Search results for: college student learning experience

Authors: Mirzahmedov Ismoiljon Karimjon Ugli, Juraeva Shakhnoza Abdumalik Kizi

Abstract:

The article deals with the current scientific problems of natural geography related to the development of new pedagogical technologies and their implementation in the educational process. The use of recommended interactive methods in independent study is considered very effective and is a very useful method for students, especially for students who work more on themselves. Today's demand is to make young people talented, intelligent, innovative, as well as mature and well-rounded individuals, as a result of the work carried out in the field of education today. This is how creating tables of different contents and filling them out shows the student's talent and desire for innovation. Also, the techniques and methods necessary for today's student are shown, the role of the teacher in conducting lessons meaningfully, the suitability of the method used by the teacher for the lesson, factors affecting the quality of education, and natural issues of the use of methods based on the specific features of geography are highlighted.

Keywords: teaching methods, educational process, educational technologies, education, problem, didactics, natural geography

Procedia PDF Downloads 45

Authors: Alexander Zibenberg, Rima’a Da’As

Abstract:

According to the author’s knowledge, individuals are naturally inclined to classify people as leaders and followers. Individuals utilize cognitive structures or prototypes specifying the traits and abilities that characterize the effective leader (implicit leadership theories) and effective follower in an organization (implicit followership theories). Thus, the present study offers insights into understanding how teachers' personal values (self-enhancement and self-transcendence) explain the preference for styles of effective leader (i.e., principal) and assumptions about the traits and behaviors that characterize effective followers (i.e., student). Beyond the direct effect on perceptions of effective types of leader and follower, the present study argues that values may also interact with organizational and personal contexts in influencing perceptions. Thus authors suggest that teachers' managerial position may moderate the relationships between personal values and perception of the effective leader and follower. Specifically, two key questions are addressed in the present research: (1) Is there a relationship between personal values and perceptions of the effective leader and effective follower? and (2) Are these relationships stable or could they change across different contexts? Two hundred fifty-five Israeli teachers participated in this study, completing questionnaires – about the effective student and effective principal. Results of structural equations modeling (SEM) with maximum likelihood estimation showed: first: the model fit the data well. Second: researchers found a positive relationship between self-enhancement and anti-prototype of the effective principal and anti-prototype of the effective student. The relationship between self-transcendence value and both perceptions were found significant as well. Self-transcendence positively related to the way the teacher perceives the prototype of the effective principal and effective student. Besides, authors found that teachers' managerial position moderates these relationships. The article contributes to the literature both on perceptions and on personal values. Although several earlier studies explored issues of implicit leadership theories and implicit followership theories, personality characteristics (values) have garnered less attention in this matter. This study shows that personal values which are deeply rooted, abstract motivations that guide justify or explain attitudes, norms, opinions and actions explain differences in perception of the effective leader and follower. The results advance the theoretical understanding of the relationship between personal values and individuals’ perceptions in organizations. An additional contribution of this study is the application of the teacher's managerial position to explain a potential boundary condition of the translation of personal values into outcomes. The findings suggest that through the management process in the organization, teachers acquire knowledge and skills which augment their ability (beyond their personal values) to predict perceptions of ideal types of principal and student. The study elucidates the unique role of personal values in understanding an organizational thinking in organization. It seems that personal values might explain the differences in individual preferences of the organizational paradigm (mechanistic vs organic).

Keywords: implicit leadership theories, implicit followership theories, organizational paradigms, personal values

Procedia PDF Downloads 141

Authors: Lourdita Llanto

Abstract:

This study described and assessed the implementation of artificial insemination (AI) for cattle and carabaos in the Bicol Region, Philippines: Albay, Sorsogon and Camarines Sur. Three hundred respondents were interviewed. Results were analyzed using frequency counts, means, percentages and chi-square test. Semen samples from different stations were analyzed for motility, viability and morphology. T-test was used in semen quality evaluation. Provincial AI coordinators (PAIC) were male, averaging 59 years old, married, had college education, served in government service for 34 years, but as PAIC for 5.7 years. All had other designations. Mean AI operation was 11.33 years with annual support from the local government unit of Php76,666.67. AI technicians were males, married, with college education, and trained on AI. Problems were on mobility; inadequate knowledge of farmers in animal raising and AI; and lack of liquid nitrogen and frozen semen supply. There was 2.95 municipalities and breedable cattle/carabaos of 3,091.25 per AI technician. Mean number of artificially inseminated animals per AI technician for 2011 was 28.57 heads for carabaos and 8.64 heads for cattle. There was very low participation rate among farmers. Carabaos were 6.52 years with parity 1.53. Cattle were 5.61 years, with parity of 1.51. Semen quality significantly (p ≤ 0.05) deteriorated in normal and live sperm with storage and handling at the provincial and field stations. Breed, AI technicians practices and AI operation significantly affected conception rate. Mean conception rate was 57.62%.

Keywords: artificial insemination, carabao, parity, mother tanks, frozen semen

Procedia PDF Downloads 425

Authors: Liza Michaeli

Abstract:

Fermata, from fermare, means to be on hold, conjoining contenere (contain), fissare (fasten), and rimanere (stay). It is a musical indication that a note should be (that is, calls to be) prolonged beyond the "normal duration" the note value would indicate. To be "held up" is to be held impractically in the lunga pausa, where the breath "is to be taken," taken in, but the release is impeded. In this pause of unspecified length, life is being prolonged against your discretion but given to you to inhabit. That is why the note value, the recognized "normative value," does not "accept" the significance of the prolongation. The value is interested in "saving time." The query at the heart of "Life in the fermata" will therefore be: is this life on hold, or rather, life holding. The paper shall meditate, via musical notation, on the significance of experience "inside": namely, the hold.

Keywords: fermata, experience, significance, the hold, prolongation

Procedia PDF Downloads 157

Authors: V. Argyropoulos, M. Nikolaraizi, K. Tanou

Abstract:

There is little available information concerning the cognitive and communicative abilities of the people who are deaf-blind. This mainly stems from the general inadequacy of existing assessment instruments employed with deafblind individuals. Although considerable variability exists with regard to cognitive capacities of the deaf-blind, careful examination of the literature reveals that the majority of these persons suffer from significant deficits in cognitive and adaptive functioning. The few reports available primarily are case studies, narrative program descriptions, or position papers by workers in the field. Without the objective verification afforded by controlled research, specialists in psychology, education, and other rehabilitation services must rely on personal speculations or biases to guide their decisions in the planning, implementation, and evaluation of services to deaf-blind children and adults. This paper highlights the framework and discusses the results of an action research network. The aim of this study was twofold: a) to describe and analyse the different ways in which a student with deafblindness approached a number of developmental issues such as novel tasks, exploration and manipulation of objects, reactions to social stimuli, motor coordination, and quality of play and b) to map the appropriate functional approach for the specific student that could be used to develop strategies for classroom participation and socialization. The persons involved in this collaborative action research scheme were general teachers, a school counsellor, academic staff and student teachers. Rating scales and checklists were used to gather information in natural activities and settings, and additional data were also obtained through interviews with the educators of the student. The findings of this case study indicated that there is a great need to focus on the development of effective intervention strategies. The results showed that the identification of positive reinforcers for this population might represent an important and challenging aspect of behaviour programmes. Finally, the findings suggest that additional empirical work is needed to increase attention to methodological and social validity issues.

Keywords: action research, cognitive and communicative abilities, deafblindness, effective strategies

Procedia PDF Downloads 169

Authors: Atma Sahu

Abstract:

After 9/11, there will only be cyberwars. The cyberwars increase in intensity the country's cybersecurity workforce's hiring and retention issues. Currently, many organizations have unfilled cybersecurity positions, and to a lesser degree, their cybersecurity teams are understaffed. Therefore, there is a critical need to develop a new program to help meet the market demand for cybersecurity engineers (CYSE) and personnel. Coppin State University in the United States was responsible for developing a cybersecurity engineering BS degree program. The CYSE curriculum design methodology consisted of three parts. First, the ACM Cross-Cutting Concepts standard's pervasive framework helped curriculum designers and students explore connections among the core courses' knowledge areas and reinforce the security mindset conveyed in them. Second, the core course context was created to assist students in resolving security issues in authentic cyber situations involving cyber security systems in various aspects of industrial work while adhering to the NIST standards framework. The last part of the CYSE curriculum design aspect was the institutional student learning outcomes (SLOs) integrated and aligned in content courses, representing more detailed outcomes and emphasizing what learners can do over merely what they know. The CYSE program's core courses express competencies and learning outcomes using action verbs from Bloom's Revised Taxonomy. This aspect of the CYSE BS degree program's design is based on these three pillars: the ACM, NIST, and SLO standards, which all CYSE curriculum designers should know. This unique CYSE curriculum design methodology will address how students and the CYSE program will be assessed and evaluated. It is also critical that educators, program managers, and students understand the importance of staying current in this fast-paced CYSE field.

Keywords: cyber security, cybersecurity engineering, systems engineering, NIST standards, physical systems

Procedia PDF Downloads 65

Authors: Fuad M. Alkoot

Abstract:

We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

Procedia PDF Downloads 261

Authors: Raimi, Kehinde Olawuyi, Omoare Ayodeji Motunrayo

Abstract:

In the last two decades, there has been rising youth unemployment, restiveness, and social vices in Nigeria. The relevance of Vocational Education for skills acquisition, global learning, and national development to address these problems cannot be underestimated. Thus, the need to economically empower Nigerian youths to be able to develop the nation and meet up in the ever-changing global learning and economy led to the assessment of Vocational Education as Synergy for the Skills Acquisition and Global Learning in Ogun State, Nigeria. One hundred and twenty out of 1,500 students were randomly selected for this study. Data were obtained through a questionnaire and were analyzed with descriptive statistics and Chi-square. The results of the study showed that 59.2% of the respondents were between 20 – 24 years of age, 60.8% were male, and 65.8% had a keen interest in Vocational Education. Also, 90% of the respondents acquired skills in extension/advisory, 78.3% acquired skills in poultry production, and 69.1% acquired skills in fisheries/aquaculture. The major constraints to Vocational Education are inadequate resource personnel (χ² = 10.25, p = 0.02), inadequate training facilities (x̅ = 2.46) and unstable power supply (x̅ = 2.38). Results of Chi-square showed significance association between constraints and Skills Acquisition (χ² = 12.54, p = 0.00) at p < 0.05 level of significance. It was established that Vocational Education significantly contributed to students’ skills acquisition and global learning. This study, therefore, recommends that inadequate personnel should be looked into by the school authority in order not to over-stretch the available staff of the institution while the provision of alternative stable power supply (solar power) is also essential for effective teaching and learning process.

Keywords: vocational education, skills acquisition, national development, global learning

Procedia PDF Downloads 110

Authors: Nima Mahmoudi, Hamzeh Khazaei

Abstract:

Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

Procedia PDF Downloads 155

Authors: Meduranda Marco

Abstract:

This paper aimed to discuss the Integrative Assessment (IA) initiative of the Schools Division Office - Navotas City. The introduction provided a brief landscape analysis of the current state of education, the context of SDO Navotas, and the rationale for the administration of Integrative Assessment (IA) in schools. The IA methodology, procedure, and implementation activities were also shared. Feedback and reports on IA showed positive results as all schools in the Division were able to operationalize IA and consequently foster academic ease for learners and parents. Challenges met after compliance were also documented and strategies to continuously improve the Integrative Assessment process were proposed.

Keywords: distance learning assessment, integrative assessment, academic ease, learning outcomes evaluation

Procedia PDF Downloads 123

Authors: Abdullahi Bn Umar

Abstract:

Over the years curriculum planners and researchers in education have continued to seek for ways to improve teaching and learning by way of varying approaches to curriculum and instruction in line with dynamic nature of knowledge. In this regards various innovative strategies to teaching and learning have been adopted to match with the technological advancement in education particularly in the aspect of instructional delivery through Information Communication Technology (ICT) as a tools. This paper reviews some innovative strategies and how they impact on learner’s achievement and educational development in Nigeria. The paper concludes by recommending innovative approach appropriate for use in Nigerian context.

Keywords: innovation, instructional delivery, virtual laboratory, educational design

Procedia PDF Downloads 458

Authors: Hamad Albadr

Abstract:

With a rapid influence to sustain the needs for global trends that had arisen for the increasing complexities in health-care provision, the increasing number of health professionals at different levels, and the need to assure more equitable access to health care, the great variation in the levels of initial education for health care professional around the world had been assign bachelor's degree as the minimum point of entry to the health professions. This intent had affected all the health care professions including biomedical engineering. In Saudi Arabia, these challenges add more pressure to retain the global trends for associate degree graduates to upgrade their education to the bachelor's degree or called birding. This paper is to review the reality of biomedical technology programs that offered in Saudi Arabia by Technical Colleges or Community Colleges nationwide and the challenges that face these colleges to run such bridging program to achieve the Bachelor's degree in biomedical engineering and the official requirements by the Ministry of Higher Education and to maintain the international standards. The author will use strategic planning methodology for designing the biomedical engineering bridging of bachelor's program by reviewing the responsibilities of the biomedical engineers in hospitals through their job descriptions to determine the job assessment needs in advance to Developing a Curriculum (DACUM) through Instructional System Design (ISD) approach via five steps: Analysis, Design, Development, Implement, Evaluate (ADDIE).

Keywords: bachelor's degree bridging, biomedical engineering program, Saudi Arabia, Riyadh College of Technology

Procedia PDF Downloads 468

Authors: Abdullah Abu-Tineh, Hissa Sadiq, Fatma Al-Mutawah, Youmen Chabaan

Abstract:

The current study examined the experiences of educators in Qatar with the licensure process currently implemented at government schools. Using a survey study design, a total of 1,669 participants expressed their perceptions on the strengths and weaknesses of the licensure system, the professional standards, and the professional portfolio. Findings included participants’ beliefs on the importance of the licensure system in improving their performance, the necessity of using the professional standards as tools for professional growth and development, the importance of refining the professional portfolio for authenticity and reliability, and the inclusion of multiple sources of evidence, such as classroom observations, interviews, student learning outcomes, and surveys. Documenting teachers’ and school leaders’ voices was fundamental in finding ways to successfully drive future developments of the licensure system. The findings may also provide implications for other countries interested in developing or refining their own appraisal systems.

Keywords: licensure system, educator voice, professional standards, professional portfolio

Procedia PDF Downloads 178

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 116

Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

Abstract:

Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

Procedia PDF Downloads 215

Authors: Bahia Braktia, Ana Marcela Montenegro Sanchez

Abstract:

Social media, such as Facebook, Twitter, and YouTube, has been used for teaching and learning for quite some time. These platforms have been proven to be a good tool to improve various language skills, students’ performance of the English language, motivation as well as trigger the authentic language interaction. However, little is known about the potential effects of social media usage on the learning performance of Arabic language learners. The present study explores the potential role that the social media technologies play in learning Arabic as a foreign language at a university in Southeast of United States. In order to investigate this issue, an online survey was administered to examine the perceptions and attitudes of American students learning Arabic. The research questions were: How does social media, specifically Facebook and Twitter, impact the students' Arabic language skills, and what is their attitude toward it? The preliminary findings of the study showed that students had a positive attitude toward the use of social media to enhance their Arabic language skills, and that they used a range of social media features to expose themselves to the Arabic language and communicate in Arabic with native Arabic speaking friends. More detailed findings will be shared in the light data analysis with the audience during the presentation.

Keywords: foreign language learning, social media, students’ perceptions, survey

Procedia PDF Downloads 198

Authors: Muhammad Shahid Shah, Akram Maqbool, Samina Ashraf

Abstract:

Since start of this century, world has adopted inclusion as a trend in special education. To meet the challenges of inclusion response, the Punjab government has developed a progressive policy to implement inclusive education. The objectives of this research were to analyze the administration and implementation process by consideration on the management, student’s admission process, screening and assessment, adaptations in curriculum and instruction along with an evaluation, government and nonprofit organizations support. The sample consisted of 50 schools both public and private with a total of 3000 students, 9 percent of which (270) were students with disabilities. Among all the students with disabilities, 63 percent (170) were male and 37 percent (100) were female. The concluded remarks regarding management revealed that a large number of inclusive schools was lacking in terms of developing a certain model for inclusion, including the managerial breakup of staff, the involvement of stakeholders, and conducted frequent meetings. Many of schools are not able to restructure their school organizations due to lack of financial resources, consultations, and backup. As for as student’s admission/identification/assessment was concerned, only 12 percent schools applied a selection process regarding student admission, half of which used different procedures for disable candidates. Approximately 5 percent of inclusive schools had modified their curriculum, including a variety of standards. In terms of instruction, 25 percent of inclusive schools reported that they modified their instructional process. Only a few schools, however, provided special equipment for students with visual impairment, physical impairment, speech and hearing problems, students with mild intellectual disabilities, and autism. In a student evaluation, more than 45 percent reported that test items, administration, time allocations, and students’ reports were modified. For the primary board examination conducted by the Education Department of Government of Punjab, this number decreased dramatically. Finally, government and nonprofit organizations support in the forms of funding, coaching, and facilities were mostly provided by provincial governments and by Ghazali Education Trust.

Keywords: inclusion, identification, assessment, funding, facilities, evaluation

Procedia PDF Downloads 119

Authors: Robert John Godby

Abstract:

To be responsive now and in the future, workplaces must address the demands of multicultural teams as they become more common elements of the global labor force. This is especially the case for aged care due to the aging population, industry growth and migrant recruitment. This research identifies influences on and improvements for learning in these environments. Its unique contribution is to illuminate how culturally diverse workplaces can work and learn together more effectively. A mixed-methods approach was used to gather data about this topic in two phases. Firstly, the research methods included a survey of 102 aged care workers around Australia from two multi-site aged care organisations. The questionnaire elicited both quantitative and qualitative data about worker characteristics and perspectives on working and learning in aged care. Secondly, a case study of one aged care worksite was formulated drawing on worksite information and interviews with workers. A review of the literature suggests that learning in multicultural work environments is influenced by three main factors: 1) the individual workers themselves, 2) their interaction with each other and 3) the environment in which they work. There are various accounts of these three factors, how they are manifested and how they lead to a change in workers’ disposition, knowledge, or expertise when confronted with new circumstances. The study has found that a key individual factor influencing learning is cultural background. Their unique view of the world was shown to affect their approach to both their work and co-working. Interactional factors suggest that the high requirement for collaboration in aged care positively supports learning in this context; however, it can be hindered by cultural bias and spoken accent. The study also found that environmental factors, such as disruptions caused by the pandemic, were another key influence. For example, the need to wear face masks hindered the communication needed for workplace learning. This was especially challenging due to the diverse language backgrounds and abilities within the teams. Potential improvements for learning in multicultural aged care work environments were identified. These include more frequent and structured inter-peer learning (e.g. buddying), communication training (e.g. English language usage for both native and non-native speaking workers) and support for cross-cultural habitude (e.g. recognizing and adapting to cultural differences). Workplace learning in cross-cultural aged care environments is an area that is not extensively dealt with in the literature. This study addresses this gap and holds the potential to contribute practical insights to aged care and other diverse industries.

Keywords: cross-cultural learning, learning in aged care, migrant learning, workplace learning

Procedia PDF Downloads 138

Authors: C.W. Kan

Abstract:

Softening applied on textile products based on several reasons. First, the synthetic detergent removes natural oils and waxes, thus lose the softness. Second, compensate the harsh handle of resin finishing. Also, imitate natural fibres and improve the comfort of fabric are the reasons to apply softening. There are different types of softeners for softening finishing of textiles, nonionic softener, anionic softener, cationic softener and silicone softener. The aim of this study is to illustrate the proper application of different softeners and their final softening effect in textiles. The results could also 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, softening, textiles, effect

Procedia PDF Downloads 200

Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

Abstract:

We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

Procedia PDF Downloads 55

Authors: Maiya Smith, Tyler Thorne

Abstract:

Background: The Pacific faces multiple healthcare crises, including high rates of noncommunicable diseases, infectious disease outbreaks, and susceptibility to natural disasters. These issues are expected to worsen in the coming decades, increasing the burden on an already understaffed healthcare system. Telehealth is not new to the Pacific, but improvements in technology and accessibility have increased its utility and have already proven to reduce costs and increase access to care in remote areas. Telehealth includes distance learning; a form of education that can help alleviate many healthcare issues by providing continuing education to healthcare professionals and upskilling staff, while decreasing costs. This study examined distance learning programs at the Ministry of Health in the Pacific nation of Palau and identified key elements to their successful distance learning programs. Methods: Staff at the Belau National Hospital in Koror, Palau as well as private practitioners were interviewed to assess distance learning programs utilized. This included physicians, IT personnel, public health members, and department managers of allied health. In total, 36 people were interviewed. Standardized questions and surveys were conducted in person throughout the month of July 2019. Results: Two examples of successful distance learning programs were identified. Looking at the factors that made these programs successful, as well as consulting with staff who undertook other distance learning programs, four factors for success were determined: having a cohort, having a facilitator, dedicated study time off from work, and motivation. Discussion: In countries as geographically isolated as the Pacific, with poor access to specialists and resources, telehealth has the potential to radically change how healthcare is delivered. Palau shares similar resources and issues as other countries in the Pacific and the lessons learned from their successful programs can be adapted to help other Pacific nations develop their own distance learning programs.

Keywords: distance learning, Pacific, Palau, telehealth

Procedia PDF Downloads 122

Authors: Slava Kalyuga

Abstract:

There are two opposing major points of view on the optimal degree of initial instructional guidance that is usually discussed in the literature by the advocates of the corresponding learning approaches. Using unguided or minimally guided problem-solving tasks prior to explicit instruction has been suggested by productive failure and several other instructional theories, whereas an alternative approach - using fully guided worked examples followed by problem solving - has been demonstrated as the most effective strategy within the framework of cognitive load theory. An integrated approach discussed in this paper could combine the above frameworks within a broader theoretical perspective which would allow bringing together their best features and advantages in the design of learning tasks for STEM education. This paper represents a systematic review of the available empirical studies comparing the above alternative sequences of instructional methods to explore effects of several possible moderating factors. The paper concludes that different approaches and instructional sequences should coexist within complex learning environments. Selecting optimal sequences depends on such factors as specific goals of learner activities, types of knowledge to learn, levels of element interactivity (task complexity), and levels of learner prior knowledge. This paper offers an outline of a theoretical framework for the design of complex learning tasks in STEM education that would integrate explicit instruction and inquiry (exploratory, discovery) learning approaches in ways that depend on a set of defined specific factors.

Keywords: cognitive load, explicit instruction, exploratory learning, worked examples

Procedia PDF Downloads 104

Authors: Jonathan Frank, Michelle Salmona

Abstract:

We conducted quantitative and qualitative analyses of nurses’ perceived ease of use of electronic medical records and telemedicine in the Cook Islands. We examined antecedents of perceived ease of use through the lens of social construction of learning, and cultural diffusion. Our findings confirmed expected linkages between PEOU, attitudes and intentions. Interviews with nurses suggested infrastructural barriers to engaged learning. We discussed managerial implications of our findings, and areas of interest for future research.

Keywords: health information technology, ICT4D, TAM, developing countries

Procedia PDF Downloads 265

Authors: Fiseha M. Guangul, Annissa Muhammed, Aja O. Chikere

Abstract:

Group task is one method to create the conducive environment for the active teaching-learning process. Performing group task with active involvement of students will benefit the students in many ways. However, in most cases all students do not participate actively in the group task, and hence the intended benefits are not acquired. This paper presents the improvements of students’ participation in the group task and learning from the group task by introducing different techniques to enhance students’ participation. For the purpose of this research Carpentry and Joinery II (WT-392) course from Wood Technology Department at Adama Science and Technology University was selected, and five groups were formed. Ten group tasks were prepared and the first five group tasks were distributed to the five groups in the first day without introducing the techniques that are used to enhance participation of students in the group task. On another day, the other five group tasks were distributed to the same groups and various techniques were introduced to enhance students’ participation in the group task. The improvements of students’ learning from the group task after the implementation of the techniques. After implementing the techniques the evaluation showed that significant improvements were obtained in the students’ participation and learning from the group task.

Keywords: group task, students participation, active learning, the evaluation method

Procedia PDF Downloads 198

Authors: Nasser Mansour, Ziad Said, Abdullah Abu-Tineh

Abstract:

STEM teachers face the challenge of possessing expertise not only in their subject disciplines but also in the pedagogical knowledge required for integrated STEM lessons. However, research reveals a lack of pedagogical competencies related to project-based learning (PBL) in the STEM context. To bridge this gap, the study examines teachers' competencies and self-efficacy in TPACK (Technological Pedagogical Content Knowledge) and its specific integration with PBL and STEM content. Data from 245 specialized science and math teachers were collected using a questionnaire. The study emphasizes the importance of addressing gender disparities, supporting formal teacher education, and recognizing the expertise and experiences of STEM teachers in effective technology integration. The findings indicate that gender plays a role in self-efficacy beliefs, with females exhibiting higher confidence in pedagogical knowledge and males demonstrating higher confidence in technological knowledge. Teaching experience and workload factors have a limited impact on teachers' Technological Pedagogical Content Knowledge (TPACK). These findings enhance our understanding of contextual factors impacting science and math teachers' self-efficacy in utilizing TPACK for STEM and PBL. They inform the development of targeted interventions, professional development programs, and support systems to enhance teachers' competencies and self-efficacy in TPACK for teaching science and Mathematics through STEM and PBL.

Keywords: technological pedagogical content knowledge, TPACK, STEM, project-based learning, PBL, self-efficacy, mathematics, science

Procedia PDF Downloads 46

Authors: Beulah Rani Inbanathan

Abstract:

In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

Procedia PDF Downloads 70

Authors: Paul Koffitse Agobia

Abstract:

In 2020 the Ministry of Education in Ghana and the National Council for Curriculum and Assessment (NaCCA) rolled out a new curriculum, Common Core Programme (CCP) for Basic 7 to 10, that lays emphasis on character building and values which are important to the Ghanaian society by providing education that will produce character–minded learners, with problem solving skills, who can play active roles in dealing with the increasing challenges facing Ghana and the global society. Therefore, learning and teaching approaches that prioritise the use of digital learning resources and active learning are recommended. The new challenge facing Ghanaian teachers is the ability to use new technologies together with the appropriate content pedagogical knowledge to help learners develop, aside the communication skills in French, the essential 21st century skills as recommended in the new curriculum. This article focusses on the pedagogical approaches that are recommended by NaCCA. The study seeks to examine French language teachers’ understanding of the recommended pedagogical approaches and how they use digital learning resources in class to foster the development of these essential skills and values. 54 respondents, comprised 30 teachers and 24 head teachers, were selected in 6 Junior High schools in rural districts (both private and public) and 6 from Junior High schools in an urban setting. The schools were selected in three regions: Volta, Central and Western regions. A class observation checklist and an interview guide were used to collect data for the study. The study reveals that some teachers adopt teaching techniques that do not promote active learning. They demonstrate little understanding of the core competences and values, therefore, fail to integrate them in their lessons. However, some other teachers, despite their lack of understanding of learning and teaching philosophies, adopted techniques that can help learners develop some of the core competences and values. In most schools, digital learning resources are not utilized, though teachers have smartphones or laptops.

Keywords: active learning, core competences, digital learning resources, pedagogical approach, values.

Procedia PDF Downloads 55

Authors: Golnush Masghati-Amoli, Paul Chin

Abstract:

Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

Procedia PDF Downloads 117

Authors: Yi-Cheng Tian, Miin-Shen Yang

Abstract:

The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

Procedia PDF Downloads 490

Authors: V. Howard, R. Maguire, S. Corrigan

Abstract:

Background: Type 1 Diabetes (T1D) is a chronic autoimmune disease, typically diagnosed in childhood. T1D puts an enormous strain on families; controlling blood-glucose in children is difficult and the consequences of poor control for patient health are significant. Successful illness management and better health outcomes can be dependent on quality of caregiving. On diagnosis, parent-caregivers face a steep learning curve as T1D care requires a significant level of knowledge to inform complex decision making throughout the day. The majority of illness management is carried out in the home setting, independent of clinical health providers. Parent-caregivers vary in their level of knowledge and their level of engagement in applying this knowledge in the practice of illness management. Enabling researchers to quantify these aspects of the caregiver experience is key to identifying targets for psychosocial support interventions, which are desirable for reducing stress and anxiety in this highly burdened cohort, and supporting better health outcomes in children. Currently, there are limited tools available that are designed to capture this information. Where tools do exist, they are not comprehensive and do not adequately capture the lived experience. Objectives: Development of quantitative tools, informed by lived experience, to enable researchers gather data on parent-caregiver knowledge and engagement, which accurately represents the experience/cohort and enables exploration of questions that are of real-world value to the cohort themselves. Methods: This research employed an engaged approach to address the problem of quantifying two key aspects of caregiver diabetes management: Knowledge and engagement. The research process was multi-staged and iterative. Stage 1: Working from a constructivist standpoint, literature was reviewed to identify relevant questionnaires, scales and single-item measures of T1D caregiver knowledge and engagement, and harvest candidate questionnaire items. Stage 2: Aggregated findings from the review were circulated among a PPI (patient and public involvement) expert panel of caregivers (n=6), for discussion and feedback. Stage 3: In collaboration with the expert panel, data were interpreted through the lens of lived experience to create a long-list of candidate items for novel questionnaires. Items were categorized as either ‘knowledge’ or ‘engagement’. Stage 4: A Delphi-method process (iterative surveys) was used to prioritize question items and generate novel questions that further captured the lived experience. Stage 5: Both questionnaires were piloted to refine wording of text to increase accessibility and limit socially desirable responding. Stage 6: Tools were piloted using an online survey that was deployed using an online peer-support group for caregivers for Juveniles with T1D. Ongoing Research: 123 parent-caregivers completed the survey. Data analysis is ongoing to establish face and content validity qualitatively and through exploratory factor analysis. Reliability will be established using an alternative-form method and Cronbach’s alpha will assess internal consistency. Work will be completed by early 2024. Conclusion: These tools will enable researchers to gain deeper insights into caregiving practices among parents of juveniles with T1D. Development was driven by lived experience, illustrating the value of engaged research at all levels of the research process.

Keywords: caregiving, engaged research, juvenile type 1 diabetes, quantified engagement and knowledge

Procedia PDF Downloads 39