Matching Items (5)
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- All Subjects: Well-being
- Creators: Nakagawa, Kathryn
- Creators: Jimenez Arista, Laura
- Member of: Theses and Dissertations
Description
This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive (ICAP) framework. The current work combined these two cognitive-based approaches to design collaborative learning activities that can serve as alternatives to existing methods, which carry limitations and challenges. The "preparing-to-interact" method avoids the need for training students in specific collaboration skills or guiding/scripting their dialogic behaviors, while providing the opportunity for students to acquire the necessary prior knowledge for maximizing their discussions towards learning. The study used a 2x2 experimental design, investigating the factors of Preparation (No Prep and Prep) and Type of Activity (Active and Constructive) on deep and shallow learning. The sample was community college students in introductory psychology classes; the domain tested was "memory," in particular, concepts related to the process of remembering/forgetting information. Results showed that Preparation was a significant factor affecting deep learning, while shallow learning was not affected differently by the interventions. Essentially, equalizing time-on-task and content across all conditions, time spent individually preparing by working on the task alone and then discussing the content with a partner produced deeper learning than engaging in the task jointly for the duration of the learning period. Type of Task was not a significant factor in learning outcomes, however, exploratory analyses showed evidence of Constructive-type behaviors leading to deeper learning of the content. Additionally, a novel method of multilevel analysis (MLA) was used to examine the data to account for the dependency between partners within dyads. This work showed that "preparing-to-interact" is a way to maximize the benefits of collaborative learning. When students are first cognitively prepared, they seem to make the most efficient use of discussion towards learning, engage more deeply in the content during learning, leading to deeper knowledge of the content. Additionally, in using MLA to account for subject nonindependency, this work introduces new questions about the validity of statistical analyses for dyadic data.
ContributorsLam, Rachel Jane (Author) / Nakagawa, Kathryn (Thesis advisor) / Green, Samuel (Committee member) / Stamm, Jill (Committee member) / Arizona State University (Publisher)
Created2013
Description
The primary objective of this study was to develop the Perceived Control of the Attribution Process Scale (PCAPS), a measure of metacognitive beliefs of causality, or a perceived control of the attribution process. The PCAPS included two subscales: perceived control of attributions (PCA), and awareness of the motivational consequences of attributions (AMC). Study 1 (a pilot study) generated scale items, explored suitable measurement formats, and provided initial evidence for the validity of an event-specific version of the scale. Study 2 achieved several outcomes; Study 2a provided strong evidence for the validity and reliability of the PCA and AMC subscales, and showed that they represent separate constructs. Study 2b demonstrated the predictive validity of the scale and provided support for the perceived control of the attribution process model. This study revealed that those who adopt these beliefs are significantly more likely to experience autonomy and well-being. Study 2c revealed that these constructs are influenced by context, yet they lead to adaptive outcomes regardless of this contextual-specificity. These findings suggest that there are individual differences in metacognitive beliefs of causality and that these differences have measurable motivational implications.
ContributorsFishman, Evan Jacob (Author) / Nakagawa, Kathryn (Committee member) / Husman, Jenefer (Committee member) / Graham, Steve (Committee member) / Moore, Elsie (Committee member) / Arizona State University (Publisher)
Created2014
Description
ABSTRACT The major hypothesis tested in this research is that the psychological well-being and life satisfaction of elderly adult individuals can be predicted from religiosity (organizational and non-organizational religious beliefs and behaviors). The sample consisted of 142 adults between the ages of 65-90, with the majority in the 65-70 age group (48%) (SD = 1.176). The entire sample resides in the state of Arizona, in both urban and rural communities. Participants were administered a questionnaire which requested demographic information, and three instruments: the Duke University Religion Index (the DUREL), and the Affect Balance Scale and the Life Satisfaction Index - Z (LSIZ). Correlational and Multiple regression analyses were used to examine the relation between these adults' psychological well-being, life satisfaction and their religiosity. Independent t-tests were also used to examine possible sex, ethnic and religiosity effects on psychological well-being and life satisfaction. Findings revealed that psychological well-being and life satisfaction are higher when religiosity is higher, regardless of sex or ethnicity. These findings are consistent with those of previous research in this field.
ContributorsMoreno-Weinert, Inez (Author) / Moore, Elsie (Thesis advisor) / Nakagawa, Kathryn (Committee member) / Ladd, Becky (Committee member) / Cohen, Adam (Committee member) / Arizona State University (Publisher)
Created2012
Description
During the global COVID-19 pandemic in 2020, many universities shifted their focus to hosting classes and events online for their student population in order to keep them engaged. The present study investigated whether an association exists between student engagement (an individual’s engagement with class and campus) and resilience. A single-shot survey was administered to 200 participants currently enrolled as undergraduate students at Arizona State University. A multiple regression analysis and Pearson correlations were calculated. A moderate, significant correlation was found between student engagement (total score) and resilience. A significant correlation was found between cognitive engagement (student’s approach and understanding of his learning) and resilience and between valuing and resilience. Contrary to expectations, participation was not associated with resilience. Potential explanations for these results were explored and practical applications for the university were discussed.
ContributorsEmmanuelli, Michelle (Author) / Jimenez Arista, Laura (Thesis director) / Sever, Amy (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.
ContributorsBarolli, Adeiron (Author) / Jimenez Arista, Laura (Thesis director) / Wilson, Jeffrey (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05