difference-in-means (or
sampleproportions)testsacrossthetwo
samplesarealsopresented.
Thecharacteristicsofthespringand
fall sections of the course are similar. However, several significant differences should be noted. First—and
most important—the share of students
that do match to the environment in
which they undertake the course is
much greater in the structured semester.Itisinterestingthatthemajorityof
students(59%inthespringand61%in
the fall) are not ready for independent
learningatthebeginningofthesemester. Second, the fall semester had far
fewernightstudentsthandidthespring
semester. This difference was because
of scheduling demands in the department. There was also some variation
in the mix of student major across the
semesters. With these few exceptions,
the student populations were roughly
similar across semesters. The preponderance of students in both semesters
wasseniors.However,imminentgraduationdistractionsaffectbothsemesters
because graduations take place in the
springandthefall.
In each semester, we estimated
the difference-in-means tests of the
TABLE1.DifferenceinMeansorSampleProportions
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:46 11 January 2016
Variable
Final
Pretestscore
Posttestscore
Change
Negativechange
Actualmatch
Night
Male
Age
Gradepointaverage
Numberofdependents
Hourspaidwork
Yearsincollege
Informationsystems
Accounting
Economics/finance
Management
Businessadministration
Marketing
Senior
Instructor1
Structured
(n=88)
Unstructured
(n=97)
Difference
80.32
222.82
225.70
2.89
0.38
0.57
0.49
0.55
25.10
3.12
0.38
27.11
5.40
0.09
0.19
0.19
0.13
0.13
0.27
0.94
0.44
79.56
216.71
221.57
4.86
0.29
0.39
0.27
0.51
24.85
3.15
0.37
28.67
5.37
0.07
0.22
0.08
0.27
0.14
0.22
0.93
0.44
0.97
5.23
3.50
–1.73
0.07
0.19*
0.21*
0.04
0.04
–0.04
–0.03
–1.99
–0.02
0.01
–0.02
0.11**
–0.13**
–0.02
0.06
0.02
–0.01
*
p