An Automated Feedback System Framework to Facilitate Instructor Self-Assessment

dc.contributor.advisorMcCuaig, Judi
dc.contributor.advisorGillis, Dan
dc.contributor.authorAlmutawa, Ammar
dc.date.accessioned2023-04-13T20:24:47Z
dc.date.available2023-04-13T20:24:47Z
dc.date.copyright2023-04
dc.date.created2023-04-12
dc.degree.departmentSchool of Computer Scienceen_US
dc.degree.grantorUniversity of Guelphen
dc.degree.nameDoctor of Philosophyen_US
dc.degree.programmeComputational Sciencesen_US
dc.description.abstractInstructors in higher education face challenges getting feedback about their instructional artifacts. It could impact instructors' performance and students' learning outcomes. Exploring a better way to assist instructors to self-examine their work is important. This research investigated the creation of a framework to automatically generate individualized feedback for instructors regarding their instructional artifacts. It limited the investigation to use one instructional artifact, the course outline preparation, as the proof-of-concept experiment to demonstrate the potential of automatically providing instructors with feedback about communication, organizational, and planning instructional skills.Limited studies investigated instructors' skills. This research conducted a thorough literature review to identify the skills of successful instructors and the process used to evaluate those skills. It used a mixed approach looking for specific skills that appear more frequently and indicate clear impacts on success. The investigation concluded with a clear identification of the essential skills possessed by good instructors that can help to understand how to improve the quality of their instructions.Furthermore, this research conducted a single exploratory survey using closed-ended questions. The goal of the survey's questions is to gather opinions from participants in different departments and colleges from the University of Guelph. The results investigated the essential components in the course outlines and how they impact instructional skills. The outcomes from the survey demonstrated the data components used in data analysis. The data analysis outcomes identified the way to design the proposed framework, which can help university instructors. This research made three major contributions: a) the identification of essential skills for successful instructors; b) the necessary components to design the proposed Automated Feedback System for Instructors (AFSI) framework; and c) the exploration of data to demonstrate that feedback topics can be automatically determined. The objective of the AFSI feedback is not to judge the instructors' performance but to provide private and immediate feedback that can help instructors to adjust their work as the semester progresses.en_US
dc.description.sponsorshipThe University of Jeddah
dc.identifier.urihttps://hdl.handle.net/10214/27497
dc.language.isoenen_US
dc.publisherUniversity of Guelphen
dc.rights.licenseAll items in the Atrium are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectAutomated Feedback Systemsen_US
dc.subjectAssessmenten_US
dc.subjectCourse Outlinesen_US
dc.subjectEvaluationen_US
dc.subjectFeedbacken_US
dc.subjectHigher Educationen_US
dc.subjectInstructional Artifactsen_US
dc.subjectInstructors Skillsen_US
dc.subjectUniversity Instructorsen_US
dc.titleAn Automated Feedback System Framework to Facilitate Instructor Self-Assessmenten_US
dc.typeThesisen

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