Conventional Learning System Research Articles

The Influence of Distance Learning Contracted Live Teaching Strategies on Learning Effectiveness, Learning Motivation, Self-efficacy, and Cognitive Load

<p>Distance learning lacks person-to-person interaction, which makes learning less interesting. While peer interaction can gain the support, assistance, and discussion of peer empathy, which can effectively motivate learning. This study proposes a remote peer live learning strategy, which allows learners to conduct peer learning anytime and anywhere via the Internet and uses peer-to-peer video methods to conduct peer-to-peer live teaching. Explores the influence of adding peer factors on their learning effectiveness and learning motivation. The findings of this study are as follows: (1) The learners who use peer live teaching strategy, regardless of whether they are high or low achievement, can effectively improve their learning effectiveness, learning motivation and reduce their cognition compared with those who use general distance teaching. (2) Students who utilized the peer-to-peer live teaching platform exhibited notably higher levels of technology acceptance compared to their counterparts enrolled in the conventional distance learning system.</p> <p> </p>

Integrated Spatial and Temporal Features Based Network Intrusion Detection System Using SMOTE Sampling

With attackers discovering more inventive ways to take advantage of network weaknesses, the pace of attacks has drastically increased in recent years. As a result, network security has never been more important, and many network intrusion detection systems (NIDS) rely on old, out-of-date attack signatures. This necessitates the deployment of reliable and modern Network Intrusion Detection Systems that are educated on the most recent data and employ deep learning techniques to detect malicious activities. However, it has been found that the most recent datasets readily available contain a large quantity of benign data, enabling conventional deep learning systems to train on the imbalance data. A high false detection rate result from this. To overcome the aforementioned issues, we suggest a Synthetic Minority Over-Sampling Technique (SMOTE) integrated convolution neural network and bi-directional long short-term memory SCNN-BIDLSTM solution for creating intrusion detection systems. By employing the SMOTE, which integrates a convolution neural network to extract spatial features and a bi-directional long short-term memory to extract temporal information; difficulties are reduced by increasing the minority samples in our dataset. In order to train and evaluate our model, we used open benchmark datasets as CIC-IDS2017, NSL-KDD, and UNSW-NB15 and compared the results with other state of the art models.

Project Based Learning: Development of Taxiway Light as a Visual Landing Aid Using Solar Power

This research aims to determine the differences in learning methods in the classroom using project-based learning and conventional learning. The research was carried out using quantitative methods by conducting evaluations and interviews with cadets. Data processing uses the Manova test statistical data processing application. The sample from this research was Palembang Aviation Polytechnic cadets in visual aid courses, especially taxiway lights. From the results of data processing, we can see differences in terms of creativity and learning outcomes between cadets who use project-based learning methods and those who use conventional learning systems. Project-based learning methods have fostered creativity and better learning outcomes. Hopefully with the results of this research, lecturers will more often use project-based learning methods to foster the creativity of Aviation Polytechnic cadets within the Ministry of Transportation of Indonesia.

Self-Organizing Democratized Learning: Toward Large-Scale Distributed Learning Systems.

Emerging cross-device artificial intelligence (AI) applications require a transition from conventional centralized learning systems toward large-scale distributed AI systems that can collaboratively perform complex learning tasks. In this regard, democratized learning (Dem-AI) lays out a holistic philosophy with underlying principles for building large-scale distributed and democratized machine learning systems. The outlined principles are meant to study a generalization in distributed learning systems that go beyond existing mechanisms such as federated learning (FL). Moreover, such learning systems rely on hierarchical self-organization of well-connected distributed learning agents who have limited and highly personalized data and can evolve and regulate themselves based on the underlying duality of specialized and generalized processes. Inspired by Dem-AI philosophy, a novel distributed learning approach is proposed in this article. The approach consists of a self-organizing hierarchical structuring mechanism based on agglomerative clustering, hierarchical generalization, and corresponding learning mechanism. Subsequently, hierarchical generalized learning problems in recursive forms are formulated and shown to be approximately solved using the solutions of distributed personalized learning problems and hierarchical update mechanisms. To that end, a distributed learning algorithm, namely DemLearn, is proposed. Extensive experiments on benchmark MNIST, Fashion-MNIST, FE-MNIST, and CIFAR-10 datasets show that the proposed algorithm demonstrates better results in the generalization performance of learning models in agents compared to the conventional FL algorithms. The detailed analysis provides useful observations to further handle both the generalization and specialization performance of the learning models in Dem-AI systems.

Bridging the Gap between Purpose-Driven Frameworks and Artificial General Intelligence

Artificial General Intelligence (AGI) has leaped forward in capabilities, offering applications that reach far beyond conventional machine learning systems [...]

Teknoloji Kabul Modeli ve Sosyal Sermaye Teorisi Açısından Online Muhasebe Eğitimini Etkileyen Faktörler: Türkiye Örneği

With the developing technology and COVID-19 pandemic, certain changes have been made in various areas. One of these changes has emerged in education as the transformation of conventional learning systems into online learning systems. The online learning system is effective if both teaching staff and students are prepared in terms of presenting information content and assessing student performance. Otherwise, certain problems may be encountered throughout the adaptation process. Therefore, it is crucial to determine the factors affecting the utilization of online learning systems. The present study aims to find out the factors influencing the utilization of online learning systems by accounting students enrolled in both state and foundation universities in Türkiye during the COVID-19 pandemic. To this end, a survey questionnaire method was employed and survey questionnaire data were analyzed using SPSS and SmartPLS software. The analysis results revealed that social trust had an impact on perceived ease of use and perceived usefulness, perceived ease of use had an impact on perceived usefulness, and subjective norms had an impact on perceived usefulness; whereas perceived ease of use, perceived usefulness, and subjective norms were predictors of behavioral intention to use, and actual use was also affected by behavioral intention to use.

PERANCANGAN MEDIA INTERAKTIF PERUBAHAN ENERGI SISWA SD MENGGUNAKAN ADOBE FLASH CS3

The teaching and learning process during the pandemic is where schools must continue to deliver material even though it is online because students study at home. The teacher's learning process still uses a conventional learning system, which is dominated by text and reading, the delivery of material like this causes students to be less enthusiastic and difficult to understand the material being taught. Multimedia that supports interactive-based learning is currently growing, so it can be an option for schools to build interactive learning media. Multimedia can create dynamic and interactive presentations by combining text, graphics, animation, audio, and video images. The research aims to produce interactive multimedia learning energy changes. The method used in conducting this research is a field study with interview and observation data collection techniques. The results are in the form of interactive animation applications for learning energy changes which are expected to increase understanding of the material as well as facilitate the teaching and learning process during the online learning period.

Design and Build a Web-Based E-Learning Application System at Paramarta Vocational High School

The conventional learning system is still being implemented at SMK Paramarta, which includes direct contact between teachers and students. However, with the advancement of technology, there is a need for an e-learning system that can facilitate the teaching and learning process and provide more varied learning activities for students. Therefore, this research aims to design and develop a web-based e-learning application system at SMK Paramarta. As a result, when a teacher is unable to attend, the teaching and learning process will be disrupted because there is no other media to deliver learning materials from the teacher to the students. The design of the Web-based E-learning Application System is built using HTML, JavaScript, PHP, MySQL, and CSS to beautify the e-learning pages that will be created. The web-based e-learning application system designed in this research can be an alternative modern and varied learning activity for students at SMK Paramarta. Additionally, this system can also assist teachers in providing learning materials and testing student understanding in a more effective and efficient manner. Therefore, it is hoped that the use of this system can improve the quality of education at SMK Paramarta. To ensure that the application runs smoothly, two testing phases are conducted: white-box testing and black-box testing on the data transfer process that runs within the e-learning application

Applying a wearable MR-based mobile learning system on museum learning activities for university students

ABSTRACT This study developed a wearable mixed reality (MR)-based mobile learning system and applied it to museum learning activities to explore whether the proposed system can effectively improve university students’ learning outcomes, situational interest, and cognitive load. Four museums were selected as the informal learning sites, and 64 university students were randomly divided into the experimental group (using the wearable MR-based mobile learning system) and the control group (using the conventional mobile learning system). The results show that in the retention and comprehension dimensions of the learning outcome, the experimental group has significantly better learning performance than the control group. The experimental group showed improvements in almost all dimensions of situational interest, except for the challenge dimension, while their extraneous cognitive load was reduced. Furthermore, this study found that the proposed system has a positive influence on museum learning in higher education, and has good potential for improving the conventional mobile learning system and enhancing students’ learning performance. The findings of this study can provide a reference for future research on the possibilities of using wearable devices for museum education.

Nextcloud Storage Design as E-Learning Data Storage Media in SMA Negeri 2 Manokwari

Conventional learning systems in general have difficulty in distributing teaching materials which certainly require costs, giving assignments to students that burden the teacher himself in the collection of assignments and the process of assessing assignments, subject matter whose storage security in memory/flashdisk is not guaranteed so that with the nextcloud storage media which is cloud storage and integrated with e-learning applications, has features that are in accordance with the learning environment and easy to use both teachers and students. The system will be built using Moodle on hosting with Nextcloud as a storage medium, then using the SDLC method as a system design so that this system is well integrated. With this application, the needs of students and teachers in online teaching and learning activities are answered by using every feature in e-learning with Nextcloud helping the performance of the e-learning system application.

PENGEMBANGAN MEDIA PEMBELAJARAN MAGIC BOX BERBASIS SAVI (SOMATIC, AUDITORIAL, VISUAL DAN INTELEKTUAL)

This research stems from the problem of the need for more learning media teachers provide because, in general, a teacher still uses a conventional learning system and does not thoroughly understand the material that students can understand. This study aimed to determine the development and feasibility of SAVI-based magic box media for SD Kertasana Serang, Banten fourth-grade students. This research uses the research and development method (Research and Development). This research and development step uses six steps: problem analysis, data collection, product design, design validation, design revision, and product trials. The results of this study are the feasibility of Magic Box learning media in SAVI learning as a means of visual learning styles of students in class IV SD Negeri Kertasana obtained through validation of material experts, linguists, and media experts. The feasibility level obtained from two material experts is 92.5%, from two language experts is 78.3%, and from two media experts is 89.5%. The three experts obtained an average value of 86.76% which was included in the "Very Feasible" category. Based on the explanation, it can be concluded that the SAVI-based Magic Box learning media is suitable for students IV SD Negeri Kertasana Serang, Banten.

ICT (Instruction Computer Technology) Based PKN and IPS Learning Designs in Elementary Schools

The learning process that is usually carried out in schools or what is often referred to as the conventional learning system is now seen as less effective. In the current era of globalization, ICT (Information and Communication Technology) is a requirement that is used as the basis for determining the quality and effectiveness of the learning process. Designing ICT-based IPS-Civics learning can help teachers or students in the learning process so that knowledge and learning materials can be conveyed to students properly. This research was obtained and collected through literature studies, which were carried out by literature review and from searches carried out on the internet via Google. ICT-based learning media, namely learning media in which all electronic components consist of hardware and software as well as all activities related to data processing, retrieval, collection (acquisition), processing, storage, dissemination, and presentation of information/data using computers and telecommunications. ICT-based learning media include: computer technology, multimedia, telecommunication, and computer network technology. The function of ICT in learning media is as a tool in learning media, learning facilities/places, as a source of learning, and as a means of increasing professionalism. The purpose of this research is to make it easier for teachers to develop learning designs that use information technology so that learning becomes less monotonous and more creative, especially in Social Studies and Internship learning which is often considered boring by students, using ICT-based learning designs will attract more students' attention keywords: Learning Design, Civics, and Social Studies, ICT (Instruction Computer Technology).

Material Removal Rate Prediction Based on Broad Echo State Learning System for Magnetically Driven Internal Finishing

Material removal rate (MRR) modeling is crucial for process and quality control in abrasive finishing processes. In this paper, a novel broad echo state learning system (BESLS) is developed to predict MRR in the magnetically driven internal finishing process based on the force signal. This BESLS model employs reservoirs with echo state properties to replace the enhancement layer nodes of the conventional broad learning system. Three representative BESLS architectures are designed and experiments are conducted to validate the developed models. The effect of feature-fusion approaches on prediction accuracy is investigated. Results demonstrate that the prediction error of MRR is only 6.86% for the proposed BESLS model. The model has one reservoir with variable nodes (BESLS-III) and fuses extracted force features and process parameters as input. It also shows remarkable computational efficiency with a testing time of 0.134 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm s$</tex-math></inline-formula> , making it a potential candidate for online process control.

Transforming Teaching from Conventional to Digital Learning: Students Sensitivity in Higher Education

This study surveyed transforming teaching from conventional to digital learning: student sensitivity in higher education. The study was a descriptive survey which adopted the ex-post-facto design. 378 respondents were selected at random from a population of 24,888, students in Delta State higher education. The study instrument was self-constructed and titled Student Sensitivity to Conventional and Digital Learning System Questionnaire (SSCDLSQ). Face and content validity were employed for the instrument and it was further subjected to Cronbach alpha to establish the reliability and a value of .85 was obtained. Graphical representation to interpret the respondents’ information such as gender, academic level, and institution of learning. Research questions were analysed with mean rating and standard deviation. Hypothesis 1 was tested using a t-test. Hypotheses 2 and 3 were tested using ANOVA at a.05 significance level. Findings revealed, among others, that students display positive sensitivity to transforming teaching from conventional to digital learning. The researchers recommended, among others, that teaching should be transformed from a traditional classroom setting to digital learning, particularly for large classes, since it increases reading habits and collaboration.

Multi-Scopic Cognitive Memory System for Continuous Gesture Learning.

With the advancement of artificial intelligence technologies in recent years, research on intelligent robots has progressed. Robots are required to understand human intentions and communicate more smoothly with humans. Since gestures can have a variety of meanings, gesture recognition is one of the essential issues in communication between robots and humans. In addition, robots need to learn new gestures as humans grow. Moreover, individual gestures vary. Because catastrophic forgetting occurs in training new data in traditional gesture recognition approaches, it is necessary to preserve the prepared data and combine it with further data to train the model from scratch. We propose a Multi-scopic Cognitive Memory System (MCMS) that mimics the lifelong learning process of humans and can continuously learn new gestures without forgetting previously learned gestures. The proposed system comprises a two-layer structure consisting of an episode memory layer and a semantic memory layer, with a topological map as its backbone. The system is designed with reference to conventional continuous learning systems in three ways: (i) using a dynamic architecture without setting the network size, (ii) adding regularization terms to constrain learning, and (iii) generating data from the network itself and performing relearning. The episode memory layer clusters the data and learns their spatiotemporal representation. The semantic memory layer generates a topological map based on task-related inputs and stores them as longer-term episode representations in the robot's memory. In addition, to alleviate catastrophic forgetting, the memory replay function can reinforce memories autonomously. The proposed system could mitigate catastrophic forgetting and perform continuous learning by using both machine learning benchmark datasets and real-world data compared to conventional methods.

GAME EDUKASI PENGEMBANGAN GAME EDUKASI I’TIKAD 50 BERBASIS POWER POINT DI DAYAH AL-FURQAN ACEH BESAR

This study is to answer the problem of developing power point-based i'tikaf 50 educational games in Dayah Al-furqan Aceh Besar because students are not very interested in lecture or conventional learning systems. Therefore, an educative and interesting game was made in learning I'tiqad 50. The method used in the research was R&amp;D (Research and Development) or research development. The results of the validation test by the validator were 16 respondents with the aspect of material assessment getting a score. as much as 77.2%, and the media assessment aspect got a score of 78.2%. The results of the implementation of the I'tikad 50 educational game learning media which were applied to the control class (KK) in Dayah Al-furan obtained an average score of 89.3 and the traditional (conventional) learning outcomes were applied to the ordinary class (KB) in Dayah Al -furqan obtained an average score of 74.6.

Review

Deep Learning is-one of the machine learning areas, applied in recent areas. Various techniques have been proposed depends on varieties of learning, including unsupervised, semi-supervised, and supervised-learning. Some of the experimental results proved that the deep learning systems are performed well compared to conventional machine learning systems in image processing, computer vision and pattern recognition. This paper provides a brief survey, beginning with Deep Neural Network (DNN) in Deep Learning area. The survey moves on-the Convolutional Neural Network (CNN) and its architectures, such as LeNet, AlexNet, GoogleNet, VGG16, VGG19, Resnet50 etc. We have included transfer learning by using the CNN’s pre-trained architectures. These architectures are tested with large ImageNet data sets. The deep learning techniques are analyzed with the help of most popular data sets, which are freely available in web. Based on this survey, conclude the performance of the system depends on the GPU system.

PENGELOLAAN KELAS PADA PEMBELAJARAN AKHLAK DI SEKOLAH DARUL ISLAH RANGAE NARATHIWAT THAILAND

This research was conducted at darul islah school located in Rangae, Narathiwat, Southern Thailand. Darul Islah School is one of the schools located in Rangae village city, which implements two leadership systems so as to make class management very varied in each field or subject system. This type of research is using qualitative research methods. The determination of the subject used is purposive sampling with the object of research class management activities consisting of class management of learners and physical management of the class, inhibitory factors and efforts made to overcome inhibitory factors in class management. Research data is collected through semistructured interviews, participatory observations, and documentation. The results showed that in observations, interviews, and documentation there are several things that teachers do to manage the classroom, including, Teachers use freedom and socio-emotional approaches, coaching techniques and the application of discipline provided by teachers in the form of preventive measures, maintenance and improvement of discipline of teacher students to impose curative actions, Teachers create a conducive classroom climate by providing advice, Teachers manage learning interactions with teachers. Applying a conventional learning system, the Teacher applies punishment in the form of tadarus or read surah Yasin, doing tasks, sucking bitter types of plants, while gifts in the form of gifts. In the physical arrangement of the classroom, the teacher gives freedom to students to organize their respective classrooms.

Promoting Students’ Programming Logic and Problem-Solving Awareness With Precision Feedback: A Two-Tier Test-Based Online Programming Training Approach

Fostering students' computer programming skills has become an important educational issue in the globe. However, it remains a challenge for students to understand those abstract concepts when learning computer programming, implying the need to provide instant learning diagnosis and feedback in computer programming activities. In this study, a Two-Tier Test-Based Programming Training (T3PT) approach was proposed. Accordingly, an online learning system was developed to provide students with precision feedback for guiding them to identify misconceptions of computer programming to improve their computer programming learning achievement. In order to examine the effects of the proposed approach, a learning system was developed and a quasi-experiment was conducted. Two classes of 99 eighth-grade students from Taiwan were divided into an experimental group and a control group. The students in the experimental group used the learning system based on the T3PT approach, while the control group used the conventional learning system. The experimental results showed that the proposed approach was significantly superior to the conventional programming learning approach in terms of students' programming logic concepts, problem-solving awareness, technology acceptance, and satisfaction with the learning approach. Accordingly, discussion and suggestions are provided for future research.

A novel remote hands-on training for neuroendovascular-based treatment in the era of the COVID-19 pandemic.

The COVID-19 pandemic has demanded a change in learning modalities, which led us to develop a remote personal training system for clinicians performing neuroendovascular procedures. A portable vascular model designed for practicing catheter navigation guidance, thrombus retrieval, and intracranial aneurysm coil embolisation was established. We created an environment that enabled interactive dialogue and communication across long distances using the Internet. The instructor conducted approximately 2 h of hands-on training with two to four trainees at a time. Despite the restrictions enforced by the Government of Japan due to the COVID-19 pandemic, 17 online hands-on training were successfully conducted throughout Japan over 1 year for a total of 48 trainees. The developed remote training programme, to avoid the aggregation of a large number of trainees at a developed time, proved to be at par with the conventional learning system. The training was well-received since the operation time was longer and the question and answer sessions were more fulfilling compared to the conventional format in which a group of trainees had got a brief opportunity to receive actual hands-on experience.