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Full Issue: Journal On Empowering Teaching Excellence, Volume 8, Issue 1, Spring 2024

Journal on Empowering Teaching Excellence

The full-length Spring 2024 issue (Volume 8, Issue 1) of the Journal on Empowering Teaching Excellence

Access the online Pressbooks version (with downloadable EPUB format) here.

The Spring 2024 issue presents research and commentary on trends and best practices in higher education, with a focus on public policy implications for literacy instruction, adjusting instructional programs to Generation Z learning preferences in English courses, and increasing students' critical thinking and self-reported ability through an interrupted case study approach.

2024 Nsu Undergraduate Commencement Program, Nova Southeastern University

NSU Commencement Programs

No abstract provided.

2024 Nsu Graduate Commencement Program, Nova Southeastern University

NSU Commencement Programs

No abstract provided.

Burnout And Work Fatigue In Contingent Faculty During The Covid-19 Pandemic, Gina Dimartino

Dissertations

The COVID-19 pandemic and immediate shift to remote learning had a major impact on faculty and students in higher education institutions (HEIs). As a result of the pandemic, many stakeholders in HEIs have experienced burnout and work fatigue, specifically, contingent/adjunct faculty. Contingent/adjunct faculty comprise a majority of faculty who serve students in colleges and universities across the country.

As the needs of students increased during the pandemic, contingent/adjunct faculty experienced increased workloads due to the additional support needed by diverse and challenged students. This further intensified the unique challenges faced by contingent faculty that existed prior to the pandemic in …

Differences In Student-Ai Interaction Process On A Drawing Task: Focusing On Students' Attitude Towards Ai And The Level Of Drawing Skills, Jinhee Kim, Yoonhee Ham, Sang-Soog Lee

STEMPS Faculty Publications

Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in …