impact of faculty learning styles on the integration of media-rich content into instruction

Impact of Faculty Learning Styles on the Integration of Media-Rich Content into Instruction

Impact of Faculty Learning Styles on the Integration of Media-Rich Content into InstructionCeleste M. Schwartz, Ph.D.Montgomery County Community CollegeBlue Bell, [email protected] Higher Education ChallengesNational Education Technology Plans (NETP) request that faculty use technology to create engaging learning environments.EDUCAUSE 2009 Teaching and Learning Technology Challenges of student engagement and faculty integration of new technologies into teaching and learning.Federal Higher Education Challenge to increase the percentage of 2- and 4- year degree completers. BackgroundWhy do some faculty embrace and integrate new proven technologies sooner than others?The GapLittle is known regarding different learning styles of faculty and its impact on their use of technology in teaching.

TheoriesLearning Styles & Technology Implementation Based on human learning and development theories, and information systems theories

Theories UsedTechnology Acceptance Model (Davis) - the perceived usefulness and perceived ease of use of a technologyKolbs Experiential Learning Theory (Kolb) - an individuals preferred learning style

Research QuestionsAre there differences, based on their learning styles, in community college full-time facultys perceived usefulness of integrating media-rich content into their courses, after controlling for effects due to age?Are there differences, based on their learning styles, in community college full-time facultys perceived ease of integrating media-rich content into their courses, after controlling for effects due to age?Is there a significant correlation between community college full-time facultys perceived usefulness of integrating media-rich content into their courses and their perceived ease of integrating media-rich content into their courses?

Media-rich Content DefinitionMedia-rich content is defined as technologies that enable learners to participate in an engaging interactive learning environment supported by technologies. Media-rich content provides learners with the ability to see, hear, and interact with multiple communication streams synchronously and asynchronously.

Instruments used in the studyDemographic questionnaire

Kolbs Learning Style Inventory (LSI)

Daviss Technology Acceptance Model (TAM)Demographics InstrumentAgeDisciplineGenderProfessional Development Integration of Media-rich contentKolbs Learning Style InventoryKolbs Experiential Learning TheoryTwo preference dimensionsperception dimension - two opposite dimensions for perception of the experience are concrete experience (CE) and abstract conceptualization (AC)processing dimension - two opposite dimensions for processing the experience are reflective observation (RO) and active experimentation (AE). Kolbs Learning Style InventoryCombining one perception preference and one processing preference results in one of four learning styles.

Diverger (CE & RO)Converger (AC & AE) Accommodator (CE & AE)Assimilator (AC & RO)Learning ModesConcrete Experience (CE) Active ReflectiveExperimentation (AE) Observation (RO)

Abstract Conceptualization (AC)Learning Style Types CEAccommodatorDiverger

AE RO

ConvergerAssimilator

ACData AnalysesResearch Question 1 & 2 used a casual-comparative research design

Research Question 3 used a non-experimental correlational design.

Daviss Technology Acceptance ModelPerception Survey

Perceived Usefulness (PU)

Perceived Ease of Use (PEOU)Anticipated FindingsFaculty members preferred learning styles identified as converging or accommodating will be more likely to perceive usefulness of integrating media-rich content into their courses than faculty members identified as diverging or assimilating. Faculty members preferred learning styles identified as converging or accommodating will be more likely to perceive ease of integrating media-rich content into their courses than faculty members identified as diverging or assimilating.Significant correlation between facultys perceived usefulness of integrating media-rich content into their courses and their perceived ease of use of integrating media-rich content into their courses. FindingsRespondents from the sample population were 149 (valid responses) which represented a slightly higher number of female respondents to the sample population.The respondents represented 35 academic disciplines and 5 academic divisions.Participants LSI types34 divergers 50 assimilators 35 accommodators30 convergers

FindingsAnalyses for alpha scoresCronbach alpha scores for LSI learning cycle mode CE, RO, AC, &,AE were all above the acceptable value of .70.Cronbach alpha scores for TAM PU and PEOU were also above the acceptable value of .70.NOTE: Because Cronbach alphas were strong the research questions could be examined.Analyses of the relationship between age and PU, age and PEOU, and age and LSI typePearson product moment found no significant correlation between age and PU scoresPearson product moment found a small relationship between age and PEOU scores.As expected there was no relationship between age and LSI type.FindingsMain AnalysesAnova was not able to explain the observed differences in PU scores based on LSI scores.Ancova was run to determine the impact of LSI type on PEOU scores after controlling for age. The covariate age did not appear to contribute meaning information Anova found that the LSI scores impacted the PEOU scores based on the finding with a more stringent alpha level of p