Search results for: professional learning communities (PLCs)

Authors: Joan Esper Kuhnly, Jess Holden, Lynn Shelley, Nicole Kuhnly

Abstract:

Empathy serves as a foundational nursing principle inherent in the nurse’s ability to form those relationships from which to care for patients. Evidence supports, including empathy in nursing and healthcare education, but there is limited data on what methods are effective to do so. Building evidence supports experiential and interactive learning methods to be effective for students to gain insight and perspective from a personalized experience. The purpose of this project is to evaluate learning activities designed to promote the attainment of empathic behaviors across 5 levels of the nursing curriculum. Quantitative analysis will be conducted on data from pre and post-learning activities using the Toronto Empathy Questionnaire. The main hypothesis, that simulation learning activities will increase empathy, will be examined using a repeated measures Analysis of Variance (ANOVA) on Pre and Post Toronto Empathy Questionnaire scores for three simulation activities (Stroke, Poverty, Dementia). Pearson product-moment correlations will be conducted to examine the relationships between continuous demographic variables, such as age, credits earned, and years practicing, with the dependent variable of interest, Post Test Toronto Empathy Scores. Krippendorff’s method of content analysis will be conducted to identify the quantitative incidence of empathic responses. The researchers will use Colaizzi’s descriptive phenomenological method to describe the students’ simulation experience and understand its impact on caring and empathy behaviors employing bracketing to maintain objectivity. The results will be presented, answering multiple research questions. The discussion will be relevant to results and educational pedagogy in the nursing curriculum as they relate to the attainment of empathic behaviors.

Keywords: curriculum, empathy, nursing, simulation

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Authors: Lakshmi Shenoy

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In today’s era of Globalization, arises the need that students and professionals relocate temporarily or permanently to another country in order to pursue their respective academic and career goals. This involves not only learning the local language of the country but also integrating oneself into the native culture. This paper explains the method of understanding a nation’s culture through the study of its language. The method uses language not as a series of rules that connect words together but as a social practice in which one can actively participate. It emphasizes on how culture provides an environment in which languages can flourish and how culture dictates the interpretation of the language especially in case of German. This paper introduces language and culture as inseparable entities, as two sides of the same coin.

Keywords: language and culture, sociolinguistics, Ronald Wardhaugh, German

Procedia PDF Downloads 310

Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

Procedia PDF Downloads 100

Authors: Anna Keuchenius

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Broadly speaking, scientific development is studied in either a qualitative manner with a focus on the behavior and interpretations of academics, such as the sociology of science and science studies or in a quantitative manner with a focus on the analysis of publications, such as scientometrics and bibliometrics. Both come with a different set of methodologies and few cross-references. This paper contributes to the bridging of this divide, by on the on hand approaching the process of scientific progress from a qualitative sociological angle and using on the other hand quantitative and computational techniques. As a case study, we analyze the diffusion of Granovetter's hypothesis from his 1973 paper 'On The Strength of Weak Ties.' A network is constructed of all scientists that have referenced this particular paper, with directed edges to all other researchers that are concurrently referenced with Granovetter's 1973 paper. Studying the structure and growth of this network over time, it is found that Granovetter's hypothesis is used by distinct communities of scientists, each with their own key-narrative into which the hypothesis is fit. The diffusion within the communities shares similarities with the diffusion of an innovation in which innovators, early adopters, and an early-late majority can clearly be distinguished. Furthermore, the network structure shows that each community is clustered around one or few hub scientists that are disproportionately often referenced and seem largely responsible for carrying the hypothesis into their scientific subfield. The larger implication of this case study is that the diffusion of scientific hypotheses and ideas are not the spreading of well-defined objects over a network. Rather, the diffusion is a process in which the object itself dynamically changes in concurrence with its spread. Therefore it is argued that the methodology presented in this paper has potential beyond the scientific domain, in the study of diffusion of other not well-defined objects, such as opinions, behavior, and ideas.

Keywords: diffusion of innovations, network analysis, scientific development, sociology of science

Procedia PDF Downloads 309

Authors: Sakapas Saengchai, Wilasinee Jintalikitdee, Matinee Kongsatit, Natapol Puaprasert

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The study on promotion of public participation in community planning is a qualitative research. The data collection tools included participating observation, in-depth interview and focus group of executives of sub-district administrative organizations, sub-district headmen, community leaders of 5 villages, including civil society forums for exchanging ideas of village members. The study results revealed that key promotions of public participation in community planning were as follows: 1) Perception on public authorities’ information: Public relations should be set and information on community planning, key principles of local people participation should be prepared. Collaboration with community leaders in each village via sub-district administrative organizations should be established. 2) Discussion: In civil society forums, village members should brainstorm their opinions towards community development, village development, quality of life, current situation and problems to be revolved. 3) Participation: Members of each village should jointly participate, with community leaders, in setting sub-district development policies and community development projects. 4) Collaboration: To achieve goals, communities of each member should participate in project implementation and activities of community plans. 5) People power promotion: In each stage of communication planning, community leaders, village committees, local people should jointly set directions of village development and make decisions. This will enhance their joint learning and create community driving power. Community will become strong leading to sustainable self-reliance.

Keywords: people participation, community plans, community development, community driving power

Procedia PDF Downloads 373

Authors: Gebreegziabher Hailu Gebrecherkos

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This study examines the effectiveness of GeoGebra in developing the conceptual understanding of transformation geometry among Grade 11 students. Utilizing a quasi-experimental design, the research compares the learning outcomes of students who engaged with GeoGebra against those who received traditional instruction. Pre- and post-tests were administered to assess students' grasp of key transformation concepts, including translations, rotations, reflections, and dilations. Additionally, qualitative data were gathered through student interviews and classroom observations to explore their experiences and perceptions of using GeoGebra. Results indicate that students utilizing GeoGebra showed significantly greater improvement in their understanding of transformation geometry concepts. The interactive features of GeoGebra facilitated visualization and exploration, leading to enhanced engagement and deeper conceptual insights. The findings underscore the potential of GeoGebra as a powerful educational tool that not only fosters mathematical understanding but also accommodates diverse learning styles in the classroom. This study contributes valuable insights for educators seeking to improve the teaching and learning of transformation geometry in secondary education.

Keywords: calculus, conceptual understanding, GeoGebra, transformation geometry

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Authors: Sharon Sibanda, Benny Motileng

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The World Health Organisation (WHO) identified the Sars-Cov-2 (COVID-19) as a pandemic on the 12ᵗʰ of March 2020, with South Africa recording its first case on the 5ᵗʰ of March 2020. The rapidly spreading virus led the South African government to implement one of the strictest nationwide lockdowns globally, resulting in the closing down of all institutions of higher learning effective March 18ᵗʰ 2020. Thus, this qualitative study primarily aimed to explore whether post-graduate psychology students were in a state of a depleted or cohesive self, post the psychological isolation of COVID-19 risk-adjusted level 5 lockdown. Semi-structured interviews from a qualitative interpretive approach comprising N=6 psychology post-graduate students facilitated a rich understanding of their intra-psychic experiences of the self. Thematic analysis of data gathered from the interviews illuminated how students were forced into the self by the emotional isolation of hard lockdown, with the emergence of core psychic conflict often defended against through external self-object experiences. The findings also suggest that lockdown stripped off this sample of psychology post-graduate students’ defensive escape from the inner self through external self-object distractions. The external self was stripped to the core of the internal self by the isolation of hard lockdown, thereby uncovering the psychic function of roles and defenses amalgamated throughout modern cultural consciousness that dictates self-functioning. The study suggests modelling reflexivity skills in the integration of internal and external self-experience dynamics as part of a training model for continued personal and professional development for psychology students.

Keywords: COVID-19, fragmentation, self-object experience, true/false self

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Authors: Ayomide Oyedele

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In the dynamic landscape of cybersecurity, "Strategic Cyber Sentinel" emerges as a revolutionary framework, transcending traditional approaches. This paper pioneers a holistic strategy, weaving together threat intelligence, machine learning, and adaptive defenses. Through meticulous real-world simulations, we demonstrate the unprecedented resilience of our framework against evolving cyber threats. "Strategic Cyber Sentinel" redefines proactive threat mitigation, offering a robust defense architecture poised for the challenges of tomorrow.

Keywords: cybersecurity, resilience, threat intelligence, machine learning, adaptive defenses

Procedia PDF Downloads 87

Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Olga Guseynova

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Being an individual activity, the memorizing process is affected to a greater degree by the individual variables; therefore, one of the decisive factors influencing the memorization is students’ individual characteristics. Based on an extensive literature study in the domains of piano education, psychology, and neuroscience, this comprehensive research was designed in order to develop three memorizing strategies that are reflective of individual students’ learning modalities (visual, kinesthetic and auditory) applied to the piano education. The design of the study required an interdisciplinary approach which incorporated the outcome of neuropsychological and pedagogic experiments. The objectives were to determine the interaction between the process of perception and the process of memorizing music; to systematize the methods of memorizing piano sheet music in accordance with the specifics of perception types; to develop Piano Memorization Inventory (PMI) and the Three Memorizing Strategies (TMS). The following research methods were applied: a method of interdisciplinary analysis and synthesis, a method of non-participant observation. As a result of literature analysis, the following conclusions were made: the majority of piano teachers and piano students participated in the surveys, had not used and usually had not known any memorizing strategy regarding learning styles. As a result, they had used drilling as the main strategy of memorizing. The Piano Memorization Inventory and Three Memorizing Strategies developed by the author of the research were based on the observation and findings of the previous researches and considered the experience of pedagogical and neuropsychological studies.

Keywords: interdisciplinary approach, memorizing strategies, perceptual learning styles, piano memorization inventory

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Authors: Prakash Singh, Piet Maphodisa Kgohlo

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Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

Procedia PDF Downloads 281

Authors: Ali Aghahosseini Dehaghani

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Every year in this globalized world, thousands of migrants leave their countries hoping to find a better situation of life in other parts of the world. In this regard, many questions, from a human rights point of view, have been raised about how this phenomenon should be managed in the host countries. Although legal approaches such as legislation and litigation are inevitable in the way to respect the human rights of migrants, there is an increasing consensus about the fact that a strict juridical approach is inadequate to protect as well as to prevent violations of migrants’ rights. Indeed, given the multiplicity of factors that affect and shape the application of these rights and considering the fact that law is a social phenomenon, what is needed is an interdisciplinary approach, which combines both juridical approaches and perspectives from other disciplines. In this respect, a sociological approach is important because it shows the social processes through which human rights of migrants have been constructed or violated in particular social situations. Sociologists who study international migration ask the questions such as how many people migrate, who migrates, why people migrate, what happens to them once they arrive in the host country, how migration affects sending and receiving communities, the extent to which migrants help the economy, the effects of migration on crimes, and how migrants change the local communities. This paper is an attempt to show how sociology can promote human rights of migrants. To this end, the article first explores the usefulness and value of an interdisciplinary approach to realize how and to what extent sociology may improve and promote the human rights of migrants in the destination country. It then examines mechanisms which help to reach to a systematic integration of law and sociological discipline to advance migrants’ rights as well as to encourage legal scholars to consider the implications of societal structures in their works.

Keywords: human rights, migrants, sociological approach, interdisciplinary study

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Authors: Nuttha Kirdsinsap, Watchaneeporn Setthasakko

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This paper aims to gain opinions and perspectives of Certified Public Accountants (CPA) in Thailand regarding the driven force of Integrated Reporting. It employs in-depth interviews with CPA from different big 4 audits firms in Thailand, including PWC, Ernst and Young, Deloitte, and KPMG. It is found that the driven force of Integrated Reporting made CPA in Thailand awaken to the big change that is coming in the future, and it is said to be another big learning and integrating period between certified public accountants and other professionals (for example, engineers, environmentalists and lawyers), which, certified public accountants in Thailand will have to push themselves so hard to catch up.

Keywords: integrated reporting, learning, knowledge, certified public accountants, Thailand

Procedia PDF Downloads 276

Authors: Mohd Afif Md Nasir, Faizal Amin Nur Yunus, Jamaluddin Hashim, Abd Samad Hassan Basari, A. Halim Sahelan

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The aim of this study is to identify the suitability of Virtual Learning Environment (VLE) in welding simulator application towards Computer-Based Training (CBT) in developing skills upon new students at the Advanced Technology Training Center (ADTEC), Batu Pahat, Johor, Malaysia and GIATMARA, Batu Pahat, Johor, Malaysia. The purpose of the study is to create a computer-based skills development approach in welding technology among new students in ADTEC and GIATMARA, as well as cultivating the elements of general skills among them. This study is also important in elevating the number of individual knowledge workers (K-workers) working in manufacturing industry in order to achieve a national vision which is to be an industrial nation in the year of 2020. The design of the study is a survey type of research which uses questionnaires as the instruments and 136 students from ADTEC and GIATMARA were interviewed. Descriptive analysis is used to identify the frequency and mean values. The findings of the study shows that the welding technology skills have developed in the students as a result of the application of VLE simulator at a high level and the respondents agreed that the skills could be embedded through the application of the VLE simulator. In summary, the VLE simulator is suitable in welding skills development training in terms of exposing new students with the relevant characteristics of welding skills and at the same time spurring the students’ interest towards learning more about the skills.

Keywords: computer-based training (CBT), knowledge workers (K-workers), virtual learning environment, welding simulator, welding technology

Procedia PDF Downloads 356

Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

Procedia PDF Downloads 110

Authors: Amreth Chandrasehar

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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

Procedia PDF Downloads 117

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

Procedia PDF Downloads 164

Authors: William Li

Abstract:

Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

Procedia PDF Downloads 266

Authors: Michael Lekan-Kehinde, Abimbola Asojo, Bonnie Sanborn

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Good acoustic performance has been identified as one of the critical Indoor Environmental Quality (IEQ) factors for student learning and development by the National Research Council. Childhood presents the opportunity for children to develop lifelong skills that will support them throughout their adult lives. Acoustic performance of a space has been identified as a factor that can impact language acquisition, concentration, information retention, and general comfort within the environment. Increasingly, students learn by communication between both teachers and fellow students, making speaking and listening crucial. Neurodiversity - while initially coined to describe individuals with autism spectrum disorder (ASD) - widely describes anyone with a different brain process. As the understanding from cognitive and neurosciences increases, the number of people identified as neurodiversity is nearly 30% of the population. This research looks at guidelines and standard for spaces with good acoustical quality and relates it with the experiences of students with autism spectrum disorder (ASD), their parents, teachers, and educators through a mixed methods approach, including selected case studies interviews, and mixed surveys. The information obtained from these sources is used to determine if selected materials, especially properties relating to sound absorption and reverberation reduction, are equally useful in small, medium sized, and large learning spaces and methodologically approaching. The results describe the potential impact of acoustics on Neurodiverse students, considering factors that determine the complexity of sound in relation to the auditory processing capabilities of ASD students. In conclusion, this research extends the knowledge of how materials selection influences the better development of acoustical environments for autism students.

Keywords: acoustics, autism spectrum disorder (ASD), children, education, learning, learning spaces, materials, neurodiversity, sound

Procedia PDF Downloads 109

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

Procedia PDF Downloads 45

Authors: G. Infante Dennis, S. Balinas Elvira, C. Valencia Yolanda, Cunanan

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This paper examined the feed-backs, concerns, and insights of the teachers, supervisors, and teacher-trainers on the nature and qualities of the K-12 grade 8 design, content, approaches, and materials. Specifically, it sought to achieve the following objectives: 1) to describe the critical nature and qualities of the design, content, teaching-learning-and-evaluation approaches, and the materials to be utilized in the implementation of the grade 8 curriculum; 2) to extract the possible challenges relevant to the implementation of the design, content, teaching-learning-and-evaluation approaches, and the materials of the grade 8 curriculum in terms of the linguistic and technical competence of the teachers, readiness to implement, willingness to implement, and capability to make relevant adaptations; 3) to present essential demands on the successful and meaningful implementation of the grade 8 curriculum in terms of teacher-related factors, school-related factors, and student-related concerns.

Keywords: curriculum reforms, K-12, teacher-training, language teaching, learning

Procedia PDF Downloads 258

Authors: Raziel Mojica

Abstract:

This study delves into the challenging working conditions faced by physical education (PE) teachers in public schools, particularly during the transition to remote teaching due to the impact of the COVID-19 pandemic. Using a qualitative, hermeneutic phenomenological approach, the research involves in-depth interviews with PE teachers to gain profound insight into their lived experiences and to answer the main question: What is the essence of the lived experience of physical education? The study explores the following sub-questions: (1) How do the participants describe their lived experience regarding their working conditions as physical education teachers in the new normal setup?; (2) What themes emerge from the testimonies of Physical Education Public School teachers from the Division of Calamba?; (3) Based on the consolidated findings and reflection, what material may be produced to inspire the physical education public school teachers? The study identifies emerging themes such as professional growth, personal life boundaries, accessible facilities and equipment, time management, and school leadership. Framed by Frederick Herzberg's Work-Motivation Theory, the study emphasizes motivator and hygienic factors that significantly impact job satisfaction and dissatisfaction. As a result of the study, the teachers vividly identified the challenges they face, including the lack of resources, training, and support from school leaders, which have made it difficult for them to adapt to the new teaching environment. These findings underscore the urgent need to revise teacher training curricula and for school leaders to provide strategic support to PE teachers in remote learning contexts. In conclusion, the study recommends targeted interventions to address these challenges and better equip PE teachers for the new normal in education.

Keywords: PE teachers, COVID-19 pandemic, hermeneutic phenomenological, physical education, new normal

Procedia PDF Downloads 38

Authors: G. Yanay-Ventura, H. Desivilya Syna, K. Michael

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Social businesses are based on the idea that an enterprise can be established for the sake of profit and, at the same time, with the aim of fulfilling social goals. Yet, the question of how these goals can be integrated in practice to derive parallel benefit in both realms still needs to be examined. Particularly notable in this context is the ‘governance challenge’ of social businesses, meaning the danger of the mission drifts from the social goal in the pursuit of good business. This study is based on an evaluation study of a social business that operates as a restaurant providing professional training to at-risk youth. The evaluation was based on the collection of a variety of data through interviews with stakeholders in the enterprise (directors and managers, business partners, social partners, and position holders in the restaurant and the social enterprise), a focus group consisting of the youth receiving the professional training, observations of the restaurant’s operation, and analysis of the social enterprise’s primary documents. The evaluation highlighted significant strengths of the social enterprise, including reaching relatively fast business sustainability, effective management of the restaurant, stable employment of the restaurant staff, and effective management of the social project. The social enterprise and business management have both enjoyed positive evaluations from a variety of stakeholders. Clearly, the restaurant was deemed by all a promising young business. However, the social project suffered from a 90% dropout rate among the youth entering its ranks, extreme monthly fluctuation in the number of youths participating, and a distinct minority of the youth who have succeeded in completing their training period. Possible explanations of the high dropout rate included the small number of cooks, which impeded the effectiveness of the training process and the provision of advanced cooking skills; lack of clarity regarding the essence and the elements of training; and lack of a meaningful peer group for the youth engaged in the program. Paradoxically, despite the stakeholders’ great appreciation for the social enterprise, the challenge of governability was also formidable, revealing a tangible risk of mission drift in the reduction of the social enterprise’s target population and a breach of the commitment made to the youth with regard to practical training. The risk of mission drifts emerged as a hidden and evasive issue for the stakeholders, who revealed a deep appreciation for the management and the outcomes of the social enterprise. The challenge of integration, therefore, requires an in-depth examination of how to maintain a successful business without hindering the achievement of the social goal. The study concludes that clear conceptualization of the training process and its aims, increased cooks’ participation in the social project, and novel conceptions with regard to the evaluation of success could serve to benefit the youth and impede mission drift.

Keywords: evaluation study, management, mission drift, social business

Procedia PDF Downloads 117

Authors: Jenney Perez Bacalla

Abstract:

The study was conducted to assess the five (5) identified school administrators of the identified secondary schools in terms of professional characteristics, management skills and values patterns in the Division of Leyte Area IV for a proposed enhancement model for school administrators. The study utilized the qualitative method. There were two (2) groups of respondents: the teachers and the school administrators. The teachers perceived the management skills of the school administrators in their technical and conceptual skills and values in planning and organizing work, allocating and using of funds, submitting reports, decision-making, leading people, public relations and community involvement and other value development. It was found out in the study that most of the school administrators’ management skills were very well manifested. Their value patterns were also very well manifested. Most of them had earned master’s degree and with a unit in doctoral and five (5) years and above in service as a school administrator. Most administrators were performing and successfully execute the planning, organizing and utilizing funds and they were able to lead their subordinates. In planning, it shows that administrators studied the future and arrange the plan. Administrators also were able to manage, maintained the good environment wherein individual work together. School administrators were creating an environment conducive to learning. The school administrator is manifesting the desirable practices in school management. In terms of their educational qualifications, they were all qualified. Academic preparation, trainings and maturation were their attributes to the development of managerial skills of the school administrators. They showed competence in the areas of management skills that they were able to carry their functions with utmost responsibility and capability. School administrators in terms of seminars and trainings on administration and supervision were already equipped. It is concluded that the school administrators possessed the necessary skills and work values in administering the school.

Keywords: management skills and values, public secondary schools, qualitative, school administrators

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Authors: Ibrahim Abubakar Mikugi

Abstract:

Nigerian graduates could only be self-employed and marketable if they acquire relevant skills and knowledge for successful establishment in various occupation and gainful employment. Research has shown that entrepreneurship education will be successful through developing individual entrepreneurial attitudes, raising awareness of career options by integrating and inculcating a positive attitude in the mind of students through skill acquisition. This paper examined the student- led entrepreneurship education through skill acquisition with specific emphasis on analysis of David Kolb experiential learning cycle. This Model allows individual to review their experience through reflection and converting ideas into action by doing. The methodology used was theoretical approach through journal, internet and Textbooks. Challenges to entrepreneurship education through skill acquisition were outlined. The paper concludes that entrepreneurship education is recognised by both policy makers and academics; entrepreneurship is more than mere encouraging business start-ups. Recommendations were given which include the need for authorities to have a clear vision towards entrepreneurship education and skill acquisition. Authorities should also emphasise a periodic and appropriate evaluation of entrepreneurship and to also integrate into schools academic curriculum to encourage practical learning by doing.

Keywords: entrepreneurship, entrepreneurship education, active learning, Cefe methodology

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Authors: Sujith Gunawardhana

Abstract:

The circular economy is a system in which resources and energy are derived from renewable sources, utilized efficiently, recycled, and reused to reduce waste, reduce nonrenewable resource consumption, and mitigate negative environmental impacts. However, it poses moral questions about sustainability, the environment, and societal issues. Many societies face challenges when implementing the circular economy, as the concept is still young. The equitable distribution of the advantages and costs of circularity should be ensured during implementation, as some communities, particularly disadvantaged or marginalized ones, may suffer unfairly disproportionately from the harmful effects of production and recycling facilities. Prioritizing the health and safety of workers, communities, and the environment is essential, and strict rules must be implemented to guard against harm. However, most underdeveloped countries need a legal safeguard for this situation. The ultimate objective of the circular economy is to improve social, environmental, and economic performance, but its implementation also requires consideration of the ethics of care and non-epistemic values. Those are often hindered in underdeveloped countries, as the availability of infrastructure and technology, affordability, and legislative framework are poor. To achieve long-term success in the circular economy, evaluating implementation steps and considering health, safety, environmental, and social risks is crucial. To implement the circular economy, respect ethics of care and non-epistemic values. Adopt Kantian Ethics and control technology design to ensure equal benefits for all involved. Ethical gaps may lead underdeveloped countries to generate social pressure against the circular economy.

Keywords: circular economy, ethics, values, sustainability

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Authors: Sarah Barnard, John Arnold, Fehmidah Munir, Sara Bosley

Abstract:

Gender issues in higher education continue to represent a complex issue as institutions grapple with the role that organisations can play in combatting inequality. Schemes like Athena SWAN and the Aurora leadership programme in the UK context are attempting to tackle some of the issues around representation and the recognition of women in the sector. This paper is the first of its kind in reporting findings from a mixed-methods longitudinal study on both professional services and academic women in higher education in the UK. Online surveys have been completed by over 2,000 women in the sector. The qualitative elements include interviews with women and their mentors, and diaries with a select group of women. So far results have shown that contrary to the stereotype of women lacking leadership skills or having no desire to go into higher roles, women in the sector consistently assessed their leadership abilities positively, especially but not only regarding interpersonal interaction and facilitation. Over 80% of women agreed that they felt confident about putting themselves forward for positions of responsibility at work. However, qualitative data shows that confidence remains a salient term for how women talk about the challenges they have faced at work. This suggests that the work needed to challenge systemic gender issues requires action to be driven above the individual level. Overall, academics reported more negative experiences than professional services staff. Similarly BAME women’s responses are more negative. Therefore, the study offers some information on the differential experiences of women. In conclusion, women in higher education are undertaking considerable ‘below the radar’ leadership activities in what they perceive to be a somewhat inhospitable hostile workplace culture. The significant amount of effort expended in the sector is affecting slow, partial impacts on gender inequalities.

Keywords: gender, higher education, leadership, longitudinal research

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Authors: Jaya Mathew

Abstract:

Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

Procedia PDF Downloads 380

Authors: Fatemeh Jannesarvatan, Ghazaal Parastooei, Jimmy frerejan, Saedeh Mokhtari, Peter Van Rosmalen

Abstract:

Medical and dental education increasingly emphasizes the acquisition, integration, and coordination of complex knowledge, skills, and attitudes that can be applied in practical situations. Instructional design approaches have focused on using real-life tasks in order to facilitate complex learning in both real and simulated environments. The Four component instructional design (4C/ID) model has become a useful guideline for designing instructional materials that improve learning transfer, especially in health profession education. The objective of this study was to apply the 4C/ID model in the creation of virtual patients (VPs) that dental students can use to practice their clinical management and clinical reasoning skills. The study first explored the context and concept of complication factors and common errors for novices and how they can affect the design of a virtual patient program. The study then selected key dental information and considered the content needs of dental students. The design of virtual patients was based on the 4C/ID model's fundamental principles, which included: Designing learning tasks that reflect real patient scenarios and applying different levels of task complexity to challenge students to apply their knowledge and skills in different contexts. Creating varied learning materials that support students during the VP program and are closely integrated with the learning tasks and students' curricula. Cognitive feedback was provided at different levels of the program. Providing procedural information where students followed a step-by-step process from history taking to writing a comprehensive treatment plan. Four virtual patients were designed using the 4C/ID model's principles, and an experimental design was used to test the effectiveness of the principles in achieving the intended educational outcomes. The 4C/ID model provides an effective framework for designing engaging and successful virtual patients that support the transfer of knowledge and skills for dental students. However, there are some challenges and pitfalls that instructional designers should take into account when developing these educational tools.

Keywords: 4C/ID model, virtual patients, education, dental, instructional design

Procedia PDF Downloads 85