Application of Multiple Intelligence Theory to an E-Learning Technology Acceptance Model

252 Pages·2017·3.04 MB·English

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ETD Archive
2010
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Alfred J. Degennaro
Cleveland State University
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Degennaro, Alfred J., "Application of Multiple Intelligence Theory to an E-Learning Technology Acceptance
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APPLICATION OFMULTIPLE INTELLIGENCETHEORY TO AN ELEARNING
TECHNOLOGYACCEPTANCE MODEL
ALFRED J.DEGENNARO
Bachelor ofArtsin Mathematics& Philosophy
ClevelandStateUniversity
December, 1981
MasterofArtsin Mathematics
ClevelandStateUniversity
December, 1986
MasterofArtsinComputerand InformationSystems
ClevelandStateUniversity
June,1987
submittedin partialfulfillmentofrequirementforthedegree
DOCTOR OFBUSINESS ADMINISTRATION IN INFORMATION SYSTEMS
atthe
CLEVELANDSTATE UNIVERSITY
MAY,2010
Thisdissertationhas been approved
fortheDepartment ofINFORMATION SCIENCES
andtheCollegeofGraduateStudies by
DissertationChairperson,Dr. SantoshMisra
Department& Date
Dr. VictorMatos
Department& Date
Dr. SridharMadhavaram
Department& Date
Dr. Susan Rakow
Department& Date
Inlovingmemoryofmy grandfather, whosawthepotentialinmeandplanted theseed.
Itakepauseto acknowledgethatnoneofthiscould havebeen accomplishedwithoutthe
supportofmyfamilyand theprayers ofmymotherand father. Iam especiallythankful
formywife, Sarah, who providedtheopportunityand motivationto bringthiswork to
closure. Iextendthisgratitudetomy committeeand especiallyDr. SantoshMisraand his
infinitepatience.
APPLICATION OFMULTIPLE INTELLIGENCETHEORY TO AN ELEARNING
TECHNOLOGYACCEPTANCE MODEL
ALFRED J.DEGENNARO
ABSTRACT
Withthespeedofdoingbusinessontherise,employeesmustlearntoadapttonew
technologies and improved performance expectations without losing productivity or
timeontask. Students looking toenter theworkforce mustunderstand that education
does not end withgraduation; rather the expectation isthat everyone willbe lifelong
learners.
To meet the challenge, education providers are looking for alternative ways to
bring education to the student and enhance the learning experience. With e-learning,
students enjoy flexiblescheduling, businesses canrealize improvements inworkforce
skills while reducing education expenditures (i.e. improved Return On Investment,
ROI) and education providers extend their campuses at minimal cost. E-learning is
fastbecomingapreferredmethodofdeliveringqualityeducationanytime,anywhere.
Educators, however, have mixed feelings on the subject. Many have embraced
the new technology and report positive results. Others question the effectiveness of
e-learning, pointingtothehighdropoutrateine-learning coursesandbiasintheliter-
aturesupporting e-learning. Thecautiousareconcerned aboutrushinginonuncertain
ground. Theyrecalltheadventoftelevisionandtheunmetpromisesofthattechnology
withrespecttoeducation.
Thepurposeofthisstudyistodevelopane-learningadoptionmodelthatisfirmly
foundedineducation research(especially withrespecttolearning)coupled withwhat
is understood about the diffusion and acceptance of (information) technology. The
goalofdeveloping suchamodelistoidentify andpaircruciallearningcharacteristics
v
of students with the acceptance of the technology used to deliver educational content
electronically so as to foster mastery learning. Students can use the results of this
studytohelpdecidewhetherornottoenrollinane-learningcourseorwhatadditional
strategies they may need to employ so as to maximize the experience. Businesses
may benefit from an understanding of how to match the needs of their employees
with appropriate criteria for selecting the most effective e-learning delivery system.
Schools and colleges can use such a model to help minimize the dropout rate from
distancelearning coursesandtopromoteoverallstudentsuccess.
vi
TABLE OFCONTENTS
Page
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
LIST OFTABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
LIST OFFIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv
CHAPTER
I INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 TrendsinDistanceLearning . . . . . . . . . . . . . . . . . . . . . . 4
1.1.1 Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1.2 Enrollment . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.1.3 Faculty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.1.4 Academic . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.1.5 Business . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.2 Controversy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.3 ThePurposeofthisStudy . . . . . . . . . . . . . . . . . . . . . . . 18
1.4 ContributionsofResearch . . . . . . . . . . . . . . . . . . . . . . . 20
1.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
II LITERATURE REVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.1 Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.2 Instructor/DeliveryAgent . . . . . . . . . . . . . . . . . . . . . . . 29
2.3 Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.4 Student . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.4.1 AcceptanceModels . . . . . . . . . . . . . . . . . . . . . . . 35
2.4.2 External Variables Related to e-Learning; An Extended Edu-
cationalTAM . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.4.2.1 SelfEfficacy . . . . . . . . . . . . . . . . . . . . . . . 39
2.4.2.2 ComputerExperience . . . . . . . . . . . . . . . . . . 41
vii
Chapter Page
2.4.2.3 Social InfluenceProcesses . . . . . . . . . . . . . . . 42
2.4.2.4 Culture . . . . . . . . . . . . . . . . . . . . . . . . . 45
2.4.2.5 Gender . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.4.2.6 LearningStyleand MultipleIntelligences . . . . . . . 47
2.4.2.7 IntrinsicMotivations . . . . . . . . . . . . . . . . . . 50
2.4.2.8 ExtrinsicMotivations . . . . . . . . . . . . . . . . . . 51
2.4.2.9 Acceptance . . . . . . . . . . . . . . . . . . . . . . . 51
2.4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
2.5 Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
2.6 Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
2.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
III METHODOLOGY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.1 Research Question . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.2 Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.3 Research Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
3.3.1 Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
3.3.2 SurveyInstruments . . . . . . . . . . . . . . . . . . . . . . . 78
3.3.2.1 TAMSurvey . . . . . . . . . . . . . . . . . . . . . . . 78
3.3.2.2 MultipleIntelligencesDevelopmentalAssessmentScales 79
3.3.3 DataCollection . . . . . . . . . . . . . . . . . . . . . . . . . 80
3.3.4 DataAnalysisMethods . . . . . . . . . . . . . . . . . . . . . 83
3.3.4.1 RegressionAssumptions . . . . . . . . . . . . . . . . 85
3.3.4.2 LinearRelationship . . . . . . . . . . . . . . . . . . . 89
3.3.4.3 Outliers . . . . . . . . . . . . . . . . . . . . . . . . . 90
3.3.4.4 TestforHomogenityofVariance . . . . . . . . . . . . 91
3.3.4.5 CriteriaforSelecting Between CompetingModels . . 92
viii
Chapter Page
IV FINDINGS AND DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . 94
4.1 AnalysisofFindings . . . . . . . . . . . . . . . . . . . . . . . . . . 102
4.1.1 TechnologyAcceptanceModel . . . . . . . . . . . . . . . . . 102
4.1.1.1 Relationship between Perceived Usefulness and Per-
ceivedEaseofUse(PU ~ PEU) . . . . . . . . . . . . . 112
4.1.1.2 RelationshipbetweenAttitudeTowardUsingandPer-
ceived Usefulness and Perceived Ease of Use (ATU ~
PU +PEU) . . . . . . . . . . . . . . . . . . . . . . . 122
4.1.1.3 RelationshipbetweenBehavioralIntentiontoUseand
AttitudeToward Using(BIU ~ ATU) . . . . . . . . . . 134
4.1.2 MultipleIntelligencesDevelopmentalAssessmentScales(MI-
DAS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
4.1.3 RelationshipbetweentheTechnologyAcceptanceModeland
MultipleIntelligences(TAM~ MIDAS) . . . . . . . . . . . . 148
4.2 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
V CONCLUSIONS ANDRECOMMENDATIONS . . . . . . . . . . . . . . . 159
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
A CompiledTimeline. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
B Bloom’sTaxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
C elearning Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
D Factors from theLiterature . . . . . . . . . . . . . . . . . . . . . . . . . . 203
E Generations ofDistanceLearning . . . . . . . . . . . . . . . . . . . . . . . 207
F Learning Concepts andDomains . . . . . . . . . . . . . . . . . . . . . . . 211
G Learning Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
H MIDASProfile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
ix