E-learning Research Articles

Generative AI: Student Perception on ChatGPT Prompt Feedback in Post-Secondary Online Education

Generative AI: Student Perception on ChatGPT Prompt Feedback in Post-Secondary Online Education

Analysis of Local Governance and Legal Protection of Students' Information Security in the Context of Sustainable Development of Digital Education

Local governments are dealing with student information more and more frequently, resulting in the risk of student information being leaked, so it is necessary to introduce relevant policies, laws and regulations to standardize information collection activities and improve the level of social information governance. Therefore, this study proposes three hypotheses: on the one hand, whether the information policy issued by the local government can guide students' information collection activities, and on the other hand, whether the introduction of local laws and regulations can provide protection for students' information security; Finally, whether public participation can provide supervision for student information collection and governance, and create a good public management environment. The results show that local information laws and regulations can regulate the behavior of students' information collection and clarify the purpose and direction of students' information collection. At the same time, laws and regulations such as privacy protection and local codes of conduct can improve the security of student information and ensure the legal collection of information. The active participation of the public is conducive to the public information collection environment and ensures the overall security of student information. Therefore, local government policies, laws, and regulations can provide assurance and support for students' information security and promote the sustainable development of digital education.

Comparing Computer-Assisted and Teacher-Led Instruction for Teaching Emergent Literacy Skills to Chinese Preschoolers With Autism

Emergent literacy skills are critical for future reading development, but children with autism commonly struggle with these skills. Computer-assisted instruction (CAI) is increasingly utilized to enhance literacy skills in these children, yet research on the relative efficacy of CAI and traditional teacher-led instruction (TLI) for these children has yielded inconsistent findings. The varied implementation of CAI and TLI has further complicated efforts to determine their relative efficacy. This study combined a multiple probe and multitreatment design to compare the efficacy of CAI and TLI, incorporating consistent instructional strategies, in teaching Chinese emergent literacy skills to three preschoolers with autism. Results showed significant progress in emergent literacy skills for all children. Computer-assisted instruction slightly outperformed TLI in overall emergent literacy scores and character application scores, while differences in pronunciation-form-meaning were minimal. Recommendations are proposed to enhance CAI and emergent literacy intervention strategies for children with autism.

Tackling antibiotic resistance-insights from eHealthResp's educational interventions.

Antibiotic resistance (AR) poses a significant challenging issue in public health worldwide. This phenomenon led to the emergence of antibiotic-resistant bacterial strains, making the treatment of respiratory infections increasingly difficult. Educational interventions targeting healthcare professionals are important to improve prescription practices and promote responsible antibiotic use. Digital tools, including clinical decision support systems and mobile applications, have proven to effectively enhance educational interventions and clinical decision-making. The eHealthResp project is one such initiative that includes an online course and a mobile app designed to improve antibiotic use for upper respiratory tract infections (URTIs). The online course provides clinical information and case studies, whereas the mobile app acts as a clinical decision support system for URTIs diagnosis. The purpose of this study is to analyse the utilization patterns of eHealthResp digital tools among primary care physicians and community pharmacists. Results showed that both physicians and pharmacists (n = 35) had favorable progress and high grades when completing the online course assessment. The mobile app data indicated a diverse range of searched cases with different respiratory symptoms, with the most common being acute nasal discharge and pain when swallowing. Most observations presented mild symptoms for less than seven days, suggesting the occurrence of acute self-limited infections. Despite limitations, digital tools show promise in enhancing patient care outcomes for managing URTIs. Future efforts should focus on expanding participation among health professionals and enhancing educational interventions to promote responsible antibiotic use.

Exploring a Collaborative Synchronous Online Learning Environment in an Initial Language Teacher Education Program

This qualitative study explores pre-service language teachers’ experiences in a collaborative synchronous online course in language teacher education program in Turkey. A course was designed to equip pre-service language teachers of English with the skills and knowledge necessary to effectively incorporate technology into their teaching and self-learning practices. Adopting a generic qualitative inquiry design, data were collected over 14 weeks from 63 pre-service EFL teachers through weekly reflection papers, online surveys, and face-to-face follow-up semi-structured interviews. The study found that technology-enhanced collaborative online course had a positive influence on participants’ engagement, interaction, and professional development with participants perceiving the course experience positively. The findings suggest that collaborative online courses, when they are effectively taught, can be a valuable professional development opportunity in initial language teacher education programs.

Online Learning and Decision Making Under Generalized Linear Model with High-Dimensional Data

We propose a minimax concave penalized multiarmed bandit algorithm under the generalized linear model (G-MCP-Bandit) for decision-makers facing high-dimensional data in an online learning and decision-making environment. We demonstrate that in the data-rich regime, the G-MCP-Bandit algorithm attains the optimal cumulative regret in the sample size dimension and a tight bound in the covariate dimension and the significant covariate dimension. In the data-poor regime, the G-MCP-Bandit algorithm maintains a tight regret upper bound. In addition, we develop a local linear approximation method, the two-step weighted Lasso procedure, to identify the minimax concave penalty (MCP) estimator for the G-MCP-Bandit algorithm when samples are not independent and identically distributed. Under this procedure, the MCP estimator can match the oracle estimator with high probability and converge to the true parameters at the optimal convergence rate. Finally, through experiments based on both synthetic and real data sets, we show that the G-MCP-Bandit algorithm outperforms other benchmarking algorithms in terms of cumulative regret and that the benefits of the G-MCP-Bandit algorithm increase in the data’s sparsity level and the size of the decision set. This paper was accepted by J. George Shanthikumar, big data analytics. Funding: This work was supported by the National Natural Science Foundation of China (NSFC) [Grants W2441021, 72371172, 72342023, and 71929101] and the National Science Foundation (NSF) [Grant DMS 1820702]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01557 .

Analisis Persepsi Pengguna Media Sosial Tentang Pembelajaran Online dan Offline Sebagai Kajian Desain Pembelajaran Blended yang Efektif dan Berkualitas

This research was conducted with the aim of examining the perception of twitter or X users about online and offline learning as a basis for considering blended learning design. The research was carried out using the Atlas.ti rocky thematic analysis approach. The stages of thematic analysis are data collection, category construction, sorting categories and data, naming categories, and finding meaning in each stage of analysis. The results of the study show that there are four groups of perceptions among students regarding the learning method they want: (1) students who prefer online learning, (2) students who prefer face-to-face learning, (3) students who are neutral, and (4) students who want a combination of online and face-to-face learning. Some of the factors that affect this perception include physical, psychological, and convenience factors offered by each learning method. This study also found a tendency to change perceptions among students. In order for online learning to provide optimal results, several important conditions are needed, namely guaranteed learning quality, student readiness to participate in learning independently and responsibly, and adequate online learning facility support

Effects of psychological need thwarting during COVID-19 remote instruction on Chinese, math, and EFL teachers' well-being and online teaching intentions.

The COVID-19 pandemic's "Great Online Transition" significantly impacted teachers. Existing research on Emergency Remote Teaching (ERT) lacks longitudinal designs and consideration of subject-specific contexts. This study, using the Stressor-Strain-Outcome framework, investigates psychological needs thwarting (PNT) during ERT on teachers' well-being and online teaching intentions, considering subject of instruction as a potential factor. Data were collected from 1,369 Chinese primary and middle school teachers of Chinese literature, mathematics, and English as a Foreign Language (EFL) at two time points: two weeks after ERT implementation (Time 1, mid-November 2021) and two months later, after returning to face-to-face teaching (Time 2, mid-January 2022). PNT, emotional exhaustion, psychological distress, and intention towards online teaching were evaluated. Among the types of PNT, competence thwarting emerged as the strongest predictor of emotional exhaustion, which was,in turn, associated with reduced online teaching intention and increased psychological distress. EFL teachers showed stronger associations between PNT, emotional exhaustion, and adverse outcomes, indicating higher susceptibility to strain during ERT. Subject of instruction, particularly for EFL teachers, significantly influences the relationship between PNT and teacher outcomes during ERT. Our findings underscore the need for subject-specific support strategies in online teaching environments.

Unveiling Digital Transformation and Teaching Prowess in English Education During COVID‐19 With Structural Equation Modelling

ABSTRACTThe present research looks at the reputation of digital platforms in online pedagogical English education in Pakistan, and the use of digital technology in virtual classrooms during public health emergencies. It explores how faculty members use digital technology in their pedagogical English teaching approaches by analysing their technological skill level. To achieve the study's objectives, an online survey was undertaken to gather primary data. University teachers delivering online courses during COVID‐19 in several cities throughout Punjab Province answered an online questionnaire survey. Smart‐PLS 3.3.9 and structural equation modelling (SEM) were used to investigate the recommended research framework. SEM analysis results showed that all proposed hypotheses were confirmed. This research presents an overview of faculty members' online pedagogical teaching abilities and digital technology during COVID‐19. The research findings are critical for determining how to incorporate technology during the pandemic period and to integrate technology into higher education during the new normal.

TRANSFORMASI PRAKTIK AKREDITASI BAN-PDM MALUKU MELALUI PELATIHAN DARING DALAM PENERAPAN INSTRUMEN AKREDITASI TERBARU

The purpose of this community service is to enhance the capacity of BAN-PDM assessors in Maluku Province through online training on the 2024 Accreditation Instrument. This training aims to deepen assessors' understanding of key aspects of educational accreditation, such as school climate, principal leadership, the role of educators, and the learning process. By integrating online methods, it is expected that this training can address the geographical challenges in the Maluku archipelago and improve the quality of educational accreditation in the region. The results of this training show that online methods are effective in enhancing assessors' understanding of the latest accreditation instruments. Despite facing technical challenges and connectivity limitations, participants demonstrated a significant increase in their understanding and skills related to educational accreditation. The evaluation of the training results indicates that assessors can effectively apply new knowledge in their accreditation practices, making a positive contribution to improving the quality of education in Maluku Province.

Assessment of Practice Preparedness among Novice Nurses in Private Hospitals: A Cross-sectional Study

Background. The crop of novice nurses who are currently employed is a product of flexible learning who had limited contact hours with actual patients, which is contrary to those who graduated from traditional learning modalities. Hence, it is essential to evaluate how the impact of flexible learning modality has affected the practice preparedness levels of novice nurses in the hospital setting. Objective. This study aimed to determine the level of practice preparedness and its associated factors among novice nurses who work in private hospitals. Methods. The study utilized a cross-sectional survey design. Data was gathered from a total enumeration of ninetyfour novice staff nurses who graduated from the flexible learning curriculum and are currently employed in private hospitals in Baguio City and La Trinidad. The tool used was a questionnaire in two parts. Part 1 consisted of questions related to demographic information and factors related to practice preparedness, and part 2 included the Nursing Practice Readiness Scale, with validity and reliability scores of >0.924 and 0.90, respectively. The data was analyzed using the SPSS V27 trial version. The protocol was approved by the Saint Louis University Research Ethics Committee. Results. Findings reveal that more novice nurses in private hospitals perceived themselves as well-prepared across all domains of practice preparedness: “Collaborative Interpersonal Relationship” (n = 94, 100%); “Patient Centeredness” (n = 92, 97.90%); “Self-regulation” (n = 90, 95.70%); “Clinical Judgment and Nursing Performance” (n = 78, 83.00%); and “Professional Attitudes” (n = 76, 80.90%). There is a significant association between practice preparedness and the following factors: “Attended more than one Training/Seminars per year” (p = 0.02), “Graduated from Private Schools” (p = 0.03), and “Assigned in Regular Wards” (p = 0.05).On the other hand, no significant association was found between practice preparedness and the following factors: “Sex” (p = 0.61) and “Membership in Professional Organizations” (p = 0.73). Conclusion. In agreement with existing studies, practice preparedness is multifactorial. However, what this study contributes are new factors that are favorable in making novice nurses more confident in performing their roles and responsibilities. These include being a graduate of private schools, being assigned to regular wards, and attending professional training/seminars more than once annually. Advantageously, these factors that promote practice preparedness are modifiable.

Effect of virtual education on health responsibility of overweight students during the COVID-19 pandemic.

The global prevalence of obesity is increasing not only in adults but also in children and adolescents. In addition to the role of genetic and biological factors, policies such as the need for quarantine during the coronavirus epidemic and the family's behavioral and socioeconomic status in causing obesity cannot be ignored. The current research aimed to investigate the effect of virtual education programs on the health responsibility of overweight students during the outbreak of the Coronavirus. This was a semi-experimental study with a pre-test-post-test design and a randomized control group, which was conducted in three stages)pre-intervention, intervention, and post-intervention) during 2021-22 in Tehran Province, Iran. The samples were 60 adolescent girls aged 12-18 with a body mass index higher than 25 and placed in two test and control groups through random cluster sampling. Data was collected using the demographic information profile and the 12-item health responsibility questionnaire from HPLPII. The intervention was implemented as 6 virtual training sessions of 1.5h for the test group. After 1.5 months, BMI was measured and a post-test was done. SPSS version 22 software was used for data analysis. There was no significant change in the BMI of students after the intervention in the control group (p = 0.476), but it decreased significantly in the test group (p < 0.001). Before the intervention, there was no statistically significant difference between the average score of health responsibility in the test group (54.63 ) and the control group (53.03 6.79) (P= 0.370). After the intervention, the mean difference between the test group (62.56) and the control group (55.10) was statistically significant (P< 0.001). Before the intervention, about 70% of the students in both the test and control groups were at a relatively favorable health responsibility level. After the study, the number of students in the test group who were placed at a completely favorable level was almost twice as before, and a statistically significant difference was observed between the two groups(P = 0.035). The results of the present study showed that virtual education during the outbreak of COVID-19 has led to an increase in the responsibility for the health of overweight and obese students (in terms of improving health behaviors, increasing the hours of physical activity, and modifying the eating pattern) and reducing the body mass index of students.

Can Digital Technology Revolutionize Continuous Education in Diabetes Care?

Rapid technological advancements, such as artificial intelligence, wearable technologies, and telehealth with remote monitoring, are transforming continuous education for health care providers (HCPs) in diabetes management. These technologies improve patient care and necessitate innovative educational approaches to prepare HCPs for clinical integration. Digital education offers real-time, scalable, and cost-effective solutions, especially in areas with health care workforce shortages. However, the effect of digital education on HCPs' knowledge, skills, attitudes, and patient outcomes remains under-researched and necessitates further study. As technologies advance, achieving precision in diabetes continuous education becomes feasible. The 2024 ADA Standards of Care emphasize early adoption of advanced technologies and proficiency among HCPs. This commentary explores transformative trends, discussing limitations and proposing solutions to revolutionize continuous education in diabetes care.

Validating the impact of gamified technology-enhanced learning environments on motivation and academic performance: enhancing TELEs with digital badges

This research focuses on validating the impact of gamified technology-enhanced learning environments (TELEs) on motivation and academic performance. The study aims to categorize and design digital badges based on game mechanics and to evaluate the effects of two distinct types of digital badges on learning outcomes. The research involved 95 university students learning classical Japanese grammar. The findings reveal that digital badges significantly enhance learners’ intrinsic motivation, positively affecting all five dimensions of intrinsic motivation, while their impact on extrinsic motivation was found to be minimal. Additionally, when comparing the two categories of digital badges, no significant differences in effectiveness were observed. The primary interest of this paper lies in exploring the design and efficacy of digital badges within technology-enhanced learning environments, contributing valuable insights into how these elements can enhance student engagement and learning outcomes.

Harnessing hybrid deep learning approach for personalized retrieval in e-learning.

The current worldwide pandemic has significantly increased the need for online learning platforms, hence presenting difficulty in choosing appropriate course materials from the vast online educational resources due to user knowledge frameworks variations. This paper presents a novel course recommendation system called the Deep Learning-based Course Recommendation System (DLCRS). The DLCRS combines a hybrid Sequential GRU+adam optimizer with collaborative filtering techniques to offer accurate and learner-centric course suggestions. The proposed approach integrates modules for learner feature extraction and course feature extraction that is performed using (Embeddings from Language Models) ELMO word embedding technique in order to gain a thorough understanding of learner and course profiles and feedback. In order to evaluate the efficacy of the proposed DLCRS, several extensive experiments were carried out utilizing authentic datasets sourced from a reputable public organization. The results indicate a notable area under the receiver operating characteristic curve (AUC) score of 89.62%, which exceeds the performance of similar advanced course recommendation systems. The experimental findings support the viability of the DLCRS, as seen by a significant hit ratio of 0.88, indicating high accuracy in its suggestions.

Evaluasi Platform Elearning pada Matakuliah Metodologi Penelitian Menggunakan Model Evaluasi CIPP

The problem in this study is the lack of student understanding in the online learning process through the e-learning platform in the Research Methodology course and the absence of an evaluation of the effectiveness of using the e-learning platform in the learning process. The purpose of this study is to determine the evaluation of the e-learning platform in the Research Methodology course using the CIPP evaluation model which includes Context, Input, Process, and Product. Overall, the results of this study indicate that the e-learning platform has a positive impact on Research Methodology learning. Although all aspects are in the good category, the percentage value of each aspect is still close to the lower limit of the category, so there is still room for further improvement to increase the effectiveness of learning as a whole.

Investigating the Factors Influencing Online Learning for Sustainability in Higher Education

Investigating the Factors Influencing Online Learning for Sustainability in Higher Education

Profiles of goal adjustment capacities are differentially associated with perfectionism, excellencism, and psychological adjustment of students in a time of crisis

ABSTRACT Students had to adjust their goals during the sudden shift to online teaching amidst the COVID-19 pandemic. This study with 613 university students identified four multidimensional profiles based on how they relied on goal disengagement, reengagement, and perseverative engagement (a new dimension of goal adjustment capacities). Students who disengaged from goals, reengaged in new ones, and were less likely to dwell on their former goals (goal reengagement profile) experienced less stress and burnout and more growth experiences. Students who reengaged less in goals (goal entrapment profile) and those who reengaged but dwelled on their former goals (action crisis profile) experienced worse psychological outcomes. Perfectionists were more likely than excellence strivers to be part of an action crisis goal adjustment profile.

The impact of UTeach observation protocol-based multiple-source feedback on improving the quality of online teaching in medical education.

The ability to teach, as a core competency, has always suffered from a lack of systematic cultivation. This study aimed to explore the difference in teaching quality before and after the application of the UTOP (UTeach observation protocol)-based multiple source feedback (MSF) formative assessment of the quality improvement of medical education classrooms. This study retrospectively analyzed the teaching quality of the Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine and the Third Affiliated Hospital of Chongqing Medical University. The participants were divided into control and UTOP groups according to the actual training they took in the teaching. All the participants, including teachers and trainee teachers, who were under conventional teaching methods were in the control group, and those who were under MSF training were in the UTOP group. UTOP and New Teacher Assessment Scores (NTAS) were evaluated, and the differences between the two courses were analyzed. The UTOP group was divided into a teacher group and a practice group according to differences in the participants' teaching experience. The UTOP-MSF evaluation data were extracted and analyzed, and the differences in teaching quality were compared before and after the implementation of MSF training. The study was conducted for 10 months, with 43 participants completing 120 web-based lectures. In the control group, 32 participants were included, including 22 teachers with 27 courses and 10 trainee teachers who had no teaching experience with 13 courses. Eleven participants in the UTOP group received 9 rounds of MSF feedback training and completed 80 online lectures, including 3 teachers with 19 courses and 8 trainee teachers with 61 courses. A total of 324 evaluations from researchers were extracted and analyzed, including 162 UTOP scores and 162 NTAS; 575 MSF assessments were analyzed, including 438 from the teachers and 137 from the trainee teachers. The participants in the UTOP group had significantly higher UTOP and NTAS scores than did those in the control group did (59.84 ± 14.64 vs. 40.74 ± 6.80, p = 0.000; 73.00 (62.25, 80.00) vs. 53.00 (50.75, 57.00), p = 0.000, respectively). Among the participants who performed UTOP training, the UTOP-MSF scores increased for both teachers and trainee teachers (51.50 (37.75, 68.25) vs. 73.00 (68.00, 76.50), p = 0.022; 41.00 (36.00, 51.75) vs. 68.00 (59.75, 77.00), p = 0.000, respectively). The mean UTOP MSF scores were strongly positively correlated with the mean NTAS (r = 0.640, p = 0.000). UTOP-based MSF training significantly improved teaching quality in medical education, and it can be an effective tool for evaluating teaching quality.

A Space-Efficient One-Pass Online SVM Algorithm

In this paper we consider the problem of training a Support Vector Machine (SVM) online using a stream of data in random order. We provide a fast online training algorithm for general SVM on very large datasets. Based on the geometric interpretation of SVM known as the polytope distance, our algorithm uses a gradient descent procedure to solve the problem. With high probability our algorithm outputs an [Formula: see text]-approximation result in constant time and space, which is independent of the size of the dataset, where [Formula: see text]-approximation means that the separating margin of the classifier is almost optimal (with error [Formula: see text]), and the number of misclassified training points is very small (with error [Formula: see text]). Experimental results show that our algorithm outperforms most of existing online algorithms, especially in the space requirement aspect, while maintaining high accuracy.