Search results for: traditional learning approach

Authors: Hauwau Mohammed

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Research purpose: the integration of Traditional Birth Attendants (TBAs) has long been initiated into healthcare systems. This has been to help improve maternal mortality, particularly in developing countries. Nigeria is seen as one of the countries with a high maternal death rate due to common pregnancy complications and low resources. Communities with challenges of universal coverage of skilled workers rely on TBAs for pregnancy-related services, including delivery. The Sokoto State government has conducted several training programs on a significant number of TBAs to enable a formal integration of relationships with skilled healthcare for women in rural regions. This study aims to explore a standard method and develop an assessment framework for improving TBAs training programs in Sokoto State. Research Design, Methodology & Methods : Using a qualitative design, an interpretive phenomenology approach will be applied to explore the lived-experiences of 28 TBAs, who have undergone a form of training while also examining the strategies used to develop those programs through 8 policymakers and/or program trainers. For the collection stage, a focus group discussion and a face-to-face interview will be conducted, where the latter is for TBAs and the former for policymakers and training officials. Analysis: Data will be analyse through IPA format while using Nvivo to code and catalog personal experiential generated patterns. Secondary review: a scoping review of secondary data from Nigeria was used to map the knowledge gap and the extent of available data. The thematic analytic findings suggested that there are various approaches used to incorporate TBAs into the healthcare system, which include interventional programs targeted at specific health issues. In addition, incentives were used to encourage TBAs to facilitate the frequent use of skilled care for women.

Keywords: traditional birth attendants, Nigeria, training, program

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Bryony Pound

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This study investigated how views of green or urban space affect learning performance. It provides evidence of the value of visual access to greenspace in work and learning environments, and builds on the extensive research into the cognitive and learning-related benefits of access to green and natural spaces, particularly in learning environments. It demonstrates that benefits of visual access to natural spaces whilst learning can produce statistically significant faster responses than those facing urban views after only 5 minutes. The primary hypothesis of this research was that a greenspace view would improve short-term learning. Participants were randomly assigned to either a view of parkland or of urban buildings from the same room. They completed a psychological test of two stages. The first stage consisted of a presentation of words from eight different categories (four manmade and four natural). Following this a 2.5 minute break was given; participants were not prompted to look out of the window, but all were observed doing so. The second stage of the test involved a word recognition/false memory test of three types. Type 1 was presented words from each category; Type 2 was non-presented words from those same categories; and Type 3 was non-presented words from different categories. Participants were asked to respond with whether they thought they had seen the words before or not. Accuracy of responses and reaction times were recorded. The key finding was that reaction times for Type 2 words (highest difficulty) were significantly different between urban and green view conditions. Those with an urban view had slower reaction times for these words, so a view of greenspace resulted in better information retrieval for word and false memory recognition. Importantly, this difference was found after only 5 minutes of exposure to either view, during winter, and with a sample size of only 26. Greenspace views improve performance in a learning task. This provides a case for better visual access to greenspace in work and learning environments.

Keywords: benefits, greenspace, learning, restoration

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Authors: Nahla Khatib

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This study investigated several learning difficulties that affected the classroom learning experience of preservice students who are studying general science and methods of teaching science students at Faculty of Educational Studies at the Arab Open University (AOU) in Amman, Jordan. The focus questions for this study were to find answers for the following: 1. What are the main areas of learning difficulty among preservice students towards science education? 2. What are the main aspects of reducing obstacles towards success in science education? To achieve this goal, the researcher prepared a questionnaire which included 30 items to point out the learning difficulties among preservice students towards science education. The questionnaire was distributed among students enrolled in the general science courses 1&2 and methods of teaching science courses at the beginning of the spring semester of year (2013-2014). After collecting the filled questionnaire a descriptive statistical analysis was carried out (means and standard deviation) for the items of the questionnaire. After analyzing the data statistically our findings showed that student control–factors as well as course controlled factor, factors related to the nature of science, and factors related to the role of instructor affected student success toward science education. The study was concluded with a number of recommendations.

Keywords: nature of science, preservice teachers, science education, learning difficulties

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

Procedia PDF Downloads 157

Authors: Ma'ruf

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Pilgrimage has a universal value, founded in every religion. No exception to Islam, has a ritual value, and became part of the religion, as well as the procession of a social culture in nature. The tradition of pilgrimage, especially in Indonesia, rooted in the society, because the Islam that entered into the archipelago through Sufism (tasawuf). In the Sufi tradition, the interconnecty of the human spirit (ruh) to the spirit (ruh) of God, must go through a guardian (wasilah) appointed by God himself ,the prophet Muhammad and wali. In the process of pilgrimage rituals usually by reading the prayer to praise God, the prophet and wali, then convey intent (hajat). In the pilgrimage procession, usually not only done in the house, but aslo completed the process by direct pilgrimage visiting the tombs of saints. The tradition of pilgrimage, especially in Indonesia continues to be maintained, and still attached to the traditions in Nahdiyin (NU followers). The relationship with God manifested in wasilah prayer to God, the prophet Muhammad, the best companions of the Prophet and Nine wali (Songo), who had been influential in spreading Islam in Java. The tradition of pilgrimage in Indonesia is also linked to the Shia community in Indonesia, along with a growing number of followers of the Shia in Indonesia, especially after the Islamic revolution of Iran after the 1979. Pilgrimage in the Shia community, Likewise NU members also pray with supplication of tawasul to the Prophet and Shia Imams. If NU members to make improvements pilgrimage to visit the tomb wali Songo in Java, residents Shia pilgrimage rituals abroad, usually one package with umrah trip, with a pilgrimage to the tomb of the prophet, proceed to the tomb of the Imam Shia, in Iran and Iraq. Trends of pilgrimage as a ritual in the Indonesian Shia tradition, together with the growing number of Shia residents increased, followed by increasing the awareness (syi’isme) - bond with the Imam, Shia. In every certain months (arbaeen, asyuro) Shia pilgrims routinely perform pilgrimage, along with increasing number spiritual travel.

Keywords: traditional approach, religious experience, culture, religion, pilgrimage, Syria

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Authors: Rosaline Govender

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This research study is an exploration of the self-directed professional development of teachers who teach in public schools in an era of democracy and educational change in South Africa. Amidst an ever-changing educational system, the teachers in this study position themselves as self-directed teacher-learners where they adopt particular learning practices which enable change within the broader discourses of public schooling. Life-story interviews were used to enter into the private and public spaces of five teachers which offer glimpses of how particular systems shaped their identities, and how the meanings of self-directed teacher-learner shaped their learning practices. Through the Multidimensional framework of analysis and interpretation the teachers’ stories were analysed through three lenses: restorying the field texts - the self through story; the teacher-learner in relation to social contexts, and practices of self-directed learning.This study shows that as teacher-learners learn for change through self-directed learning practices, they develop their agency as transformative intellectuals, which is necessary for the reworking of South African public schools.

Keywords: professional development, professionality, professionalism, self-directed learning

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: Jonathan J. Foo, Keng Hao Chew

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Interest in virtual reality (VR) technologies as virtual learning environments have been on the rise in recent years. With thanks to the aggressively competitive consumer electronics environment, VR technology has been made affordable and accessible to the average person with developments like Google Cardboard and Oculus Go. While the promise of virtual access to unique virtual learning environments with the benefits of experiential learning sounds extremely attractive, there are still concerns over user comfort in the psychomotor, cognitive, and affective domains. Reports of motion sickness and short durations create doubt and have stunted its growth. In this paper, a multidimensional framework is proposed for the evaluation of VR learning environments within the three dimensions: tactual quality, didactic quality, and autodidactic quality. This paper further proposes a mixed-methods experimental research plan that sets out to evaluate a virtual reality training simulator in the context of amateur sports fencing. The study will investigate if an immersive VR learning environment can effectively simulate an authentic learning environment suitable for instruction, practice, and assessment while providing the user comfort in the tactual, didactic, and autodidactic dimensions. The models and recommendations developed for this study are designed in the context of fencing, but the potential impact is a guide for the future design and evaluation of all VR developments across sports and technical classroom education.

Keywords: autodidactic quality, didactic quality, tactual quality, virtual reality

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Authors: Sara M. Ismael, Ali H. Al-Badi

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The rapid development and growth of technology has changed the method of obtaining information for educators and learners. Technology has created a new world of collaboration and communication among people. Incorporating new technology into the teaching process can enhance learning outcomes. Billions of individuals across the world are now connected together, and are cooperating and contributing their knowledge and intelligence. Time is no longer wasted in waiting until the teacher is ready to share information as learners can go online and get it immediately. The objectives of this paper are to understand the reasons why changes in teaching and learning methods are necessary, to find ways of improving them, and to investigate the challenges that present themselves in the adoption of new ICT tools in higher education institutes. To achieve these objectives two primary research methods were used: questionnaires, which were distributed among students at higher educational institutes and multiple interviews with faculty members (teachers) from different colleges and universities, which were conducted to find out why teaching and learning methodology should change. The findings show that both learners and educators agree that educational technology plays a significant role in enhancing instructors’ teaching style and students’ overall learning experience; however, time constraints, privacy issues, and not being provided with enough up-to-date technology do create some challenges.

Keywords: e-books, educational technology, educators, e-learning, learners, social media, Web 2.0, LMS

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Authors: Julian Pigott

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This paper introduces the Language Learning as a Means of Drive Engagement (LLMDE) theory, derived from a grounded theory analysis of interviews with Japanese university students. According to LLMDE theory, language learning can be understood as a means of engaging one or more of four self-fulfillment drives: the drive to expand one’s horizons (perspective drive); the drive to make a success of oneself (status drive); the drive to engage in interaction with others (communication drive); and the drive to obtain intellectual and affective stimulation (entertainment drive). While many theories of learner psychology focus on conscious agency, LLMDE theory addresses the role of the unconscious. In addition, supplementary thematic analysis of the data revealed the role of context in mediating drive engagement. Unexpected memorable events, for example, play a key role in instigating and, indirectly, in regulating learning, as do institutional and cultural contexts. Given the apparent importance of such factors beyond the immediate control of the learner, and given the pervasive role of habit and drives, it is argued that the concept of motivation merits theoretical reappraisal. Rather than an underlying force determining language learning success or failure, it can be understood to emerge sporadically in consciousness to promote behavioral change, or to protect habitual behavior from disruption.

Keywords: drives, grounded theory, motivation, significant events

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Authors: Sofia Hartati

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This research is aimed at describing training in early childhood education program empirically, describing teachers ability to plan lessons empirically, and acquiring empirical data as well as analyzing the influence of guided and independent training toward teachers competence in planning early childhood learning program. The method used is an experiment. It collected data with a population of 76 early childhood educators in Tunjung Teja Sub District area through random sampling technique and grouped into two namely 38 people in an experiment class and 38 people in a controlled class. The technique used for data collections is a test. The result of the research shows that there is a significant influence between training for guided educators toward Teachers Ability toward Planning Early Childhood Learning Program. Guided training has been proven to improve the ability to comprehend planning a learning program. The ability to comprehend planning a learning program owned by teachers of early childhood program comprises of 1) determining the characteristics and competence of students prior to learning; 2) formulating the objective of the learning; 3) selecting materials and its sequences; 4) selecting teaching methods; 5) determining the means or learning media; 6) selecting evaluation strategy as a part of teachers pedagogic competence. The result of this research describes a difference in the competence level of teachers who have joined guided training which is relatively higher than the teachers who joined the independent training. Guided training is one of an effective way to improve the knowledge and competence of early childhood educators.

Keywords: competence, planning, teachers, training

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Authors: Moet Moet Myint lay

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Professional learning communities provide ongoing professional development for teachers, where they become learning leaders and actively participate in school improvement. The development of professional knowledge requires a significant focus on professional competence in the work of teachers, and a solid foundation of professional knowledge and skills is necessary for members of society to become intelligent members. Continuing professional development (CPD) plays a vital role in improving educational outcomes, as its importance has been proven over the years. This article explores the need for CPD for teachers in Myanmar and the utility of professional learning communities in improving teacher quality. This study aims to explore a comprehensive understanding of professional learning communities to support the continuing professional development of teacher educators in improving the quality of education. The research questions are: (1) How do teacher educators in Myanmar understand the concept of professional learning communities for continuing professional development? (2) What CPD training is required for all teachers in teachers' colleges? Quantitative research methods were used in this study. Survey data were collected from 50 participants (teacher trainers) from five educational institutions. The analysis shows that professional learning communities when done well, can have a lasting impact on teacher quality. Furthermore, the creation of professional learning communities is the best indicator of professional development in existing education systems. Some research suggests that teacher professional development is closely related to teacher professional skills and school improvement. As a result of the collective learning process, teachers gain a deeper understanding of the subject matter, increase their knowledge, and develop their professional teaching skills. This will help improve student performance and school quality in the future. The lack of clear understanding and knowledge about PLC among school leaders and leads teachers to believe that PLC activities are not beneficial. Lack of time, teacher accountability, leadership skills, and negative attitudes of participating teachers were the most frequently cited challenges in implementing PLCs. As a result of these findings, educators and stakeholders can use them to implement professional learning communities.

Keywords: professional learning communities, continuing professional development, teacher education, competence, school improvement

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Authors: Cara DiGirolamo

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In his 2017 Ph.D. thesis, script doctor David Baboulene presented a theory of fiction in which differences in the knowledge states between participants in a literary experience, including reader, author, and characters, create many story elements, among them suspense, expectations, subtext, theme, metaphor, and allegory. This theory can be adjusted and modeled by incorporating a formal pragmatic approach that understands narrative as a speech act with a conversational function. This approach requires both the Speaker and the Listener to be understood as participants in the discourse. It also uses theories of cooperativity and the QUD to identify the existence of implicit questions. This approach predicts that what an effective literary narrative must do: provide a conversational context early in the story so the reader can engage with the text as a conversational participant. In addition, this model incorporates schema theory. Schema theory is a cognitive model for learning and processing information about the world and transforming it into functional knowledge. Using this approach can extend the QUD model. Instead of describing conversation as a form of information gathering restricted to question-answer sets, the QUD can include knowledge modeling and understanding as a possible outcome of a conversation. With this model, Baboulene’s “Knowledge Gaps” can provide real insight into storytelling as a conversational move, and extend the QUD to be able to simply and effectively apply to a more diverse set of conversational interactions and also to narrative texts.

Keywords: literature, speech acts, QUD, literary theory

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Authors: Joud Tayeb, Dunia Moussa, Rafal Al-Khawlani, Huda Elyas

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This research delves into the intricate AI features of Jenni, an AI-powered chatbot designed to offer personalized and engaging conversations. We explore the fundamental technologies driving Jenni's capabilities, including natural language processing (NLP), machine learning, and deep learning. Through a meticulous analysis of these technologies, we aim to unravel how Jenni effectively processes and understands user queries, generates contextually relevant responses, and continuously learns from interactions. To gain deeper insights into user experiences and satisfaction, a comprehensive survey was conducted. By analyzing the collected data, we determine that consumers mostly like Jenni AI and reported that it has improved their essay writing process, yet the algorithm needs to improve certain aspects, such as accuracy.

Keywords: natural language processing, machine learning, deep learning, artificial intelligence, Jenni

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Authors: C. W. Kan

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Fabrics can be treated to equip them with certain functional properties in which water repellency is one of the important functional effects. In this study, commercial water repellent agent was used under different application conditions to cotton fabric. Finally, the water repellent effect was evaluated by standard testing method. Thus, the aim of this study is to illustrate the proper application of water repellent finishing to cotton fabric and the results could provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, water repellent, textiles, cotton

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Authors: Melanie Adrian, Elspeth McCulloch, Emily-Jean Gallant

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Resources -financial, physical, and human- are increasingly constrained in higher education. University classes are getting bigger, and the concomitant grading burden on faculty is growing rapidly. Multiple-choice exams are seen by some as one solution to these changes. How much students retain, however, and what their testing experience is, continues to be debated. Are multiple-choice exams serving students well, or are they bearing the burden of these developments? Is there a way to address both the resource constraints and make these types of exams more meaningful? In short, how do we engender evaluation methods for large-scale classes that provide opportunities for heightened student learning and enrichment? The following article lays out a testing approach we have employed in four iterations of the same third-year law class. We base our comments in this paper on our initial observations as well as data gathered from an ethics-approved study looking at student experiences. This testing approach provides students with multiple opportunities for revision (thus increasing chances for long term retention), is both individually and collaboratively driven (thus reflecting the individual effort and group effort) and is automatically graded (thus draining limited institutional resources). We found that overall students appreciated the approach and found it more ‘humane’, that it notably reduced pre-exam and intra-exam stress levels, increased ease, and lowered nervousness.

Keywords: exam, higher education, multiple-choice, law

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Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

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Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

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Authors: Martin Hagan

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Teacher identity has been recognised as a crucial field of research which supports understanding of the ways in which teachers navigate the complexities of professional life in order to grow in competence, knowledge and practice. As a field of study, teacher identity is concerned with understanding: how identity is defined; how it develops; how teachers make sense of their emerging identity; and how the act of teaching is mediated through the individual teacher’s values, beliefs and sense of professional self. By comparing two particular, socially constructed learning contexts or ‘learning milieu’, one in Northern Ireland and the other in the United States of America, this study aims specifically, to gain better understanding of how teacher identity develops during the initial phase of teacher education. The comparative approach was adopted on the premise that experiences are constructed through interactive, socio-historical and cultural negotiations with others within particular environments, situations and contexts. As such, whilst the common goal is to ‘become’ a teacher, the nuances emerging from the different learning milieu highlight variance in discourse, priorities, practice and influence. A qualitative, interpretative research design was employed to understand the world-constructions of the participants through asking open-ended questions, seeking views and perspectives, examining contexts and eventually deducing meaning. Data were collected using semi structured interviews from a purposive sample of student teachers (n14) in either the first or second year of study in their respective institutions. In addition, a sample of teacher educators (n5) responsible for the design, organisation and management of the programmes were also interviewed. Inductive thematic analysis was then conducted, which highlighted issues related to: the participants’ personal dispositions, prior learning experiences and motivation; the influence of the teacher education programme on the participants’ emerging professional identity; and the extent to which the experiences of working with teachers and pupils in schools in the context of the practicum, challenged and changed perspectives on teaching as a professional activity. The study also highlights the varying degrees of influence exercised by the different roles (tutor, host teacher/mentor, student) within the teacher-learning process across the two contexts. The findings of the study contribute to the understanding of teacher identity development in the early stages of professional learning. By so doing, the research makes a valid contribution to the discourse on initial teacher preparation and can help to better inform teacher educators and policy makers in relation to appropriate strategies, approaches and programmes to support professional learning and positive teacher identity formation.

Keywords: initial teacher education, professional learning, professional growth, teacher identity

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: Anne-Marie Tuomala

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Education for sustainable development (ESD) aims to provide students with the attitudes, values, and behaviors necessary for the contribution to sustainability. The research was implemented as a part of the Horizons Europe research project, where each partner organization had at least one pilot project locally. The pilot in question was an online course about the basics of the natural stone industry in Finland and its sustainability and circular economy aspects. The course was open to all students of applied universities in Finland, and it was implemented twice during the research. The Stone from Finland association participated in the course design, and it was also an expert in the local context and real-life provider. The multiple case-study method was chosen, as it enables purposeful sampling of cases that are tailored to the specific study. It was also assumed that it predicts quite comparable results of two different course implementations of the course with the same topic and content. The Curtin University of Technology’s Attitudes Towards Thinking and Learning Survey was adapted. The results show the importance of the trans-disciplinary nature of sustainability education. In addition, the new industry areas with the general - but also industry-specific sustainability issues - must be introduced to students and encourage them to do critically reflective learning. Surveys that guide them to analyze their own attitudes to thinking and learning may expose students to their weaknesses but also result in forms of more active sustainability interaction.

Keywords: education for sustainable development, learning attitudes, learning of circular economy, virtual learning

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Authors: Boy Subirosa Sabarguna, Aria Kekalih, Irzan Nurman

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Introduction: Software in the form of Clinical Decision Support System could help students in understanding the mind set of decision-making in diagnosis and treatment at the stage of general practitioners. This could accelerate and ease the learning process which previously took place by using books and experience. Method: Gather 1000 members of the National Medical Multimedia Digital Community (NM2DC) who use the “flowchart of diagnosis and treatment” software, and analyse factors related to: display, speed in learning, convenience in learning, helpfulness and usefulness in the learning process, by using the Likert Scale through online questionnaire which will further be processed using percentage. Results and Discussions: Out of the 1000 members of NM2DC, apparently: 97.0% of the members use the software and 87.5% of them are students. In terms of the analysed factors related to: display, speed in learning, convenience in learning, helpfulness and usefulness of the software’s usage, the results indicate a 90.7% of fairly good performance. Therefore, the “Flowchart of Diagnosis and Treatment” software has helped students in understanding the decision-making of diagnosis and treatment. Conclusion: the use of “Flowchart of Diagnosis and Treatment” software indicates a positive role in helping students understand decision-making of diagnosis and treatment.

Keywords: usage, software, diagnosis and treatment, medical education

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Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

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Authors: Feng Yang

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Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

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Authors: Rochelle Botha-Marais

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When lecturing future educators in South Africa, praxis is an indispensable aspect that is often neglected. Without properly understanding how the theory taught in lecture halls relates to their future position as educators, we can not expect these students to be fully equipped future teachers. To enable education students at the Vaal Campus of the North West University - who have the Afrikaans language as major - to discover the link between theory and practice, the author created an assignment on phonetics in which the use of technology was incorporated. In the past, students had to submit an assignment or worksheet and they did not get the opportunity to apply their newly found knowledge in a practical manner. For potential future teachers, this application is essential. This paper will demonstrate how technology is used in the second year Afrikaans education module to promote student engagement and self-directed learning. Students were introduced to innovative new technologies alongside more familiar applications to shape a 21st century learning environment where students can think, communicate, solve problems, collaborate and take responsibility for their own teaching and learning. The paper will also reflect on student feedback pertaining the use and efficiency of technology in the Afrikaans module and the possible impact thereof on their own teaching and learning landscape. The aim of this paper is to showcase how technology can be used to maximize the students learning experience and equip future education students with the tools and knowledge to introduce technology-enhanced learning in their own teaching practice.

Keywords: education students, theory and practice, self-directed learning, student engagement, technology

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Authors: Naomi Nathan

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Introduction Digitalization of medical education can revolutionize how medical students learn and interact with the medical curriculum across contexts. With the increasing availability of the internet and mobile connectivity in LMICs, online medical education platforms and digital learning tools are becoming more widely available, providing new opportunities for learners to access high-quality medical education and training. However, the adoption and integration of digital technologies in medical education in LMICs is a complex process influenced by various factors, including learners' perceptions and attitudes toward digital learning. In Ethiopia, the adoption of digital platforms for medical education has been slow, with traditional face-to-face teaching methods still being the norm. However, as access to technology improves and more universities adopt digital platforms, it is crucial to understand how medical students perceive this shift. Methodology This study investigated medical students' perception of the digitalization of medical education in relation to their access to the Lecturio Digital Medical Education Platform through a capacity-building project. 740 medical students from over 20 medical universities participated in the study. The students were surveyed using a questionnaire that included their attitudes toward the digitalization of medical education, their frequency of use of the digital platform, and their perceived benefits and challenges. Results The study results showed that most medical students had a positive attitude toward digitalizing medical education. The most commonly cited benefit was the convenience and flexibility of accessing course material/curriculum online. Many students also reported that they found the platform more interactive and engaging, leading to a more meaningful learning experience. The study also identified several challenges medical students faced when using the platform. The most commonly reported challenge was the need for more reliable internet access, which made it difficult for students to access content consistently. Overall, the results of this study suggest that medical students in Ethiopia have a positive perception of the digitalization of medical education. Over 97% of students continuously expressed a need for access to the Lecturio platform throughout their studies. Conclusion Significant challenges still need to be addressed to fully realize the Lecturio digital platform's benefits. Universities, relevant ministries, and various stakeholders must work together to address these challenges to ensure that medical students fully participate in and benefit from digitalized medical education - sustainably and effectively.

Keywords: digital medical education, EdTech, LMICs, e-learning

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Authors: Fernanda Laureti T. Ferreira, Kazuo Nishimoto

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This paper presents a summary of the experience on videoconferencing tools that have been used to teach regular classes during this pandemic period in educational institutions in São Paulo, which tools and applications are most used and the challenges related to this mode of delivery. At this moment, the massive online education is not a choice of students or a structured development of education system, but a solution that emerged to attend urgent needs and it presents the opportunity to teach and learning available for the most students in this single time of social isolation that forced among others, this significant change for education, students, teachers, institutions and families. Distance education enables synchronous and asynchronous mode classes, and even though the current circumstances generate discomfort and uncertainty, on the other hand, there is a chance to promote a 'learning to learn'. The videoconference is a preferred choice of schools because synchronous mode to give more interaction between a group of students and teachers, but this mode requires specifics teacher competencies and skills, in addition to equipment and provision of adequate internet signal for all participants of the process. The approach is making use of known technical information about video conference tools and the results of search answered by a group of students, teachers, schools, and parents. The results presented refer to the perspectives of students and parents as respondents.

Keywords: distance education, interaction on education, online classes, synchronous e-learning, videoconference

Procedia PDF Downloads 126

Authors: Hoong C. Chin, Soon H. Chew, Zhaoxia Wang

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Work on sustainable developments and the call for action in education for sustainable development have been ongoing for a number of years. Training engineering students with the relevant competencies, particularly in sustainable development literacy, has been identified as an urgent task in universities. This requires not only a holistic, multi-disciplinary approach to education but also a suitable training environment to develop the needed skills and to inculcate the appropriate attitudes in students towards sustainable development. To demonstrate how this can be done, a module involving an overseas field trip was introduced in 2013 at the National University of Singapore. This paper provides details of the module and describes its training philosophy and methods. Measured against the student learning outcomes, stipulated by the Engineering Accreditation Board, the module scored well on all of them, particularly those related to complex problem solving, environmental and sustainability awareness, multi-disciplinary team work and varied-level communications.

Keywords: civil engineering education, socio-economically sustainable infrastructure, student learning outcome, sustainable development

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Authors: Peeranan Wisanskoonwong, Sumitta Sawangtook

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Practicum in Midwifery II is the subject that affects most students to be stressed and anxious because they lack of experiences and self-confidence in delivery baby. This study is a qualitative research. That research objectives were (1) to study learning through reflective practice of nursing students (2) to explain the effects of learning through reflective practice of nursing students in the delivery room. The selected key informant method was criterion-based selection. Thirty-two of fourth-year nursing students in Kuakarun Faculty of nursing who practiced in Delivery room at Taksin Hospital in academic year 2014 were selected. Data collection was data triangulation which consisted of in-depth interview, group discussion and reading students’ reflective practice journal. The research instruments were students’ reflective practice journal, semi-structured questionnaires for in-depth interview, group discussion. Data analysis was thematic analysis. The research result found that: The learning method through reflective practice of nursing students in the delivery room were (1) reflective practice journal (2) dialogue (3) critical thinking and problem solving (4) incident analysis (5) self-criticism (6) observation and evaluation of practice. There were eight issues that students learned through their reflective practice were that (1) students' ethics and morality. (2) students' knowledge and comprehension (3) creative thinking of students (4) communications and collaboration (5) experiential learning of students (6) students’memories and impressions (7) students’experience in delivery baby (8) self-learning of students. Learning through reflective practice supported students’ awareness in improving knowledge and learning continuously and systematically. It helped to adjust the attitude to learning and leadership to be careful which help develop their skills, including critical thinking and understand themselves and understand others. Recommendation for applying research results: midwifery and nursing lecturers can apply these results to be a guide for development their clinical teaching in delivery rooms and other wards.

Keywords: learning, reflection, birth, qualitative research

Procedia PDF Downloads 282