Search results for: English as a foreign language (EFL) learning

Authors: Marta Gràcia, Ana Luisa Adam-Alcocer, Jesús M. Alvarado, Verónica Quezada, Tere Zarza, Priscila Garza

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In secondary education, integrating linguistic content and reflection on it is a crucial challenge that should be included in course plans to enhance students' oral communication competence. In secondary education classrooms, a continuum can be identified in relation to teaching methodologies: 1) the traditional teacher-dominated transmission approach, which is described as that in which teachers transmit content to students unidirectionally; 2) dialogical, bidirectional teaching approach that encourages students to adopt a critical vision of the information provided by the teacher or that is generated through students’ discussion. In this context, the EVALOE-DSS (Assessment Scale of Oral Language Teaching in the School Context-Decision Support System) digital instrument has emerged to help teachers in transforming their classes into spaces for communication, dialogue, reflection, evaluation of the learning process, teaching linguistic contents, and to develop curricular competencies. The tool includes various resources, such as a tutorial with the objectives and an initial screen for teachers to describe the class to be evaluated. One of the main resources of the digital instrument consists of 30 items-actions with three qualitative response options (green, orange, and red face emoji) grouped in five dimensions. In the context of the participation of secondary education teachers in a professional development program using EVALOE-DSS, a digital tool resource aimed to generate more participatory, interactive, dialogic classes, the objectives of the study were: 1) understanding the changes in classrooms’ dynamics and in the teachers’ strategies during their participation in the professional developmental program; 2) analyzing the impact of these changes in students’ oral language development according to their teachers; 3) Deeping on the impact of these changes in the students’ assessment of the classes and the self-assessment of oral competence; 4) knowing teachers’ assessment and reflections about their participation in the professional developmental program. Participants were ten teachers of different subjects and 250 students of secondary education (16-18 years) schools in Spain. The principal instrument used was the digital tool EVALOE-DSS. For 6 months, teachers used the digital tool to reflect on their classes, assess them (their actions and their students’ actions), make decisions, and introduce changes in their classes to be more participatory, interactive, and reflective about linguistic contents. Other collecting data instruments and techniques used during the study were: 1) a questionnaire to assess students’ oral language competence before and at the end of the study, 2) a questionnaire for students’ assessment of the characteristics of classes, 3) teachers’ meetings during the professional developmental program to reflect collaboratively on their experience, 4) questionnaire to assess teacher’s experience during their participation in the professional developmental program, 5) focus group meetings between the teachers and two researchers at the end of the study. The results showed relevant changes in teaching strategies, in the dynamics of the classes, which were more interactive, participative, dialogic and self-managed by the students. Both teachers and students agree about the progressive classes’ transformation into spaces for communication, discussion, and reflection on the language, its development, and its use as an essential instrument to develop curricular competencies.

Keywords: digital tool, individual and collaborative reflection, oral language competence, professional development program, secondary education

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Authors: Sirapop Nuannimnoi, Hojjat Baghban, Ching-Yao Huang

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Over the past decade, with the fast development of blockchain technology since the birth of Bitcoin, there has been a massive increase in the usage of Cryptocurrencies. Cryptocurrencies are not seen as an investment opportunity due to the market’s erratic behavior and high price volatility. With the recent success of deep reinforcement learning (DRL), portfolio management can be modeled and automated. In this paper, we propose a novel DRL-based multi-agent system to automatically make proper trading decisions on multiple cryptocurrencies and gain profits in the highly volatile cryptocurrency market. We also extend this multi-agent system with horizontal federated transfer learning for better adapting to the inclusion of new cryptocurrencies in our portfolio; therefore, we can, through the concept of diversification, maximize our profits and minimize the trading risks. Experimental results through multiple simulation scenarios reveal that this proposed algorithmic trading system can offer three promising key advantages over other systems, including maximized profits, minimized risks, and adaptability.

Keywords: cryptocurrency portfolio management, algorithmic trading, federated learning, multi-agent reinforcement learning

Procedia PDF Downloads 119

Authors: Kemal Izci

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Assessment forms an important part of instruction. Assessment that aims to support learning is known as formative assessment and it contributes student’s learning gain and motivation. However, teachers rarely use assessment formatively to aid their students’ learning. Thus, reviewing the factors that limit or support teachers’ practices of formative assessment will be crucial for guiding educators to support prospective teachers in using formative assessment and also eliminate limiting factors to let practicing teachers to engage in formative assessment practices during their instruction. The study, by using teacher’s change environment framework, reviews literature on formative assessment and presents a tentative model that illustrates the factors impacting teachers’ adoption of formative assessment in their teaching. The results showed that there are four main factors consisting personal, contextual, resource-related and external factors that influence teachers’ practices of formative assessment.

Keywords: assessment practices, formative assessment, teacher education, factors for use of formative assessment

Procedia PDF Downloads 376

Authors: Md. Minhazul Islam, Shah Ashisul Abed Nipun, Majharul Islam, Md. Abdur Rakib Rahat, Jonayet Miah, Salsavil Kayyum, Anwar Shadaab, Faiz Al Faisal

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The target of this research is to predict Myocardial Infarction using unsupervised Machine Learning algorithms. Myocardial Infarction Prediction related to heart disease is a challenging factor faced by doctors & hospitals. In this prediction, accuracy of the heart disease plays a vital role. From this concern, the authors have analyzed on a myocardial dataset to predict myocardial infarction using some popular Machine Learning algorithms K-Means and Hierarchical Clustering. This research includes a collection of data and the classification of data using Machine Learning Algorithms. The authors collected 345 instances along with 26 attributes from different hospitals in Bangladesh. This data have been collected from patients suffering from myocardial infarction along with other symptoms. This model would be able to find and mine hidden facts from historical Myocardial Infarction cases. The aim of this study is to analyze the accuracy level to predict Myocardial Infarction by using Machine Learning techniques.

Keywords: Machine Learning, K-means, Hierarchical Clustering, Myocardial Infarction, Heart Disease

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Authors: Ida Srdić, Luka Mandić, LidijaMandić

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Digitization and intensive use of tablets, smartphones, the internet, mobile, and web applications have massively disrupted our habits, and the way audiences (especially youth) consume content. To introduce educational content in games and animations, and at the same time to keep it interesting and compelling for kids, is a challenge. In our work, we are comparing the different possibilities and potentials that digital games could provide to successfully mitigate direct connection with education. We analyze the main directions and educational methods in game-based learning and the possibilities of interactive modeling through questionnaires for user experience and requirements. A pre and post-quantitative survey will be conducted in order to measure levels of objective knowledge as well as the games perception. This approach enables quantitative and objective evaluation of the impact the game has on participants. Also, we will discuss the main barriers to the use of games in education and how games can be best used for learning.

Keywords: Bloom’s taxonomy, epistemic games, learning objectives, virtual learning environments

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Vilma Zydziunaite, Monika Kelpsiene

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In early childhood and preschool education, play has an important role in learning and cognitive processes. In the context of a changing world, personal autonomy and the use of technology are becoming increasingly important for the development of a wide range of learner competencies. By integrating technology into learning environments, the educational reality is changed, promoting unusual learning experiences for children through play-based activities. Alongside this, teachers are challenged to develop encouragement and motivation strategies that empower children to act independently. The aim of the study was to reveal the changes in the roles and experiences of teachers in the application of AR technology for the enrichment of the learning process. A quantitative research approach was used to conduct the study. The data was collected through an electronic questionnaire. Participants: 319 teachers of 5-6-year-old children using AR technology tools in their educational process. Methods of data analysis: Cronbach alpha, descriptive statistical analysis, normal distribution analysis, correlation analysis, regression analysis (SPSS software). Results. The results of the study show a significant relationship between children's learning and the educational process modeled by the teacher. The strongest predictor of child learning was found to be related to the role of the educator. Other predictors, such as pedagogical strategies, the concept of AR technology, and areas of children's education, have no significant relationship with child learning. The role of the educator was found to be a strong determinant of the child's learning process. Conclusions. The greatest potential for integrating AR technology into the teaching-learning process is revealed in collaborative learning. Teachers identified that when integrating AR technology into the educational process, they encourage children to learn from each other, develop problem-solving skills, and create inclusive learning contexts. A significant relationship has emerged - how the changing role of the teacher relates to the child's learning style and the aspiration for personal leadership and responsibility for their learning. Teachers identified the following key roles: observer of the learning process, proactive moderator, and creator of the educational context. All these roles enable the learner to become an autonomous and active participant in the learning process. This provides a better understanding and explanation of why it becomes crucial to empower the learner to experiment, explore, discover, actively create, and foster collaborative learning in the design and implementation of the educational content, also for teachers to integrate AR technologies and the application of the principles of shared leadership. No statistically significant relationship was found between the understanding of the definition of AR technology and the teacher’s choice of role in the learning process. However, teachers reported that their understanding of the definition of AR technology influences their choice of role, which has an impact on children's learning.

Keywords: teacher, learner, augmented reality, collaboration, shared leadership, preschool education

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Authors: Shazmeen Maroof

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The study is motivated by a desire to investigate whether there is substance to claims that, relative to traditional donors, China disregards human rights considerations when allocating overseas aid. While the stated policy of the U.S. is that consideration of potential aid recipients’ respect for human rights is mandatory, some quantitative studies have cast doubt on whether this is reflected in actual allocations. There is a lack of academic literature that formally assesses the extent to which the two countries' aid allocations differ; which is essential to test whether the criticisms of China's aid policy in comparison to that of the U.S. are justified. Using data on two standard human rights measures, 'Political Terror Scale' and 'Civil Liberties', the study analyse the two donors’ aid allocations among 125 countries over the period 2000 to 2014. The bivariate analysis demonstrated that a significant share of China’s aid flow to countries with poor human rights record. At the same time, the U.S. seems little different in providing aid to these countries. The empirical results obtained from the Fractional Logit model also provided some support to the general pessimism regarding China’s provision of aid to countries with poor human rights record, yet challenge the optimists expecting better targeted aid from the U.S. These findings are consistent with the split between humanitarian and non-humanitarian aid and in the sample of countries whose human rights record is below some threshold level.

Keywords: China's aid policy, foreign aid allocation, human rights, United States Foreign Assistance Act

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Authors: Tahir Mehmood, Mumtaz Akhter

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The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

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Authors: Pedro Paulo Galindo Francisco, Eli Dhadad Junior

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This study addresses the Meese-Rogoff Puzzle by introducing the latest machine learning techniques as alternatives for predicting the exchange rates. Using RMSE as a comparison metric, Meese and Rogoff discovered that economic models are unable to outperform the random walk model as short-term exchange rate predictors. Decades after this study, no statistical prediction technique has proven effective in overcoming this obstacle; although there were positive results, they did not apply to all currencies and defined periods. Recent advancements in artificial intelligence technologies have paved the way for a new approach to exchange rate prediction. Leveraging this technology, we applied five machine learning techniques to attempt to overcome the Meese-Rogoff puzzle. We considered daily data for the real, yen, British pound, euro, and Chinese yuan against the US dollar over a time horizon from 2010 to 2023. Our results showed that none of the presented techniques were able to produce an RMSE lower than the Random Walk model. However, the performance of some models, particularly LSTM and N-BEATS were able to outperform the ARIMA model. The results also suggest that machine learning models have untapped potential and could represent an effective long-term possibility for overcoming the Meese-Rogoff puzzle.

Keywords: exchage rate, prediction, machine learning, deep learning

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Authors: Olubukola Olumuyiwa Tokede, Dominic D. Ahiaga-Dagbui, John Morrison

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The project environment in construction has been widely criticised for its inability to learn from experience effectively. As each project is bespoke, learning is ephemeral, as it is often confined within its bounds and seldom assimilated with others that are being delivered in the project environment. To engender learning across construction projects, collaborative contractual arrangements, such as alliancing and partnering, have been embraced to aid the transferability of lessons across projects. These cooperative arrangements, however, tend to be costly, and hence construction organisations could revert to less expensive traditional procurement approaches after successful collaborative project delivery. This research, therefore, seeks to assess the lessons-learned in a post-alliance contractual framework. Using a case-study approach, we examine the experiences of a public sector authority who engaged a project facilitator to foster learning during the delivery of a significant piece of critical infrastructure. It was found that the facilitator enabled optimal learning outcomes in post-alliance contractual frameworks by attenuating the otherwise adversarial relationship between clients and contractors. Further research will seek to assess the effectiveness of different knowledge-brokering agencies in construction projects.

Keywords: facilitation, knowledge-brokering, learning, projects

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Authors: Eric Fang, Robert Chen, Ghim Song Chia, Bien Soo Tan

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Objective and Rationale: Training of radiology residents hinges on practical, on-the-job training in all facets and modalities of diagnostic radiology. Although residency is structured to be comprehensive, clinical exposure depends on the case mix available locally and during the posting period. To supplement clinical training, there are several e-learning resources available to allow for greater exposure to radiological cases. The objective of this study was to survey residents and faculty on the usefulness of these e-learning resources. Methods: E-learning resources were shortlisted with input from radiology residents, Google search and online discussion groups, and screened by their purported focus. Twelve e-learning resources were found to meet the criteria. Both radiology residents and experienced radiology faculty were then surveyed electronically. The e-survey asked for ratings on breadth, depth, testing capability and user-friendliness for each resource, as well as for rankings for the top 3 resources. Statistical analysis was performed using SAS 9.4. Results: Seventeen residents and fifteen faculties completed an e-survey. Mean response rate was 54% ± 8% (Range: 14- 96%). Ratings and rankings were statistically identical between residents and faculty. On a 5-point rating scale, breadth was 3.68 ± 0.18, depth was 3.95 ± 0.14, testing capability was 2.64 ± 0.16 and user-friendliness was 3.39 ± 0.13. Top-ranked resources were STATdx (first), Radiopaedia (second) and Radiology Assistant (third). 9% of responders singled out R-ITI as potentially good but ‘prohibitively costly’. Statistically significant predictive factors for higher rankings are familiarity with the resource (p = 0.001) and user-friendliness (p = 0.006). Conclusion: A good e-learning system will complement on-the-job training with a broad case base, deep discussion and quality trainee evaluation. Based on our study on twelve e-learning resources, no single program fulfilled all requirements. The perception and use of radiology e-learning resources depended more on familiarity and user-friendliness than on content differences and testing capability.

Keywords: e-learning, medicine, radiology, survey

Procedia PDF Downloads 333

Authors: Botirjon Kosimov

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This work sheds light on the reforms towards the independence of the judiciary in Uzbekistan, as well as issues of further ensuring judicial independence in the country based on international values, particularly the legal practice of the United States. In every democratic state infringed human rights are reinstated and violated laws are protected by the help of justice based on the strict principle of judicial independence. The realization of this principle in Uzbekistan has been paid much attention since the proclamation of its independence. In the country, a series of reforms have been implemented in the field of the judiciary in order to actualize the principle of judicial independence. Uzbekistan has been reforming the judiciary considering both international and national values and practice of foreign countries. While forming a democratic state based on civil society, Uzbekistan shares practice with the most developed countries in the world. The United States of America can be a clear example which is worth learning how to establish and ensure an independent judiciary. It seems that although Uzbekistan has reformed the judiciary efficiently, it should further reform considering the legal practice of the United States.

Keywords: dependent judges, independent judges, judicial independence, judicial reforms, judicial life tenure, obstacles to judicial independence

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Authors: Shwadhin Sharma

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As there has been increasing focus on the shorter attention span of the millennials students, there is a relative absence of instructional tools on behavioral assessments in learning information technology skills within the information systems field and textbooks. This study uses project-based learning in which students gain knowledge and skills related to information technology by working on an extended project that allows students to find a real business problem design information systems based on information collected from the company and develop an information system that solves the problem of the company. Eighty students from two sections of the same course engage in the project from the first week of the class till the sixteenth week of the class to deliver a small business information system that allows them to employ all the skills and knowledge that they learned in the class into the systems they are creating. Computer Information Systems related courses are often difficult to understand and process especially for the Under Representative Minorities students who have limited computer or information systems related (academic) experiences. Project-based learning demands constant attention of the students and forces them to apply knowledge learned in the class to a project that helps retaining knowledge. To make sure our assumption is correct, we started with a pre-test and post-test to test the students learning (of skills) based on the project. Our test showed that almost 90% of the students from the two sections scored higher in post-test as compared to pre-test. Based on this premise, we conducted a further survey that measured student’s job-search preparation, knowledge of data analysis, involved with the course, satisfaction with the course, student’s overall reaction the course and students' ability to meet the traditional learning goals related to the course.

Keywords: project-based learning, job-search preparation, satisfaction with course, traditional learning goals

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Authors: Liliana O. Martínez, Juan E. González, Manuel Ramírez-Aranda, Ana Cervantes-Herrera

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In this work, the use of a collection of mathematical challenges and puzzles aimed at students who are starting in algebra is proposed. The selected challenges and puzzles are intended to arouse students' interest in this area of mathematics, in addition to facilitating the teaching-learning process through challenges such as riddles, crossword puzzles, and board games, all in everyday situations that allow them to build themselves the learning. For this, it is proposed to carry out a "Math Rally: algebra" divided into four sections: mathematical reasoning, a hierarchy of operations, fractions, and algebraic equations.

Keywords: algebra, algebraic challenge, algebraic puzzle, math rally

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Authors: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

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Authors: Dorota Kobus-Ostrowska

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Work for everyone, especially for person with disability is a condition in independence; it secures basic needs and develops manual and intellectual capabilities. The work is a source of income, and it builds and strengthens of self-esteem and competence. The purpose of this article is to identify work as an important factor in everyone’s life, despite Polish disabled persons rarely having the chance to undertake a job. In order to achieve this purpose, two methods were used: comparative and qualitative. The theoretical part of this article is based on studies of a wide range of Polish and foreign literature devoted to the issue of the occupational development of people with disabilities. The article was also enriched with the institutional and legal analysis types of support for people with disabilities in Poland. Currently, a Polish person with disability who wants to enter or return to the labor market is under a special protection. Those entities employing workers with disabilities may obtain a subsidy for the salary of a person with disabilities. Unfortunately, people with disability in Poland rarely participate in the workforce. The factors that contribute to this include the difficulty in obtaining work, the uncertainty of keeping it, and the low salary offered. Despite that domestic and foreign literature highlight the important role of disabled people as a workforce, very few people with disability in Poland are economically active.

Keywords: disabled person, employer, rehabilitation, work

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

Procedia PDF Downloads 92

Authors: J. Miranda, D. Chavarría-Barrientos, M. Ramírez-Cadena, M. E. Macías, P. Ponce, J. Noguez, R. Pérez-Rodríguez, P. K. Wright, A. Molina

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Higher education methods need to evolve because the new generations of students are learning in different ways. One way is by adopting emergent technologies, new learning methods and promoting the maker movement. As a result, Tecnologico de Monterrey is developing Open Innovation Laboratories as an immediate response to educational challenges of the world. This paper presents an Open Innovation Laboratory for Rapid Realization of Sensing, Smart and Sustainable Products (S³ Products). The Open Innovation Laboratory is composed of a set of specific resources where students and teachers use them to provide solutions to current problems of priority sectors through the development of a new generation of products. This new generation of products considers the concepts Sensing, Smart, and Sustainable. The Open Innovation Laboratory has been implemented in different courses in the context of New Product Development (NPD) and Integrated Manufacturing Systems (IMS) at Tecnologico de Monterrey. The implementation consists of adapting this Open Innovation Laboratory within the course’s syllabus in combination with the implementation of specific methodologies for product development, learning methods (Active Learning and Blended Learning using Massive Open Online Courses MOOCs) and rapid product realization platforms. Using the concepts proposed it is possible to demonstrate that students can propose innovative and sustainable products, and demonstrate how the learning process could be improved using technological resources applied in the higher educational sector. Finally, examples of innovative S³ products developed at Tecnologico de Monterrey are presented.

Keywords: active learning, blended learning, maker movement, new product development, open innovation laboratory

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Brwa Abdulrahman Abubaker

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Recently, there has been a lot of interest in the difficult task of applying reinforcement learning to autonomous mobile robots. Conventional reinforcement learning (TRL) techniques have many drawbacks, such as lengthy computation times, intricate control frameworks, a great deal of trial and error searching, and sluggish convergence. In this paper, a modified Spiking Neural Network (SNN) is used to offer a distinct method for autonomous mobile robot learning and control in unexpected surroundings. As a learning algorithm, the suggested model combines dopamine modulation with spike-timing-dependent plasticity (STDP). In order to create more computationally efficient, biologically inspired control systems that are adaptable to changing settings, this work uses the effective and physiologically credible Izhikevich neuron model. This study is primarily focused on creating an algorithm for target tracking in the presence of obstacles. Results show that the SNN trained with three obstacles yielded an impressive 96% success rate for our proposal, with collisions happening in about 4% of the 214 simulated seconds.

Keywords: spiking neural network, spike-timing-dependent plasticity, dopamine modulation, reinforcement learning

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

Procedia PDF Downloads 478

Authors: Fetoon K. Algarawi, Wejdan A. Alslamah, Ahlam A. Alhabib, Afnan S. Alfehaid, Dina M. Ibrahim

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Over the past 20 years, technology was rapidly developed and no one expected what will come next. Advancements in technology open new opportunities for immersive learning environments. There is a need to transmit education to a level that makes it more effective for the student. Augmented reality is one of the most popular technologies these days. This paper is an experience of applying Augmented Reality (AR) technology using a marker-based approach in E-learning system to transmitting virtual objects into the real-world scenes. We present a marker-based approach for transmitting virtual objects into real-world scenes to explain information in a better way after we developed a mobile phone application. The mobile phone application was then tested on students to determine the extent to which it encouraged them to learn and understand the subjects. In this paper, we talk about how the beginnings of AR, the fields using AR, how AR is effective in education, the spread of AR these days and the architecture of our work. Therefore, the aim of this paper is to prove how creating an interactive e-learning system using AR technology will encourage students to learn more.

Keywords: augmented reality, e-learning, marker-based, monitor-based

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Authors: Azizeh Chalak, Niloufar Nasri

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Students' academic achievement, along with the effects of different variables, has been a serious concern of educators since long ago. This study was an attempt to investigate the interplay of Locus of Control (LOC), academic achievement and biological variables among Iranian online EFL Learners. The participants of the study included 100 students of different age groups and genders studying English online at Iran Language Institute (ILI), Isfahan, Iran. The instrument used was Trice Academic LOC questionnaire which identifies orientations of internality or externality. The participants' Grade Point Averages (GPAs) were used as the measure of their academic achievement. A series of independent samples t-tests were performed on the data. The results of the study showed that (a) there were no significant differences between male and female participants in LOC orientation, (b) there was no relationship between LOC and academic achievement among internal males and females, (c) external females were better achievers than external males, (d) and the age had no significant relationship with LOC and academic achievement. It can be concluded that the social, cultural patterns of genders have changed. This study might help sociologists and psychologists as well as applied linguists in that they reflect the recent social changes and their effects on the LOC and their consequent implications in teaching languages.

Keywords: academic achievement, biological variables, Iranian online EFL learners, locus of control

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Authors: Abdulmutallib U. Baraya, Aishatu M. Chadi, Zainab A. Aliyu, Agatha Samson

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Learning Resources is the field of study that investigates the process of analyzing, designing, developing, implementing, and evaluating learning materials, learners, and the learning process in order to improve teaching and learning in university-level education essential for empowering students and various sectors of Nigeria’s economy to succeed in a fast-changing global economy. Innovation in the information age of the 21st century is the use of educational technologies in the classroom for instructional delivery, it involves the use of appropriate educational technologies like smart boards, computers, projectors and other projected materials to facilitate learning and improve performance. The study examined learning resources as determinants for improving the teaching and learning process in Abubakar Tafawa Balewa University (ATBU), Bauchi, Bauchi state of Nigeria. Three objectives, three research questions and three null hypotheses guided the study. The study adopted a Survey research design. The population of the study was 880 lecturers. A sample of 260 was obtained using the research advisor table for determining sampling, and 250 from the sample was proportionately selected from the seven faculties. The instrument used for data collection was a structured questionnaire. The instrument was subjected to validation by two experts. The reliability of the instrument stood at 0.81, which is reliable. The researchers, assisted by six research assistants, distributed and collected the questionnaire with a 75% return rate. Data were analyzed using mean and standard deviation to answer the research questions, whereas simple linear regression was used to test the null hypotheses at a 0.05 level of significance. The findings revealed that physical facilities and digital technology tools significantly improved the teaching and learning process. Also, consumables, supplies and equipment do not significantly improve the teaching and learning process in the faculties. It was recommended that lecturers in the various faculties should strengthen and sustain the use of digital technology tools, and there is a need to strive and continue to properly maintain the available physical facilities. Also, the university management should, as a matter of priority, continue to adequately fund and upgrade equipment, consumables and supplies frequently to enhance the effectiveness of the teaching and learning process.

Keywords: education, facilities, learning-resources, technology-tools

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Authors: Liu Yi Hui

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The COVID-19 pandemic in 2020 has globally affected all aspects of life, with social distancing and quarantine orders causing turmoil and learning in community colleges being temporarily paused. In fact, this is the first time that adult education has faced such a severe challenge. It forces researchers to reflect on the impact of pandemics on adult education and ways to respond. Distance learning appears to be one of the pedagogical tools capable of dealing with interpersonal isolation and social distancing caused by the pandemic. This research aims to examine whether the impact of social distancing during COVID-19 will lead to increased acceptance of technology and, subsequently, an increase in adults ’ willingness to participate in distance learning. The hypothesis that social distancing and the desire to participate in distance learning affects learners’ tendency to accept technology is investigated. Teachers ’ participation in distance education and acceptance of technology are used as adjustment variables with the relationship to “social distancing,” “participation in distance learning,” and “acceptance of technology” of learners. A questionnaire survey was conducted over a period of twelve months for teachers and learners at all community colleges in Taiwan who enrolled in a basic unit course. Community colleges were separated using multi-stage cluster sampling, with their locations being metropolitan, non-urban, south, and east as criteria. Using the G*power software, 660 samples were selected and analyzed. The results show that through appropriate pedagogical strategies or teachers ’ own acceptance of technology, adult learners’ willingness to participate in distance learning could be influenced. A diverse model of participation can be developed, improving adult education institutions’ ability to plan curricula to be flexible to avoid the risk associated with epidemic diseases.

Keywords: social distancing, adult learning, community colleges, technology acceptance model

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Yasaswi Palagummi, Sareh Rowlands

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Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

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Authors: Ehi E. Aimiuwu

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As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: class facilitation, class management, online teaching, online education, pedagogy

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Authors: Jennifer Gallup, Joel Bocanegra, Greg Callan, Abigail Vaughn

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Students with disabilities (SWD) engaged in a distance summer program delivered over multiple virtual mediums that used gaming principles to teach and practice self-regulated learning (SRL) through the process of exploring possible jobs. Gaming quests were developed to explore jobs and teach transition skills. Students completed specially designed quests that taught and reinforced SRL and problem-solving through individual, group, and teacher-led experiences. SRL skills learned were reinforced through guided job explorations over the context of MinecraftEDU, zoom with experts in the career, collaborations with a team over Marco Polo, and Zoom. The quests were developed and laid out on an accessible web page, with active learning opportunities and feedback conducted within multiple virtual mediums including MinecraftEDU. Gaming mediums actively engage players in role-playing, problem-solving, critical thinking, and collaboration. Gaming has been used as a medium for education since the inception of formal education. Games, and specifically board games, are pre-historic, meaning we had board games before we had written language. Today, games are widely used in education, often as a reinforcer for behavior or for rewards for work completion. Games are not often used as a direct method of instruction and assessment; however, the inclusion of games as an assessment tool and as a form of instruction increases student engagement and participation. Games naturally include collaboration, problem-solving, and communication. Therefore, our summer program was developed using gaming principles and MinecraftEDU. This manuscript describes a virtual learning summer program called Virtual Academy New and Exciting Transitions (VAN) that was redesigned from a face-to-face setting to a completely online setting with a focus on SWD aged 14-21. The focus of VAN was to address transition planning needs such as problem-solving skills, self-regulation, interviewing, job exploration, and communication for transition-aged youth diagnosed with various disabilities (e.g., learning disabilities, attention-deficit hyperactivity disorder, intellectual disability, down syndrome, autism spectrum disorder).

Keywords: autism, disabilities, transition, summer program, gaming, simulations

Procedia PDF Downloads 75