The use of digital learning technologies and platforms has skyrocketed over the past decade. Although digital materials have many advantages, using them can be frustrating to students. Frustration is a negative achievement emotion that can serve as a barrier to learning. Therefore, understanding how frustration influences student learning and attitudes toward technology can help create more engaging and effective digital learning experiences. Previous research has identified three areas of frustration with academic e-textbooks (e-text frustration): (1) interactions with e-text interface, (2) technical difficulties, and (3) curriculum integration. This study investigated the relationships among e-text frustration and motivational, cognitive, attitudinal, academic, and demographic factors that impact frustration with e-texts in undergraduate biology classes. Extraneous cognitive load and motivation significantly predicted each of the three frustration constituents. Surprisingly, intrinsic cognitive load failed to predict e-text frustration. This study makes an important contribution to emotion research in education by examining the factors that impact learning in digital settings and emotions. Its implications are relevant for educators, researchers, and developers of digital learning materials and environments.

e-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. Practitioner notes What is already known about this topic Prolonged student frustration can be harmful to learning. Educational technology may introduce an additional layer of factors that contribute to end-user frustration with technology. Research on frustration with educational technology is scarce. What this paper adds We developed and validated a scale for assessing students' frustration with e-textbooks. The E-Text Frustration scale includes three factors: frustration with technology, e-text screen interactions and e-text curriculum. The three factors correlated with students' e-text cognitive load and motivation to learn. Implications for practice and/or policy The identified factors represent barriers to students' successful learning with e-textbooks. Educators can reduce student frustration by aligning the curriculum with e-text materials. Student sources of frustration with technology should be studied systematically to reduce frustration in technology-rich learning environments.

This 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.

The faculty in a biology department at a four-year public comprehensive university adopted e-texts for all 100 and 200 level biology courses with the primary motivation of reducing textbook costs to students. This study examines the students’ perceptions of the e-texts adopted for these 100 and 200 level biology courses. An online questionnaire was developed and administered in multiple sections of six 100 and 200 level biology courses during the spring and fall semesters of 2014 to measure student perceptions of the e-texts used in these courses. Results suggest a bimodal distribution among our sample (N = 2,152) of student participants. However, there are statistically significant and noteworthy exceptions to this general pattern. Black students reported a significantly higher satisfaction with e-texts compared to white students, and students repeating one of these courses reported significantly higher levels of satisfaction with the e-text compared to students taking the for the first time. Additionally, students with lower grade point averages (GPAs) preferred the e-text significantly more compared to those with higher GPAs. Further analyses reveal that the majority of student participants perceived the use of value-added technologies, such as e-homework, favorably.

This study is motivated by recent investigations in measuring intrinsic and extraneous cognitive load associated with human learning in non-digital environments (Leppink et al. (2013) Development of an instrument for measuring different types of cognitive load. Behav. Res. Methods., 45, 1058-1072; Leppink et al.(2014) Effects of pairs of problems and examples on task performance and different types of cognitive load. Learn. Instr., 30, 32-42) and the increased interest and adoption rates of e-textbooks in higher education. Intrinsic cognitive load associated with the processing of new information is influenced by students' prior knowledge and learning task difficulty; whereas, extraneous cognitive load involves processes that do not contribute to or even hamper knowledge construction. We adapted Leppink and colleagues' cognitive load questionnaire to measure intrinsic and extraneous cognitive complexity of e-textbook learning. Undergraduate biology students (N = 1337) completed an online questionnaire, which included e-text cognitive load questions and questions about their preferences and attitudes toward e-textbooks. Results from exploratory and confirmatory factor analyses yielded some support for the use of two constructs of intrinsic and extraneous cognitive load with e-textbook learning. The instrument validity was established using an analysis of the relationships between intrinsic and extraneous cognitive load and student's academic achievement, e-text preferences and attitude measures. Reading off a screen and navigating and manipulating e-texts were among the factors that negatively correlated with e-text extraneous cognitive load.

A new generation has entered higher education that learns differently from generations before. To meet the changing needs of this generation, a biology department at a four year university introduced e-textbooks and e-materials in the fall of 2013 to most low-level classes. An unforeseen product of this shift was a change in the way that some faculty taught and assessed their classes. This study examines the changes in pedagogical techniques among professors of 100- and 200-level biology classes due to introduction of new e-text and ematerials. Syllabi were collected from these classes pre- and post-implementation and common characteristics were inductively coded and statistically analyzed to identify changes in pedagogy. Interviews were conducted of faculty teaching these classes. It was found that biology professors increased their average number of homework assignments by 23%. There was also a 458% increase in the number of courses that offered homework assignments as a means of assessment, indicating a shift from traditional summative assessments to more formative assessments after the implementation of the e-materials. This work provides insight into simple strategies that affect pedagogy in higher education STEM disciplines