Date of Graduation

Spring 2018

Document Type


Degree Name

Doctor of Education (Ed.D.)


School of Education


Learning and Instruction


Learning & Instruction EdD

First Advisor

Mathew Mitchell

Second Advisor

Susan Prion

Third Advisor

Kevin Oh


Challenged to teach complex content to students, university educators in healthcare disciplines face a practical need for effective pedagogical approaches. The preponderance of multimedia and digital resources in and beyond college classrooms suggests that solutions to teaching complex content should leverage educational technology and multimedia resources. The multimedia principle of pretraining is one effective way to augment complex content learning. The pretraining principle specifies that learning is more effective when the names and characteristics of main terms and concepts are introduced before more nuanced and complex content is presented.

The purpose of this study was to investigate three approaches to pretraining—traditional pretraining, pretraining with a static concept map, and pretraining with an animated concept map—to examine the effect that the method of pretraining had on schematic knowledge and near transfer achievement. Pretraining has been found especially effective with learners who have low prior knowledge, with difficult and conceptual content, and with fast-paced instruction. The study also explored whether student perceptions about the usefulness of concept maps as a learning resource was reflected in achievement.

Using a quasi-experimental pretest-posttest design, 145 occupational therapy students were assigned to one of the three treatment conditions. Following a pretest to obtain a baseline of prior knowledge, the 12-minute pretraining treatment on the topic of sensory integration theory was administered via a video module, and then participants were exposed to a 60-minute multimedia lecture. An immediate posttest was completed, followed two weeks later by a delayed posttest. A questionnaire to measure participant perceptions about concept maps was also administered at the posttest.

Data analysis was completed using repeated measures ANOVA to examine gain scores from pretest to posttest to delayed posttest. On the measures of schematic knowledge and near transfer, the static concept map group demonstrated statistically significant gains and stronger scores than the other two groups. The findings suggest that the most effective of these three strategies for learning complex content is pretraining with a static concept map. Traditional pretraining is another viable option but pretraining with an animated concept map is not an efficient approach.


Educational Technology