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The theoretical framework used in this study is Mezirow's Transformative Learning Theory (1997/2012), which indicates that transformation is possible only if our frames of references—the beliefs and values shaped by experience and cultural context—are changed. Transformative Learning Theory will provide the analytic lens for data analysis. This study employs a case study research methodology to determine what effect the instructor's use of technology has on student's willingness to use it in their own practice, and how well students transform their frames of reference about the use of technology in teaching. The strength of case study research is its use of multiple data types to describe a "case" or context (Yin, 2009).
Data were collected through surveys, artifacts, and reflections. The surveys were issued as a pre and post, though participant match-up was not possible due to the variability in the students who completed the first one and the second. The seven questions in the pre and post assessment survey were individually aligned to each of the seven International Society for Technology in Education (ISTE) Standards for Educators, and the response options were aligned with each set of standard indicators. This implies that the more indicators the students selected, the more they aligned to each specific standard. Findings suggest that all participants felt they were prepared to positively contribute to society in a digital world in various ways.
The Frames of Reference survey looked at three general themes from Transformative Learning Theory: Attitudes and Beliefs, Relationships and Values, and Models and Experience. Findings indicate that while participants value technology, they are still trying to feel comfortable with it as a part of their teaching, even though they do feel they have the general skills needed.
The technology innovation models Substitution Augmentation Modification Redefinition (SAMR) (Puentedura, 2006) and Technological Pedagogical Content Knowledge (TPACK) (Mishra and Koehler, 2006) served as guidelines to evaluate the artifacts and demos collected for this study. An adapted rubric of the SAMR model served this purpose, and included descriptors for tasks involving substitution, augmentation, modification, and redefinition, in order to determine to what degree technology integration was employed.
Reflection Data was analyzed using the qualitative analysis software Atlas.ti, using structured themes related to transformative learning theory. Themes include the following: attitudes and beliefs about technology, value assigned to technology, and experiences that color their technology use. Overall, the reflections tracked a trend of whether students demonstrated a transformation of values and beliefs, though this analysis only applied to those participants that completed more than one reflection.
Leticia De Leon, The University of Texas - Rio Grande Valley
Zulmaris Diaz, University of Texas Rio Grande Valley
Janet Martinez, University of Texas Rio Grande Valley
Carmen Peña, The University of Texas - Rio Grande Valley
Michael Whitacre, The University of Texas - Pan American