Search results for: life-long learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7282

Search results for: life-long learning

5152 The Correlation between Self-Regulated Learning Strategies and Reading Proficiency

Authors: Nguyen Thu Ha, Vu Viet Phuong, Do Thi Tieu Yen, Nguyen Thi Thanh Ha

Abstract:

This semi-experimental research investigated the correlation between 42 English as a foreign language (EFL) sophomores' self-regulated learning strategies (SRL) use and their reading comprehension in the Vietnamese context. The analysis from TOEIC reading tests with SPSS 25.0 indicated that there are substantial differences between the post-test reading scores between the experimental group and the control group; therefore, SRL impacts the reading comprehension of EFL participants. Contrary to the alternative hypothesis, teaching learners SRL approaches had a statistically significant influence on reading comprehension. The findings may aid educators in teaching reading comprehension as an essential skill and in using SRL to improve reading comprehension and achievement and enhance reading comprehension aids for language students and instructors. They should equip educators with a variety of instructional strategies which assist academics in preparing learners for lifetime language study and independence. Moreover, the results might encourage educators, administrators, and policymakers to capitalize on the effects of teaching SRL strategies by providing EFL teachers with preparation programs and experiences that help them improve their teaching methods and strategies, especially when teaching reading comprehension.

Keywords: correlation, reading proficiency, self-regulated learning strategies, SRL, TOEIC reading comprehension

Procedia PDF Downloads 95
5151 Water Body Detection and Estimation from Landsat Satellite Images Using Deep Learning

Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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5150 MIMIC: A Multi Input Micro-Influencers Classifier

Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

Procedia PDF Downloads 184
5149 Designing Effective Serious Games for Learning and Conceptualization Their Structure

Authors: Zahara Abdulhussan Al-Awadai

Abstract:

Currently, serious games play a significant role in education, sparking an increasing interest in using games for purposes beyond mere entertainment. In this research, we investigate the main requirements and aspects of designing and developing effective serious games for learning and developing a conceptual model to describe the structure of serious games with a focus on both aspects of serious games. The main contributions of this approach are to facilitate the design and development of serious games in a flexible and easy-to-use way and also to support the cooperative work between the multidisciplinary developer team.

Keywords: game development, game design, requirements, serious games, serious game model.

Procedia PDF Downloads 65
5148 Assessing Distance Education Practices: Teachers Experience and Perceptions

Authors: Mohammed Amraouy, Mostafa Bellafkih, Abdellah Bennane, Aziza Benomar

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Distance education has become popular due to their ability to provide learning from almost anywhere and anytime. COVID-19 forced educational institutions to urgently introduce distance education to ensure pedagogical continuity, so all stakeholders were invited to adapt to this new paradigm. In order to identify strengths and weaknesses, the research focuses on the need to create an effective mechanism for evaluating distance education. The aims of this research were to explore and evaluate the use of digital media in general and official platforms in particular in distance education practices. To this end, we have developed and validated a questionnaire before administering it to a sample of 431 teachers in Morocco. Teachers reported lower knowledge and skills in the didactic use of ICT in the distance education process. In addition, although age and educative experience of the teachers continue to modulate the level of instrumental skills. Therefore, resources (digital resources and infrastructure) and the teachers’ ICT training present serious limitations, which require a training more focused on the distance educational paradigm and educational environments that allow teachers to create educational activities able to promote and facilitate the distance learning process.

Keywords: distance education, e-learning, teachers’ perceptions, assessment

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5147 Exploring Enabling Effects of Organizational Climate on Academicians’ Emotional Intelligence and Learning Outcomes: A Case from Chinese Higher Education

Authors: Zahid Shafait, Jiayu Huang

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Purpose: This study is based on a trait-based theory of emotional intelligence. This study intends to explore the enabling effect of organizational climate, i.e., affiliation, innovation, and fairness, on the emotional intelligence of teachers in Chinese higher education institutes. This study, additionally, intends to investigate the direct impact of teachers’ emotional intelligence on their learning outcomes, i.e., cognitive, social, self-growth outcomes and satisfaction with the university experience. Design/methodology/approach: This study utilized quantitative research techniques to scrutinize the data. Moreover, partial least squares structural equation modeling, i.e., PLS-SEM, was used to assess the hypothetical relationships to conclude their statistical significance. Findings: Results confirmed the supposed associations, i.e., the organizational climate has an enabling effect on emotional intelligence. Likewise, emotional intelligence was concluded to have a direct and positive association with learning outcomes in higher education. Practical implications: This study has investigated abandoned research that is enabling the effects of organizational climate on teachers’ emotional intelligence in Chinese higher education. Organizational climate enables emotionally intelligent teachers to learn efficiently and, at the same time, augments their satisfaction and productivity within an institution. Originality/value: This study investigated the enabling effects of organizational climate on teachers’ emotional intelligence in Chinese higher education that is original in investigated country and sector.

Keywords: organizational climate, emotional intelligence, learning outcomes, higher education

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5146 Using Mixed Methods in Studying Classroom Social Network Dynamics

Authors: Nashrawan Naser Taha, Andrew M. Cox

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In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.

Keywords: mixed methods, social network analysis, multi-cultural learning, social network dynamics

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5145 Recommendation Systems for Cereal Cultivation using Advanced Casual Inference Modeling

Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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5144 Applying Serious Game Design Frameworks to Existing Games for Integration of Custom Learning Objectives

Authors: Jonathan D. Moore, Mark G. Reith, David S. Long

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Serious games (SGs) have been shown to be an effective teaching tool in many contexts. Because of the success of SGs, several design frameworks have been created to expedite the process of making original serious games to teach specific learning objectives (LOs). Even with these frameworks, the time required to create a custom SG from conception to implementation can range from months to years. Furthermore, it is even more difficult to design a game framework that allows an instructor to create customized game variants supporting multiple LOs within the same field. This paper proposes a refactoring methodology to apply the theoretical principles from well-established design frameworks to a pre-existing serious game. The expected result is a generalized game that can be quickly customized to teach LOs not originally targeted by the game. This methodology begins by describing the general components in a game, then uses a combination of two SG design frameworks to extract the teaching elements present in the game. The identified teaching elements are then used as the theoretical basis to determine the range of LOs that can be taught by the game. This paper evaluates the proposed methodology by presenting a case study of refactoring the serious game Battlespace Next (BSN) to teach joint military capabilities. The range of LOs that can be taught by the generalized BSN are identified, and examples of creating custom LOs are given. Survey results from users of the generalized game are also provided. Lastly, the expected impact of this work is discussed and a road map for future work and evaluation is presented.

Keywords: serious games, learning objectives, game design, learning theory, game framework

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5143 Educational Infrastructure a Barrier for Teaching and Learning Architecture

Authors: Alejandra Torres-Landa López

Abstract:

Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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5142 Students’ Perception and Patterns of Listening Behaviour in an Online Forum Discussion

Authors: K. L. Wong, I. N. Umar

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Online forum is part of a Learning Management System (LMS) environment in which students share opinions. This study attempts to investigate the perceptions of students towards online forum and their patterns of listening behaviour during the forum interaction. The students’ perceptions were measured using a questionnaire, in which seven dimensions were used including online experience, benefits of forum participation, cost of participation, perceived ease of use, usefulness, attitude and intention. Meanwhile, their patterns of listening behaviours were obtained using the log file extracted from the LMS. A total of 25 postgraduate students undertaking a course were involved in this study, and their activities in the forum session were recorded by the LMS and used as a log file. The results from the questionnaire analysis indicated that the students perceived that the forum is easy to use, useful, and bring benefits to them. Also, they showed positive attitude towards online forum, and they have the intention to use it in future. Based on the log data, the participants were also divided into six clusters of listening behaviour, in which they are different in terms of temporality, breadth, depth and speaking level. The findings were compared to previous clusters grouping and future recommendations are also discussed.

Keywords: e-learning, learning management system, listening behavior, online forum

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5141 The Effectiveness of a Courseware in 7th Grade Chemistry Lesson

Authors: Oguz Ak

Abstract:

In this study a courseware for the learning unit of `Properties of matters` in chemistry course is developed. The courseware is applied to 15 7th grade (about age 14) students in real settings. As a result of the study it is found that the students` grade in the learning unit significantly increased when they study the courseware themselves. In addition, the score improvements of the students who found the courseware is usable is not significantly higher than the score improvements of the students who did not found it usable.

Keywords: computer based instruction, effect of courseware and usability of courseware, 7th grade

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5140 More Than a Game: An Educational Application Where Students Compete to Learn

Authors: Kadir Özsoy

Abstract:

Creating a moderately competitive learning environment is believed to have positive effects on student interest and motivation. The best way today to attract young learners to get involved in a fun, competitive learning experience is possible through mobile applications as these learners mostly rely on games and applications on their phones and tablets to have fun, communicate, look for information and study. In this study, a mobile application called ‘QuizUp’ is used to create a specific game topic for elementary level students at Anadolu University Preparatory School. The topic is specially designed with weekly-added questions in accordance with the course syllabus. Students challenge their classmates or randomly chosen opponents to answer questions related to their course subjects. They also chat and post on the topic’s wall in English. The study aims at finding out students’ perceptions towards the use of the application as a classroom and extra-curricular activity through a survey. The study concludes that educational games boost students’ motivation, lead to increased effort, and positively change their studying habits.

Keywords: competitive learning, educational application, effort, motivation 'QuizUp', study habits

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5139 Transnational Initiatives, Local Perspectives: The Potential of Australia-Asia BRIDGE School Partnerships Project to Support Teacher Professional Development in India

Authors: Atiya Khan

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Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

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5138 Experiences of Students in a Cultural Competence Learning Project in Hong Kong- Themes from Qualitative Analysis

Authors: Diana Kwok

Abstract:

Introduction: There is a rising concern on the educational needs of school guidance teachers, counselors, and sex educators to work effectively with students from multicultural groups, such as racial minorities, gender minorities, sexual minorities, and disability groups etc., and to respect cultural diversities. A specialized training model, the multicultural framework based on contact theory is recognized as necessary training model for professional training programs. Methodology: While the major focus of this project is on improving teaching and learning in teacher training courses within the department of Special Education and Counselling, it specifically aims to enhance the cultural competence of 102 participants enrolled in counseling and sexuality education courses by integrating the following teaching and learning strategies: 1) Panel presentation; 2) Case studies; 3) Experiential learning. Data sources from the participants consisted of the following: (a) questionnaires (MCKAS and ATLG) administered in classes; (b) weekly reflective journals, and c) focus group interviews with panel members. The focus group interviews with panel members were documented. Qualitatively, the weekly reflections were content analyzed. The presentation in this specific conference put focus on themes we found from qualitative content analysis of weekly reflective journals from 102 participants. Findings: Content analysis had found the following preliminary emergent themes: Theme I) Cultural knowledge and challenges to personal limitation. Students had gained a new perspective that specific cultural knowledge involved unique values and worldview. Awareness of limitation of counsellors is very important after actively acquiring the cultural knowledge. Theme 2 - Observation, engagement and active learning. Through the sharing and case studies, as well as visits to the communities, students recognized that observation and listening to the needs of cultural group members were the essential steps before taking any intervention steps. Theme 3 - Curiosity and desire for further inter-group dialogue. All students expressed their desire, curiosity, and motivation to have further inter-group dialogue in their future work settings. Theme 4: Experience with teaching and learning strategies. Students shared their perspectives on how teaching and learning strategies had facilitated their acquisition of cultural competence. Results of this analysis suggests that diverse teaching and learning strategies based on contact perspective had stimulated their curiosity to re-examine their values and motivated them to acquire cultural knowledge relevant to the cultural groups. Acknowledgment: The teaching and learning project was funded by the Teaching and Development Grant, Hong Kong Institute of Education (Project Number T0142).

Keywords: cultural competence, Chinese teacher students, teaching and learning, contacts

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5137 The Identification of Instructional Approach for Enhancing Competency of Autism, Attention Deficit Hyperactivity Disorder and Learning Disability Groups

Authors: P. Srisuruk, P. Narot

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The purpose of this research were 1) to develop the curriculum and instructional approach that are suitable for children with autism, attention deficit hyperactivity disorder and learning disability as well as to arrange the instructional approach that can be integrated into inclusive classroom 2) to increase the competency of the children in these group. The research processes were to a) study related documents, b) arrange workshops to clarify fundamental issues in developing core curriculum among the researchers and experts in curriculum development, c) arrange workshops to develop the curriculum, submit it to the experts for criticism and editing, d) implement the instructional approach to examine its effectiveness, e) select the schools to participate in the project and arrange training programs for teachers in the selected school, f) implement the instruction approach in the selected schools in different regions. The research results were 1) the core curriculum to enhance the competency of children with autism, attention deficit hyperactivity disorder and learning disability , and to be used as a guideline for teachers, and these group of children in order to arrange classrooms for students with special needs to study with normal students, 2) teaching and learning methods arranged for students with autism, attention deficit, hyperactivity disorder and learning disability to study with normal students can be used as a framework for writing plans to help students with parallel problems by developing teaching materials as part of the instructional approach. However, the details of how to help the students in each skill or content differ according to the demand of development as well as the problems of individual students or group of students. Furthermore; it was found that most of target teacher could implement the instructional approach based on the guideline model developed by the research team. School in each region does not have much difference in their implementation. The good point of the developed instructional model is that teacher can construct a parallel lesson plan. So teacher did not fell that they have to do extra work it was also shown that students in regular classroom enjoyed studying with the developed instructional model as well.

Keywords: instructional approach, autism, attention deficit hyperactivity disorder, learning disability

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5136 Language Services as a Means of Language Repository for Tuition Support and Facilitation of Learning in Institution of Higher Learning

Authors: Mzamani Aaron Mabasa

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The research study examines the reality that the Language Services Directorate can be considered a language repository hub. The study postulates that multilingual education guided by language policy implementation can improve student performance and pass rate. Various documents in the form of style guides, glossaries and tutorial letters may be used to enable students to understand complex words, sentences, phrases and paragraphs when technical vocabularies are used. This paper addresses the way in which quality assurance can transform South African official languages, including Sign Language, as mandated by the Language Policy for Higher Education. The paper further emphasizes that Language Services is unique in the sense that it involves all South African officials as tools for student support and facilitation of learning. This is in line with the Constitution of the Republic of South Africa (1996) and the Unisa Language Policy of 2023, which declares the status, parity and esteem of these official languages regarding usage in formal function domains, namely education, economy, social and politics. The aim of this paper is to ensure that quality assurance is ultimately accomplished in terms of teaching and learning standards. Eventually, all South African languages can be used for official domains to achieve functional multilingualism. This paper furthermore points out that content analysis as a research instrument as far as a qualitative approach is concerned may be used as a data collection technique.

Keywords: repository, multilingualism, policy, education

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5135 Using Indigenous Knowledge Systems in Teaching Early Literacy: A Case Study of Zambian Public Preschools

Authors: Ronald L. Kaunda

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The education system in Zambia still bears scars of colonialism in the area of policy, curriculum and implementation. This historical context resulted in the failure by the Government of the Republic of Zambia to achieve literacy goals expected among school going children. Specifically, research shows that the use of English for initial literacy and Western based teaching methods to engage learners in literacy activities at lower levels of education including preschool has exacerbated this situation. In 2014, the Government of the Republic of Zambia implemented a new curriculum that, among others things, required preschool teachers to use local and cultural materials and familiar languages for early literacy teaching from preschool to grade 4. This paper presents findings from a study that sought to establish ways in which preschool teachers use Zambian Indigenous knowledge systems and Indigenous teaching strategies to support literacy development among preschool children. The study used Indigenous research methodology for data collection and iterative feature of Constructivist Grounded Theory (CGT) in the data collection process and analysis. This study established that, as agents of education, preschool teachers represented community adult educators because of some roles which they played beyond their academic mandate. The study further found that classrooms as venues of learning were equipped with learning corners reflecting Indigenous literacy materials and Indigenous ways of learning. Additionally, the study found that learners were more responsive to literacy lessons because of the use of familiar languages and local contextualized environments that supported their own cultural ways of learning. The study recommended that if the education system in Zambia is to be fully inclusive of Indigenous knowledge systems and cultural ways of learning, the education policy and curriculum should include conscious steps on how this should be implemented at the classroom level. The study further recommended that more diverse local literacy materials and teaching aids should be produced for use in the classroom.

Keywords: agents of learning, early literacy, indigenous knowledge systems, venues of education

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5134 Comparing Machine Learning Estimation of Fuel Consumption of Heavy-Duty Vehicles

Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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5133 Survey Study of Integrative and Instrumental Motivation in English Language Learning of First Year Students at Naresuan University International College (NUIC), Thailand

Authors: Don August G. Delgado

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Foreign Language acquisition without enough motivation is tough because it is the force that drives students’ interest or enthusiasm to achieve learning. In addition, it also serves as the students’ beacon to achieve their goals, desires, dreams, and aspirations in life. Since it plays an integral factor in language learning acquisition, this study focuses on the integrative and instrumental motivation levels of all the first year students of Naresuan University International College. The identification of their motivation level and inclination in learning the English language will greatly help all NUIC lecturers and administrators to create a project or activities that they will truly enjoy and find worth doing. However, if the findings of this study will say otherwise, this study can also show to NUIC lecturers and administrators how they can help and transform NUIC freshmen on becoming motivated learners to enhance their English proficiency levels. All respondents in this study received an adopted and developed questionnaire from different researches in the same perspective. The questionnaire has 24 questions that were randomly arranged; 12 for integrative motivation and 12 for instrumental motivation. The questionnaire employed the five-point Likert scale. The tabulated data were analyzed according to its means and standard deviations using the Standard Deviation Calculator. In order to interpret the motivation level of the respondents, the Interpretation of Mean Scores was utilized. Thus, this study concludes that majority of the NUIC freshmen are neither integratively motivated nor instrumentally motivated students.

Keywords: motivation, integrative, foreign language acquisition, instrumental

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5132 A Risk Assessment Tool for the Contamination of Aflatoxins on Dried Figs Based on Machine Learning Algorithms

Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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5131 Indigenous Learning of Animal Metaphors: The ‘Big Five’ in King Shaka’s Praise-Poems

Authors: Ntandoni Gloria Biyela

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During traditional times, there were no formal institutions of learning as they are today, where children attend classes to acquire or develop knowledge. This does not mean that there was no learning in indigenous African societies. Grandparents used to tell their grandchildren stories or teach them educational games around the fireplace, which this study refers to as a ‘traditional classroom’. A story recreated in symbolic or allegorical way, forms a base for a society’s beliefs, customs, accepted norms and language learning. Through folklore narratives, a society develops its own self awareness and education. So narrative characters, especially animals may be mythical products of the pre-literate folklore world and thus show the closeness that the Zulu society had with the wildlife. Oral cultures strive to create new facets of meaning by the use of animal metaphors to reflect the relationship of humans with the animal realm and to contribute to the language learning or literature in cross-cultural studies. Although animal metaphors are widespread in Zulu language because of the Zulu nation’s traditional closeness to wildlife, little field-research has been conducted on the social behavior of animals on the way in which their characteristics were transferred with precision to depictions of King Shaka’s behavior and activities during the amalgamation of Nguni clans into a Zulu kingdom. This study attempts to fill the gap by using first-hand interviews with local informants in areas traditionally linked to the king in KwaZulu-Natal province, South Africa. Departing from the conceptual metaphor theory, the study concentrates on King Shaka’s praise-poems in which the praise-poet describes his physical and dispositional characteristics through bold animal metaphors of the ‘Big Five’; namely, the lion, the leopard, the buffalo, the rhinoceros and the elephant, which are often referred to as Zulu royal favorites. These metaphors are still learnt by young and old in the 21st century because they reflect the responsibilities, status, and integrity of the king and the respect in which he is held by his people. They also project the crescendo growth of the Zulu nation, which, through the fulfillment of his ambitions, grew from a small clan to a mighty kingdom.

Keywords: animal, indigenous, learning, metaphor

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5130 Identifying Degradation Patterns of LI-Ion Batteries from Impedance Spectroscopy Using Machine Learning

Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

Abstract:

Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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5129 Summer STEM Camp for Elementary Students: A Conduit to Pre-Service Teacher Training to Learn How to Include a Makerspace for an Inclusive Classroom

Authors: Jennifer Gallup, Beverly Ray, Esther Ntuli

Abstract:

Many students such as students from linguistically or culturally diverse backgrounds and those with a disability remain chronically underrepresented in higher level science and mathematics disciplines as well as many hands-on-lab-based activities due to the need for remedial reading and mathematics instruction. Makerspace labs can be a conduit for supporting inclusive learning for these students through hands-on active learning strategies that support equitable access to STEM disciplines. Makerspace is a physical space where individuals gather to create, invent, innovate, and learn while using hands-on materials such as 2D and 3D printers, software programs, electronics, and other tools and supplies. Makerspaces are emerging across many P-12 settings; however, many teachers enter the field not prepared to harness the power inherent in a makerspace, especially for those with disabilities and differing needs. This paper offers suggestions on teaching pre-service teachers and practicing teachers how to incorporate a makerspace into their professional practice through guided instruction and hands-on practice. Recommendations for interested stakeholders are included as well.

Keywords: STEM learning, technology, autism, students with disabilities, makerspace

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5128 The Role of Art and Music in Enriching Adult Learning in Maltese as a Second Language

Authors: Jacqueline Zammit

Abstract:

Currently, a considerable number of individuals from different backgrounds are being drawn to Malta due to its favourable environment for business, investment, and employment. This influx has led to a growing interest among expats in learning Maltese as a second language (ML2) to enrich their experience of working and residing in Malta. However, the intricacies of Maltese grammar, particularly challenging for second language (L2) learners unfamiliar with Arabic, can pose difficulties in the learning process. Furthermore, it's worth noting that the teaching of ML2 is an emerging field with limited existing research on effective pedagogical strategies. The realm of second language acquisition (SLA) can be notably demanding for adults, requiring well-founded interventions to facilitate learning. Among these interventions, approaches grounded in empirical evidence have incorporated artistic and musical elements to augment SLA. Both art and music have proven roles in facilitating L2 communication, aiding vocabulary retention, and improving comprehension skills. This study aims to delve into the utilization of music and art as catalysts for enhancing the progress of adult learners in mastering ML2. The research employs a qualitative methodology, employing a sample selected through convenience sampling, which encompassed 37 adult learners of ML2. These participants engaged in individual interviews. The data derived from these interviews were subjected to thorough analysis. The outcomes of the study underscore the substantial positive influence exerted by art and music on the academic advancement of adult ML2 learners. Notably, it emerged from the participants' accounts that the current ML2 curricula lack the integration of art and music. Therefore, this study advocates for the incorporation of art and music components within both traditional classroom settings and online ML2 courses. The intention is to bolster the academic accomplishments of adult learners in the realm of Maltese as a second language, bridging the current gap between theory and practice.

Keywords: academic accomplishment, mature learners, visual art, learning Maltese as a second language, musical involvement, acquiring a second language

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5127 R Data Science for Technology Management

Authors: Sunghae Jun

Abstract:

Technology management (TM) is important issue in a company improving the competitiveness. Among many activities of TM, technology analysis (TA) is important factor, because most decisions for management of technology are decided by the results of TA. TA is to analyze the developed results of target technology using statistics or Delphi. TA based on Delphi is depended on the experts’ domain knowledge, in comparison, TA by statistics and machine learning algorithms use objective data such as patent or paper instead of the experts’ knowledge. Many quantitative TA methods based on statistics and machine learning have been studied, and these have been used for technology forecasting, technological innovation, and management of technology. They applied diverse computing tools and many analytical methods case by case. It is not easy to select the suitable software and statistical method for given TA work. So, in this paper, we propose a methodology for quantitative TA using statistical computing software called R and data science to construct a general framework of TA. From the result of case study, we also show how our methodology is applied to real field. This research contributes to R&D planning and technology valuation in TM areas.

Keywords: technology management, R system, R data science, statistics, machine learning

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5126 Songwriting in the Postdigital Age: Using TikTok and Instagram as Online Informal Learning Technologies

Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

Abstract:

In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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5125 Improved Computational Efficiency of Machine Learning Algorithm Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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5124 An Image Segmentation Algorithm for Gradient Target Based on Mean-Shift and Dictionary Learning

Authors: Yanwen Li, Shuguo Xie

Abstract:

In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

Procedia PDF Downloads 267
5123 Thermal Comfort Study of School Buildings in South Minahasa Regency Case Study: SMA Negeri 1 Amurang, Indonesia

Authors: Virgino Stephano Moniaga

Abstract:

Thermal comfort inside a building can affect students in their learning process. The learning process of students can be improved if the condition of the classrooms is comfortable. This study will be conducted in SMA Negeri 1 Amurang which is a senior high school building located in South Minahasa Regency. Based on preliminary survey, generally, students were not satisfied with the existing level of comfort, which subsequently affected the teaching and learning process in the classroom. The purpose of this study is to analyze the comfort level of classrooms occupants and recommend building design solutions that can improve the thermal comfort of classrooms. In this study, three classrooms will be selected for thermal comfort measurements. The thermal comfort measurements will be taken in naturally ventilated classrooms. The measured data comprise of personal data (clothing and students activity), air humidity, air temperature, mean radiant temperature and air flow velocity. Simultaneously, the students will be asked to fill out a questionnaire that asked about the level of comfort that was felt at the time. The results of field measurements and questionnaires will be analyzed based on the PMV and PPD indices. The results of the analysis will decide whether the classrooms are comfortable or not. This study can be continued to obtain a more optimal design solution to improve the thermal comfort of the classrooms. The expected results from this study can improve the quality of teaching and learning process between teachers and students which can further assist the government efforts to improve the quality of national education.

Keywords: classrooms, PMV, PPD, thermal comfort

Procedia PDF Downloads 316