Robin L. Donaldson May 5, 2010 Prospectus Defense Florida State University College of Communication and Information.

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Presentation transcript:

Robin L. Donaldson May 5, 2010 Prospectus Defense Florida State University College of Communication and Information

(Tsvetozar Georgiev, et al., 2004) Wireless delivery of learning content through handheld device – any time & anywhere.

Personal Use  32% use a cell phone for Internet access  19% use mobile Internet access  Learning & information resources Higher Education  Initial stages  Learning & information resources  Digital divide  Identifying value and determinants

 Technology acceptance research most mature research area in IS literature.  Limited research using technology acceptance theories  Unique characteristic of mobile learning  IS models may not fully address mobile learning

 Use technology acceptance theory as a theoretical framework to examine the determinants associated with community college students’ acceptance and use of mobile learning.

 TAM & TAM2 –  Do not consider variables that may negatively impact behavior (system characteristics, training, support)  Are not able to explain as much of the variance in user behavioral intention to use and actual use as UTAUT.  Failure to acknowledge individual differences such as age and gender  TAM3 -  Lack of supporting research  Non- academic participants and information systems

 Age and gender  Explain as much as 70% of the variance in user behavioral intention to use and actual use  Performance Expectancy ▪ “the degree to which an individual believes that using the system will help him or her to attain gains in job performance”  Effort Expectancy ▪ “the degree of ease associated with the use of the system”  Social Influence ▪ “the degree to which an individual perceives that important others believe he or she should use the new system”  Facilitating Conditions ▪ “the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system”

 Population being studied  Community college in north Florida  GED or Highschool degree  Large percentage required to take developmental courses & SLS 1510  Facilitating conditions  Diverse ages  Diverse access levels to technology  Participants  Convenience sample  All students enrolled in college credit courses

 Self-management of learning is “the extent to which an individual feels he or she is self- disciplined and can engage in autonomous learning”

 Voluntariness of Use  “the degree to which use of the innovation is perceived as being voluntary, or of free will”  Perceived playfulness -the extent to which the individual  perceives that his or her attention is focused,  curious during interaction,  finds the interaction intrinsically enjoyable or interesting.

 Quantitative descriptive and comparative research design  Utilize cross-sectional survey data  Mixed Method

 General  Convenience sample  Cross sectional  Course and participant availability for interviews  Survey  Statistical significance within the design does not imply cause-and-effect relationships  Self reported  Does not allow the researcher to obtain an in-depth understanding  Interviews  Protocols and transcribing is time consuming  Participants can be influenced by researcher  More difficult to analyze  Coding and theme development time consuming

 General  add breadth and depth of understanding of research questions  corroboration of research findings  Survey  cost effective  producing precise descriptions of large populations,  collection of a data from a large number of participants  repeated in other research or to assess if any changes that have taken place  Interviews  can probe for additional responses  can provide clarity to questions  observations of the respondent can be recorded  gain a more in-depth understanding of participants’ survey responses

 Procedure  Sequential explanatory strategy  Pre-existing survey ▪ Cross sectional  Interviews

 Better for answering “who” and “what” type questions.  Seeks to generalize results to a larger population  Very structured process  Answer straight forward questions  Employed to:  Estimate the characteristics and attitudes of a population  Explore relationships among variables  Describe the characteristics of large populations

 UTUAUT survey instrument, perceived playfulness, self-management of learning, voluntariness, demographic and opinion related  Demographic and opinion-related questions  Gender/age  access to a home computer  enrollment in developmental courses;  Internet experience;  frequency of use of mobile devices;  types of information, and library and learning resources currently used and interested in accessing

 Research Question 1. Are the following independent variables significant predictors of the behavioral intention to use mobile learning: performance expectancy, effort expectancy, social influence, facilitating conditions, voluntariness, perceived playfulness, and self-management of learning?  Research Question 2. Are the following independent variables significant predictors of the use of mobile learning: performance expectancy, effort expectancy, social influence, perceived playfulness, self-management of learning and facilitating conditions? Analysis: multiple regression Why? Used to explain relationships - determine if predictor variables are predicting a continuous dependent variable.

 Research Question 3. Is there a statistically significant difference between males and females on the behavioral intention to use mobile learning?  Research Question 4. Is there a statistically significant difference between males and females on the use of mobile learning? Analysis: independent samples t-test Why? comparing two groups gender and intention to use or actual use.

 Research Question 5. Are there statistically significant relationships among the participants’ age, behavioral intention to use mobile learning and the actual use of mobile learning? Analysis: bivariate Pearson correlations (r) Why? seek to determine if age is related to intention to use or actual use mobile learning.

 Better for answering how and why type questions.  Cannot be generalized  Descriptive in nature  Allow for an unstructured process  Can provide unanticipated information  Employed to:  obtain a narrow but in-depth understanding  how, why, and in what context participants make meaning of a given topic  obtain answers to questions such as “what,” “who,” “why” as it relates to the mobile learning survey items

 Research Setting and Population, and Participants  Convenience sampling  Selecting participants  Courses targeted

 Semi structured questions  Protocol  Interviewer  Script  Face-to-face, online, or phone

 Research Question 2 - Predictors of use  Research Question 4 - Difference in use between males and females  Research Question 5 - relationships among the participants’ age, intentions, and actual use Interview Question 1. What factors influence your actual use of mobile learning? What factors prevent you from using mobile learning? Interview Question 2. Do you believe there is a difference in the amount of time men spend on mobile learning when compared to the amount of time women spend on mobile learning ? Please explain your answer. Interview Question 3. Do you believe age affects your actual use of mobile learning? Please explain your answer.

 Content Analysis  Organize  Code the  Categorize  Narrative discussion  Interpretation to assign meaning

H1. Performance expectancy will not have a positive effect on behavioral intention to use mobile learning. H2. Effort expectancy will not have a positive effect on behavioral intention to use mobile learning. H3. Social influence will not have a positive effect on behavioral intention to use mobile learning. H4. Self-management of learning will not have a positive effect on behavioral intention to use mobile learning. H5. Perceived playfulness will not have a positive effect on behavioral intention to use mobile learning. H6. Voluntariness of use will not have a positive effect on behavioral intention to use mobile learning. H7. Behavioral intention will not have a positive influence on mobile learning use behavior. H8. Facilitating conditions will not have a positive influence on mobile learning use behavior.