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Browsing by Author "McDaniel, Kerrie"
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Item Frustration in Technology-Rich Learning Environments: A Scale for Assessing Student Frustration with E-Textbooks(BERA, 2022-03) Novak, Elena; McDaniel, Kerrie; Daday, Jerry; Soyturk, Ilker; Sociology, School of Liberal Artse-Textbooks and e-learning technologies have become ubiquitous in college and university courses as faculty seek out ways to provide more engaging, flexible and customizable learning opportunities for students. However, the same technologies that support learning can serve as a source of frustration. Research on frustration with technology is limited, especially in educational settings. This study examined student frustration with e-textbooks and the factors contributing to the frustration within undergraduate general biology courses through the development of an E-Text Frustration scale (ETFS). Exploratory factor analysis of the ETFS revealed a three-factor structure that provides quantified support for frustration with (1) e-textbook interactions on the screen, (2) problems with technology and (3) e-text curriculum integration. This structure was supported by a confirmatory factor analysis. The construct validity of the scale was established using a correlation analysis that revealed significant relationships among the three e-text frustration measures, cognitive load and motivation variables. Furthermore, the measurement invariance analyses indicated that the scale measures the same construct in the same way in males and females. Overall, the study findings suggest that the ETFS is a useful instrument with high reliability and validity evidence that can be used by researchers and practitioners. Implications for future research on frustration in technology-rich learning environments are discussed.Item Using a Mathematical Model of Motivation, Volition, and Performance to Examine Students’ E-Text Learning Experiences(Springer, 2018-10) Novak, Elena; Daday, Jerry; McDaniel, Kerrie; Sociology, School of Liberal ArtsThis empirical study used Keller’s (Technol Instr Cogn Learn 16:79–104, 2008b) motivation, volition, and performance (MVP) theory to develop and statistically evaluate a mathematical MVP model that can serve as a research and policy tool for evaluating students’ learning experiences in digital environments. Specifically, it explored undergraduate biology students’ learning and attitudes toward e-texts using a MVP mathematical model in two different e-text environments. A data set (N = 1334) that included student motivation and e-text information processing, frustration with using e-texts, and student ability variables was used to evaluate e-text satisfaction. A regression analysis of these variables revealed a significant model that explained 77% of the variation in student e-text satisfaction in both e-text learning environments. Student motivation and intrinsic cognitive load were positive predictors of student satisfaction, while extraneous cognitive load and student prior knowledge and background variables were negative predictors. Practical implications for e-text learning and generalizability of a mathematical MVP model are discussed.