Current Learning Systems Research Articles

Pengenalan Permainan Tradisional Bali Dolanan Bagi Anak Usia Dini

The aim of this research is to reintroduce the traditional Balinese game dolanan, whose existence needs to be maintained so that it is not eroded by the era that is starting to be touched by modern culture. The type of research used is literature review research with a focus on the traditional Balinese game "Dolanan". The data sources obtained are based on the results of identification, evaluation and synthesis of research work produced by practitioners and previous researchers such as articles, books and other documents whose authenticity can be verified. The results of the research reveal that dolanan is starting to be rarely seen and even the existence of "dolanan" is decreasing and starting to be abandoned, especially in urban areas that have touched western culture. This is also due to the current learning system which has the smell of modern and contemporary technology. Therefore, efforts are needed to refresh or reintroduce the traditional Balinese game dolanan, whose existence needs to be maintained so that it is not eroded by the times that are starting to be touched by modern culture. Training on the art of dolanan in schools is important to carry out, especially in schools which are in urban areas where if you look at the large number of children who often communicate using Indonesian rather than Balinese. Re-introducing young children to the existence of the traditional dolanan game is very important carried out as an effort to develop aspects of art in early childhood.

Fourth Person

In the context of polycrisis and systemic collapse, the primary challenge we face is a widely shared sense of collective depression—a lack of agency in regard to the bigger picture. What does it take to serve evolutionary transformation in the face of systemic collapse? In our view, it takes a form of knowing which extends beyond the current constructs of first-, second- and third-person knowing around which much of our current learning, knowledge, and leadership systems are organized. In this paper, we suggest fourth-person knowing as a distinct epistemology at the intersection of the other three, and we draw on our action research to illuminate five phenomena that point to and distinguish fourth-person knowing: (1) knowing that comes through me but is not of me; (2) knowing that shows up in my individual experience as a decentering of perception; (3) a heightened sense of potential, of possibilities that previously were experienced as unattainable now appear to be in reach; (4) sensing your own agency in helping the ‘universe’ (the larger field) to evolve; and (5) significant long term impact in terms of practical results. It is our hope that by articulating fourth person knowing we can provide an epistemic basis upon which research and inquiry methodologies can be built, complementing first-, second- and third-person forms of inquiry, methodologies based on deep sensing and presencing that support individuals and collectives to recognize, connect with and manifest what is theirs to do in the wider context of this moment and the incipient patterns of emergence and movement making.

Comparison of Outcomes Between Robot-Assisted Language Learning System and Human Tutors: Focusing on Speaking Ability

This study explores how much current mainstream Robot-Assisted Language Learning (RALL) systems produce outcomes compared to human tutors instructing a typical English conversation lesson. To this end, an experiment was conducted with 26 participants divided in RALL (14 participants) and human tutor (12 participants) groups. All participants took a pre-test on the first day, followed by 30 min of study per day for 7 days, and 3 post-tests on the last day. The test results indicated that the RALL group considerably improved lexical/grammatical error rates and fluency of speech compared to that for the human tutor group. The other characteristics, such as rhythm, pronunciation, complexity, and task achievement of speech did not indicate any differences between the groups. The results suggested that exercises with the RALL system enabled participants to commit the learned expressions to memory, whereas those with human tutors emphasized on communication with the participants. This study demonstrated the benefits of using RALL systems that can work well in lessons that human tutors find hard to teach.

Penerapan Metode Belajar Partisipatif dalam Meningkatkan Kemampuan Membaca Siswa di SDN 064960 Medan Polonia

In this era of increasingly rapid development and progress, there are so many learning resources and styles that can be applied by teaching staff to increase students' interest in learning and enthusiasm. However, even so, the current learning system still often finds cases where students will just sit listening to the teacher deliver learning material and only follow what is conveyed by the teacher without understanding what the teacher is conveying. Therefore, the teacher is expected to be able to foster students' interest in being directly involved in the learning process. Participatory learning can be interpreted as an effort by educators to involve students in learning activities. Participatory learning activities imply the participation of students in learning activities so that they can achieve the goals of the learning itself. The purpose of this study was to improve students' reading skills at UPT SDN 064960 using a participatory method. This activity is a field work practice in collaboration with campus programs teaching USU partners for approximately four months of assignment. The method used by researchers is a social work method at the mezzo intervention level with a groupwork approach. From the results of the implementation of participatory learning methods in improving students' reading skills, it was concluded that they could achieve predetermined goals in this program, namely increasing students' reading skills.

Learning IoV in 6G: Intelligent Edge Computing for Internet of Vehicles in 6G Wireless Communications

Abstract--In sixth-generation (6G) wireless communications, deep learning will still be essential for the Internet of Vehicles (IoV). 6G will bring new opportunities and challenges to current deep learning systems applied in the IoV environment. This article introduces a new framework named Learning IoV in 6G, focusing on the deep learning applications for IoV in 6G. We also apply the proposed framework in a flying base station (FBS) to evaluate the performance for future IoV in 6G.

Perancangan dan Pembuatan Sistem Informasi E-Learning Menggunakan Web Framework CodeIgniter Studi Kasus: SMA Ksatrya Jakarta

The influence of information and communication technology on the world of education is rapidly evolving, shifting the learning paradigm from face-to-face teaching to media-based learning. SMA Perguruan Ksatrya Jakarta, under the Yayasan Perguruan Ksatrya, focuses on innovation in the field of education. However, the current learning system remains manual, relying on face-to-face interactions between teachers and students, which are limited in discussions and interactions. This condition leads to a lack of achieving learning targets. This research aims to design an e-learning information system using the CodeIgniter framework. The selection of CodeIgniter is expected to facilitate e-learning, enhance efficiency, and improve the accuracy of learning management. System development involves PHP and MySQL, designed based on UML principles. The research output yields an e-learning information system aimed at enhancing the understanding of the teaching and learning process at SMA Ksatrya. This system is anticipated to support more dynamic interaction between teachers and students while expediting the learning process following the SDLC method. SMA Ksatrya Jakarta has the potential to enhance the quality of learning, facilitate better interaction, and expedite the learning process in line with the strategically set objectives.

SaRF: Saliency regularized feature learning improves MRI sequence classification

Background and objectiveDeep learning based medical image analysis technologies have the potential to greatly improve the workflow of neuro-radiologists dealing routinely with multi-sequence MRI. However, an essential step for current deep learning systems employing multi-sequence MRI is to ensure that their sequence type is correctly assigned. This requirement is not easily satisfied in clinical practice and is subjected to protocol and human-prone errors. Although deep learning models are promising for image-based sequence classification, robustness, and reliability issues limit their application to clinical practice. MethodsIn this paper, we propose a novel method that uses saliency information to guide the learning of features for sequence classification. The method uses two self-supervised loss terms to first enhance the distinctiveness among class-specific saliency maps and, secondly, to promote similarity between class-specific saliency maps and learned deep features. ResultsOn a cohort of 2100 patient cases comprising six different MR sequences per case, our method shows an improvement in mean accuracy by 4.4% (from 0.935 to 0.976), mean AUC by 1.2% (from 0.9851 to 0.9968), and mean F1 score by 20.5% (from 0.767 to 0.924). Furthermore, based on feedback from an expert neuroradiologist, we show that the proposed approach improves the interpretability of trained models as well as their calibration with reduced expected calibration error (by 30.8%, from 0.065 to 0.045). The code will be made publicly available. ConclusionsIn this paper, the proposed method shows an improvement in accuracy, AUC, and F1 score, as well as improved calibration and interpretability of resulting saliency maps.

Research on the construction of personalized learning system supported by big data in education

Abstract In order to optimize the drawbacks of current personalized learning systems on the market, a big data algorithm is used to optimize the personalized learning system. This paper first analyzes the system model, constructs the basic framework of the system, and optimizes the algorithm based on a collaborative filtering algorithm that converts user behavior into ratings and recommends personalized learning content for learners. Since learning resources and learners are interconnected, this connection is analyzed by an ant colony algorithm to provide the optimal path for students to learn and create a personalized learning path. After comparing the student models, we understand that the clearer the description of students’ interests, the clearer the accuracy returned, where User A and User C have the highest similarity of 99% and accuracy of 85% and 88% respectively, proving the feasibility of the system. The personalized learning system supported by big data in education can optimize the drawbacks of the current personalized learning system in the market, meet the concept of teaching according to student’s abilities, and outperform the learning system in the market.

A-343 Provider Performed Microscopy Program Makeover: One Institution's Experience

Abstract Background Provider Performed Microscopy (PPM) is a subset of moderate complexity tests performed by physicians and midlevel practitioners. Regulatory bodies require PPM to meet specific accreditation standards. Many institutions face challenges with engaging providers to complete required training and ongoing assessments. Not immune to these challenges, we set out to improve PPM compliance. We reviewed guidelines to identify potential gaps in our PPM program. The existing PPM program practitioners were not aware of specific regulations and current learning systems were not robust enough to meet the regulations. The Point of Care Testing team (POCT) set out to establish a root cause for non-compliance, identify and collaborate with practitioners, and develop a sustainable training and competency system. Quality improvement must establish sustainable solutions to ensure compliance. Method POCT focused efforts on improving practitioner training, competency, and collaboration with practitioners. Over a period of 2 months, we identified and engaged key stakeholders in each department to review historical data from training, competency completion, and result audits revealing gaps. We clearly communicated the standards and how the current program was not meeting standards such as a lack of formalized training and competency documentation, observation of result documentation, and proper reporting of results. By identifying gaps in training, we utilized stakeholders to develop simple processes to enable compliance such as creation of a tip sheet to guide the resulting process, development of a specific training checklist requiring both provider and POC technical consultant (TC) signatures. In collaboration, a system was created to identify practitioner availability for direct observation of the specific elements of assessment. We leveraged our clinical consultant (CC) to assist in the conversations on a peer level with providers to bolster the importance of compliance. Every practitioner was re-trained by our TC along with the CC. With sustainability in mind, POCT collaborated with administrative assistants and department administrators to be notified of new practitioners. Ongoing monitoring involves POCT completing periodic check-ins with the departments as a second layer of assurance. POCT maintains the records of training and competency expiry dates and assigns critical thinking assessments. Results After 2 months, significant improvements were observed. Completed trainings improved from 50% to 100%, competency from 40% to 85%, and proper result documentation by practitioners from 25% to 70%. A 6-month review showed training was maintained at 100%, competency maintained at 85%, and result documentation improved to 90%. Sustainable improvements were observed at 1 year where training and result documentation achieved 100% compliance and competency completion reached 95%. Conclusion Sustainable quality improvement with PPM compliance was achieved by collaborating with practitioners, understanding obstacles to meeting standards, and developing simple solutions specific to practitioner workflows. In doing so, we were able to develop a robust yet succinct system for initiating and maintaining compliance with PPM regulatory standards.

Image Tracking Berbasis AR Untuk Peningkatan Pembelajaran Buah Pada Pendidikan Anak Usia Dini (PAUD)

The current recognition and learning system still uses magazines, books and websites. This makes the lessons of the topics taught still difficult to understand. In this study, a fruit recognition learning model was created in early childhood education based on Augmented Reality and digitalized teaching aids. Augmented Reality is a technology that embodies the merging of the real world (reality) and virtual world (virtual) where this technology is also known as Virtual Reality. The marker in the form of an image will be captured by the camera, processed and a 3D fruit animation will appear on the mobile screen. The purpose of this research is to produce a fruit recognition learning model in PAUD TK Aba Sukoharjo Kalasan based on Augmented Reality and to create digitalized teaching aids. By using Augmented Reality the application can be educational and attract interest in children's curiosity. The method used in this study is the Multimedia Development Life Cycle (MDLC). The fruit recognition application has been applied to several child respondents. Based on research trials, before there was an application for interest in learning, children learned fruit recognition with a score of 73% with the predicate agreeing. The effect of positive trends on children to learn with augmented reality learning media is shown by a score of 81% of 30 child respondents stating that the application is very effective as an increase in the recognition of fruits

PENERAPAN VIDEO PEMBELAJARAN BAGIAN DAN FUNGSI PADA TANAMAN UNTUK KELAS 4 SD DI SD MUHAMMADIYAH 3 DENPASAR

Technological advances and the current pandemic situation require SD Muhammadiyah 3 Denpasar to evaluate the current learning system. The current learning system is less effective due to advances in technological developments, as well as the prolonged pandemic situation that has forced the learning system to be carried out online. Students are still confused about participating in online learning, and are often left behind in effective online learning because the gadgets students usually use for online learning are sometimes being used by their parents or other circumstances. Students need a source of literature or other sources of teaching materials that allow students to review the teaching materials after study hours. Therefore, this community service activity is carried out to provide an effective alternative to be applied to students, namely by making animated videos covering natural science subject matter regarding the functions and parts of plants. This community service activity begins with survey and preparation activities, analysis and development of learning videos, and then conducts outreach and training on how to use these learning videos. Based on the results of the training conducted, students and teachers can properly use this learning video as an alternative reference for learning materials.

FaceScan: Unmasking Identity Beyond the Surface

Biometrics, focusing on human behavior and features, encompasses face recognition as a vital technique. This paper offers a survey of face recognition methods, analyzing algorithms and approaches. Face recognition, crucial for security, is explored, emphasizing its computer-based recognition mechanisms. The paper provides an overview of face recognition methodology, recent techniques, and their efficacy under various conditions. Investigating potential biases in current deep learning systems, particularly towards children, reveals performance disparities. Strategies to mitigate this bias are evaluated, identifying effective fusion techniques. Recent advancements in face recognition, fueled by technological progress, have made automated systems practical and widely applicable. This review assesses the strengths, weaknesses, and current/future applications of face recognition technology, including IBM's system and its domains of application.

The concept of life skills employed in the epic Ramayana: A theoretical perspectives

Every human being in the world is unique creation of this universe and one is born with specific qualities and characteristics. If we are not able to use the hereditary and acquired qualities to increase our efficiency, then these qualities have no meaning in the life. In this context, the importance of life skills in the field of education is being explained today. Life skills education provides the person with the skills to face the conflicts that come in life. This creates the foundation of a cultured society that is prudent. Even scholars in modern times admit that although the current education system is familiar with these life skills principles, most of these have been developed by Western countries. While there is a comprehensive description of life skills pervading in ancient Indian scriptures. The theoretical perspective of those aspects are compiled and presented here with examples related to life skills described in the Ramcharitmanas. The current attempts may serve as a guide for moral, spiritual and social advancement in education needed in current learning system. Theoretical presentation may be contributory to the current battery of knowledge in the areas of life skill exploration in the contexts of ancient scriptures.

Perceptions of orthopaedic medicine students and their supervisors about practice-based learning: an exploratory qualitative study

BackgroundPractice-based learning is crucial in forming appropriate strategies for improving learning among the medical students that support the country’s understaffed health sector. Unsatisfactory learning consequently results in poor performance of students and poor quality of health care workforce in the long run. Exploring the perceptions about the current practice-based learning system and how to improve is thus vital. This study set out to explore the perceptions of Orthopaedic medicine students and their supervisors about practice-based learning at a tertiary training hospital.MethodsThis was an exploratory phenomenological qualitative study that involved in-depth interviews among 10 Orthopedic students during their rotation in the emergency ward of Mulago hospital and 6 of their supervisors. Interviews were audio-recorded, transcribed, and then imported into Atlas ti 8.3 for analysis. The data were coded and grouped into themes relating to perceptions of practice-based learning, general inductive analysis was used. The general inductive approach involved condensing the raw textual data into a brief and summary format. The summarized format was then analyzed to establish clear links between the perceptions of practice-based learning and the summary findings derived from the raw data.ResultsThe mean age of the students was 23 ± 1.5 years. Four out of the six supervisors were Orthopaedic officers while the remaining two were principal Orthopaedic officers, four out of the six had a university degree while the other two were diploma holders. The main themes arising were hands-on skills, an unconducive learning environment, the best form of learning, and having an undefined training structure. Particularly, the perceptions included the presence of too many students on the wards during the rotation, frequent stock-outs of supplies for learning, and supervisors being overwhelmed caring for a large number of patients.ConclusionBarriers to satisfactory practice-based learning were overcrowding on the wards and insufficient training materials. To improve practice-based learning, adequate learning materials are required and the number of students enrolled needs to be appropriate for the student – supervisor ratio.

Interpretability-Guided Inductive Bias For Deep Learning Based Medical Image.

Deep learning methods provide state of the art performance for supervised learning based medical image analysis. However it is essential that trained models extract clinically relevant features for downstream tasks as, otherwise, shortcut learning and generalization issues can occur. Furthermore in the medical field, trustability and transparency of current deep learning systems is a much desired property. In this paper we propose an interpretability-guided inductive bias approach enforcing that learned features yield more distinctive and spatially consistent saliency maps for different class labels of trained models, leading to improved model performance. We achieve our objectives by incorporating a class-distinctiveness loss and a spatial-consistency regularization loss term. Experimental results for medical image classification and segmentation tasks show our proposed approach outperforms conventional methods, while yielding saliency maps in higher agreement with clinical experts. Additionally, we show how information from unlabeled images can be used to further boost performance. In summary, the proposed approach is modular, applicable to existing network architectures used for medical imaging applications, and yields improved learning rates, model robustness, and model interpretability.

FCM Clustering on Interaction Pattern Analysis of Chinese Language Learner Behavior.

In order to meet the needs of the current personalized education, improve the shortcomings of the current digital learning system in personalized learning, and introduce the service concept into education, the development and research of the personalized learning system based on the analysis of user behavior patterns has become the development of digital learning. This paper studies a language learning method, that includes obtaining the user's language learning interaction data to determine the user's language level: wherein, the user's language level data includes the user's initial language level and the current language level; initial learning model: according to the current language level, an adaptive algorithm is used to update the initial learning model, and the user performs linguistics further according to the updated learning model. In addition, in order to realize the clustering analysis of Chinese language online learning users' learning behavior, since the Fuzzy C-means (FCM) clustering results are easily affected by the selection of their initial cluster centers, a Harmony Search (HS)-FCM-based Chinese language learning user learning behavior clustering analysis is proposed. The participation dimension, focus dimension, regularity dimension, interaction dimension, and academic performance are selected as the analysis indicators of learning behavior. The learner level is divided into 5 levels, namely excellent, good, medium, qualified, and poor. Compared with HSFCM, and decision tree, it is found that the algorithm Improved HS (HIS)-FCM in this paper has higher clustering accuracy, faster convergence speed, and lower fitness, which provides new opportunities for learner level division and optimization of course learning.

Penguatan Kegiatan Pembelajaran IPS melalui Social Science Vocabulary Recognition Model through Guessing Games

The rapid development of learning has an influence on the learning process in the teaching unit. In the midst of current conditions, it is undeniable that it has an influence on the decline in student interest in learning. The current learning system process is through the concept of distance learning, of course, this must be followed by students, even though students experience a decrease in interest in learning and begin to feel the point of saturation in the learning process. The purpose of this study is to improve social science vocabulary recognition models through guessing games in the learning process through conditions during the adaptation period of new habits, so that it will lead to students' learning motivation, then to find out the increase in students' interest in learning social studies in the learning process at time to adapt to new habits. The research method used is a qualitative research approach by looking for data in the form of case studies on students, and direct observation on students. Data collection techniques were carried out using interview techniques, documentation techniques and case studies. Data analysis techniques were carried out through data collection, data reduction, data presentation and data verification. The results of this study have a positive impact on interest in learning and increasing social skills for students in understanding vocabulary in social studies learning. So that through learning activities during the adaptation period of new habits through the method of social science vocabulary recognition model through guessing games so that it can restore students' interest in learning during the adaptation period of new habits, especially in current learning.

A study of continuance use intention of an on online learning system after Coronavirus disease 2019 pandemic outbreak

ABSTRACT This study aims to determine the continuance use intention of using the current online learning systems. After COVID-19, many online learning systems are available. There is a need to evaluate the performance of existing online learning system. “Confirmation of expectation”, “Perceived usefulness” and “Satisfaction on existing system” were hypothesized to influence students’ intention to continuously use an online system in our conceptual model. The measurement scales of these constructs were adopted from the expectation-confirmation model (ECM) and measured on a seven-point scale. A total of 146 valid samples were collected from undergraduate students through an online survey about usage of online learning system. Partial least squares structural equation model was used. An online learning system continuance use intention model was proposed. It was found that ‘Satisfaction on existing online system is a mediator between the “Confirmation of expectation” and “Continuance Use intention”. Importance–performance analysis was performed. This study projected an understanding of the continuance use intention of an online learning systems during the COVID-19 pandemic.

Student Learning Strategies During the Covid 19 Pandemic At Binjai State Madrasah Ibtidaiyah School

Covid 19 which is endemic in Indonesia causes the learning system cannot be done face-to-face. And therefore the government has set a learning system that must be carried out by Indonesia is an online payment system. Therefore, in this study, it will be seen how the strategies that must be carried out by schools in the learning system from and what obstacles are felt by schools in the current online learning system. Is this online learning system very efficient or not very efficient in the current learning system and in this study we will also discuss the system How methods are used in learning strategies in educational institutions in Indonesia, especially at Madrasah Ibtidaiyah Negeri Binjai

Peluang dan tantangan Pembelajaran Daring pada sekolah Madrasah Ibtidaiyah Swasta Madrisatul Ibrar

During the COVID-19 pandemic, all activities were hampered, one of which was in the field of education. Where in every educational institution requires online or virtual learning based on regulations set by the government to break the ropes of the spread of the COVID-19 virus. However, online learning currently has both advantages and disadvantages in the online or virtual teaching and learning process. and in this study it will be discussed about the online learning process in an educational institution to see whether the obstacles and changes contained in schools in the current online learning system