Date of Award:

12-2013

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Engineering Education

Committee Chair(s)

Oenardi Lawanto

Committee

Oenardi Lawanto

Committee

Ning Fang

Committee

Kurt Becker

Committee

Edward Reeve

Committee

Suzanne Broughton

Abstract

The purpose of this research was to investigate high school students’ computer self-efficacy, cognitive actions, and metacognitive strategies in a self-regulated learning (SRL) framework while utilizing an interactive learning module. The researcher hypothesized that computer self-efficacy is correlated positively with cognitive actions and metacognitive strategies while the students are engaged with interactive learning modules. This research used a mixed-methods approach to answer the research questions. Two research questions guided this research: (1) How is students’ computer self-efficacy related to cognitive actions and metacognitive strategies while using interactive learning modules?; and (2) How do students plan monitor their cognitive actions, and regulate their monitoring strategies during learning with interactive learning modules?
This study utilized self-regulated learning framework that covered self-efficacy, cognitive, and metacognitive components. While self-efficacy was represented by computer self-efficacy, the metacognitive component was represented by planning, monitoring, and regulating strategies. Cognitive actions represent contextual activities while using interactive learning modules.

One hundred and thirteen students from two high schools in Northern Utah, USA
(i.e., InTech Collegiate High School and Logan High School) participated in this study. Each student worked on three modules: Boolean Logic, Minimum Spanning Tree, and Modeling Using Graphs. Due to the differences in class schedules between both schools, students at InTech Collegiate High School and Logan High School completed the activities within 2 and 4 days, respectively. Three different forms of data were gathered for analysis. These data included questionnaires, screen captured videos, and audio recordings of the interviews. The students completed three questionnaires: demographic, computer self-efficacy, and self-regulated computer-based learning questionnaires.
The findings of the study revealed that while computer self-efficacy was not positively correlated with cognitive actions, it was positively correlated with metacognitive strategies. Specifically, the findings revealed a significant positive correlation between computer self-efficacy and planning strategies. Screen-captured video analyses showed that there were different profiles of cognitive actions and metacognitive strategies between high and low computer self-efficacy groups. The findings were confirmed by issues from interview analyses between the groups.

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