On Trust, Editorial Intent, and Recommender Systems for Supporting Higher Education

Institutional support of higher teaching and learning at scale poses three unique challenges. The first challenge is poor institutional accounting of instructors' use of educational platforms and software, especially the learning management system (LMS). The second challenge is a deficit of trust among stakeholders with unique job roles, prerogatives, and editorial preferences. The third challenge is one-size-fits-all, open-loop, or stopgap support processes. To address these challenges, this three-phase dissertation project proposes a novel sociotechnical framework for institutional support using trustworthy educational recommender systems. This framework accounts for LMS platform contexts, multiple stakeholders, and editorial trust relationships. In its first phase, the project proposes ``Depth of Use" (DOU): a first-principles framework of frequent LMS use-contexts. DOU is found to highlight low-adoption course cohorts, evaluate course design interventions, and improve IT emergency preparedness. The second phase of this project proposes a novel model of recommendation trustworthiness based in stakeholder allocation of RS editorial tasks. The study discovers a spectrum of faculty intentions about editorial division-of-labor and its frequent rationales, including student expertise, professional curriculum needs, authorship burdens at scale, and learner disengagement. In its third phase, the project investigates how editorial trust might be enhanced by transparency cues (guarantees, social proof, content tags). The dissertation concludes with a set of design guidelines to aid HCI practitioners in enhancing editorial transparency and algorithmic explainability, and increasing process efficacy of institutional support.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Computer Science & Applications

Department dc:contributor.department

Computer Science and#38; Applications

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2024

Author dc:creator

• Hassan, Taha

Chair dc:contributor.committeechair

• McCrickard, Donald Scott

Committee members dc:contributor.committeemember

• Edmison, Kenneth Robert
• Horning, Michael A.
• Knijnenburg, Bart
• Lee, Sang Won

• Trust
• recommender systems
• higher education
• institutional support
• process efficacy
• editorial intent
• roles
• educational technology

Statement dc:rights

• Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-nc-sa/4.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:41423

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/121125