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Stephanie Moore; Fatemeh Marzban – Distance Learning, 2024
Student mental health in higher education has been worsening for some time, even prior to the pandemic, showing up in various ways that learners struggle in online learning and other modalities. More recent research on health, sleep, and chronic illness as aspects of online learner mental fatigue and academic performance suggests that online…
Descriptors: Electronic Learning, Mental Health, Student Welfare, Caring
Lange, Christopher – Open Learning, 2023
Cognitive processing issues online may be reduced through e-learning personalisation, which allows learners to address individual learning needs by controlling how they process information. While some research shows that e-learning personalisation may actually complicate information processing under specific circumstances, this study examines…
Descriptors: Electronic Learning, Individualized Instruction, Cognitive Processes, Difficulty Level
Mary Katherine Watson; Elise M. Barrella; Kevin Skenes – Journal of Civil Engineering Education, 2024
At the onset of the COVID-19 pandemic, The Citadel transitioned from a face-to-face to an emergency online modality. We conducted a study to track changes in self-directed learning readiness (SDLR) among engineering students during the Spring 2020 semester, including trends based on demographic, performance, and cognitive load factors. SDLR was…
Descriptors: Independent Study, Undergraduate Students, Engineering Education, COVID-19
Hung-Tao M. Chen; Katelyn L. McClure; Thomas W. Morris – Technology, Knowledge and Learning, 2024
Picture-in-Picture (PIP) is an effective lecture video design that includes a screen capture video in the center and the instructor's talking head in one corner. Few research studies have directly investigated the usage of PIP lecture design by non-native English-speaking (NNES) instructors. The current study investigated the effects of PIP…
Descriptors: Undergraduate Students, Electronic Learning, Video Technology, Native Speakers
Kuhlmann, Shelbi L.; Bernacki, Matthew L.; Greene, Jeffrey A. – New Directions for Teaching and Learning, 2023
The affordances of computer-based learning environments make them powerful tools for conveying information in higher education. However, to most effectively use these environments, students must be adept at self-regulating their learning. This self-regulation is effortful, including a myriad of processes, including defining tasks, making plans,…
Descriptors: Multimedia Instruction, Learning Theories, Learning Strategies, Electronic Learning
Costley, Jamie; Lange, Christopher – Interactive Learning Environments, 2023
The use of e-learning personalization allows learners to control their learning by choosing which content to process and how to process it. In order to explain the processes that occur when students use e-learning personalization, this study looks at how it interacts with two other variables: sequencing and fading, a scaffolding technique where…
Descriptors: Electronic Learning, Individualized Instruction, Cognitive Processes, Difficulty Level
Moon, Hyunchang; Cheon, Jongphil; Kwon, Kyungbin – International Journal of Computer Science Education in Schools, 2022
To help novice learners overcome the obstacles of learning computational thinking (CT) through programming, it is vital to identify difficult CT components. This study aimed to determine the computational concepts and practices that learners may have difficulties acquiring and discuss how programming instructions should be designed to facilitate…
Descriptors: Difficulty Level, Computation, Thinking Skills, Programming
Lanqin Zheng; Yunchao Fan; Zichen Huang; Lei Gao – Journal of Computer Assisted Learning, 2024
Background: Online collaborative learning has been widely adopted in the field of education. However, learners often find it difficult to engage in collaboratively building knowledge and jointly regulating online collaborative learning. Objectives: The study compared the impacts of the three learning approaches on collaborative knowledge building,…
Descriptors: Cooperative Learning, Electronic Learning, College Students, Learning Strategies
Watson, Mary Katherine; Barrella, Elise M.; Skenes, Kevin – Journal of Civil Engineering Education, 2023
The COVID-19 pandemic created unprecedented disruptions in models for engineering student training. At The Citadel, an undergraduate-focused college in the Southeastern United States, a variety of modalities were implemented following the onset of the pandemic, including emergency online and Hyflex learning. We conducted a longitudinal study to…
Descriptors: Engineering Education, Undergraduate Students, COVID-19, Pandemics
Zheng, Lanqin; Zhong, Lu; Fan, Yunchao – Education and Information Technologies, 2023
Online collaborative learning (OCL) has been a mainstream pedagogy in the field of higher education. However, learners often produce off-topic information and engage less during online collaborative learning compared to other approaches. In addition, learners often cannot converge in knowledge, and they often do not know how to coregulate with…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Learning Analytics
Corina Milagro Mosqueira Taipe; Larissa Cristina Mazer; Nayara Paula Fernandes Martins Molina; Caíque Rossi Baldassarini; Gabriela Di Donato; Assis Do Carmo Pereira Júnior; Adriana Inocenti Miasso; Patricia Leila dos Santos – Journal of Latinos and Education, 2025
The COVID-19 pandemic has brought the challenge of online teaching to graduate courses, without prior preparation for students and teachers. In this context, the aim of the study was to identify sociodemographic predictors of difficulty in carrying out online academic activities by graduate students, by region of Brazil, during the COVID-19…
Descriptors: Social Class, Demography, Predictor Variables, Difficulty Level
Derek McClellan; Raymond J. Chastain; Marci S. DeCaro – Journal of Computing in Higher Education, 2024
Use of online video lectures is increasingly common. However, students may struggle to self-regulate their attention and passively process the content. This study examined whether, and for whom, different types of embedded learning prompts improve student learning from video lectures. Undergraduate physics students (N = 253) watched an online,…
Descriptors: Video Technology, Electronic Learning, Lecture Method, Prompting
Conrad, Colin; Deng, Qi; Caron, Isabelle; Shkurska, Oksana; Skerrett, Paulette; Sundararajan, Binod – British Journal of Educational Technology, 2022
The COVID-19 pandemic has posed a significant challenge to higher education and forced academic institutions across the globe to abruptly shift to remote teaching. Because of the emergent transition, higher education institutions continuously face difficulties in creating satisfactory online learning experiences that adhere to the new norms. This…
Descriptors: Student Attitudes, Electronic Learning, Student Satisfaction, Difficulty Level
Maria Assunção Flores; Ana Margarida Veiga Simão; Paula Costa Ferreira; Diana Pereira; Alexandra Barros; Paulo Flores; Eva Lopes Fernandes; Luís Costa – Research in Post-Compulsory Education, 2024
The closure of higher education institutions as a result of the COVID-19 pandemic has necessitated a sudden and unexpected transition from face-to-face to online teaching and learning. This paper draws on data from a broader study focusing on higher education students' perceptions and experiences of online learning during the first lockdown in…
Descriptors: Electronic Learning, Feedback (Response), COVID-19, Difficulty Level
Chih-Hung Wu; Kai-Di Tang; Kang-Lin Peng; Yueh-Min Huang; Chih-Hsing Liu – Educational Psychology, 2024
Cognitive styles and affective factors are critical factors affecting e-learning performance in this digital era. Learners can enhance their affective learning with a correct cognitive style. This study aims to examine various cognitive styles with effective learning measurement tools through subjective and objective instruments by observing…
Descriptors: Electronic Learning, Cognitive Style, Cognitive Processes, Difficulty Level