Students In Online Learning Environment Research Articles

Neurodiversity and cognitive load in online learning: A systematic review with narrative synthesis

This systematic review with narrative synthesis aimed to examine the available evidence on the relationship between neurodiversity and cognitive load in online learning. Despite the known relationship between working memory impairments and neurodiversity, there has been a lack of systematic investigation into how cognitive load impacts neurodivergent students in online learning environments. This review, which includes 90 studies conducted in 21 countries, reveals that the majority (92%) did not consider neurodiversity as a potential factor influencing cognitive load in online learning. The few that did suggest distinct patterns of cognitive load in online learning for neurodivergent students, suggesting a need for more research in this area. The results also point to the potential for methodological advancements in measuring cognitive load in online learning, highlighting that 80% of studies with only neurotypical participants and 60% of studies including neurodivergent participants relied solely on subjective measures of cognitive load. This review contributes to the field by offering a comprehensive overview of our current knowledge of the relationship between neurodiversity and cognitive load in online learning, identifying significant gaps and suggesting directions for future studies.

United We Learn: Seven Strategies for Fostering an Inclusive and Engaging Synchronous Online Teaching Environment

Since online learning may be the best option for some programs or institutions, college instructors should have the competence and confidence to offer relevant learning experiences for their students in online learning environments. This article provides physical education teacher education (PETE) faculty with effective strategies for fostering an inclusive and engaging synchronous online learning environment for college students using a range of technology tools.

Identifying the Learning Style of Students Using Machine Learning Techniques: An Approach of Felder Silverman Learning Style Model (FSLSM)

Identification of the learning style of the students in the teaching and learning environment plays a significant importance in improving both teaching and learning perspectives. The intension of the research was to investigate about applying the Machine Learning Techniques for identification of the Learning style of the students in online learning environment based on the Felder Silverman Learning Style (FSLSM) identification model. The significance of this experiment is that the proposed methodology considers the combination of access frequency (f) of course materials and total time (T) students spent on each course activity. For data collection process, it was designed reusable plugin for the Moodle for time tracking. Real-time dataset was prepared using three course modules designed according to the features of FSLSM model and the features for analyzing the students according to the FSLSM, it was selected seven criteria, and the features were validated using Pearson Correlation Coefficient method. These course modules were enrolled 150 students per each module. Once the data set was prepared, the data set was preprocessed and applied Five Supervised Classification Machine learning algorithms as Decision Tree, Logistic Regression, Random Forest, Support Vector Machine and K-Nearest Neighbors algorithm. The models were evaluated using Accuracy, Precision, Recall and F1 values. Over the five algorithms the Decision Tree classifier algorithm performed with best average accuracy with 93.5% for Input, 86% for Perception, 89.5 for Processing and 94% for Understanding dimension. The models were validated using the K-fold Cross validation and Standard Deviation values. Mean Squared Error, Bias and Variance values were considered the evaluation of underfitting or overfitting context of the model. To parameter optimization, the Grid Search Methodology was applied to find the best combination of criterion for the model. Finally, an application was developed for Identifying the Learning Style of the Students using the designed Machine learning model. The Consistency of the ML Model based on the Decision Tree classifier algorithm were evaluated using the results generated through developed application and the results suggested that consistency for taught machine learning algorithms is often between 85% to 95%, which is an acceptable range. The results generated by the application for identification of the learning style suggested the combination of learning style for particular students sample as Global-Mild, Visual- Strong, Sensing- Moderate and Reflective-Strong. Identification of these combination of learning style assist for teachers by giving an insight which components of the learning contents should be improved in course designing process.

An interpretable English reading proficiency detection model in an online learning environment: A study based on eye movement

Aiming at the low English reading proficiency of ESL (English as second language) students in online learning environments, this study proposed an eye-movement-based machine learning monitoring model to detect English reading proficiency in real time. Eye-movement data from 43 students while completing online English reading tasks were recorded and 31 eye-movement features were extracted from the taxonomy of fixation, saccade, movement direction and gaze velocity. During the model training phase, LightGBM achieved an accuracy of 96.51 % in detection. An interpretable model, SHAP (SHapley Additive exPlanation), was used to explain the main effects of eye-movement features in detection, where high gaze velocity, absolute saccade direction, and average saccade duration were found to be strong indicators of English reading proficiency. Furthermore, SHAP analysis allows the identification of individual factors contributing to differences in English reading proficiency. This study demonstrated the effectiveness of the combination of eye-movement data with machine learning methods to identify students with low English reading proficiency in online reading and provided insights into the intrinsic correlation between eye movements and reading.

Session-Based Time-Window Identification in Virtual Learning Environments

Students organize and manage their own learning time, choosing when, what, and how to study due to the flexibility of online learning. Each person has unique learning habits that define their behaviours and distinguish them from others. To investigate the temporal behaviour of students in online learning environments, we seek to identify suitable time-windows that could be used to investigate their temporal behaviour. First, we present a novel perspective for identifying different types of sessions based on individual needs. The majority of previous works address this issue by establishing an arbitrary session timeout threshold. In this paper, we propose an algorithm for determining the optimal threshold for a given session. Second, we use data-driven methods to support investigators in determining time-windows based on the identified sessions. To this end, we developed a visual tool that assists data scientists and researchers to determine the optimal settings for session identification and locating suitable time-windows.

ACADEMIC PERFORMANCE, LEARNING ENVIRONMENT AND SOCIAL SUPPORT INFLUENCING STUDENT LEVELS OF DEPRESSION IN ONLINE LEARNING: A CONCEPTUAL PAPER

The COVID-19 pandemic issue has made online learning a requirement in all educational institutions, including schools, colleges, and universities. Even though they face challenges in many ways, teachers and students must adapt to online learning technologies to ensure that it is used as usual. Some of them struggle with anxiety and depression. This study aimed to investigate the factors influencing student levels of depression in online learning. Specifically, the researcher focused on the relationship between academic performance, learning environment, and social support and their impact on students' levels of depression. Students with higher academic performance and a supportive learning environment reported lower levels of depression. Moreover, students who received greater social support from peers, instructors, and family members also reported lower levels of depression. The study contributes to the growing body of literature on the mental health of students in online learning environments by highlighting the importance of academic performance, learning environment, and social support in influencing levels of depression. The study's findings have important implications for educators and policymakers, highlighting the need to prioritize students' mental health and well-being in online learning environments. To improve students' mental health, educators must provide students with a supportive and engaging learning environment that fosters a sense of community and belonging. Additionally, educators should focus on helping students achieve academic success, as this can have a positive impact on their mental health.

Effects of an intelligent cues recognition-based multilevel knowledge graphs generation method on students in online learning environments

ABSTRACT Online learning has been greatly widespread since the explosion of COVID-19. However, due to the lack of interaction between teachers and students in online courses, it is very difficult for students to focus on course content and complete the learning. Therefore, we developed a novel intelligent multilevel knowledge graph to help students quickly and systematically grasp the framework and key content of video lectures. Specifically, our method introduced cues into the interactive knowledge mapping. This approach not only allows students to interact with the graphs but also displays different levels of knowledge based on its importance. In addition, a quasi-experiment was implemented to verify the effectiveness of our method. Specifically, we compare the effects of knowledge graphs in three weighting strategies for cues with traditional manual concept maps on students' learning effectiveness and learning perception. Our study shows that although static artificial concept maps do enhance student learning to a certain extent compared to traditional learning, its development efficiency and enhancement of student learning outcomes are not ideal. In contrast, interactive graphs presenting overlay cues can effectively help students to restructure and systematize their knowledge, direct their attention and thus improve their learning outcomes.

Achievement Emotions of Medical Students: Do They Predict Self-regulated Learning and Burnout in an Online Learning Environment?

ABSTRACT Background Achievement emotions have been proven as important indicators of students’ academic performance in traditional classrooms and beyond. In the online learning contexts, previous studies have indicated that achievement emotions would affect students’ adoption of self-regulated learning strategies and further predict their learning outcomes. However, the pathway regarding how different positive and negative achievement emotions might affect students’ burnout through self-regulated learning among medical students in online learning environments remains unclear. In this study, the aim is to investigate how achievement emotions and self-regulated learning predict burnout among medical students in online education. Methods This study involved 282 medical students who had attended online courses due to the sudden shift of learning mode caused by the COVID-19 pandemic in 2022. Confirmatory factor analysis was performed to examine the hypothesized factor structure, and structural equation modelling was conducted to test the hypothesized relationships among factors. Results The results of structural equation modelling revealed that medical students’ self-efficacy positively predicted their enjoyment (β = .57) and online self-regulated learning (β = .54). Learning-related boredom inhibited students’ adoption of online self-regulated learning strategies (β = −.24), and it was positively associated with their burnout (β = .54). Learning-related anxiety was a positive predictor of online self-regulated learning (β = .38). Discussions The results of this study suggest that achievement emotions experienced by medical students had a significant impact on their online self-regulated learning and burnout. Specifically, the experience of learning-related boredom was detrimental to the adoption of self-regulated learning strategies and increased the likelihood of burnout. However, learning-related anxiety, despite being a negative achievement emotion, was positively associated with students’ online self-regulated learning. These findings have important implications for online teaching and learning, particularly in the post-pandemic era.

Academic discourse and peer collaboration in online high school learning environments

AbstractBackgroundDialogic engagement is instrumental in promoting higher‐order thinking, motivation, and learning. Despite their dramatic uptake in the US in the past decade, there is limited evidence that online high school courses offer sufficient opportunities for students to communicate and collaborate with teachers and peers.ObjectivesThis two‐part study explores teacher perspectives and the experiences of students in online learning environments to determine if, how, and why students engage in two forms of dialogic engagement–academic discourse and peer collaboration.MethodsTo identify the extent to which teachers perceive academic discourse and peer collaboration to be valuable and feasible in online learning environments, Study 1 surveyed educators and advisors of online learning programs (n = 49). To determine whether these perspectives align with student experiences, Study 2 included a series of over‐the‐shoulder observations of five high school students engaging in their online coursework.Results and ConclusionsFindings reveal a disconnect between best practices in education and reality. Online teachers report that academic discourse is valuable and feasible, but also detail several challenges to successful implementation in online coursework. At the same time, direct observations of high school students indicate that they rarely, if ever, engage in peer collaboration and academic discourse activities.Major TakeawaysAlthough valued as a means to improve educational outcomes, opportunities for dialogic engagement are not translating to online learning environments. The solution is to develop curriculum, policies, and procedures that centre on meaningful integration of dialogic activities, motivating students to engage.

Cracking the code: Understanding lecturer performance and student success

One of the essential factors in a learning process, especially in higher education, is lecturer performance. This study aims to discover the impact of a lecturer's performance on students learning outcomes in the online learning environment. Lecturer performance is represented by four aspects which are the lecturer's performance on learning technology (X1), the lecturer's performance on learning pedagogy (X2), the lecturer's performance on supporting learners (X3), and the lecturer's performance on supporting educators (X4). This quantitative research approach aims to discover one variable's cause-and-effect relationship to another. The subject of this study is 37 lecturers and 146 students. The result shows that the lecturer's performance contributes 43.1% to students' learning outcomes. It is known that learning technology and pedagogy aspects have a significant effect on students' learning outcomes. However, supporting learners and educators does not significantly impact students' learning outcomes. Therefore, the lecturer's performance positively impacts learning outcomes and is valuable for further online learning development. A potential research contribution could be to investigate further the relationship between specific aspects of a lecturer's performance and students' learning outcomes in an online learning environment. this study's findings have significant implications for higher education institutions seeking to improve online learning experiences for students. By identifying the specific aspects of lecturer performance that most impact learning outcomes, institutions can provide targeted support and training to their lecturers, ultimately leading to improved learning outcomes for students in online learning environments.

Effects of Gamification on Behavioral and Cognitive Engagement of Students in the Online Learning Environment

The study investigated the effects of gamification on behavioral and cognitive engagement of students in online learning environments. The study was conducted in a quasi-experimental design including a control group. Students in the gamified environment were the experimental group, and the students studying in the non-gamified environment were the control group. Both groups of students studied in an online learning environment for 10 weeks. The study group consists of 46 students selected with the convenience sampling method. There were 18 male and 5 female students in the experimental group, and 19 male and 4 female students in the control group. Four research questions guided the study. Findings revealed that gamification enhanced students’ achievement by increasing their content interaction in the online learning environment. The study recommended the use of gamification in the online learning environment because it makes learning that looks difficult or boring become interesting and easier to understand. Hence, it is activity-based and involves students’ active engagement.

Exploring Educator Leadership Practices in Gifted Education to Facilitate Online Learning Experiences for (Re)Engaging Gifted Students

This article draws on case study findings of educator leadership in an online gifted education school, which emerged from a larger study exploring online engagement practices used by specialist gifted education teachers to (re)engage gifted learners. The gifted education teachers and their team leader were interviewed about leadership practices for supporting online engagement of gifted primary and high school students. Semi-structured interview data were transcribed, coded, and thematically analysed. Findings related to teachers voicing the importance of a passionate and committed team leader who understood giftedness and who acted as a facilitator in both the continuous development of teaching team skills and facilitation of online engagement practices for gifted students. Findings indicated five key themes related to transformational leadership practices: (1) understanding requirements of online practices for teaching gifted students; (2) supporting digital and online innovation and creativity for engaging gifted students; (3) leveraging the unique skills of the specialist teaching team for teaching gifted students in the online space; (4) actively facilitating and encouraging (re)engagement of gifted students through online participation; (5) follow-through to meet the needs and concerns of the specialist teaching team, gifted students, and their parents and/or carers. These leadership practices are of importance for actively supporting gifted education teachers and their students in online learning environments in order to achieve positive student engagement and learning outcomes commensurate with student potential.

Critical Competency Attributes of Technical and Vocational Education and Training (TVET) Postgraduate Students in Online Learning Environment

Student competency has become the central agenda in graduates' employability. Reflecting on the overarching situation of COVID-19 pandemic, students have been compelled to acquire knowledge using online platforms, conjecturing the competency attributes being left out from conventional teaching and learning environments. This paper examines the development of competency attributes: knowledge, skills, and attitudes, which were selected as main variables. A correlation analysis was performed to obtain the results of the relationship between the competency attributes and the online learning environment. There were 70 postgraduate students, randomly selected as samples of the study. The discussion of the results centered on the competency attributes developed by the students and their relationships with the online learning environment. The implications for educational stakeholders based on the findings are further discussed.

A sequential explanatory mixed-methods study of UK higher education teacher experiences when building rapport with international students online

Effective, interpersonal teacher–student relationships and positive rapport are widely known to positively impact student attainment and learning experiences. Establishing and maintaining these have been particularly challenging, however, since the Covid-19 pandemic forced higher education (HE) teaching online in 2020. This study, therefore, aimed to explore English for Academic Purposes (EAP) teachers’ experiences of building rapport with international students in online learning environments in UK HE institutions during emergency remote teaching via sequential explanatory mixed methods and three research questions. Study Phase 1 comprised a structured, online, quantitative and qualitative questionnaire completed by 36 participants of the target population from 19 UK HE institutions, while Phase 2 employed in-depth qualitative interviews with three selected participants from Phase 1. Three themes emerged as most significant when considering teacher experiences of building rapport with students online: online communication in online sessions; teacher–student communication outside online sessions; and teacher availability and accessibility. The findings suggest that if online sessions could primarily be used as opportunities to meet learning outcomes, then the necessary and conscious task of building teacher–student rapport might be more effective in frequent 1–1 tutorials with students or during any available pre- and post-online session time.

Initiating and maintaining student-instructor rapport in online classes

We investigated the behaviors and contextual factors college instructors rely upon to cultivate rapport with students in asynchronous online courses. Nineteen phenomenological interviews revealed that online instructors view rapport-building as a two-pronged process of initiating and subsequently maintaining rapport with students. Findings also indicated that online instructors rely upon different rapport-related strategies and contextual factors to initiate and maintain rapport. During the first weeks of the semester, these instructors rely upon connecting, information sharing, and common grounding behaviors to initiate a sense of rapport from their students. Going forward throughout the semester, these instructors rely upon attentive and courteous behaviors while providing learners with personalized instruction to maintain rapport. Findings from the present study provide insights into how college instructors approach the rapport-building process with students in online learning environments and can be used as a framework for helping college instructors make rapport-related decisions in their online classes.

Persistence and Academic Performance of Medical Students in Online Learning Environment During the COVID-19 Pandemic Lockdown

Government response to the COVID 19 pandemic in the spring of 2020 came as a wave of physical closures requiring sudden change in the method of instruction from face-to-face to a completely online. Assessment of students adaptation to this change during emergency lockdown is the focus of this study. We used a One-way ANOVA to compare pandemic and pre-pandemic Performance of First Year medical students at the University of Arkansas for Medical Sciences in the brain and behavior module. Students’ test scores related to perception of persistence levels was studied using correlation analysis. In addition, a regression analysis was performed to examine prediction factors of medical student course grades during COVID-19. Students’ grades in the module during the COVID-19 were significantly higher compared to the grades in recent prior years at the p<.001 level [F (3, 692) = 9.08].  Pearson product-moment correlation results showed a strong and positive correlation between students’ persistence level (M = 3.46, SD = .997, n = 79), and their module grade during COVID-19 (M = 258.777, SD = 14.6878, n = 79), r = .33, p = < .01. The multiple linear regression analysis accounts for 14% of the variance in students’ module grades and the variance was statistically significant at p < .05. As such, we conclude that students’ persistence to adjust to a new learning environment coupled with module directors and faculty successfully employing remote education methods, met the learning challenges during the pandemic and students maintained a high level of academic success.

Transition to online learning during the COVID-19 pandemic

BackgroundWith the new pandemic reality that has beset us, teaching and learning activities have been thrust online. While much research has explored student perceptions of online and distance learning, none has had a social laboratory to study the effects of an enforced transition on student perceptions of online learning. PurposeWe surveyed students about their perceptions of online learning before and after the transition to online learning. As student perceptions are influenced by a range of contextual and institutional factors beyond the classroom, we expected that students would be overall sanguine to the project given that access, technology integration, and family and government support during the pandemic shutdown would mitigate the negative consequences. ResultsStudents overall reported positive academic outcomes. However, students reported increased stress and anxiety and difficulties concentrating, suggesting that the obstacles to fully online learning were not only technological and instructional challenges but also social and affective challenges of isolation and social distancing. ConclusionOur analysis shows that the specific context of the pandemic disrupted more than normal teaching and learning activities. Whereas students generally responded positively to the transition, their reluctance to continue learning online and the added stress and workload show the limits of this large scale social experiment. In addition to the technical and pedagogical dimensions, successfully supporting students in online learning environments will require that teachers and educational technologists attend to the social and affective dimensions of online learning as well.

Correlation between Self-determination, Major Suitability, and Lecture Immersion of College Students in Online Learning Environments

Correlation between Self-determination, Major Suitability, and Lecture Immersion of College Students in Online Learning Environments

Correlation between Major Suitability, Major Satisfaction, Self-leadership, and Teaching Presence of College Students in Online Learning Environments

Correlation between Major Suitability, Major Satisfaction, Self-leadership, and Teaching Presence of College Students in Online Learning Environments

Effects of Task Value and Presence on Learning Flow of Nursing Students in Online Learning Environment

본 연구의 목적은 온라인 학습 환경에서 과제가치와 실재감(교수 실재감, 인지적 실재감, 감성적 실재감, 사회적 실재감)이 간호대학생의 학습몰입에 미치는 영향을 파악하기 위함이다. 자료수집은 2020년 11월부터 12월까지 진행되었고, 대상자는 경기도 소재 K대학교 간호학과 3학년 학생 115명이었다. 자료 분석은 SPSS/WIN 23.0 Program을 이용하여 실수, 백분율, 평균, 표준편차, t-test, one-way ANOVA, Pearson correlation, stepwise multiple regression으로 분석하였다. 연구결과, 과제가치(r=.44, p<.001), 교수 실재감(r=.61, p<.001), 인지적 실재감(r=.68, p<.001), 감성적 실재감(r=.76, p<.001), 사회적 실재감(r=.72, p<.001)은 모두 학습몰입과 유의한 정적인 상관관계가 있었다. 회귀분석 결과, 몰입에 유의하게 영향을 미치는 요인은 감성적 실재감(β=.58, p<.001)과 인지적 실재감(β=.23, p=.020)이었으며, 설명력은 58.6%였다. 본 연구결과를 토대로, 간호대학생의 온라인 학습 환경에서의 몰입을 높이기 위해서 교수자는 감성적 실재감과 인지적 실재감 향상을 위한 노력을 기울일 필요가 있겠다.