Building Schemata for Tax Provision Learning Based On Cognitive Load Theory and Constructivism
Date of Award
Doctor of Philosophy (PhD)
Jennifer R. Joe
R. Lynn Hannan
Lisa S. Lambert
Jennifer K. Schafer
This study investigated whether different instructional methodologies have an impact on learning a complex accounting task: tax provision work. To become proficient in making tax provision judgments, an accountant must understand the rules and principles of GAAP and the rules and regulations governing income tax reporting. However, these two sets of rules are often in direct opposition. Using cognitive load theory and constructivist learning theory as a framework, this study predicted how schema acquisition, a key component of learning, could improve tax provision performance. Greater schema acquisition should in turn lead to more accurate performance. Hypotheses include the following: (a) participants who learn using a systems instructional method will perform better than participants who learn using traditional instructional method, (b) participants who practice actively should perform better than participants who practice passively, and (c) the relationship between instructional method and performance will be moderated by the practice method. These hypotheses were tested using a 2 x 2 between-subjects experiment, manipulating instructional method and practice method as independent variables. The results of this study are inconclusive. The statistically significant findings are invalid due to potentially unequal pre-tax knowledge among the subjects, and several hypotheses were not supported. The results of this study had the potential to benefit theory, practice, and education by identifying the most effective combination of instructional method and practice method to build a tax provision schema in a novice learner. However, due to design flaws, this study did not realize that potential.
Best, Ellen, "Building Schemata for Tax Provision Learning Based On Cognitive Load Theory and Constructivism." Dissertation, Georgia State University, 2013.