Search results for: student-centered teaching and learning

Authors: Seah Siok Peh, Hashimah Mohd Yunus, Nor Hashimah Hashim, Mariam Mohamad

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A country needs a workforce that encompasses knowledge, skilled labourers to generate innovation, productivity and being able to solve problems creatively via technology. Science education experts believe that the mastery of science skills help preschoolers to generate such knowledge on scientific concepts by providing constructive experiences. Science process skills are skills used by scientists to study or investigate a problem, issue, problem or phenomenon of science. In line with the skills used by scientists. The purpose of this study is to investigate the basic science process skill and interest in learning early science through mobile application. This study aimed to explore six spesific basic science process skills by the use of a mobile application as a learning support tool. The descriptive design also discusses on the extent of the use of mobile application in improving basic science process skill in young children. This study consists of six preschoolers and two preschool teachers from two different classes located in Perak, Malaysia. Techniques of data collection are inclusive of observations, interviews and document analysis. This study will be useful to provide information and give real phenomena to policy makers especially Ministry of education in Malaysia.

Keywords: science education, basic science process skill, interest, early science, mobile application

Procedia PDF Downloads 249

Authors: Yi-Hsiu Lai

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The present study aimed to elucidate the lexical-semantic processing for Chinese as second language (CSL) learners. Twenty L1 speakers of Chinese and twenty CSL learners in Taiwan participated in a picture naming task and a category fluency task. Based on their Chinese proficiency levels, these CSL learners were further divided into two sub-groups: ten CSL learners of elementary Chinese proficiency level and ten CSL learners of intermediate Chinese proficiency level. Instruments for the naming task were sixty black-and-white pictures: thirty-five object pictures and twenty-five action pictures. Object pictures were divided into two categories: living objects and non-living objects. Action pictures were composed of two categories: action verbs and process verbs. As in the naming task, the category fluency task consisted of two semantic categories – objects (i.e., living and non-living objects) and actions (i.e., action and process verbs). Participants were asked to report as many items within a category as possible in one minute. Oral productions were tape-recorded and transcribed for further analysis. Both error types and error frequency were calculated. Statistical analysis was further conducted to examine these error types and frequency made by CSL learners. Additionally, category effects, pictorial effects and L2 proficiency were discussed. Findings in the present study helped characterize the lexical-semantic process of Chinese naming in CSL learners of different Chinese proficiency levels and made contributions to Chinese vocabulary teaching and learning in the future.

Keywords: lexical-semantic processing, Mandarin Chinese, naming, category effects

Procedia PDF Downloads 466

Authors: Jelena Slugan, Ivica Ružić

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We are witnessing the rapid development of technologies that change the world around us. However, curriculums and teaching processes are often slow to adapt to the change; it takes time, money and expertise to implement technology in the classroom. Therefore, the University of Split, Croatia, partnered with local school Marko Marulić High School and created the project "Modern competence in modern high schools" as part of which five different curriculums for STEM areas were developed. One of the curriculums involves combining information technology with physics. The main idea was to teach students how to use different circuits and microcomputers to explore nature and physical phenomena. As a result, using electrical circuits, students are able to recreate in the classroom the phenomena that they observe every day in their environment. So far, high school students had very little opportunity to perform experiments independently, and especially, those physics experiment did not involve ICT. Therefore, this project has a great importance, because the students will finally get a chance to develop themselves in accordance to modern technologies. This paper presents some new methods of teaching physics that will help students to develop experimental skills through the study of deterministic nature of physical laws. Students will learn how to formulate hypotheses, model physical problems using the electronic circuits and evaluate their results. While doing that, they will also acquire useful problem solving skills.

Keywords: ICT in physics, curriculum, laboratory activities, STEM (science, technology, engineering, mathematics)

Procedia PDF Downloads 206

Authors: Jacky Liu

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This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

Procedia PDF Downloads 111

Authors: Jian Zheng, Yoshiyasu Takahashi, Yuichi Kobayashi, Tatsuhiro Sato

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In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.

Keywords: constraint programming, factors considered in scheduling, machine learning, scheduling system

Procedia PDF Downloads 329

Authors: Foster Chilufya

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This study sought to determine factors that affect academic performance of mature age students in Science Education at University of Zambia. It was guided by Maslow’s Hierarchy of Needs. The theory provided relationship between achievement motivation and academic performance. A descriptive research design was used. Both Qualitative and Quantitative research methods were used to collect data from 88 respondents. Simple random and purposive sampling procedures were used to collect from the respondents. Concerning factors that motivate mature-age students to choose Science Education Programs, the following were cited: need for self-actualization, acquisition of new knowledge, encouragement from friends and family members, good performance at high school and diploma level, love for the sciences, prestige and desire to be promoted at places of work. As regards factors that affected the academic performance of mature-age students, both negative and positive factors were identified. These included: demographic factors such as age and gender, psychological characteristics such as motivation and preparedness to learn, self-set goals, self esteem, ability, confidence and persistence, student prior academic performance at high school and college level, social factors, institutional factors and the outcomes of the learning process. In order to address the factors that negatively affect academic performance of mature-age students, the following measures were identified: encouraging group discussions, encouraging interactive learning process, providing a conducive learning environment, reviewing Science Education curriculum and providing adequate learning materials. Based on these factors, it is recommended that, the School of Education introduces a program in Science Education specifically for students training to be teachers of science. Additionally, introduce majors in Physics Education, Biology Education, Chemistry Education and Mathematics Education relevant to what is taught in high schools.

Keywords: academic, performance, in-service, science

Procedia PDF Downloads 314

Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

Procedia PDF Downloads 209

Authors: Preston Nabors, Nasseh Tabrizi

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Portable Document Format (PDF) files have gained significant popularity for sharing and distributing documents due to their universal compatibility. However, the widespread use of PDF files has made them attractive targets for cybercriminals, who exploit vulnerabilities to deliver malware and compromise the security of end-user systems. This paper reviews notable contributions in PDF malware detection, including static, dynamic, signature-based, and hybrid analysis. It presents a comprehensive examination of PDF malware detection techniques, focusing on the emerging threat of adversarial sampling and the need for robust defense mechanisms. The paper highlights the vulnerability of machine learning classifiers to evasion attacks. It explores adversarial sampling techniques in PDF malware detection to produce mimicry and reverse mimicry evasion attacks, which aim to bypass detection systems. Improvements for future research are identified, including accessible methods, applying adversarial sampling techniques to malicious payloads, evaluating other models, evaluating the importance of features to malware, implementing adversarial defense techniques, and conducting comprehensive examination across various scenarios. By addressing these opportunities, researchers can enhance PDF malware detection and develop more resilient defense mechanisms against adversarial attacks.

Keywords: adversarial attacks, adversarial defense, adversarial machine learning, intrusion detection, PDF malware, malware detection, malware detection evasion

Procedia PDF Downloads 45

Authors: D. Shamatov

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Becoming a teacher is a journey with significant learning experiences. Exploring teachers’ lives and experiences can provide much-needed insights into the multiple realities of teaching. Teachers’ stories through qualitative narrative studies help understand and appreciate the complexities of the socio-political, economic and practical realities facing teachers. Events and experiences, both past and present, that take place at home, school, and in the broader social sphere help to shape these teachers’ lives and careers. Researchers and educators share the responsibility of listening to these teachers’ stories and life experiences and being sensitive to their voices in order to develop effective models for teacher development. A better understanding of how teachers learn to become teachers can help teacher educators prepare more effective teacher education programs. This paper is based on qualitative research which includes individual and focus group interviews, as well as auto-biography stories of Master of Science in School Leadership students at Graduate School of Education of Nazarbayev University. Twenty five MSc students from across Kazakhstan reflected on their professional journey and wrote their professional autobiographies as teachers. Their autobiographies capture the richness of their experiences and beliefs as a teacher, but also serve as window to understand broader socio-economic and political contexts where these teachers live and work. The study also provides an understanding of the systemic and socio-economic challenges of teachers in the context of post-Soviet Kazakhstan. It helps the reader better understand how wider societal forces interact and frame the development of teachers. The paper presents the findings from these stories of MSc students and offers some practical and policy implications for teacher preparation and teacher development.

Keywords: becoming a teacher, Kazakhstan, teacher stories, teacher development

Procedia PDF Downloads 434

Authors: Fung Chiat Loo, Fung Ying Loo

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This paper discusses, suggests, and constructs a notation system to facilitate the learning and understanding of the two aspects of music and movement in a sports routine. This model serves to provide a simple and logical notation that does not require training in both music and choreography. Notation is an important medium in many art forms, particularly in music and dance, transmitting information that cannot easily be expressed using words or language. Another field that is closely associated with dance and music is sports routine, which equally requires choreography and music. However, from the perspective of music, it is common to observe many incongruencies appearing between the music used and the choreography that impede an optimal perception of the performance. The concept of the notation proceeds with a discussion and review of existing dance notations that could contribute to sports routines, along with rules and a code of points in selected sports routines. The author's involvement as an insider of numerous musical theatre productions also contributed to this study. The notation constructed includes time (tempo), significances of musical accents, direction, and phrasing, along with significances of movements (jump, punch, shape). It is believed that the level of congruence between music and movement will provide optimal visualization, and in that, the notation serves to provide adequate information on both entities for the understanding of athletes and coaches.

Keywords: notation, choreography, music learning, sports routines, congruence

Procedia PDF Downloads 90

Authors: Thomas Roche, Erica Wilson, Elizabeth Goode

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Universities across the globe are considering how to effect meaningful change in their higher education (HE) delivery in the face of increasingly diverse student cohorts and shifting student learning preferences. This paper reports on a descriptive case study of whole-of-institution curriculum reform at one regional Australian university, where more traditional 13-week semesters were replaced with a 6-week immersive block model drawing on active learning pedagogy. Based on a synthesis of literature in best practice HE pedagogy and principles, the case study draws on student performance data and senior management staff interviews (N = 5) to outline the key changes necessary for successful HE transformation to deliver increased student pass rates and retention. The findings from this case study indicate that an institutional transformation to an immersive block model requires both a considered change in institutional policy and process as well as the appropriate resourcing of roles, governance committees, technical solutions, and, importantly, communities of practice. Implications for practice at higher education institutions considering reforming their curriculum model are also discussed.

Keywords: student retention, immersive scheduling, block model, curriculum reform, active learning, higher education pedagogy, higher education policy

Procedia PDF Downloads 79

Authors: Maaly Jarrah

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In a study abroad context, students have the advantage of immersing themselves in the environment of the target language and being exposed to it. However, in and a stay home context, where English is not the mother tongue, students’ exposure to the second language is often times restricted to the classroom. Although language teachers are keen to develop inside class room activities and practices that increase the suitability of students to acquire a second language (Cook & Singleton, 2014), many would agree that class time is too limited to enhance students’ oral fluency skills. Consequently, creating opportunities outside the classroom for students to speak English is an effective strategy in compensating for students’ limited use of the L2. In an argument by Ortega (2012) external classroom activities have equal significance in enabling students learn English as a second language. The author further asserts that the activities provide a non-educational environment from which a student may feel free and comfortable to acquire new language skills. This study investigates the significance of outside classroom activities in promoting students’ oral proficiency. In addition, it reports on students’ perceptions of such activities. 15 participants from the American University of Kuwait took part in this study. Open-ended interviews were done to find out what the participants thought of these activities, and what they gained from them. Interview results show that students found outside classroom activities very effective in improving not only their oral fluency skills, but their confidence and critical thinking skills as well. The implications of this research study are for language practitioners and language programs in the EFL context to be aware of the benefits of incorporating outside classroom activities in language teaching.

Keywords: language teaching, oral fluency, outside classroom activities

Procedia PDF Downloads 462

Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

Procedia PDF Downloads 158

Authors: Antonella Poce, Deborah Seid Howes, Maria Rosaria Re, Mara Valente

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The Creative Industries education contexts, Museum Education in particular, generally presents a low emphasis on the use of new digital technologies, digital abilities and transversal skills development. The spread of the Covid-19 pandemic has underlined the importance of these abilities and skills in cultural heritage education contexts: gaining digital skills, museum professionals will improve their career opportunities with access to new distribution markets through internet access and e-commerce, new entrepreneurial tools, or adding new forms of digital expression to their work. However, the use of web, mobile, social, and analytical tools is becoming more and more essential in the Heritage field, and museums, in particular, to face the challenges posed by the current worldwide health emergency. Recent studies highlight the need for stronger partnerships between the cultural and creative sectors, social partners and education and training providers in order to provide these sectors with the combination of skills needed for creative entrepreneurship in a rapidly changing environment. Considering the above conditions, the paper presents different examples of digital learning experiences carried out in Italian and USA contexts with the aim of promoting digital skills in museum professionals. In particular, a quali-quantitative research study has been conducted on two international Postgraduate courses, “Advanced Studies in Museum Education” (2 years) and “Museum Education” (1 year), in order to identify the educational effectiveness of the online learning strategies used (e.g., OBL, Digital Storytelling, peer evaluation) for the development of digital skills and the acquisition of specific content. More than 50 museum professionals participating in the mentioned educational pathways took part in the learning activity, providing evaluation data useful for research purposes.

Keywords: digital skills, museum professionals, technology, education

Procedia PDF Downloads 180

Authors: Nimrod Bantigue

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The Department of Education is continuously providing safe teaching-learning facilities and hazard-free environments to the learners. To achieve this goal, teachers’ awareness of DepEd’s DRRM programs and activities is extremely important; thus, this descriptive correlational quantitative study was conceptualized. This research answered four questions on the profile and level of awareness of the 153 teacher respondents of Oriental Mindoro National High School for the academic year 2018-2019. Stratified proportional sampling was employed, and both descriptive and inferential statistics were utilized to treat data. The findings revealed that the majority of the teachers at OMNHS are female and are in the age bracket of 20-40. Most are married and pursue graduate studies. They have moderate awareness of the Department of Education’s DRRM programs and activities in terms of assessment of risks activities, planning activities, implementation activities during disaster and evaluation and monitoring activities with 3.32, 3.12, 3.40 and 3.31 as computed means, respectively. Further, the result showed a significant relationship between the profile of the respondents such as age, civil status and educational attainment and the level of awareness. On the contrary, sex does not have a significant relationship with the level of awareness. The Support School DRRM program with Utilization Guide on School DRRM Manual was proposed to increase, improve and strengthen the weakest areas of awareness rated in each DRRM activity, such as assessment of risks, planning, and implementation during disasters and monitoring and evaluation.

Keywords: awareness, management, monitoring, risk reduction

Procedia PDF Downloads 227

Authors: Meltem Eryılmaz

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With the emergence of the COVID-19 infection outbreak, the socio-cultural, political, economic, educational systems dynamics of the world have gone through a major change, especially in the educational field, specifically dentistry preclinical education, where the students must have a certain amount of real-time experience in endodontics and other various procedures. The totality of the digital and physical elements that make our five sense organs feel as if we really exist in a virtual world is called virtual reality. Virtual reality, which is very popular today, has started to be used in education. With the inclusion of developing technology in education and training environments, virtual learning platforms have been designed to enrich students' learning experiences. The field of health is also affected by these current developments, and the number of virtual reality applications developed for students studying dentistry is increasing day by day. The most widely used tools of this technology are virtual reality glasses. With virtual reality glasses, you can look any way you want in a world designed in 3D and navigate as you wish. With this project, solutions that will respond to different types of dental practices of students who study dentistry with virtual reality applications are produced. With this application, students who cannot find the opportunity to work with patients in distance education or who want to improve themselves at home have unlimited trial opportunities. Unity 2021, Visual Studio 2019, Cardboard SDK are used in the study.

Keywords: dentistry, intelligent tutoring system, virtual reality, online learning, COVID-19

Procedia PDF Downloads 206

Authors: Michael Amankwaa Adu

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This study investigates the speech acts employed by a Career Technology teacher during classroom interactions in a junior high school. While much research exists on speech acts in language teaching, little attention has been given to technical subjects. This has created a gap in understanding how teachers of non-language subjects utilize speech acts in classroom communication. This study aims to analyze the types and frequencies of speech acts used by a Career Technology teacher during three key classroom encounters: lesson introduction, content delivery, and classroom management. Using a mixed-methods approach, the study examines 113 utterances from the teacher's lesson, categorizing them into four primary speech act types: directives, assertives, expressives, and commissives. Directives emerged as the most dominant form, accounting for 59.3% of the utterances, followed by assertives (20.4%), expressives (14.2%), and commissives (6.2%). No declarations were observed. The study demonstrates how the teacher uses directives to manage student behavior and assertives to reinforce information. Expressives are used sparingly but play a role in motivating or disciplining students, while commissives help establish classroom rules and set expectations. The findings contribute to understanding classroom interaction strategies in non-language subjects, offering insights that could inform teacher training and curriculum development. The study underscores the importance of effective communication in technical subjects and suggests ways in which language teaching techniques might be integrated into other subject areas.

Keywords: classroom management, directives, speech acts, technical subjects., assertives

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Authors: Amit Prakash Singh, Shyamli Singh, Chavi Srivastav

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This paper presents the idea of Internet of Thing (IoT) for the infrastructure of smart cities. Internet of Thing has been visualized as a communication prototype that incorporates myriad of digital services. The various component of the smart cities shall be implemented using microprocessor, microcontroller, sensors for network communication and protocols. IoT enabled systems have been devised to support the smart city vision, of which aim is to exploit the currently available precocious communication technologies to support the value-added services for function of the city. Due to volume, variety, and velocity of data, it requires analysis using Big Data concept. This paper presented the various techniques used to analyze big data using machine learning.

Keywords: IoT, smart city, embedded systems, sustainable environment

Procedia PDF Downloads 579

Authors: Mazeni Ismail, Nurul Aliah, Hasmadi Hassan

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The purpose of this study is to gather the consensus of experts regarding the use of moral guidance amongst preschool teachers vis-a-vis the Islamic Project module (I-Project Module). This I-Project Module seeks to provide pertinent data on the assimilation of noble values in subject-matter teaching. To obtain consensus for the various components of the module, the Modified Delphi technique was used to develop the module. 12 subject experts from various educational fields of Islamic education, early childhood education, counselling and language fully participated in the development of this module. The Modified Delphi technique was administered in two mean cycles. The standard deviation value derived from questionnaires completed by the participating panel of experts provided the value of expert consensus reached. This was subsequently analyzed using SPSS version 22. Findings revealed that the panel of experts reached a discernible degree of agreement on five topics outlined in the module, viz; content (mean value 3.36), teaching strategy (mean value 3.28), programme duration (mean value 3.0), staff involved and attention-grabbing strategy of target group participating in the value program (mean value 3.5), and strategy to attract attention of target group to utilize i-project (mean value 3.0). With regard to the strategy to attract the attention of the target group, the experts proposed for creative activities to be added in order to enhance teachers’ creativity.

Keywords: Modified Delphi Technique, Islamic project, noble values, teacher moral guidance

Procedia PDF Downloads 188

Authors: Yelena Agranovich, Larissa Ageyeva, Aigul Syzdykbayeva, Violetta Tyan

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The modernization of the education system in the Republic of Kazakhstan is aimed at improving the quality of teacher training and enhancing key competencies among teachers. The current professional standard ‘Teacher’ defines the general characteristics of teachers’ activities, key competencies, and criteria according to relevant qualification categories structured on the principle of progression, thereby enabling Continuous Professional Development (CPD). The essence of CPD lies in the constant integration of new knowledge and skills that help teachers adapt to changes in the education system, in technologies, and teaching methods. This developmental process enables teachers to stay updated on recent scientific achievements, innovations, and modern pedagogical practices. Continuous learning helps teachers remain flexible and open to new developments, creating conditions for improving educational quality and fostering students' personal growth. This study aims to address the following objectives: analysis of international CPD practices, identification of conceptual foundations, and investigation of CPD implementation mechanisms in Kazakhstan. The core principles of CPD are identified as longitudinality, systematicity, and fragmentation. CPD implementation is based on various theoretical approaches: axiological, systemic, competency-based, activity-based, and learner-centered. The study analyzes leading models of teacher CPD, with a target sample that includes countries such as Australia, Japan, South Korea, England, Singapore, Sweden, Finland, and Kazakhstan. The research methods include analysis (comparative, historical, content analysis, systematic), case studies of CPD models, and synthesis and systematization of scientific data. As research results, the mechanisms for CPD implementation in Kazakhstan will be identified, along with further perspectives on transforming resources within the teacher professional development system. In comparing CPD models from various countries, it is noted that teacher CPD in the Republic of Kazakhstan: (1) is implemented through educational programs, professional development courses, teacher certification, professional networks, in-school professional development, self-education, and self-assessment; (2) includes the development of pedagogical values and competencies (tolerance, inclusivity, communication, critical thinking, creativity, reflection, etc.); (3) is carried out based on traditional forms (professional development courses, retraining) and informal forms (self-learning, self-development, experience sharing and exchange). Further research will focus on creating a digital ecosystem for teacher CPD, based on an educational platform that facilitates individualized professional development pathways for teachers (competency diagnostics, course selection, and a methodological system of course and post-course support for teachers).

Keywords: continuous professional development, CPD models, professional development, professional upgrading, teacher, teacher training

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Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

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Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

Procedia PDF Downloads 56

Authors: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

Procedia PDF Downloads 145

Authors: Rika Uchida

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In teaching sophomore level aural skills, I have dealt with students with absolute pitch do poorly in my courses, particularly in harmonic dictation. They can identify triads; however, identifying quality of seventh chords or chromatic chords poses serious challenges. Most often, they need to spell all the pitches before identifying the chord qualities and Roman Numerals. Growing up in a country where acquiring absolute pitch is considered essential, I started my early music training with fixed do system at age three and learned all my music with solfege. When I was assigned as a TA in aural skills courses at graduate school in US, I had to learn relative pitch quickly. My survival method was listening to music with absolute pitch first, then quickly "translate" to relative pitch. In teaching my courses, I have been using chord progressions (5-8 chords total), in which students are asked to sing chord arpeggiation with movable do solfege. I use same progressions for harmonic dictation; I hoped that students learn to incorporate singing and listening skills by overlapping same materials. This method has proven to be successful for most students; in particular, it has helped students with absolute pitch to hear chord quality and function. Although original progressions are written in C as a tonic, they can identify chords in harmonic dictation in other keys as well. In short, I believe singing chord progression with movable do arpeggiation helps students with absolute pitch to improve hearing function and quality of chords in harmonic dictation.

Keywords: aural skills pedagogy, music theory, absolute pitch, harmonic dictation

Procedia PDF Downloads 148

Authors: Maheshwari Payal, Shapurkar Mayaan

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The present research aimed at studying the awareness and attitudes of teachers towards inclusive education. The sample consisted of 60 teachers, teaching in the primary section (1st – 4th) of regular schools affiliated to the SSC board in Mumbai. The sample was selected by Multi-stage cluster sampling technique. A semi-structured self-constructed interview schedule and a self-constructed attitude scale were used to study the awareness of teachers about disability and Inclusive education, and their attitudes towards inclusive education respectively. Themes were extracted from the interview data and quantitative data was analyzed using SPSS package. Results revealed that teachers had some amount of awareness but an inadequate amount of information on disabilities and inclusive education. Disability to most (37) teachers meant “an inability to do something”. The difference between disability and handicap was stated by most as former being cognitive while handicap being physical in nature. With regard to Inclusive education, a large number (46) stated that they were unaware of the term and did not know what it meant. The majority (52) of them perceived maximum challenges for themselves in an inclusive set up, and emphasized on the role of teacher training courses in the area of providing knowledge (49) and training in teaching methodology (53). Although, 83.3% of teachers held a moderately positive attitude towards inclusive education, a large percentage (61.6%) of participants felt that being in inclusive set up would be very challenging for both children with special needs and without special needs. Though, most (49) of the teachers stated that children with special needs should be educated in a regular classroom, but they further clarified that only those should be in a regular classroom who have physical impairments of mild or moderate degree.

Keywords: attitude, awareness, inclusive education, teachers

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Authors: Rochelle Elva

Abstract:

Faculty in Higher Education today are faced with the challenge of convincing their students of the importance of learning and mastery of skills. This is because most students often have a single motivation -to get high grades. If it appears that this goal will not be met, they lose their motivation, and their academic efforts wane. This is true even for students in the competitive fields of STEM, including Computer Science majors. As educators, we have to understand our students and leverage what motivates them to achieve our learning outcomes. This paper presents a case study that utilizes cognitive psychology’s Expectancy Value Theory and Motivation Theory to investigate the effect of sustained expectancy for success on students’ learning outcomes. In our case study, we explore how students’ motivation and persistence in their academic efforts are impacted by providing them with an unexpected possible path to success that continues to the end of the semester. The approach was tested in an undergraduate computer science course with n = 56. The results of the study indicate that when presented with the real possibility of success, despite existing low grades, both low and high-scoring students persisted in their efforts to improve their performance. Their final grades were, on average, one place higher on the +/-letter grade scale, with some students scoring as high as three places above their predicted grade.

Keywords: expectancy for success and persistence, motivation and performance, computer science education, motivation and performance in computer science

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Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

Abstract:

A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: analogy-making, categorization, learning of categories, abstraction, hierarchical structure

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Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim

Abstract:

Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.

Keywords: building envelope, machine learning, perforated metal, multi-factor optimization, façade

Procedia PDF Downloads 227

Authors: Prakash Singh

Abstract:

Many schools throughout the world are facing constant pressure to cope with the violence and drug abuse of learners who show little or no respect for acceptable and desirable social norms. These delinquent learners tend to harbour feelings of being beyond reproach because they strongly believe that it is well within their rights to engage in violent and destructive behaviour. Knives, guns, and other weapons appear to be more readily used by them on the school premises than before. It is known that learners smoke, drink alcohol, and use drugs during school hours, hence, their ability to concentrate, work, and learn, is affected. They become violent and display disruptive behaviour in their classrooms as well as on the school premises, and this atrocious behaviour makes it possible for drug dealers and gangsters to gain access onto the school premises. The primary purpose of this exploratory quantitative study was therefore to establish how tobephobia (TBP), caused by school violence and drug abuse, affects teaching and learning in schools. The findings of this study affirmed that poor discipline resulted in producing poor quality education. Most of the teachers in this study agreed that educating learners who consumed alcohol and other drugs on the school premises resulted in them suffering from TBP. These learners are frequently abusive and disrespectful, and resort to violence to seek attention. As a result, teachers feel extremely demotivated and suffer from high levels of anxiety and stress. The word TBP will surely be regarded as a blessing by many teachers throughout the world because finally, there is a word that will make people sit up and listen to their problems that cause real fear and anxiety in schools.

Keywords: aims and objectives of quality education, debilitating effects of tobephobia, fear of failure associated with education, learners' violent behaviour and drug abuse

Procedia PDF Downloads 281

Authors: Solly M. Seeletse, Joel L. Thabane

Abstract:

Students enrolling at the Sefako Makgatho Health Sciences University (SMU) come mostly from the previously disadvantaged communities of South Africa. Their backgrounds are deprived in resources and modern technologies of education. Most of those admitted in the basic sciences were rejected in medicine and health related study programmes in SMU. Mathematics (maths) is the main subject for admission into SMU study programmes. However, maths results are usually low. In an attempt to help to prepare the students in the neighbourhood schools of SMU, some Maths educators partnered with local schools to communicate the needs and investigate the causes of poor maths results. They embarked on an action research to determine the level of educators’ maths education. The general aim of the research was to investigate the causes of deficiencies in maths teaching and results in the local secondary schools, focusing on teachers and learners. Asking the teachers about their education and learners about maths concepts of most difficulty, these were identified. The researchers assisted in teaching the difficult concepts. The study highlighted the most difficult concepts and the teachers’ lack of training in some content. Intervention of the researchers showed to be effective only for the very poor performing schools. Those with descent pass rates of over 50% did not benefit from it. This was the sign of lack of optimality in the methods used. The research recommendations suggested that intervention methods should be improved to be effective in all schools, and extension of the endeavours to more schools.

Keywords: action research, intervention, social responsibility, support

Procedia PDF Downloads 271

Authors: Lulu Liao, Huijing Chen, Yinan Zhao, Hongting Ning, Hui Feng

Abstract:

Urinary tract infection rate is an important index of care quality in nursing homes. The aim of the study is to understand the nursing assistant's current knowledge and attitudes of urinary incontinence and to explore related stakeholders' viewpoint about urinary incontinence training. This explanatory sequential study used Knowledge, Practice, and Attitude Model (KAP) and Adult Learning Theories, as the conceptual framework. The researchers collected data from 509 nursing assistants in sixteen nursing homes in Hunan province in China. The questionnaire survey was to assess the knowledge and attitude of urinary incontinence of nursing assistants. On the basis of quantitative research and combined with focus group, training demands were identified, which nurse managers should adopt to improve nursing assistants’ professional practice ability in urinary incontinence. Most nursing assistants held the poor knowledge (14.0 ± 4.18) but had positive attitudes (35.5 ± 3.19) toward urinary incontinence. There was a significant positive correlation between urinary incontinence knowledge and nursing assistants' year of work and educational level, urinary incontinence attitude, and education level (p < 0.001). Despite a general awareness of the importance of prevention of urinary tract infections, not all nurse managers fully valued the training in urinary incontinence compared with daily care training. And the nursing assistants required simple education resources to equip them with skills to address problem about urinary incontinence. The variety of learning methods also highlighted the need for educational materials, and nursing assistants had shown a strong interest in online learning. Related education material should be developed to meet the learning need of nurse assistants and provide suitable training method for planned quality improvement in urinary incontinence.

Keywords: mixed methods, nursing assistants, nursing homes, urinary incontinence

Procedia PDF Downloads 142