Search results for: the creative learning process

Authors: Zahara Abdulhussan Al-Awadai

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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.

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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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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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Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

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Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

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Authors: Thuy Hanh Nguyen Thi

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By the method of deep reading and text analysis, this article will analyze the use and creation of dialects as a way of demonstrating Yan Lianke's creative stance. This article indicates that this is the writer’s narrative strategy in a fight against aphasia, a language disorder of Chinese people and culture, demonstrating a sense of return to folklore and marks his own linguistic style. In terms of verbal text, the dialect in the Yan Lianke’s novels manifested through the use of words, sentences and dialects. There are two types of dialects that exist in Yan Lianke’s novels: the current dialect system and the particular dialect system of Pa Lau world created by the writer himself in order to enrich the vocabulary of Han Chinese.

Keywords: Yan Lianke , aphasia, dialect, Pa Lou world

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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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Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

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This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

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Authors: Yehuda Roth

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In quantum theory, a system’s time evolution is predictable unless an observer performs measurement, as the measurement process can randomize the system. This randomness appears when the measuring device does not accurately describe the measured item, i.e., when the states characterizing the measuring device appear as a superposition of those being measured. When such a mismatch occurs, the measured data randomly collapse into a single eigenstate of the measuring device. This scenario resembles the interpretation process in which the observer does not experience an objective reality but interprets it based on preliminary descriptions initially ingrained into his/her mind. This distinction is the motivation for the present study in which the collapse scenario is regarded as part of the interpretation process of the observer. By adopting the formalism of the quantum theory, we present a complete mathematical approach that describes the interpretation process. We demonstrate this process by applying the proposed interpretation formalism to the ambiguous image "My wife and mother-in-law" to identify whether a woman in the picture is young or old.

Keywords: quantum-like interpretation, ambiguous image, determination, quantum-like collapse, classified representation

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Authors: Dibyendu Adak, Saroj Mandal

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The fly ash based geopolymer concrete generally requires heat activation after casting, which has been considered as an important limitation for its practical application. Such limitation can be overcome by a modification in the process at the time of mixing of ingredients (fly and activator fluid) for geopolymer concrete so that curing can be made at ambient temperature. This process modified geopolymer concrete shows an appreciable improvement in structural performance compared to conventional heat cured geopolymer concrete and control cement concrete. The improved durability performance based on water absorption, sulphate test, and RCPT is also noted. The microstructural properties analyzed through Field Emission Scanning Electron Microscope (FESEM) with Energy Dispersive X-ray Spectroscopy (EDS) and X-ray Diffraction (XRD) techniques show the better interaction of fly ash and activator solution at early ages for the process modified geopolymer concrete. This accelerates the transformation of the amorphous phase of fly ash to the crystalline phase.

Keywords: fly ash, geopolymer concrete, process modification, structural properties, durability, micro-structures

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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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Authors: Salam Kodsi

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In this research, we sought to focus on constructive play and examine its components in the context of two different educational approaches: Waldorf and normative schools. When they are free to choose, construction is one of the forms of play most favored by children. Its short-term and long-term cognitive contributions are apparent in various areas of development. The lack of empirical studies about play in Waldorf schools, which addresses the possibility of this incidental learning inspired the need to enrich the body of existing knowledge. 90 children (4-6 yrs.old) four preschools ( two normative, two Waldorf) participated in a small homogeneous city. Naturalistic observations documented the time frame, physical space, and construction materials related to the freeform building; processes of construction among focal representative children and its products. The study’s main finding with respect to the construction output points to a connection between educational approach and level of construction sophistication. Higher levels of sophistication were found at the Waldorf preschools than at the mainstream preschools. This finding emerged due to the differences in the level of sophistication among the older children in the two types of preschools, while practically no differences emerged among the younger children. Discussion of the research findings considered the differences between the play environments in terms of time, physical space, and construction materials. The construction processes were characterized according to the design model stages. The construction output was characterized according to the sophistication scale dimensions and the connections between approach, age and gender, and sophistication level.

Keywords: constructive play, preschool, design process model, complexity

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Authors: Rakesh Prajapati, Purvik Patel, Hardik Patel

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Productivity and quality are two important aspects that have become great concerns in today’s competitive global market. Every production/manufacturing unit mainly focuses on these areas in relation to the process, as well as the product developed. The electrical discharge machining (EDM) process, even now it is an experience process, wherein the selected parameters are still often far from the maximum, and at the same time selecting optimization parameters is costly and time consuming. Material Removal Rate (MRR) during the process has been considered as a productivity estimate with the aim to maximize it, with an intention of minimizing surface roughness taken as most important output parameter. These two opposites in nature requirements have been simultaneously satisfied by selecting an optimal process environment (optimal parameter setting). Objective function is obtained by Regression Analysis and Analysis of Variance. Then objective function is optimized using Genetic Algorithm technique. The model is shown to be effective; MRR and Surface Roughness improved using optimized machining parameters.

Keywords: MMR, TWR, OC, DOE, ANOVA, minitab

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Authors: Ganiyu Rasaq Omokeji

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The growing recognition of the pivotal role of universities in promoting socio-economic development has led to a focus upon the expansion of the sector around the world. As the economy and society become more ‘knowledge intensive’, the role of universities in development is more onerous than just teaching, research, and service. It is to help create the open society upon which the progress of ideas depends on. Driven to fulfill this role, universities are likely to become even more important in building regional networks of their host communities. Currently, there are about 129 universities in Nigeria, with a total number of 37 federal, 36 state, and 56 privately owned universities. Fountain University is among the private universities in Nigeria located in Osogbo, Osun State. The university is committed to the total development of men and women in an enabling environment, through appropriate teaching, research, and service to humanity, influenced by Islamic ethics and culture. The university focuses on educational development and growth that are relevant to the nation’s manpower needs and global competitiveness through a gradual but steady process. This paper examines the role of Private University in the socio-economic development of host community using Fountain University as a case study. The research methodology design for this paper has a total of 200 respondents. The research instrument of data collection was a questionnaire and in-depth interview (IDI). The finding reveals that Fountain University plays an important role in socio-economic and cultural development through their Islamic culture. The paper recommend that universities must bridge the gaps between creative individual with innovative ideas and the application of technology for economic progress and social betterment of their host communities. University also must serve as a bridge that carries the traffic of social and economic development.

Keywords: private university, socio-economic development, host communities, role of universities and community development

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Authors: Oguz Ak

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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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Authors: Kadir Özsoy

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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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Authors: Isam A. H. Al Zubaidy

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A quick process may be needed to get the benefit the big generated quantity of waste oil sludge (WOS). The process includes the mixing process of WOS with commercial diesel fuel. Different ratios of WOS to diesel fuel were prepared ranging 1:1 to 20:1 by mass. The mixture was continuously mixing for 10 minutes using bench type overhead stirrer and followed by filtration process to separate the soil waste from filtrate oil product. The quantity and the physical properties of the oil filtrate were measured. It was found that the addition of up to 15% WOS to diesel fuel was accepted without dramatic changes to the properties of diesel fuel. The amount of waste oil sludge was decreased by about 60% by mass. This means that about 60 % of the mass of sludge was recovered as light fuel oil. The physical properties of the resulting fuel from 10% sludge mixing ratio showed that the specific gravity, ash content, carbon residue, asphaltene content, viscosity, diesel index, cetane number, and calorific value were affected slightly. The color was changed to light black color. The sulfur content was increased also. This requires other processes to reduce the sulfur content of the resulting light fuel. A new desulfurization process was achieved using adsorption techniques with activated biomaterial to reduce the sulfur content to acceptable limits. Adsorption process by ZnCl₂ activated date palm kernel powder was effective for improvement of the physical properties of diesel like fuel. The final sulfur content was increased to 0.185 wt%. This diesel like fuel can be used in all tractors, buses, tracks inside and outside the refineries. The solid remaining seems to be smooth and can be mixed with asphalt mixture for asphalting the roads or can be used with other materials as an asphalt coating material for constructed buildings. Through this process, valuable fuel has been recovered, and the amount of waste material had decreased.

Keywords: oil sludge, diesel fuel, blending process, filtration process

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Authors: Zachary Huffman, Joana Rocha

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Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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Authors: Syahruddin Sumardi Samindjaya, Indra Fajar Alamsyah, Junaidah Hashim

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Purpose: This study attempts to explore and presents a proposed recruitment model in Islamic university which aligned with holistic role. Design/methodology/approach: It is a conceptual paper in nature. In turn, this study is designed to utilize exploratory approach. Literature and document review that related to this topic are used as the methods to analyse the content found. Findings: Recruitment for any organization is fundamental to achieve its goal effectively. Staffing in universities is vital due to the important role of lecturers. Currently, Islamic universities still adopt the common process of recruitment for their academic staffs. Whereas, they have own characteristics which are embedded in their institutions. Furthermore, the FCWC (Foundation, Capability, Worldview and Commitment) model of recruitment proposes to suit the holistic character of Islamic university. Research limitation/implications: Further studies are required to empirically validate the concept through systematic investigations. Additionally, measuring this model by a designed means is appreciated. Practical implications: The model provides the map and alternative tool of recruitment for Islamic universities to determine the process of recruitment which can appropriate their institutions. In addition, it also allows stakeholders and policy makers to consider regarding Islamic values that should inculcate in the Islamic higher learning institutions. Originality/value: This study initiates a foundational contribution for an early sequence of research.

Keywords: academic staff, Islamic values, recruitment model, university

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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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Authors: Diana Kwok

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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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Authors: T. Wejrzanowski, M. Grybczuk, E. Tymicki, K. J. Kurzydlowski

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In the present study, numerical simulations of heat and mass transfer in Physical Vapor Transport reactor during silicon carbide single crystal growth are addressed. Silicon carbide is a wide bandgap material with unique properties making it highly applicable for high power electronics applications. Because of high manufacturing costs improvements of SiC production process are required. In this study, numerical simulations were used as a tool of process optimization. Computer modeling allows for cost and time effective analysis of processes occurring during SiC single crystal growth and provides essential information needed for improvement of the process. Quantitative relationship between process conditions, such as temperature or pressure, and crystal growth rate and shape of crystallization front have been studied and verified using experimental data. Basing on modeling results, several process improvements were proposed and implemented.

Keywords: Finite Volume Method, semiconductors, Physica Vapor Transport, silicon carbide

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Authors: Dorit Alt, Nirit Raichel

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Although university teaching is claimed to have a special task to support students in adopting ways of thinking and producing new knowledge anchored in scientific inquiry practices, it is argued that students' habits of learning are still overwhelmingly skewed toward passive acquisition of knowledge from authority sources rather than from collaborative inquiry activities.This form of instruction is criticized for encouraging students to acquire inert knowledge that can be used in instructional settings at best, however cannot be transferred into real-life complex problem settings. In order to overcome this critical inadequacy between current educational goals and instructional methods, the LLAF consortium (including 16 members from 8 countries) is aimed at developing updated instructional practices that put a premium on adaptability to the emerging requirements of present society. LLAF has created a practical guide for teachers containing updated pedagogical strategies and assessment tools, based on the constructivist approach for learning that put a premium on adaptability to the emerging requirements of present society. This presentation will be limited to teachers' education only and to the contribution of the project in providing a scale designed to measure the extent to which the constructivist activities are efficiently applied in the learning environment. A mix-method approach was implemented in two phases to construct the scale: The first phase included a qualitative content analysis involving both deductive and inductive category applications of students' observations. The results foregrounded eight categories: knowledge construction, authenticity, multiple perspectives, prior knowledge, in-depth learning, teacher- student interaction, social interaction and cooperative dialogue. The students' descriptions of their classes were formulated as 36 items. The second phase employed structural equation modeling (SEM). The scale was submitted to 597 undergraduate students. The goodness of fit of the data to the structural model yielded sufficient fit results. This research elaborates the body of literature by adding a category of in-depth learning which emerged from the content analysis. Moreover, the theoretical category of social activity has been extended to include two distinctive factors: cooperative dialogue and social interaction. Implications of these findings for the LLAF project are discussed.

Keywords: constructivist learning, higher education, mix-methodology, structural equation modeling

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Authors: Kofi Nkonkonya Mpuangnan, Samantha Govender, Hlengiwe Romualda Mhlongo

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In recent years, a noticeable and worrisome pattern has emerged in numerous developing nations which is a steady and persistent rise in unemployment rates. This escalation of economic struggles has become a cause of great concern for parents who, having invested significant resources in their children's education, harboured hopes of achieving economic prosperity and stability for their families through secure employment. To effectively tackle this pressing unemployment issue, it is imperative to adopt a holistic approach, and a pivotal aspect of this approach involves incorporating entrepreneurial education seamlessly into the entire educational system. In this light, the authors explored approaches to integrating entrepreneurial education into school curriculum focusing on the following questions. How can an entrepreneurial mindset among learners be promoted in school? And how far have pedagogical approaches improved entrepreneurship in schools? To find answers to these questions, a systematic literature review underpinned by Human Capital Theory was adopted. This method was supported by the three stages of guidelines like planning, conducting, and reporting. The data were specifically sought from publishers with expansive coverage of scholarly literature like Sage, Taylor & Francis, Emirate, and Springer, covering publications from 1965 to 2023. The search was supported by two broad terms such as promoting entrepreneurial mindset in learners and pedagogical strategies for enhancing entrepreneurship. It was found that acquiring an entrepreneurial mindset through an innovative classroom environment, resilience, and guest speakers and industry experts. Also, teachers can promote entrepreneurial education through the adoption of pedagogical approaches such as hands-on learning and experiential activities, role-playing, business simulation games and creative and innovative teaching. It was recommended that the Ministry of Education should develop tailored training programs and workshops aimed at empowering educators with the essential competencies and insights to deliver impactful entrepreneurial education.

Keywords: education, entrepreneurship, school curriculum, pedagogical approaches, integration

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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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Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

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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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Authors: Roli Saini, Pradeep Kumar

Abstract:

A coagulation/flocculation process was adopted for the reduction of carbamate insecticide (carbofuran) from aqueous solution. Ferric chloride (FeCl₃) was used as a coagulant to treat the carbofuran. To exploit the reduction efficiency of pesticide concentration and COD, the jar-test experiments were carried out and process was optimized through response surface methodology (RSM). The effects of two independent factors; i.e., FeCl₃ dosage and pH on the reduction efficiency were estimated by using central composite design (CCD). The initial COD of the 30 mg/L concentrated solution was found to be 510 mg/L. Results exposed that the maximum reduction occurred at an optimal condition of FeCl₃ = 80 mg/L, and pH = 5.0, from which the reduction of concentration and COD 75.13% and 65.34%, respectively. The present study also predicted that the obtained regression equations could be helpful as the theoretical basis for the coagulation process of pesticide wastewater.

Keywords: carbofuran, coagulation, optimization, response surface methodology

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

Abstract:

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

Procedia PDF Downloads 177

Authors: Mesfin Getu Woldetensay

Abstract:

Representatives and commercially viable natural gas liquids (NGLs) recovery processes were studied under various feed conditions that are classified as lean and rich. The conventional turbo- expander process scheme (ISS) was taken as a base case. The performance of this scheme was compared against with the gas sub-cooled process (GSP), cold residue-gas (CRR) and recycle split-vapor (RSV), enhanced NGL recovery process (IPSI-1) and enhanced NGL recovery process with internal refrigeration (IPSI-2). The development made for the GSP, CRR and RSV are at the top section of the demethanizer column whereas the IPSI-1 and IPSI-2 improvement focus in the lower section. HYSYS process flowsheet was initially developed for all the processes including the ISS under a common criteria that could help to demonstrate the performance comparison. Accordingly, a number of simulation runs were made for the selected eight types of feed. Results show that the reboiler duty requirement using rich feeds for GSP, CRR and RSV is quite high compared to IPSI-1 and IPSI-2. The latter shows relatively lower duty due to the presence of self-refrigeration system that allows the inlet feed to be used for achieving cooling without the need to use propane refrigerant. The energy consumption for lean feed is much lower than that of the rich feed in all process schemes.

Keywords: composition, lean, rich, duty

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Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

Abstract:

The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

Procedia PDF Downloads 167