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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Built upon Control Value Theory, this dissertation consists of two studies that examine university students’ future-oriented motivation, socio-emotional regulation, and diurnal cortisol patterns in understanding students’ well-being in the academic-context. Study 1 examined the roles that Learning-related Hopelessness and Future Time Perspective Connectedness play in predicting students’ diurnal cortisol patterns, diurnal cortisol slope (DS) and cortisol awakening response (CAR). Self-reported surveys were collected (N = 60), and diurnal cortisol samples were provided over two waves, the week before a mid-term examination (n = 46), and the week during students’ mid-term (n = 40). Using multi-nomial logistic regression, results showed that …

Contributors
Cheng, Katherine C., Husman, Jenefer, Lemery-Chalfant, Kathryn, et al.
Created Date
2017

Computer-based environments provide a window into the complex and multifaceted learning process. These systems often collect a vast amount of information concerning how users choose to engage and behave within the interface (i.e., click streams, language input, and choices). Researchers have begun to use this information to gain a deeper understanding of users’ cognition, attitudes, and abilities. This dissertation is comprised of two published articles that describe how post-hoc and real-time analyses of trace data provides fine-grained details about how users regulate, process, and approach various learning tasks within computer-based environments. This work aims to go beyond simply understanding users’ …

Contributors
Snow, Erica, McNamara, Danielle S, Connor, Carol, et al.
Created Date
2015