Search results for: traditional learning approach

Authors: Zehra Sultan

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The study is based on the task-based language teaching approach which is found to be very effective in the EFL/ESL classroom. This approach engages learners to acquire the usage of authentic language skills by interacting with the real world through sequence of pedagogical tasks. The use of technology enhances the effectiveness of this approach. This study throws light on the historical background of TBLT and its efficacy in the EFL/ESL classroom. In addition, this study precisely talks about the implementation of this approach in the General Foundation Programme of Muscat College, Oman. It furnishes the list of the pedagogical tasks embedded in the language curriculum of General Foundation Programme (GFP) which are skillfully allied to the College Graduate Attributes. Moreover, the study also discusses the challenges pertaining to this approach from the point of view of teachers, students, and its classroom application. Additionally, the operational success of this methodology is gauged through formative assessments of the GFP, which is apparent in the students’ progress.

Keywords: task-based language teaching, authentic language, communicative approach, real world activities, ESL/EFL activities

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Authors: Md. Ataur Rahman Bhuiyan, Quazi Mahabubul Hasan, Md. Rifat Ullah

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In this research, we did explore the effectiveness of the gaming environment in education and compared it with the traditional education system. We take several workshops in both learning environments. We measured student’s performance by providing a grading score (by professional academics) on their attitude in different criteria. We also collect data from survey questionnaires to understand student’s experiences towards education and study. Finally, we examine the impact of the different learning environments by applying statistical hypothesis tests, the T-test, and the ANOVA test.

Keywords: gamification, game-based learning, education, statistical analysis, human-computer interaction

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Authors: Shona Tritt, William Cunningham

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Our study examines whether teaching effectiveness is perceived differently in online versus traditional classroom contexts. To do so, we analyzed teaching evaluations from courses that were offered as web options and as in-person classes simultaneously at the University of [removed for blinding] (N=87). Although teaching evaluations were on average lower for larger classes, we found that learning context (traditional versus online) moderated this effect. Specifically, we found a crossover effect such that in relatively smaller classes, teaching was perceived to be more effective in-person versus online, whereas, in relatively larger classes, teaching was perceived to be more effective when engaged online versus in-person.

Keywords: teaching evaluations, teaching effectiveness, e-learning, web-option

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Authors: Y. Alrubyli

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Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

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Authors: Hoi-Lam Ma, Sai-Ho Chung

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In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment

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Authors: Hassan Sharafuddin, Chekra Allani

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Academicians at the Arab Open University have always voiced their concern about the efficacy of the blended learning process. Based on 75% independent study and 25% face-to-face tutorial, it poses the challenge of the predisposition to adjustment. Being used to the psychology of traditional educational systems, AOU students cannot be easily weaned from being spoon-fed. Hence they lack the motivation to plunge into self-study. For better involvement of AOU students into the learning practices, it is imperative to diagnose the factors that impede or increase their motivation. This is conducted through an empirical study grounded upon observations and tested hypothesis and aimed at monitoring and optimizing the students’ learning outcome. Recommendations of the research will follow the findings.

Keywords: academic performance, blended learning, educational psychology, independent study, pedagogy

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: Muhammad Yasir Babar, Ebrahim Panah

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Over the past 20 years, internet has seen continual advancement and with the advent of online technology, various types of web-based games have been developed. Games are frequently being used among different age groups from baby boomers to generation Z. Games are not only used for entertainment but also utilized as a learning approach transmitting education to a level that is more interesting and effective for students. One of the popular web-based education games is Kahoot with growing popularity and usage, which is being used in different fields of studies. However, little knowledge is available on university students’ perception of Kahoot environment and application for learning subjects. Hence, the objective of the current study is to investigate students’ perceptions of Kahoot application and environment as a learning tool. The study employed a survey approach by distributing Google Forms –created questionnaire, with high level of reliability index, to 62 students (11 males and 51 females). The findings show that students have positive attitudes towards Kahoot application and its environment for learning. Regarding Kahoot application, it was indicated that activities created using Kahoot are more interesting for students, Kahoot is useful for collaborative learning, and Kahoot enhances interest in learning lesson. In terms of Kahoot environment, it was found that using this application through mobile is easy for students, its design is simple and useful, Kahoot-created activities can easily be shared, and the application can easily be used on any platform. The findings of the study have implications for instructors, policymakers and curriculum developers.

Keywords: application, environment, Kahoot, learning tool

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Authors: Alexander Huang

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Online learning sessions have become an indispensable complement to in-classroom-learning sessions in the past two years due to the emergence of Covid-19. Due to social distance requirements, many courses and interaction-intensive sessions, ranging from music classes to debate camps, are online. However, online learning imposes a significant challenge for engaging students effectively during the learning sessions. To resolve this problem, Project PWR, a non-profit organization formed by high school students, developed an online kid-teach-kid learning environment to boost students' learning interests and further improve students’ engagement during online learning. Fundamentally, the kid-teach-kid learning model creates an affinity space to form learning groups, where like-minded peers can learn and teach their interests. The role of the teacher can also help a kid identify the instructional task and set the rules and procedures for the activities. The approach also structures initial discussions to reveal a range of ideas, similar experiences, thinking processes, language use, and lower student-to-teacher ratio, which become enriched online learning experiences for upcoming lessons. In such a manner, a kid can practice both the teacher role and the student role to accumulate experiences on how to convey ideas and questions over the online session more efficiently and effectively. In this research work, we conducted two case studies involving a 3D-Design course and a Speech and Debate course taught by high-school kids. Through Project PWR, a kid first needs to design the course syllabus based on a provided template to become a student-teacher. Then, the Project PWR academic committee evaluates the syllabus and offers comments and suggestions for changes. Upon the approval of a syllabus, an experienced and voluntarily adult mentor is assigned to interview the student-teacher and monitor the lectures' progress. Student-teachers construct a comprehensive final evaluation for their students, which they grade at the end of the course. Moreover, each course requires conducting midterm and final evaluations through a set of surveyed replies provided by students to assess the student-teacher’s performance. The uniqueness of Project PWR lies in its established kid-teach-kids affinity space. Our research results showed that Project PWR could create a closed-loop system where a student can help a teacher improve and vice versa, thus improving the overall students’ engagement. As a result, Project PWR’s approach can train teachers and students to become better online learners and give them a solid understanding of what to prepare for and what to expect from future online classes. The kid-teach-kid learning model can significantly improve students' engagement in the online courses through the Project PWR to effectively supplement the traditional teacher-centric model that the Covid-19 pandemic has impacted substantially. Project PWR enables kids to share their interests and bond with one another, making the online learning environment effective and promoting positive and effective personal online one-on-one interactions.

Keywords: kid-teach-kid, affinity space, online learning, engagement, student-teacher

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Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

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The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

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Authors: Usman Ghani

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Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: simulation, feedback, training, hands-on, labs

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Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: Richard Patrick Kabuye

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This study focuses on the addressing the enhancement of in-service training programs as a tool of transforming the existing traditional approaches of formal lectures/contact hours. This will be supported with a more versatile, robust, and remotely accessible means of mobile based e-learning, as a support tool for the traditional means. A combination of various factors in education and incorporation of the eLearning strategy proves to be a key factor in effective in-service education. Key factor needs to be factored in so as to maintain a credible co-existence of the programs, with the prevailing social, economic and political environments. Effective in-service education focuses on having immediate transformation of knowledge into practice for a good time period, active participation of attendees, enable before training planning, in training assessment and post training feedback training analysis which will yield knowledge to the trainers of the applicability of knowledge given out. All the above require a more robust approach to attain success in implementation. Incorporating mobile technology in eLearning will enable the above to be factored together in a more coherent manner, as it is evident that participants have to take time off their duties and attend to these training programs. Making it mobile, will save a lot of time since participants would be in position to follow certain modules while away from lecture rooms, get continuous program updates after completing the program, send feedback to instructors on knowledge gaps, and a wholly conclusive evaluation of the entire program on a learn as you work platform. This study will follow both qualitative and quantitative approaches in data collection, and this will be compounded incorporating a mobile eLearning application using Android.

Keywords: in service, training, mobile, e- learning, model

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Authors: Pimploi Tirastittam, Suppara Charoenpoom

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Nowadays the asynchronous learning has granted the permission to the anywhere and anything learning via the technology and E-media which give the learner more convenient. This research is about the design of the blended and online learning for the asynchronous learning of the process management subject in order to create the prototype of this subject asynchronous learning which will create the easiness and increase capability in the learning. The pattern of learning is the integration between the in-class learning and online learning via the internet. This research is mainly focused on the online learning and the online learning can be divided into 5 parts which are virtual classroom, online content, collaboration, assessment and reference material. After the system design was finished, it was evaluated and tested by 5 experts in blended learning design and 10 students which the user’s satisfaction level is good. The result is as good as the assumption so the system can be used in the process management subject for a real usage.

Keywords: blended learning, asynchronous learning, design, process management

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Authors: Pradeep Kumar Sahoo

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Facilitating writing skill among the young techies seems a bit challenging. Various factors may owe to this difficulty. Inappropriate syllabus, inadequate infrastructure, to some extent, untrained faculty members and above all the background of learners may be treated as the components that make the process challenging. In order to convert/create/prepare writing skill friendly, the focused items will have to be different from the classroom the present day traditional classroom situation. This paper focuses on the multiple contemporary strategies for approaching a wide range of typical problems that the writers face in a specific technical university of Odisha.

Keywords: background of learners, classroom friendly approach, inappropriate syllabus, traditional classroom situation

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Samira-Sadat JamaliDinan, Haidar Almohri, Mohammad-Reza Nazem-Zadeh

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Lateralization of temporal lobe epilepsy (TLE) is very important for positive surgical outcomes. We propose a machine learning framework to ultimately identify the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Unlike most studies that use classification algorithms, we propose an effective clustering approach to distinguish between normal and TLE cases. We apply the famous Minkowski weighted K-Means (MWK-Means) technique as the clustering framework. To overcome the problem of poor initialization of K-Means, we use particle swarm optimization (PSO) to effectively select the initial centroids of clusters prior to applying MWK-Means. We demonstrate that compared to K-means and MWK-means independently, this approach is able to improve the result of a benchmark data set.

Keywords: temporal lobe epilepsy, machine learning, clustering, magnetoencephalography

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Authors: Gabriel Sunday Ayayia

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Food waste has reached alarming levels worldwide, contributing to food insecurity, resource depletion, and environmental degradation. While numerous strategies exist to mitigate this issue, the role of traditional practices and indigenous knowledge remains underexplored. There is a need to investigate how these age-old practices can contribute to sustainable food waste reduction, particularly in the African context. This study explores the potential of traditional practices and indigenous knowledge in Africa to address this challenge sustainably. The study examines traditional African food management practices and indigenous knowledge related to food preservation and utilization; assess the impact of traditional practices on reducing food waste and its broader implications for sustainable development, and identify key factors influencing the continued use and effectiveness of traditional practices in contemporary African societies. Thus, the study argues that traditional practices and indigenous knowledge in Africa offer valuable insights and strategies for sustainable food waste reduction that can be adapted and integrated into global initiatives This research will employ a mixed-methods approach, combining qualitative and quantitative research techniques. Data collection will involve in-depth interviews, surveys, and participant observations in selected African communities. Moreover, a comprehensive review of literature on traditional food management practices and their impact on food waste reduction will be conducted. The significance of this study lies in its potential to bridge the gap between traditional knowledge and modern sustainability efforts. By uncovering the value of traditional practices in reducing food waste, this research can inform policies, interventions, and awareness campaigns aimed at achieving sustainable food systems worldwide.

Keywords: traditional practices, indigenous knowledge, food waste reduction, sustainability

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Authors: Elana Mahboub, Lamar Bakhurji, Hind Alhindi, Sara Alesayi

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Duolingo is a revolutionary language learning platform that offers an interactive and accessible learning experience. Its gamified approach makes language learning engaging and enjoyable, with a diverse range of languages available. The platform's adaptive learning system tailors lessons to individual proficiency levels, ensuring a personalized and efficient learning journey. The incorporation of multimedia elements enhances the learning experience and promotes practical language application. Duolingo's success is attributed to its mobile accessibility, offering basic access to language courses for free, with optional premium features for those seeking additional resources. Research shows positive outcomes for users, and the app's global impact extends beyond individual learning to formal language education initiatives. Duolingo is a transformative force in language education, breaking down barriers and making language learning an attainable goal for millions worldwide.

Keywords: duolingo, artificial intelligence, artificial intelligence in duolingo, benefit of artificial intelligence

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Authors: Chimey Lhamo, Ngawang Tsering

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Traditional Tibetan medicine, known as Sowa Rigpa (Science of healing), originated more than 2500 years ago with an insightful background, and it has been growing significant attention in many Asian countries like China, India, Bhutan, and Nepal. Particularly, the Indian government has targeted Traditional Tibetan medicine as its major Indian medical system, including Ayurveda. Although Traditional Tibetan medicine has been growing interest and has a long history, it is not easily recognized worldwide because it exists only in the Tibetan language and it is neither accessible nor understood by patent examiners at the international patent office, data about Traditional Tibetan medicine is not yet broadly exist in the Internet. There has also been the exploitation of traditional Tibetan medicine increasing. The Traditional Knowledge Digital Library is a database aiming to prevent the patenting and misappropriation of India’s traditional medicine knowledge by using India’s Traditional knowledge Digital Library on Sowa Rigpa in order to prevent its exploitation at international patent with the help of information technology tools and an innovative classification systems-traditional knowledge resource classification (TKRC). As of date, more than 3000 Sowa Rigpa formulations have been transcribed into a Traditional Knowledge Digital Library database. In this paper, we are presenting India's Traditional Knowledge Digital Library for Traditional Tibetan medicine, and this database system helps to preserve and prevent the exploitation of Sowa Rigpa. Gradually it will be approved and accepted globally.

Keywords: traditional Tibetan medicine, India's traditional knowledge digital library, traditional knowledge resources classification, international patent classification

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Authors: Clifford De Raffaele, Luana Bugeja, Serengul Smith

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The adaptation of social networking sites within higher education has garnered significant interest in the recent years with numerous researches considering it as a possible shift from the traditional classroom based learning paradigm. Notwithstanding this increase in research and conducted studies however, the adaption of SNS based modules have failed to proliferate within Universities. This paper, commences its contribution by analyzing the various models and theories proposed in literature and amalgamates together various effective aspects for the inclusion of social technology within e-Learning. A three phased framework is further proposed which details the necessary considerations for the successful adaptation of SNS in enhancing the students learning experience. This proposal outlines the theoretical foundations which will be analyzed in practical implementation across international university campuses.

Keywords: eLearning, higher education, social network sites, student learning

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Heesuk Seo, Yongtae Kim

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Online learning started in the 1990s, the spread of the Internet has been through the era of e-learning paradigm of online education in the era of smart learning change. Reflecting the different nature of the mobile to anywhere anytime, anywhere was also allows the form of learning, it was also available through the learning content and interaction. We are developing a cloud system, 'TLINKS CLOUD' that allows you to configure the environment of the smart learning without the need for additional infrastructure. Using the big-data analysis for e-learning contents, we provide an integrated solution for e-learning tailored to individual study.

Keywords: authority tool, big data analysis, e-learning, HTML5

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Authors: Fadoua Ouamani, Narjès Bellamine Ben Saoud, Henda Hajjami Ben Ghézala

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In the last few years and over the last decades, there was a growing interest in the development of Computer Supported Collaborative Learning (CSCL) environments. However, the existing systems ignore the variety of learners and their socio-cultural differences, especially in the case of distant and networked learning. In fact, within such collaborative learning environments, learners from different socio-cultural backgrounds may interact together. These learners evolve within various cultures and social contexts and acquire different socio-cultural values and behaviors. Thus, they should be assisted while communicating and collaborating especially in an intercultural group. Besides, the communication and collaboration tools provided to each learner must depend on and be adapted to her/his socio-cultural profile. The main goal of this paper is to present the proposed socio-cultural adaptation approach based on and guided by ontologies to adapt CSCL environments to the socio-cultural profiles of its users (learners or others).

Keywords: CSCL, socio-cultural profile, adaptation, ontology

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Authors: Shynn Lim, Ching Tan

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The paper presents the PASSION Programme designed by a government school in Singapore, guided by national goals as well as research-based pedagogies that aims to nurture students to become lifelong learners with the strength of character. The design and enactment of the integrated approach to develop in students good character, resilience and social-emotional well-being, future readiness, and active citizenship is guided by a set of principles that amalgamates Biesta’s domains of purposes of education and authentic learning. Data in terms of evidence of students’ learning and students’ feedback were collected, analysed, and suggests that the learning experience benefitted students by boosting their self-confidence, self-directed and collaborative learning skills, as well as empathy.

Keywords: lifelong learning, character and citizenship education, education and career guidance, 21CC, teaching and learning empathy

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Authors: Thuy Hang Le

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Traditional agroforestry systems are land-use practices still widespread in tropical and subtropical countries, while in Europe have significantly decreased due to land-use intensification, land abandonment, and urbanization. Nevertheless, scientific evidence reveals that traditional agroforestry systems significantly support biodiversity and ecosystem services and may positively contribute to socioeconomic rural regional development. We worked out a review that follows the PRISMA approach and compiled comprehensive information on traditional agroforestry systems in Europe. Based on the differentiation of different land-use systems, also considering the agricultural as well as forestry components, we compiled information regarding current distribution, management (agrodiversity), biodiversity and agrobiodiversity, ecosystem and landscape services, threats, and restoration initiatives. From a total of 3,304 studies that dealt with agroforestry systems in Europe, both “modern” (e.g., buffer strip) and “traditional” (e.g., meadow orchards), we filtered out 158 studies from 35 European countries which represent the basis for in-depth investigation. We found, for example, that the traditional pastoral agroforestry system in the Mediterranean region, the so-called Dehesa, can harbor up to 300 plant species as well as 238 bird species, of which 134 are breeding birds. With regard to carbon storage, the traditional orchard agroforestry system in Germany stocks ranged between 6.5 and 9.8 Mg C ha−1, showing significantly higher values compared to an intensively used grassland with around 3.4 to 6.7 Mg C ha−1. With the remarkably high benefit for biodiversity and ecosystem services provided, the important role and multifunctionality of traditional agroforestry systems in Europe should be acknowledged and promoted.

Keywords: biodiversity, ecosystem services, landscape services, traditional agroforestry systems

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Authors: Amir Masoud Dabagh, Mahsa Khaleghi

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The world has entered a new phase of cultural, social, economic, and so on in the last two centuries. Apart from its positive benefits and achievements to the world, it has also incurred many costs, most of which can be mentioned as destroying or at least diminishing the role of the costumes, traditions and authentic culture of the past communities. Understanding what lasts in traditional arts is vital and worthy of study because receiving it and embracing art and forms of art using that last the artistic creation removes the age-old color and smell of its face, making it immortal and persistent in all ages. This paper attempts to present traditional art concepts and solutions for interior design with the approach of handicrafts recreation as a symbol and manifestation of national identity and proof of ancient civilizations, which is at the center of tourists' attention today. The research method is a descriptive-analytical one that first explores the theoretical foundations of research, which are the concepts of recreation and traditional arts, and analyzes the process of recreation that conceals the recollection of past experiences as well as the dynamics and creativity.

Keywords: recreation, handicrafts, interior design, concept, traditional arts

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

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Authors: Azene Zenebe

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Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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Authors: Mohamed Chabi

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The purpose of this study is to determine Whether paper assessment especially in the subject mathematics will ever be completely replaced by online assessment using Learning Management System and Content Management System such as blackboard. In the subject mathematics, the assessment is the exercise of judgment on the quality of students’ work, as a way of supporting student learning and appraising its outcomes. Testing students has moved from the traditional scribbling and sketching on paper towards working online on a screen and keyboard.

Keywords: paper assessment, online assessment, learning management system, content management system, mathematics

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