Relationship of Self-Efficacy to Stages of Concern in the Adoption of Innovation in Higher Education

Relationship of Self-Efficacy to Stages of Concern in the Adoption of Innovation in Higher Education

Dissertation presented by

• Amber D. Marcu

March 20, 2013 from 8:00am-10:00am

OverviewOverview

• Need for the Study• Literature Review• Method• Results• Discussion• Questions

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Need for the StudyNeed for the Study

Problem StatementProblem Statement

• Cost of innovation adoption.• A desire for a prescriptive innovation adoption

model or approach.• Higher education models lack research into

underlying psychological factors.• A desire to understand the Higher Ed. Adopter;• Affective characteristics, Psychological factors;• Parallels between innovation adoption models suggest

self-efficacy should be studied.

• Could self-efficacy be indicative of adoption?

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Purpose of the StudyPurpose of the Study

• Quantitative, statistical research.• Explore the relationship between various self-

efficacies and different stages of concern of an innovation adoption.

• CBAM Stages of Concern Questionnaire• SoC Profile

• Three Self-efficacies:1.General,

2.College teaching, and

3.Teaching with Technology.

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Research QuestionsResearch Questions

Innovation Identification1.Which stage of Rogers’ (2003) Diffusion of Innovations curve is the chosen innovation in?

Identify Stages of Concern (SoC)2.What is the Stages of Concern profile for instructors in the use of the innovation?

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Research QuestionsResearch Questions

Self-Efficacy and SoC3.What is the relationship between instructor general self-efficacy and the levels of the Stages of Concern (SoC)?4.What is the relationship between instructor teaching self-efficacy and the levels of the Stages of Concern (SoC)?5.What is the relationship between instructor technology self-efficacy and the levelsof the Stages of Concern (SoC)?

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Benefits of the StudyBenefits of the Study

1. To contribute results to an area of innovation diffusion in higher education that has not yet been fulfilled;

2. To determine if results from this study are consistent with those found in a sister innovation diffusion discipline, behavioral change;

3. To possibly suggest which (if any) self-efficacy may be a predictor of adoption categories (and ultimately successful adoption of an innovation).

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Literature ReviewLiterature Review

Innovation & Diffusion ModelsInnovation & Diffusion Models

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Technology Acceptance Model (TAM)Technology Acceptance Model (TAM)

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… the TAM can only explain “about 40% of the variance in individuals’ intention to use an IT and actual usage” (p. 276). In truth, the determinants responsible for users’ adoption are still unknown.

Innovation & Diffusion ModelsInnovation & Diffusion Models

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Diffusion of Innovations (Innovation-Decision Process)Diffusion of Innovations (Innovation-Decision Process)

5 Confirmation Seeking reinforcement or reversing the adoption decision.

4 Implementation Putting the innovation into practice.

3 Decision Engaging in activities leading to a choice. [Rejection or adoption]

2 Persuasion Developing an attitude (positive or negative) toward the innovation. [Perceived characteristics of the innovation]

1 Knowledge Exposure to the innovation and knowing how the innovation works. [Social system variables]

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Transtheoretical Behavioral Change Model (TBCM)Transtheoretical Behavioral Change Model (TBCM)

7 Termination Often excluded due to the impossibility of zero temptation and 100% self-efficacy.

6 Relapse Resumption of old behavior. (Evaluate trigger, motivation, and coping strategies)

5 Maintenance Continued commitment to sustaining new behavior. (6 months – 5 years)

4 Action Practicing new behavior. (3 – 6 months)

3 Preparation Some experience with making the change and testing out the new behavior. (Planning to act within 1 month.

2 Contemplation Ambivalent about change. (Not considering change within the next month.)

1 Pre-contemplation Not considering any change. (Ignorant of change.)14

CBAM Stages of Concern (SoC)CBAM Stages of Concern (SoC)

IMPACT

6 Refocusing Exploring more benefits. Making major changes or seeking replacement.

5 Collaboration Coordinating and Cooperating with others.

4 Consequence Concerned about the innovation’s impact on students.

TASK3 Management Using the innovation with support from

resources.

SELF

2 Personal Uncertain, unclear, unsure. Considering personal conflicts.

1 Informational Not worried. Gaining awareness of the innovation.

0 Unconcerned Unaware or unconcerned about the innovation.15

Self-Efficacy (SE)Self-Efficacy (SE)

• Defined as intrinsic “beliefs about one’s perceived capability … to attain designated type of performances and achieve specific results” (Pajares, 1996, p. 546).

• TBCM already includes and assumes SE.• High SE corresponds to higher stage resolve.• High SE corresponds to higher sustaining period.• Marcus & Owen (1992) suggest that SE may

actually be clear indicators of stage change readiness.

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MethodMethod

Research Study DesignResearch Study Design

Examine the relationship between SoC and 3 types of SE (general, college teaching, and teaching with technology).

•1 survey instrument • Questionnaire, 5 parts

•Population• Large university• Actively teaching faculty

•Statistical analysis• Chi-square goodness-of-fit test• Logical and nominal regression

•A pilot study was conducted a year prior.18

Population Profile & SettingPopulation Profile & Setting

• Mid-Atlantic, land-grant university.• Population: Actively teaching faculty.• 1,713 potential participants

• Sample Population• 150 responses analyzed (~9% response rate)• 51% Female, 46% Male, 2.7% unknown

• Goodness of Fit• Unusually high number of non-research faculty• Sample does not perfectly represent population

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InstrumentsInstruments

One Questionnaire, five parts:

1.Demographic questions

2.Prieto’s College Teaching Self-Efficacy Scale (CTSES)

3.Lichty’s Teaching with Technology Self Efficacy Scale (MUTEBI)

4.Chen’s New General Self-Efficacy (NGSE) Scale

5.Hall & Hord’s Stages of Concern Questionnaire (SoCQ)

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ProcedureProcedure

• Google Applications for Education was the innovation under study.

• Ran study 7 weeks (Dec 2012 to Jan 2013)• Participants contacted via email.• Lists obtained from director of the LMS and

director of instructional development

• Email invitation includes consent form & link to online survey.

• Email reminder sent in early January.

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Data Analysis MethodologyData Analysis Methodology

• Each set of SE responses was averaged together for overall scores and std. dev. for the group.

• Descriptive statistics stratified by demographic variables.

• Chi-square goodness-of-fit test• How well does the sample reflect population?

• SoCQ profiles• “Peak” concerns represented in categories

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Data Analysis MethodologyData Analysis Methodology

For each of the three research questions pertaining to SE and SoC, the nominal logistic regression was run where:

1.X = General SE, Y = 3 Categories of the 7 Stages of Concern;

2.X = Teaching SE, Y = 3 Categories of the 7 Stages of Concern;

3.X = Teaching with Tech SE, Y = 3 Categories of the 7 Stages of Concern.

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Research Question 1 ResultsResearch Question 1 Results

Which stage of Rogers’ Diffusion of Innovations curve is the chosen innovation in?•Google Apps for Education is a new and emerging innovation.•Only innovators and early adopters so far• 24% = “non-users”• 62% = “novice” or “intermediate”• 14% = “old hand”

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Research Question 2 ResultsResearch Question 2 Results

What is the Stages of Concern profile for instructors in the use of the innovation?•Majority of users have or had used Google Apps in some capacity.•Peak Scores• 95.2% = SELF (Stages 0-2)• 2.1% = TASK (Stage 3)• 2.7% = IMPACT (Stages 4-6)

•No primary peak scores in Stage 4 or 6•“W” shaped and “tailing up” profiles

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Research Question 3 ResultsResearch Question 3 Results

What is the relationship between instructor general self-efficacy and the levels of the Stages of Concern (SoC)?•Nominal logistic regression.•X = General SE group average, Y = 3 Categories (SELF, TASK, IMPACT)•p-value = 0.9670•General self-efficacy is not related to the levels of the Stages of Concern

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Research Question 4 ResultsResearch Question 4 Results

What is the relationship between instructor teaching self-efficacy and the levels of the Stages of Concern (SoC)?•Nominal logistic regression.•X = Teaching SE group average, Y = 3 Categories (SELF, TASK, IMPACT)•p-value = 0.6416•Teaching self-efficacy is not related to the levels of the Stages of Concern

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Research Question 5 ResultsResearch Question 5 Results

What is the relationship between instructor technology self-efficacy and the levels of the Stages of Concern (SoC)?•Nominal logistic regression.•X = Teaching with Technology SE group average, Y = 3 Categories (SELF, TASK, IMPACT)•p-value = 0.0980•Instructor technology self-efficacy is not related to the levels of the Stages of Concern

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DiscussionDiscussion

• Analysis at this point of the innovation revealed no relationships to Stages of Concern.

• Why?• Google Apps for Education is an early-stage

innovation• Adoption primarily by “innovators” & “early majority” users.• Majority of users in “SELF” category.• Even “mandated” Gmail users may not perceive

themselves as Google Apps users.

• Possibly a poorly-managed innovation.

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RecommendationsRecommendations

• Run study at several different stages in the life of an innovation.

• Use of another diffusion model.• Examine other psychological factors.

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Thank you:Dr. Cennamo, Dr. Moore, Dr. Evans, and Dr. Doolittle

Thank you:Dr. Cennamo, Dr. Moore, Dr. Evans, and Dr. Doolittle

Dissertation presented by

• Amber D. Marcu

March 20, 2012 from 8:00am-10:00am

Questions?