Beyond the Virtual Classroom: Computer Self-Efficacy and Its Effects on Learning Burnout in Asynchronous E-learning

Asynchronous e-learning allows for targeted teaching, particularly advantageous when bedside and didactic education is insufficient. An asynchronous e-learning curriculum has not been studied across multiple centers in the context of a clinical rotation. We hypothesize that an asynchronous e-learning curriculum during the pediatric emergency medicine (EM) rotation improves medical knowledge among residents and students across multiple participating centers. Trainees on pediatric EM rotations at four large pediatric centers from 2012 to 2013 were randomized in a Solomon four-group design. The experimental arms received an asynchronous e-learning curriculum consisting of nine Web-based, interactive, peer-reviewed Flash/HTML5 modules. Postrotation testing and in-training examination (ITE) scores quantified improvements in knowledge. A 2 × 2 analysis of covariance (ANCOVA) tested interaction and main effects, and Pearson's correlation tested associations between module usage, scores, and ITE scores. A total of 256 of 458 participants completed all study elements; 104 had access to asynchronous e-learning modules, and 152 were controls who used the current education standards. No pretest sensitization was found (p = 0.75). Use of asynchronous e-learning modules was associated with an improvement in posttest scores (p < 0.001), from a mean score of 18.45 (95% confidence interval [CI] = 17.92 to 18.98) to 21.30 (95% CI = 20.69 to 21.91), a large effect (partial η(2) = 0.19). Posttest scores correlated with ITE scores (r(2) = 0.14, p < 0.001) among pediatric residents. Asynchronous e-learning is an effective educational tool to improve knowledge in a clinical rotation. Web-based asynchronous e-learning is a promising modality to standardize education among multiple institutions with common curricula, particularly in clinical rotations where scheduling difficulties, seasonality, and variable experiences limit in-hospital learning.

Objective To explore the correlations among academic pressure, self-compassion and learning burnout in nursing college students, so as to provide a basis for promoting nursing students to learn. Methods In May 2018, we selected 303 nursing college students of first to third grade in a vocational college in Guangzhou as subjects by convenience sampling. All of the students were investigated with the Academic Pressure Scale, Self-Compassion Scale and Learning Burnout Scale. Results The scores of academic pressure, self-compassion and learning burnout were (0.40±0.14) , (3.20±0.42) and (2.82±0.51) respectively with 31.4% for the detection rate of learning burnout. Pearson correlation analysis showed that academic pressure of nursing students had a negative correlation with self-compassion (r=-0.14, P<0.05) , and had a positive correlation with learning burnout (r=0.27, P<0.05) ; self-compassion had a negative correlation with learning burnout (r=-0.59, P<0.05) . Academic pressure had an indirect impact on learning burnout mediated by self-compassion. Conclusions Nursing college students have a middle level of learning burnout. Nursing educators could relieve the academic pressure and learning burnout by improving self-compassion of students. Key words: Students, nursing; Junior college; Academic pressure; Self-compassion; Learning burnout

Although cross-sectional studies on the learning status of nursing undergraduates during the COVID-19 epidemic have surged, few studies have explored the normalization of COVID-19 on students' learning burnout and mental health. The study was designed to investigate the learning burnout of nursing undergraduates in school under the normalization of the COVID-19 epidemic and explore the hypothesized mediation effect of academic self-efficacy in the relationship between anxiety, depression and learning burnout in Chinese nursing undergraduates. A cross-sectional study was conducted among nursing undergraduates in the school of nursing of a university in Jiangsu Province, China (n = 227). A general information questionnaire, College Students' Learning Burnout Questionnaire, Generalized Anxiety Disorder Scale (GAD-7), and Patient Health Questionnaire depression scale (PHQ-9) were administered. Descriptive statistical analysis, Pearson correlation analysis, and multiple linear regression analysis were performed via SPSS 26.0. Process plug-in (Model 4) was used to test the mediating effect of academic self-efficacy (bootstrap 5000 iterations, α = 0.05). Learning burnout (54.1 ± 0.656) was positively correlated with anxiety (4.6 ± 0.283) and depression (5.3 ± 0.366) (p < 0.01) and was negatively correlated with academic self-efficacy (74.41 ± 0.674) (p < 0.01). Academic self-efficacy plays a mediating role between anxiety and learning burnout (0.395/0.493, 80.12%) and a mediating role between depression and learning burnout (0.332/0.503, 66.00%). Academic self-efficacy has a significant predictive effect on learning burnout. Schools and teachers should strengthen the screening and counselling of students' psychological problems, detect learning burnout caused by emotional problems in advance and improve students' initiative and enthusiasm for learning.

This study aims to examine the relationship between university students’ views of distance education system and their computer self-efficacy in terms of some variables using Information Systems Success Model (ISSM) and Technology Acceptance Model (TAM). The study is important since the studies on the distance education system made with Unified Learning Style Model (ULSM) are limited in the COVID-19 pandemic period when distance education has become widespread. The views of university students on distance education and computer self-efficacy were examined in the study in accordance with the causal-comparative design, taking into account the variables of gender, year of study and academic achievement. Then, the correlation between the Technology Acceptance Model, participants’ achievement levels and computer self-efficacy was explained. 895 students attending Necmettin Erbakan University Faculty of Applied Sciences undergraduate program participated in the study. While gathering data, previously tested Technology Acceptance and Information Systems Success Model Integration and Computer Self-efficacy scales were used by combining the components from both models.

BackgroundWith the popularization of higher education, the problems of academic adaptability and learning burnout among college students have become increasingly prominent. The purpose of this study was to investigate the relationship between academic adaptability, learning burnout, self-esteem and self-efficacy of college students and their underlying mechanisms.MethodsThe study was conducted on 2110 college students using the College Student Learning Adjustment Scale, the Learning Burnout Undergraduates Scale, the Self-Esteem Scale, and the Self-Efficacy Scale to establish a mediating model of adjustment. SPSS 26.0 was used for descriptive statistics and Pearson correlation analysis. Model 4 and Model 14 in the process plug-in prepared by Hayes (2017) were used for mediating effects analysis and moderating mediator analysis respectively, and the significance of the mediating effects was tested using the bias-corrected percentile Bootstrap method.Results(1) academic adaptability significantly and positively predicted self-esteem; (2) self-esteem significantly and negatively predicted learning burnout; (3) academic adaptability significantly and negatively predicted learning burnout; (4) self-esteem partially mediated the effect of academic adaptability on learning burnout; and (5) self-efficacy moderated the latter half of the mediation process of academic adaptability-self-esteem-learning burnout.ConclusionThese findings are useful for college educators and related researchers to better understand the mechanisms underlying the relationship between academic adaptability and learning burnout, thus providing practical and effective operational suggestions on the prevention and intervention of learning burnout in college students.

Students always suffer from burnout during online learning. Although social support and cognitive engagement are associated with learning burnout, limited information is available on whether and how these relationships change over time in an online learning setting. This study investigated the longitudinal relationships between social support, cognitive engagement, and learning burnout and the further relations associated with performance. Forum data and self-reported data from 116 online college students were analyzed at two different timepoints. We found received social support is not related to learning burnout but shows a positive relationship with cognitive engagement that increases over time. Perceived social support is always positively correlated with cognitive engagement and negatively associated with learning burnout. Cognitive engagement has a negative relation with learning burnout that increases over time. Moreover, the negative relationship between learning burnout and performance emerges in the middle of the term but not at the end, thus indicating a significant change over time. The findings have significant ramifications for both preventing and intervening in online learning burnout.

Objective To explore conduct disorder tendency and it's influence factors on secondary school students. Methods 669 students of grade 1 in Dezhou Vocational and Technical College were investigated by Conduct Disorder Tendency Questionnaire, Revised Version of MBI-SS and SRHMS Version1.0. Results The secondary vocational school students' scores on violation tendency, addiction tendency and aggression tendency were 11.51±4.08,5.90±2.68 and 6.68±2.63,and were significant different from vocational college students or high school students(addiction tendency:F(2, 1578)=7.48,P =0.001;aggression tendency:F(2, 1579)=24.40,P 3.85,P <0.001).Conduct disorder tendency of secondary vocational students' was positive correlated with their learning burnout (Pearson correlation coefficient was between 0.16 and 0.52 for each pair), but negative correlated with mental health(Pearson correlation coefficient was between -0.13 and -0.27 for each pair). The linear regression showed that some dimensions of learning burnout and self-rated mental health predicted students' conduct disorder tendency. Conclusion Conduct disorder tendency of secondary vocational students is affected by their learning burnout and mental health. Key words: Secondary vocational students; Conduct disorder; Learning burnout; Self-rated health

During global COVID-19 outbreak, universities in many countries were closed, and students experienced the exclusive online learning as never before. This study aimed to examine the mediating role of Intolerance of Uncertainty (IU) in the effects of university students’ technostress caused by remote learning on three dimensions of learning burnout, namely emotional exhaustion, cynicism, and academic inefficacy, and possible moderating role of gender, ICT competence, and course load in the indirect effects of university students’ technostress on their learning burnout mediated by IU. Altogether 801 Chinese students from 72 universities voluntarily participated in this study by filling out an online questionnaire consisting of Technostress Survey, Maslach Burnout Inventory-Student Survey, and Intolerance of Uncertainty Scale-12. The participants reported relatively low technostress, learning burnout with a moderate level of IU during online learning. Structural equation modelling showed that: 1) technostress positively predicted IU, emotional exhaustion, and academic inefficacy; 2) IU partially mediated the effects of technostress on emotional exhaustion, cynicism, and academic inefficacy. 3) ICT competence moderated the indirect effects of technostress on emotional exhaustion via IU while moderating effects of gender and course load were not found.

In an era of rapid digital development, e-learning has become a significant trend in the educational field. Medical technology students need to acquire extensive theoretical knowledge and practical skills. E-learning can enhance learning experiences, improving students' understanding and application abilities. This study examined the impact of learning motivation, learning approaches, and learning burnout on the academic performance of medical technology students in an e-learning environment. This study conducted a quantitative survey on 37 medical technology students. The questionnaires included learning motivations, learning methods, and burnout, and responses provided on a 5-point Likert scale. First, the 37 students were categorized into three groups based on their academic performance. Then, differences between these groups were analyzed using the Kruskal-Wallis test, and correlations between academic performance and questionnaire variables were calculated using Spearman correlation analysis. It revealed that motivation varies among different academic performance levels. Furthermore, in the high-grade group, self-efficacy (r = -0.502, p = 0.047), monitoring studying (r = 0.494, p = 0.032), and emotional exhaustion (r = 0.514, p = 0.024) were correlated to academic performance. In the middle-grade group, self-efficacy for learning and performance was correlated to academic performance (r = 0.858, p = 0.001). In the low-grade group, academic performance was correlated to depth approach (r = 0.826, p = 0.022) and organized studying (r = 0.833, p = 0.020). This study, through a quantitative survey, found significant differences in learning motivation, learning methods, and learning burnout among medical technology students with different academic performance levels. High-grade students demonstrated higher levels of emotional exhaustion, which may reflect feelings of overextension and academic burnout in e-learning environments; the academic performance of the middle-grade group was related to intrinsic motivation; and low-grade students showed a stronger correlation between their learning methods in e-learning and their academic performance. These insights underscore the necessity for personalized learning strategies to enhance educational outcomes effectively.

Faculty use of technology is a critical issue in higher education; administrators and students are expecting faculty instruction to incorporate technology in classroom and distance education. Competition is demanding technologically proficient graduates for schools and colleges. Research indicates that computer self-efficacy (CSE) may be one determinant of who uses technology and who does not. A survey of education faculty at the Lebanese University in Beirut, Lebanon, conducted in 2006, revealed varying degrees of CSE; of 127 respondents, 14 had low levels of CSE; 68 were at a moderate level, and 45 self-evaluated themselves to have high CSE. Although other barriers may deter the implementation of technology in teaching, strategies and techniques for increasing CSE should be developed. For those with low CSE, special attention must be given to enhancing their levels of CSE.

This study focuses on college students and explores the mechanisms of action and intervention effects on time management ability, problematic short-video use duration, and learning burnout. A mixed design of "cross-sectional survey-single-group longitudinal intervention experiment" is adopted. Data are collected using tools such as Wenjuanxing and the mobile phone system's screen time function, and methods like Pearson correlation analysis and mediating effect analysis are employed for verification. The results show that there is a significant negative correlation between problematic short-video use duration and learning burnout, and a significant positive correlation between time management ability and learning burnout. Time management ability has a "double-edged sword" mechanism for learning burnout, that is, "positive direct effect + negative indirect effect". The study indicates that short videos may provide "emotional compensation" for college students, while excessive time management may lead to stress accumulation. Although the intervention strengthens the constraint of time management on short-video use, it also amplifies the risk of directly causing burnout. This study provides a new perspective for optimizing the intervention of college students' learning burnout.

The study aimed to determine the significant relationship between motivation and computer self-efficacy in teaching quality. This research used a quantitative descriptive correlational design to investigate the relationship of the three variables; there were 120 public elementary teacher participants. Random selection was used to choose the respondents in this study. Data utilized in this study were gathered through adapted and modified questionnaires that were validated by experts, undergone reliability test and pilot testing. Mean, standard deviation and Pearson correlation coefficient were among the statistical tools used. The result of the study showed that the level of motivation of teachers has an overall rating that was described as very high. Similarly, the level of computer self-efficacy of teachers has an overall mean that was described as very high. The level of teaching quality among teachers has an overall mean that was described as excellent. The findings revealed that the null hypothesis was rejected except for intrinsic and fostering effective relationships and basic computer skills. It is concluded that motivation and computer self-efficacy of public elementary teachers affect their teaching quality. It is recommended that school administrators may strengthen teachers’ intrinsic and extrinsic motivation and may be given abundant support on computer skills through comprehensive hands-on seminars and trainings in media related skills and web-based skills. School principals may design and implement effective motivators and training workshops.

This study explores the acceptance of educational support technologies in distance learning within a Chinese higher education context. It examines the influence of perceived usefulness, perceived ease of use, facilitating conditions, computer self-efficacy, and instructor efficiency on students’ behavioral intention toward distance learning. Utilizing a quantitative approach with surveys and structural equation modeling, data from 720 participants at Mianyang Teachers’ College, China, were analyzed. The findings reveal significant positive effects of these factors on the intention to engage in distance learning, offering valuable insights for enhancing technology acceptance in educational settings.

This study discusses the factors influencing students’ perceptions of using accounting software during distance learning. This study uses a descriptive quantitative approach. The data were obtained from questionnaires distributed to 134 students. SEM-PLS method with smartPLS was employed in this study. The result of this study states that distance learning has a negative effect on computer anxiety and computer anxiety itself negatively affects computer self-efficacy, perceived ease of use, and perceived usefulness. Computer self-efficacy has a positive effect on perceived ease of use. Perceived ease of use has a positive effect on perceived usefulness. This study examines only the factors influencing student perception and intention to use accounting software. This study provides empirical evidence on the effect of transactional distance and other factors such as computer anxiety and computer self-efficacy on perceptions of using accounting software. In addition, this research can enrich study materials or references for the future research.

Since the outbreak of COVID-19, remote teaching methods have been widely adopted by schools. However, distance education can frequently lead to low student emotional engagement, which can not only cause learning burnout, but also weaken students’ interest in online learning. In view of the above problems, this study first proposed a learner knowledge state model that integrates learning emotions under the background of digital teaching to accurately describe the current learning state of students. Then, on the basis of the public face dataset lapa, we built an online multi-dimensional emotion classification model for students based on ResNet 18 neural network. Experiments showed that the method has an average recognition accuracy of 88.76% for the four cognitive emotions of joy, concentration, confusion, and boredom, among which the accuracy of joy and boredom is the highest, reaching 96.3% and 97.0% respectively. Finally, we analyzed the correlation between students’ emotional classification and grades in distance learning, and verified the effectiveness of the student’s emotional classification model in distance learning applications. In the context of digital teaching, this study provides technical support for distance learning emotion classification and learning early warning, and is of great significance to help teachers understand students’ emotional states in distance learning and promote students’ deep participation in the distance learning process.