Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Psychology

Abstract

Quality requirements are not easy to define. In higher Education, defining quality requirements and communicating those requirements to students may be accomplished through a variety of mechanisms. Students still may not know what it takes to get a good grade on an assignment and may have to wait for an instructor to clarify the assignment. This study was conducted because students and instructors may have different opinions as to which forms of feedforward and what technology are best to convey assignment requirements. The purpose of this study was to determine effective feedforward mechanisms as well as the technology used to convey quality requirements for assignments. A Delphi Panel was utilized to identify feedforward mechanisms as well as technology currently used. A survey was conducted to quantify waste in the assignment process via statistical testing. Minitab 19 with selected T-tests were used to determine if there is a difference between students and instructors as to what feedforward mechanisms or combinations of feedforward mechanisms are preferred to effectively convey quality requirements. The study involved Master-degree seeking students and instructors as well as university resources from teaching excellence programs from three universities. Combining the information from the Delphi Panel and the survey, a model was created that using the syllabus and instructions as mechanisms to convey quality requirements for assignments. Depending on the assignment a rubric, criteria sheet, or model/sample may be used to clarify requirements. Using the web-based learning management system allows students to access information outside of the classroom and at any time. The LMS can contain written as well as video or audio recordings of assignment information. The results of this study have led to improvements in a Project Management course at the University of Kansas.

Download

Share

COinS