Online Learning Policy Research Articles

The Impact of Public Policies on Teaching Learning Activities Due to The Covid-19 Pandemic

Covid-19 In response to the COVID-19 pandemic, Indonesia, as declared a national disaster by President Joko Widodo through Presidential Decree No. 12 of 2020, has transitioned into an emergency response phase for non-natural disasters. The World Health Organization labeled COVID-19 a global pandemic on March 11, 2020. The pandemic has significantly disrupted various aspects of daily life, notably the education sector. To maintain educational continuity amidst this crisis, the Indonesian government implemented online learning policies. This shift from traditional face-to-face instruction to distance education poses unique challenges, especially for elementary and kindergarten students. This journal explores the impact of these public policies on teaching and learning during the pandemic, using a descriptive-analytical literature review. Findings reveal that while technology facilitates continued education, it also introduces challenges related to academic culture, values, attitudes, skills, and technological readiness. The study underscores the crucial role of technology in bridging the gap created by the pandemic and highlights the need for addressing associated obstacles to enhance the effectiveness of online education.

Analysis of the structural relationship emotional regulation, academic procrastination, and academic burnout

<span lang="EN-US">Academic burnout (AB) is a problem that many students are currently facing since the online learning policy was implemented. This research aims to analyze the structural relationship between emotional regulation (ER), academic procrastination (AP), and student AB. This research used ex post facto causal relationship explanatory design. The research subjects were 417 high school students in East Java. The sampling was cluster random sampling technique. The data analysis technique used the Rasch model and structural equation modelling (SEM). The results showed that there was a significant relationship between ER and AP and AB. The implication of findings on the school guidance and counselling program is that the counsellors must pay attention to the factors that contribute to student AB so that counselling services can be designed to prevent student AB.</span>

Get a Head Start: On-Demand Pedagogical Policy Selection in Intelligent Tutoring

Reinforcement learning (RL) is broadly employed in human-involved systems to enhance human outcomes. Off-policy evaluation (OPE) has been pivotal for RL in those realms since online policy learning and evaluation can be high-stake. Intelligent tutoring has raised tremendous attentions as highly challenging when applying OPE to human-involved systems, due to that students' subgroups can favor different pedagogical policies and the costly procedure that policies have to be induced fully offline and then directly deployed to the upcoming semester. In this work, we formulate on-demand pedagogical policy selection (ODPS) to tackle the challenges for OPE in intelligent tutoring. We propose a pipeline, EduPlanner, as a concrete solution for ODPS. Our pipeline results in an theoretically unbiased estimator, and enables efficient and customized policy selection by identifying subgroups over both historical data and on-arrival initial logs. We evaluate our approach on the Probability ITS that has been used in real classrooms for over eight years. Our study shows significant improvement on learning outcomes of students with EduPlanner, especially for the ones associated with low-performing subgroups.

Advancing Digital Transformation in Chinese Education: A Comprehensive Analysis of Current Trends, Opportunities, Challenges, and Strategic Imperatives

This study assesses the progress and identifies the pivotal advancements in China's digital education, including infrastructure improvements, the growth of online learning platforms, policy support, and technological innovations. It underscores digital education's significance in promoting educational equality, updating teaching methods, raising educational standards, expanding resources, and encouraging lifelong learning. Nevertheless, digital education's expansion encounters significant challenges: the digital divide, educators' insufficient digital skills, inconsistent quality of educational content, difficulties in developing students' self-learning skills, and concerns over data security and privacy. To address these issues, the study outlines strategic directions specific to China's educational context: enhancing infrastructure and technology access, increasing digital literacy among teachers and students, supporting personalized and adaptive learning approaches, improving digital resources and evaluation methods, integrating online and offline learning experiences, and expanding international cooperation. These strategies are designed to address existing challenges and stimulate ongoing innovation and improvement in China's digital education sector.

Online Policy Learning-Based Output-Feedback Optimal Control of Continuous-Time Systems

Online Policy Learning-Based Output-Feedback Optimal Control of Continuous-Time Systems

Challenges and Strategies: Online Learning for Elementary School Teacher Education Students

The existence of an online learning policy that seems suddenly has an impact on many students who are not ready to carry out the online learning process. The aim of this research is to examine perceptions, problems, and summarize students' experiences regarding strategies for resolving challenges when participating in online learning. This research is classified as a qualitative descriptive research type, with research subjects namely 61 students. Data collection in the research was carried out using observation, interviews and questionnaires, with research instruments in the form of observation and interview guidelines. The data obtained in the research was then analyzed using the Bogdan & Biklen model data triangulation technique. The data obtained is then presented in qualitative descriptive form, by adjusting the research results with the results of previous research. The results of the research analysis show that the challenges faced by students when carrying out online learning activities consist of interference from the surrounding environment, less than optimal use of the internet, students' lack of understanding of the material delivered by lecturers and reduced interaction between students and lecturers during online learning. The strategies used to face challenges for students taking part in online learning are adapted to the students' different conditions and abilities so that solutions can be found individually.

ONLINE LEARNING POLICY EVOLUTION STUDY: BIBLIOMETRIC ANALYSIS

This study aims to analyze the scientific literature on online learning policies, from the first published paper (2001) to the present (2022) through bibliometric analysis and visualization by utilizing the Scopus database-based VOSviewer software. This study took 384 articles from international authors that focused on the topic of policy online learning. Articles are classified according to the year of publication, author country, co-author, affiliation, keywords and journal title. Furthermore, articles are examined based on several indicators, including the contribution of the state/institution/author. Journal distribution, heavily cited articles, bibliographic coupling and keyword analysis. The search results show that the United States serves as the country of origin of the most prolific author affiliation in publishing articles, the Department of Early Childhood Education, The Education University (Hong Kong) serves as the home of the most prolific author affiliation, and Agaton CB, from The Open University (United States), is considered the most prolific writer. In addition, the Sustainability (Switzerland) Journal is the source of the most discussed publication topics in its journals. Furthermore, Impacts of the Covid-19 Pandemic on Life of Higher Education Students: A Global Perspective is considered the article with the most references. In addition, the most widely discussed topics are online learning policies, e-learning, public education policies, educational policies, sustainable development, digital technologies teaching and learning, mobile learning, blended learning, and distance education.

Evaluation of PAI Teachers in Online Learning During The Covid-19 Pandemic at SMA Negeri Palu

The sudden online learning policy resulted in teachers experiencing inequality. Therefore, the purpose of this study is to examine the results of teacher evaluation in implementing online learning after the enactment of government policies during the COVID-19 pandemic with the aim of analyzing teacher performance during online learning, then mapping the obstacles faced as consideration in finding solutions for the next implementation of online learning. The method used in this study is qualitative descriptive by collecting observation data, student and teacher survey data through google form and teacher monitoring and evaluation results from school LMS. From the results of the study, it was found that teacher evaluation in online learning was less effective. The reason is the gap in teachers' digital literacy due to unpreparedness with online learning and the age of teachers so they cannot operate IT or digital applications for online learning.

Assessing the Prospects and Challenges of Online Learning in Kenyan Public Universities: A Case Study of Masinde Muliro University of Science and Technology

The increase in the number of internet users, the demand for education, and the widespread use of electronic devices among scholars have created a potential in online learning as an alternative to traditional education. This can be linked proper planning, clear online learning policies and trained personnel to facilitate the online learning process. Recent studies point to the possibility of African public universities adopting online learning more aggressively in the future than ever before. This study therefore outlines the opinions of lecturers, students and the management of Masinde Mulari University of Science and Technology regarding the prospects and challenges of online pedagogical infrastructure and how it affects learning in public universities. The study used a descriptive survey. Data was collected from a sample size of 682 which included students, members of faculty, and technical staff. The sample was selected using a stratified sampling technique. Data was collected using questionnaires and interview schedules. Analysis was done using frequencies, means, standard deviations, and regression analysis. The findings showed that mobile learning is the solution to online learning problems given its accessibility and availability amongst most learners. It also shows that online learning provides customized learning experiences in which learning is student-centered. The results from ordered logistic regression, (Wald = 0.673,) showed that indeed challenges of use of online pedagogical infrastructure affects learning in public universities. This was confirmed by the analysis of interval data using simple linear regression in which the outcome for both faculty and students also were in line with the findings of logistic ordered regression,

The Influence of Problem Characteristics, Regulatory and Non-Regulatory Supporting Capabilities on The Process of Implementing E-Learning Online Learning Policies at Nusa Cendana University

This research aims to analyze the influence of problem characteristic factors, regulatory and non-regulatory carrying capacity on the implementation process of e-learning based online learning policies at Nusa Cendana University. This type of research uses a positivism paradigm with a quantitative approach, where to obtain the truth of the data, direct interviews are conducted with the object under study. The sample used in this research was 467 people who were lecturers and students at Nusa Cendana University. Research data was analyzed using descriptive statistical tests and PLS-SEM inferential statistics. The results obtained show that descriptively the four variables received a good category response with indicators of problem characteristic factors reaching 73.28%, regulatory carrying capacity of 78.27%, non-regulatory carrying capacity of 77.11% and the e-learning implementation process of 75.05%. Hypothesis testing shows that the problem characteristic factor has a significant positive influence (p<0.05) directly at 18.4% and through non-regulatory carrying capacity at 48.3% but through regulatory carrying capacity at only 5.3% it does not have a significant influence (p>0.05) towards the process of implementing e-learning based online learning policies at Nusa Cendana University. The results of the determinant test show that the problem characteristic factors have a significant moderate/moderate influence (p<0.05) through regulatory carrying capacity of 50.2% and through non-regulatory carrying capacity of 53.0% but together/simultaneously they give a strong influence of 75.3% while 24.7% was influenced by other factors outside this research.

Kendala Penerapan Pembelajaran Daring pada Mahasiswa di Fakultas Keguruan dan Ilmu Pendidikan Universitas Khairun

The implementation of online learning was implemented suddenly due to the Covid-19 pandemic that hit in 2019, online learning policies are a temporary solution to stop the spread of Covid-19. However, this policy has had a big impact on the world of education, various problems arise from the factor of implementing the policy. This study aims to examine the obstacles to the implementation of online learning experienced by FKIP students, Unkhair. The method used in this study is a descriptive quantitative approach. Data collection through surveys. The instrument used is an electronic questionnaire via google form. The questionnaire used is a closed questionnaire and an open questionnaire. The correspondents of this study were FKIP Unkhair students as many as 150 correspondents who were representatives of 7 study programs. Based on the results of the research analysis, it can be concluded that there are 4 points of obstacles faced by FKIP students during online learning, namely limited internet quota, inadequate internet network, low understanding of IT and limited infrastructure. However, these obstacles can be anticipated through serious online learning designs by considering the convenience of learning, the readiness factors of lecturers and students and the availability of supporting facilities. In conclusion, there are 4 obstacles to implementing online learning policies. To overcome them, the involvement of all parties is required to design high-quality online learning.

The Effect of Implementation of Syam-OK Based Online Learning Policies and Lecturer Competence on Student Learning Motivation at the Faculty of Social Sciences and Law, Makassar State University

This study aims to examine the Effect of Implementation of Syam-Ok-Based Online Learning Policies and Lecturer Competence on Student Learning Motivation in the Faculty of Social Sciences and Law, Makassar State University. This type of research is a quantitative research using a descriptive approach. Data collection techniques were carried out by means of observation, interviews, questionnaires and documentation. The data analysis technique used consists of testing the validity and reliability of the instrument, descriptive statistical analysis, normality test and inferential statistical analysis. The results of the study show that the implementation of the Syam-Ok-based online learning policy is well implemented with a percentage of 75.73%, the competence of lecturers at the Faculty of Social Sciences and Law, Makassar State University is in the good category with a percentage of 79.20%, student learning motivation is in the good category with a percentage of 73%, the implementation of online learning policies based on Sham-Ok has a significant influence on student learning motivation with a percentage of influence of 56.9% in the medium category, lecturer competence has a significant influence on student learning motivation with a percentage of influence of 70.2% in the high category , and the implementation of Syam-Ok-based online learning policies and lecturer competencies together can influence student learning motivation in the Faculty of Social Sciences and Law, Makassar State University with an influence percentage of 70.4% in the high category and 29.6% influenced by other variables. Keywords: Policy Implementation, Lecturer Competence and Motivation

Academic Performance of Higher Education Students Through Online Learning

The objective of this study is to investigate the relationship between academic success and personal development in students, as measured by their grades. The study aims to evaluate the effectiveness of policies in higher education institutions that promote both academic achievement and personal growth. The analytical method used is confirmatory factor analysis. The result of this study shows that students' personal development has no impact on the determination of online learning policies. Hence online learning policy determination cannot affect the assessment of online learning outcomes. Nonetheless, student’s personal development undertaken can influence the assessment of online learning outcomes, and implementing online learning policies can mediate the effect of personal development on online learning outcomes assessment. Therefore, a student's future achievement should be determined only by the academic performance that does not have to depend on local government policy.

RAPID: Enabling fast online policy learning in dynamic public cloud environments

Resource sharing between multiple workloads has become a prominent practice among cloud service providers, motivated by demand for improved resource utilization and reduced cost of ownership. Effective resource sharing, however, remains an open challenge due to the adverse effects that resource contention can have on high-priority, user-facing workloads with strict Quality of Service (QoS) requirements. Although recent approaches have demonstrated promising results, those works remain largely impractical in public cloud environments since workloads are not known in advance and may only run for a brief period, thus prohibiting offline learning and significantly hindering online learning. In this paper, we propose RAPID, a novel framework for fast, fully-online resource allocation policy learning in highly dynamic operating environments. RAPID leverages lightweight QoS predictions, enabled by domain-knowledge-inspired techniques for sample efficiency and bias reduction, to decouple control from conventional feedback sources and guide policy learning at a rate orders of magnitude faster than prior work. Evaluation on a real-world server platform with representative cloud workloads confirms that RAPID can learn stable resource allocation policies in minutes, as compared with hours in prior state-of-the-art, while improving QoS by 9.0x and increasing best-effort workload performance by 19%–43%.

HUBUNGAN KEPERCAYAAN DIRI DENGAN KECEMASAN MAHASISWA KEPERAWATAN ANESTESIOLOGI DALAM MENYELESAIKAN SKRIPSI PADA MASA PANDEMI COVID-19 DI YOGYAKARTA

The Covid-19 pandemic affected the whole world, including Indonesia. The central and regional governments provided online learning policies for school and college children to minimize the spread of Covid-19. This situation caused psychological stress including anxiety in Anesthesiology Nursing students who were finishing their thesis. The study aimed to find out the factors related to the anxiety of Anesthesiology Nursing students in completing their thesis during the Covid-19 pandemic in Yogyakarta. This research employed quantitative correlation with a cross-sectional approach. The samples were 119 respondents. The research instrument used the HARS anxiety questionnaire and the RSES self-confidence questionnaire. The results of statistical tests using Spearman Rank found that there was a relationship between self-confidence and anxiety with a p value 0.000. Self-confidence were related to the anxiety of Anesthesiology Nursing students in completing thesis during the Covid-19 pandemic in Yogyakarta.

ANALISIS PEMBELAJARAN DARING DI MADRASAH ALIYAH AN-NUR BENER MERIAH


 Since the issuance of the circular letter of the Minister of Education and Culture on March 24, 2020, regarding the implementation of education in the emergency period of the spread of Covid-19, the learning process has been carried out throughout Indonesia online. This study aims to determine the implementation and process of making online learning policies, the media used in online learning, and the assessment carried out in online learning at Madrasah Aliyah An-Nur Bener Meriah. The research method used in this research is descriptive qualitative research, data collection techniques are carried out by means of observation, interviews and documentation, while the data is analyzed using qualitative analysis. This study resulted in findings in the form of the implementation of online learning at Madrasah Aliyah An-Nur Bener Meriah since April 2020 after a discussion was held by the head of the madrasa with stakeholders. There are several media used in online learning at Madrasah Aliyah An-Nur Bener Meriah, including Whatsapp, Google Classroom, Zoom Meeting. Assessment is carried out in a formative, fair, objective and transparent manner to get feedback from students and parents.
 

Sentiment Analysis Of Student Opinion Related To Online Learning Using Naïve Bayes Classifier Algorithm And SVM With Adaboost On Twitter Social Media

Twitter is one of the social media that functions to express opinions on issues or problems that are currently happening, such as problems in the social, economic, educational and other fields. One of the issues being discussed so far is online learning. The government has issued a policy, one of which is for all students to study at home online by using a network to be able to interact with each other like in the classroom. The government's reason for issuing this policy is to break the chain of the spread of the Covid-19 virus, which until now has not subsided. Regarding this online learning policy, there are pros and cons. This opinion is widely expressed on social media, one of which is Twitter. Sentiment analysis is a method for analyzing an opinion which aims to classify texts. The Naïve Bayes Classifier and Support Vector Machine methods are methods machine learning that can be used for sentiment analysis. The problem in classifying text is that the resulting accuracy is less than optimal, so feature selection or boosting is needed to improve its accuracy. In this study, optimization of boosting was carried out using Adaboost. The purpose of this study is to compare the performance of the algorithm before and after using Adaboost. The results of the sentiment analysis on online learning obtained the highest accuracy results by the Naïve Bayes Classifier algorithm coupled with Adaboost of 99.26%, with a precision of 99.39% and recall of 99.20%.

Students Resilience: The Impact of Online Learning Policies During The Covid-19 Pandemic on Academic Stress

The focus of this research is to investigate the symptoms of academic stress, its causes, and its impact on student resilience during the Covid-19 pandemic's online learning policies. This research used a qualitative approach conducted in April-June 2021 at two state vocational high schools in Salatiga, Central Java, Indonesia through an online survey and interviews. The results show that many students were experiencing symptoms of academic stress when online learning policies during the Covid-19 pandemic such as sleep disturbances, difficulty concentrating, irritability, headaches, and even physical illness due to overwhelming stress levels. The highest indicator that caused academic stress came from pressure to complete all subject's test targets and assignments in a limited time, disruption to the teaching and learning system, limited access to the internet network, preparation for graduation, and the difficulties students experienced in understanding the subject matter. Strong support networks, along with competent self-management, excellent social relationships, emotional control, and integration, can have a significant impact on student resilience. Overall, especially strong self-management has a very large influence in preventing or overcoming academic stress problems. Support networks are very important in limiting the impact of academic stress on student resilience during the Covid-19 pandemic online learning policies.

Warm-Starting Nested Rollout Policy Adaptation with Optimal Stopping

Nested Rollout Policy Adaptation (NRPA) is an approach using online learning policies in a nested structure. It has achieved a great result in a variety of difficult combinatorial optimization problems. In this paper, we propose Meta-NRPA, which combines optimal stopping theory with NRPA for warm-starting and significantly improves the performance of NRPA. We also present several exploratory techniques for NRPA which enable it to perform better exploration. We establish this for three notoriously difficult problems ranging from telecommunication, transportation and coding theory namely Minimum Congestion Shortest Path Routing, Traveling Salesman Problem with Time Windows and Snake-in-the-Box. We also improve the lower bounds of the Snake-in-the-Box problem for multiple dimensions.

The gap between teachers' English proficiency, necessity and online learning skills in the COVID-19 pandemic

Purpose: This study aims to investigate the relationship between teachers’ perceived necessity and their online learning skills during the COVID-19 pandemic in Indonesia. It focuses on four key elements of online course design: course communication, resource authenticity, time management and technical skills.
 Design/Methodology/Approach: A quantitative survey was used to collect data from 39 teachers using the Survey Monkey application and manual returns. The data was collected through five Likert- scale questionnaires.
 Finding: The findings showed a significant discrepancy between teachers' perceived necessity and their actual online learning skills. The mean score for teachers' perceived necessity for online learning was at the highest level while their actual skills were at the lowest. A positive correlation between English proficiency and teachers' online learning skills was found. Further analysis demonstrated a significant relationship between English proficiency and teachers' online learning skills.
 Conclusion: Teachers perceived the necessity for online learning skills as crucial as their actual skills were found to be limited or low during the pandemic. Furthermore, the study demonstrated that English proficiency skills positively impact teachers’ online learning skills.
 Research Limitations: It is recommended to carry out a more extensive investigation involving a larger population to obtain generalizable results.
 Practical Implication: The result indicates that teacher training in online learning skills is crucial in preparation for the future. The study informs the policymaker to consider further emergency situations related to the full online learning policy.
 Contribution to Literature: This study highlights the importance of English proficiency in the development of online teaching skills.