Electronic Theses and Dissertations

Date

2024

Document Type

Dissertation

Degree Name

Doctor of Education

Department

Instruction & Curriculum Leadership

Committee Chair

Andrew Tawfik

Committee Member

Craig Shepherd

Committee Member

Logan Caldwell

Committee Member

Andrew Olney

Abstract

This non-experimental causal-comparative study aims to explore the possible effect of expertise on learning experience design (LXD) deviation identification and the classification of these deviations in alignment with provided learning experience design constructs within a learning technology. Additionally, this study challenges Nielsen’s (1993) Five User Assumption regarding how many novices or experts are needed to identify 80% of LXD deviations within the learning technology. According to Nielsen’s (1993) Five User Assumption, only five participants are required to identify 80% percent of usability problems; however, this assumption has yet to be tested within a learning technology (Nielsen, 1993). A convenience sample of 10 participants (five novices and five experts) were recruited from a business corporation in the Mid-South region of the United States. Participants were presented with a Gooru module and asked to identify LXD deviations present within the module and rate their severity. Before this, two outside LXD experts evaluated the learning technology and comprised a list of LXD deviations and classifications. Descriptive statistics were used to calculate the total average LXD deviations, average severity ratings, and average for the number of interaction within the learning environment and interaction within the learning space LXD problems that novices and experts identified. Results suggest that experience may impact the LXD deviation identification and classification, but there are no significant differences between groups on severity rating.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest.

Notes

Open Access

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