What factors impact university learners’ online learning outcome? Validating the theory of dialectical principle of internal and external causes

In education, online learning with an e-learning system is an irreplaceable need. Many argue that online learning is the current educational crisis. Several studies show how complicated the handling of COVID-19 for universities is, especially in online learning (e-learning) outcomes. The variables influencing online learning during the COVID-19 epidemic have been shown in numerous studies. However, the influence of several other factors still needs to be investigated. Therefore, this study aims to determine non-academic factors that affect online learning during the COVID-19 pandemic. With data collected from the International University of Logistics and Business (ULBI), this study uses Cronbach’s-Alpha analysis, Bayesian Exploratory Factor Analysis (BEFA), Principal Component Analysis (PCA), and Multivariate Regression Analysis. The evaluation of the research scale shows 20 observed variables. The test results prove that three non-academic factors influence students’ online learning outcomes during the COVID-19 pandemic: education cost policy (H1), communication quality (H2), and student support (H3). Each factor has p – value < 0.001, p – value = 0.029, and p – value = 0.004, respectively. Meanwhile, family circumstances do not affect students’ online learning outcomes during the COVID-19 pandemic (H4 rejected) because the p-value is 0.152. An example case in the questionnaire shows that most students say family income can adapt to changes during the COVID-19 pandemic.

Recently, achievement emotions have attracted much scholarly attention since these emotions could play a pivotal role in online learning outcomes. Despite the importance of achievement emotions in online education, very few studies have been committed to a systematic review of their effects on online learning outcomes. This study aimed to systematically review studies examining the effects of achievement emotions on online learning outcomes in terms of motivation, performance, satisfaction, engagement, and achievement. According to the selection process of Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) principles, a total of 23 publications were included in this review. It was concluded that positive achievement emotions, such as enjoyment, pride, and relaxation, could generally exert a positive effect on online learning motivation, performance, engagement, satisfaction, and achievement. It should be noted that excessive positive emotions might be detrimental to online learning outcomes. On the other hand, it has been difficult to determine the effects of negative achievement emotions on online learning outcomes because of disagreement on the effects of negative achievement emotions. In order to improve online learners' learning outcomes, instructors should implement interventions that help online learners control and regulate their achievement emotions. Teaching interventions, technological interventions, and treatment interventions could benefit online learners emotionally and academically. Future studies could examine the moderating roles of contextual factors and individual variables in the effects of achievement emotions on online learning outcomes.

This study aims to determine the effect of the quality of online learning and learning on the learning outcomes of senior sales counters in the PT Astra Honda Motor network. The method used is a quantitative method with analytical techniques using statistical analysis with regression, correlation, determination and hypothesis testing. The results of this study that the quality of online learning has a significant effect on learning outcomes by 43.4%, hypothesis testing is obtained t count &gt; t table or (4,748 &gt; 1,990). learning has a significant effect on online learning outcomes by 37.4%%, hypothesis testing is obtained t count &gt; t table or (3.623 &gt; 1,990). Online Learning Quality and Learning Outcomes simultaneously have a significant effect on the regression equation Y = 4.089 + 0.434 X1 + 0, 374 X2 and the contribution of the influence is 64.8%, the test is obtained by F arithmetic &gt; F table or (75.338 &gt; 3, 11).

Several factors that can affect learning outcomes are the quality of learning and interest in learning. During the Covid-19 pandemic, the teaching and learning system underwent changes, namely there was no face-to-face learning or so-called learning from home and online learning was implemented. It is known from interviews with classroom teachers that interest in learning and learning outcomes are low. The objectives of this study are: (1) to determine the relationship between quality and learning outcomes during the Covid-19 pandemic, (2) to determine interest in online learning and learning outcomes during the pandemic, (3) to determine the relationship between quality and interest in online learning and learning outcomes. learn students during the pandemic.This research method is correlation research. The population of this study amounted to 285 students. The research sample amounted to a sample of 156 students by means of cluster random sampling. Data collection methods in this study used interviews, documentation and questionnaires. The research analysis technique uses person correlation and multiple correlation. The results of this study show: (1) there is no relationship between the quality of learning and learning outcomes during the Covid-19 pandemic with an rcount of -0.148 &lt; rtable 0.1572 a significant value of 0.06 &gt; 0.05, (2) there is no relationship between interest in learning online learning outcomes during the Covid-19 pandemic with an rcount value of 0.107 &lt; rtable 0.1572 a significant value of 0.184 &gt; 0.05, (3) there is no relationship between quality and interest in online learning with student learning outcomes during the Covid-19 pandemic with an rcount value -0.145 &lt;rtable0.1572 significant value of 0.92 &gt; 0.05. The conclusion of this study shows that there is no relationship between learning quality and online learning interest with student learning outcomes during the Covid-19 pandemic.

This study aims to investigate the effect of digital literacy skills and learning motivation on students' online learning outcomes in Fiqh subjects at Madrasah Tsanawiyah (MTs). The approach used in this study is quantitative with the data collection technique being a survey model. The sample includes 52 students, along with the corresponding teacher, from MTs Nurul Falah. The correlation data analysis is conducted using SPSS 25 software. The findings reveal a significant influence of digital literacy skills and learning motivation on online learning outcomes. Specifically, digital literacy skills account for a 90% influence on the online learning outcomes of MTs Nurul Falah students, while learning motivation accounts for an 88% influence. Moreover, the combined impact of both variables on online learning outcomes is 82%. The implications of this study underscore the necessity of enhancing digital literacy skills and nurturing learning motivation in online Fiqh courses at MTs Nurul Falah to improve students' learning outcomes. This can be accomplished through adequate training and support for students and teachers to develop digital literacy skills and learning motivation. Additionally, it is crucial to address the internal factors influencing students' digital literacy. Moreover, addressing factors such as technical issues and student motivation within the online learning environment is equally essential for optimizing online learning experiences.

The COVID-19 pandemic, a public health crisis of worldwide importance, announced by the World Health Organization (WHO) in January 2020 as an outbreak, has made distance education through the E-learning system an urgent and irreplaceable requirement. The study assessed factors affecting students’ online learning outcomes during the COVID-19 pandemic through interviews with 404 students who were subjects of the survey using the convenience sampling method via questionnaires. The study utilized the reliability analysis through Cronbach’s Alpha and the Bayesian Exploratory Factor Analysis (BEFA). The evaluation results of the research scales showed that 28 observed variables were used to measure 7 research concepts. Test results of the hypotheses showed that students’ online learning outcomes are affected by 6 factors in the descending order, respectively, learner characteristics, perceived usefulness, course content, course design, ease of use, and faculty capacity.

This study aims to determine the effect of learning facilities and the role of teachers on online learning outcomes in odd semester economic subjects in class X BDP SMK Pasundan 4 Bandung. The method used in this research is a survey. The subjects in this study used a sample of 56 students. Analysis of the data used is descriptive analysis, classical assumption test and hypothesis testing through multiple linear regression calculation and coefficient of determination with the help of SPSS 25.0 for Windows. From the results of research using descriptive analysis, it is obtained that the average score recapitulation of respondents regarding learning facilities is in the "undecided" category, indicated by an average weight of 3.11 with a percentage of 62.40%. This indicates that most of the students are hesitant about learning facilities according to the average respondent. Meanwhile, regarding online learning outcomes, students are in the "Strongly Agree" category, indicated by an average weight of 4.50 with a percentage of 89.20%. This indicates that most students strongly agree that students' online learning outcomes increase according to the average respondent. Based on the classical assumption test through the normality test that has been carried out, it is obtained a significant value of 0.200&gt; 0.05, it can be concluded that the residual value is normally distributed. In the hypothesis test, multiple linear regression coefficients (Y= 1.638 – 0.513X1 + 0.577X2 + 0.347) which means that if learning facilities (variable X1) and the role of teachers (variable X2) increase, it will cause a tendency to increase student online learning outcomes (variable X2). Y) of 1.09. The contribution of the influence given by the learning facilities variable to students' online learning outcomes is 34.5% and the teacher's role variable to students' online learning outcomes is 35.8%, the percentage is calculated based on the results of the calculation of the coefficient of determination is 70.3%, while the rest amounted to 29.7% influenced by external factors that were not examined by the researcher, and the conclusion was acceptable. As the end of the research, the author conveys suggestions for schools for learning facilities and teachers to use adequate learning facilities in the ongoing teaching and learning process, specifically on learning facilities and the role of teachers in general so as to improve student online learning outcomes.

Due to COVID-19, universities have shifted to offer online learning for their students from traditional face-to-face learning. Despite various efforts made by university administrators for their students’ online learning during the COVID-19 pandemic, not much has been identified about how students perceived online learning and what factors affected their online learning engagement and outcomes. Examining students’ motivation, self-efficacy, and anxiety as key factors for their online learning engagement and outcomes, this study conducted a self-administered online survey with college students in three countries: the U.S., South Korea, and Colombia. This study used SEM to test hypotheses and conducted a multi-group analysis to find differences among students. The findings indicated that students’ self-efficacy and anxiety significantly impacted their online learning engagement, influencing online learning outcomes. Although students were highly engaged in online learning, their perceived online learning was not so effective and rigorous compared to face-to-face learning.

Self-Efficacy (SE) is an essential component in mathematics learning that must be improved so that the teaching performance can convince students. The purpose of this study is how brightspace SPADA (Online Learning System) is developed to measure PPG participants' self-efficacy, which can contribute to the creation of an increase in the quality of education. This study's subjects were PPG participants in the Department of Mathematics Studies in one private LPTK in Bandung, which before the workshop began with online learning. The research method used is the Mixed Method of Embedded Design type and Embedded Experimental Model type. The instrument used was an online test on e-learning and a closed statement SE scale of 10. The analysis used include, (1) Descriptive analysis of online learning outcomes and self-efficacy, (2) Comparative analysis of online learning outcomes between classes (Class A and B) using the Mann Whiney-U test because the data are not normally distributed, (3) Comparative analysis of online learning outcomes between levels, namely junior high, high school, and vocational school (SMP, SMA, and SMK) using ANOVA, (4) Comparative analysis of self-efficacy between classes (Classes A and B) using t-test, because the data is normally distributed, (5) Comparative analysis self-efficacy between levels (SMP, SMA, and SMK) using ANOVA, (6) Analysis of the effect of online learning outcomes on self-efficacy using simple linear regression. The study results are: (1) Descriptive online learning results can be concluded that PPG Mathematics online learning outcomes are above average (≥ 75), based on levels. The result of descriptive statistical data analysis of online learning outcomes is that the average value of participants from SMP, SMA, and SMK is 76.93, 93.12, and 85.92. PPG Mathematics participants' self-efficacy is in the very good category (8.6 from 0-10 intervals), based on the level. Descriptive statistical data analysis obtained the average value of participants from SMP, SMA, and SMK is 8.68, 8.65, and 8.76. (2) There is no significant difference in online learning outcomes between classes A and B. (3) There is no significant difference in online learning outcomes between SMP, SMA, and SMK. (4) There is no significant difference in self-efficacy between classes A and B. (5) There is no significant difference in self-efficacy between SMP, SMA, and SMK. (6) There is no online learning outcomes influence on Self-Efficacy.

Student motivation and self-regulation are critical for optimizing online learning outcomes. This study aims to determine the effect of intrinsic motivation, extrinsic motivation, and self-regulation on students' online learning outcomes. This research design is comparative causal research using a quantitative approach. The population in this study was 3,414 students with a sample of 358 students. Data collection techniques and instruments used questionnaires. The validity of the instrument was proved by exploratory factor analysis, while the reliability estimated by using the Alpha formula. Multiple regression analysis was performed to test the research hypothesis. The results showed a positive and significant effect of intrinsic motivation, extrinsic motivation, and self-regulation on students' online learning outcomes. To get the most out of online learning, every student must improve their learning motivation and self-regulation skills.

During the COVID-19 pandemic, teachers had to conduct online classes because of the breakdown of school learning. Teacher competence has a great impact on the students’ learning outcomes in online learning. Teacher resilience is also important to help teachers survive and achieve a high level of well-being in emergency situations. Previous studies have explored the protective and risk factors of teacher resilience, among which teacher competence in various aspects is included. In addition, teachers’ age differences in competence and resilience have been the focus of past studies. However, few studies have investigated the impact of teacher competence on students’ online learning outcomes, the mediating role of teacher resilience, and the moderating effect of age when teachers participate in emergent online teaching. To address the above gap, this study explored teachers’ perceptions of students’ online learning outcomes and how teacher competence in online teaching and resilience can predict these outcomes. The data of 159,203 participants were collected and subjected to correlation analyses and a moderated-mediation effect test. The results indicated that (1) teacher competence in online teaching was positively related to perceived online learning outcomes; (2) teacher resilience was positively related to the teachers’ perceived online learning outcomes; (3) teacher resilience played a partial mediating role between teacher competence in online teaching and perceived online learning outcomes; and (4) teachers’ age moderated the direct and indirect relation between teacher competence in online teaching and perceived online learning outcomes. The findings imply that teachers should strengthen their own teaching competence and their resilience before conducting online teaching. In addition, this study proposes intervention strategies to enhance teachers’ resilience and well-being through teacher competence cultivation and provides suggestions for different age levels of teachers to develop and train their online teaching competence and resilience in the future.

The hypothesis that shyness would be associated with attribution of emotional reactions to stable internal causes rather than to less stable internal and external causes was tested in Study 1 (N = 60). In Study 2 (N= 112) the hypothesis that the explanatory power of shyness would decrease once the effect of self-focused attention on attribution to stable internal causes had been controlled for was tested. The results confirmed both hypotheses. Shyness correlated positively with attribution to stable internal causes, but non-significant with attribution to less stable internal and external causes. Shyness explained a lesser portion of the variance in attribution to both of the internal causes when controlling for self-focus. Even though the findings indicate that self-focus is central to the social cognitive processes of shy individuals, they also suggest that self-focus cannot fully explain attribution to internal causes in general and shy individuals' attributional pattern in particular.

Higher education institutions are undergoing radical transformations driven by the need to digitalize education and training processes rapidly. Universities continue to prioritize online learning as a means of meeting the diverse needs of students, ensuring accessibility, flexibility, and continuity in education. However, for students to effectively benefit from online learning, two crucial constructs play a pivotal role: academic motivation and self-regulation. These factors significantly influence students’ ability to engage with, persist in, and succeed in online learning environment. Despite the growing emphasis on online education, many students in public universities in the Western region of Kenya face challenges related to self-discipline which affect their learning outcomes. The purpose of this study was to assess the impact of self-regulation strategies on students’ online learning outcomes. This study was guided by self-regulation theory. A mixed-methods research design was employed, targeting 4,551 respondents, comprising 4,475 undergraduate students from the Department of Education, 24 heads of the Education Department, 39 instructors, and 4 ODEL administrators. Data was collected using questionnaires and key informant interview schedules. A pilot study was conducted to ensure reliability, with Cronbach’s alpha used to test the internal consistency of research instruments. Face, content, and criterion validity of the instruments were ascertained. Data analysis involved correlation to assess relationships between variables and multiple regression to predict their interactions. The qualitative results from the interview showed that self-regulation influences students’ online learning outcomes in public universities within this region. The results showed a strong positive relationship (correlation coefficients of 0.821, respectively) between students' online learning outcomes and self-regulation behavior. According to linear regression analysis, students' online learning results were positively and significantly impacted by self-regulation behavior (regression coefficients of 1.271, respectively) The study found that self-regulation explained around 55.2% of the variance in students' online learning results. For education stakeholders, these findings have important ramifications, especially when evaluating readiness for the competency-based curriculum (CBC) in Kenya by 2026, which includes the use of online learning techniques. The Teachers Service Commission (TSC), Kenya Institute of Curriculum Development (KICD), and Ministry of Education (MOE) may utilize these findings to create efficient teacher training plans for online instruction and to address challenges hindering the adoption of online learning. Enhancing students' academic motivation and self-control will be key to a successful digital learning experience.

BackgroundPublic attention is given to infants with socially high risks of child abuse and neglect, while clinical attention is provided to infants with a biologically high risk of diseases. However, few studies have systematically evaluated how biological or social factors cross over and affect cause-specific infant mortality.MethodsWe linked birth data with death data from the Japanese national vital statistics database for all infants born from 2003–2010. Using multivariate logistic regression, we examined the association between biological and social factors and infant mortality due to medical causes (internal causes), abuse (intentional external causes), and accidents (unintentional external causes).ResultsOf 8,941,501 births, 23,400 (0.26%) infants died by 1 year of age, with 21,884 (93.5%) due to internal causes, 175 (0.75%) due to intentional external causes, and 1,194 (5.1%) due to unintentional external causes. Infants with high social risk (teenage mothers, non-Japanese mothers, single mothers, unemployed household, four or more children in the household, or birth outside of health care facility) had higher risk of death by intentional, unintentional, and internal causes. Infant born with small for gestational age and preterm had higher risks of deaths by internal and unintentional causes, but not by intentional causes.ConclusionsBoth biological as well as social factors were associated with infant deaths due to internal and external causes. Interdisciplinary support from both public health and clinical-care professionals is needed for infants with high social or biological risk to prevent disease and injury.

In this COVID-19 pandemic, learners across the world are encouraged to stay at home receiving online education, which has nearly caused various learning outcomes. It is thus necessary to analyze online learning outcomes, as well as their gender differences to provide constructive references for learners, teachers, and technology developers. This study obtained reliable data from various databases using searching techniques. The study also selected the research articles based on inclusion and exclusion criteria. After analyzing the forest and funnel plots drawn via Review Manager 5.3, the study arrived at the conclusion that online learning outcomes were significantly higher than the traditional learning outcomes with a large effect size (d = 1.24), while the gender differences in learning outcomes were not significant with a small effect size (d = -0.03). In the future, experts could make every effort to develop advanced emotion detection applications via interdisciplinary cooperation to improve online learning outcomes.