Search results for: student performance prediction

Authors: H. A. Mansour

Abstract:

The objective of this research work is studying the water use prediction, prediction technology for water use by action agencies, and others involved in conservation, planning, and environmental assessment of the Water Erosion Prediction Project (WEPP) simulation model. Models the important physical, processes governing erosion in Egypt (climate, infiltration, runoff, ET, detachment by raindrops, detachment by flowing water, deposition, etc.). Simulation of the non-uniform slope, soils, cropping/management., and Egyptian databases for climate, soils, and crops. The study included important parameters in Egyptian conditions as follows: Water Balance & Percolation, Soil Component (Tillage impacts), Plant Growth & Residue Decomposition, Overland Flow Hydraulics. It could be concluded that we can adapt the WEPP simulation model to determining the previous important parameters under Egyptian conditions.

Keywords: WEPP, adaptation, soil properties, tillage impacts, water balance, soil percolation

Procedia PDF Downloads 271

Authors: Elizelle Juanee Cilliers

Abstract:

Recent planning thinking has laid the foundations for a general sense of best practice that aims to enhance the quality of life, suggesting an open and participatory process. It is accepted that integration of top-down and bottom-up approaches may lead to efficient action in environments and sustainable planning and development, although it is also accepted that such an integrated approach has various challenges of implementation. A flexible framework in which the strengths of both the top-down and bottom-up approaches were explored in this research, based on the EU Interreg VALUE Added project and five case studies where student education and student involvement played a crucial role within the participation process of the redesign of the urban environment. It was found that international student workshops were an effective tool to integrate bottom-up and top-down structures, as it acted as catalyst for communication, interaction, creative design, quick transformation from planning to implementation, building social cohesion, finding mutual ground between stakeholders and thus enhancing overall quality of life and quality of environments. It offered a good alternative to traditional participation modes and created a platform for an integrative planning approach. The role and importance of education and integration within the urban environment were emphasized.

Keywords: top-down, bottom-up, flexible, student involvement

Procedia PDF Downloads 190

Authors: Nurlaila Effendy

Abstract:

Companies in Asia face a number of constraints in tight competitiveness in ASEAN Economic Community 2015 and globalization. An economic capitalism system as an integral part of globalization processing brings broad impacts. They need to improve business performance in globalization and ASEAN Economic Community. Organizational development has quite clearly demonstrated that aligning individual’s personal goals with the goals of the organization translates into measurable and sustained performance improvement. Human capital is a key to achieve company performance. Employee Engagement (EE) creates and expresses themselves physically, cognitively and emotionally to achieve company goals and individual goals. One will experience a total involvement when they undertake their jobs and feel a self integration to their job and organization. A leader plays key role in attaining the goals and objectives of a company/organization. Any Manager in a company needs to have leadership competence and global mindset. As one the of positive organizational behavior developments, psychological capital (PsyCap) is assumed to be one of the most important capitals in the global mindset, in addition to intellectual capital and social capital. Textile companies also need to face a number of constraints in tight competitiveness in regional and global. This research involved 42 managers in two textiles and a spinning companies in a group, in Central Java, Indonesia. It is a quantitative research with Partial Least Squares (PLS) studying job resource (Social Support & Organizational Climate) and Personal Resource (4 dimensions of Psychological Capital & Leadership Competence) as prediction of Employee Engagement, also Employee Engagement and leadership competence as prediction of leader’s performance. The performance of a leader is measured by means of achievement on objective strategies in terms of 4 perspectives (financial and non-financial perspectives) in a Balanced Score Card (BSC). It took one year during a business plan of year 2014, from January to December 2014. The result of this research is there is correlation between Job Resource (coefficient value of Social Support is 0.036 & coefficient value of organizational climate is 0.220) and Personal Resource (coefficient value of PsyCap is 0.513 & coefficient value of Leadership Competence is 0.249) with employee engagement. There is correlation between employee engagement (coefficient value is 0.279) and leadership competence (coefficient value is 0.581) with performance.

Keywords: organizational climate, social support, psychological capital leadership competence, employee engagement, performance, integrated textile companies

Procedia PDF Downloads 414

Authors: Joseph C. Chen, Venkata Mohan Kudapa

Abstract:

Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

Procedia PDF Downloads 118

Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

Procedia PDF Downloads 253

Authors: Emad A. Mohammed

Abstract:

Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

Procedia PDF Downloads 119

Authors: Shawndra Bowers, Allie Brandriet, Betsy Gilbertson

Abstract:

This paper will highlight how Auburn Online’s instructional designers leveraged student and faculty data to update and improve online course design and instructional materials. When designing and revising online courses, it can be difficult for faculty to know what strategies are most likely to engage learners and improve educational outcomes in a specific discipline. It can also be difficult to identify which metrics are most useful for understanding and improving teaching, learning, and course design. At Auburn Online, the instructional designers use a suite of data based student’s performance, participation, satisfaction, and engagement, as well as faculty perceptions, to inform sound learning and design principles that guide growth-mindset consultations with faculty. The consultations allow the instructional designer, along with the faculty member, to co-create an actionable course improvement plan. Auburn Online gathers learning analytics from a variety of sources that any instructor or instructional design team may have access to at their own institutions. Participation and performance data, such as page: views, assignment submissions, and aggregate grade distributions, are collected from the learning management system. Engagement data is pulled from the video hosting platform, which includes unique viewers, views and downloads, the minutes delivered, and the average duration each video is viewed. Student satisfaction is also obtained through a short survey that is embedded at the end of each instructional module. This survey is included in each course every time it is taught. The survey data is then analyzed by an instructional designer for trends and pain points in order to identify areas that can be modified, such as course content and instructional strategies, to better support student learning. This analysis, along with the instructional designer’s recommendations, is presented in a comprehensive report to instructors in an hour-long consultation where instructional designers collaborate with the faculty member on how and when to implement improvements. Auburn Online has developed a triage strategy of priority 1 or 2 level changes that will be implemented in future course iterations. This data-informed decision-making process helps instructors focus on what will best work in their teaching environment while addressing which areas need additional attention. As a student-centered process, it has created improved learning environments for students and has been well received by faculty. It has also shown to be effective in addressing the need for improvement while removing the feeling the faculty’s teaching is being personally attacked. The process that Auburn Online uses is laid out, along with the three-tier maintenance and revision guide that will be used over a three-year implementation plan. This information can help others determine what components of the maintenance and revision plan they want to utilize, as well as guide them on how to create a similar approach. The data will be used to analyze, revise, and improve courses by providing recommendations and models of good practices through determining and disseminating best practices that demonstrate an impact on student success.

Keywords: data-driven, improvement, online courses, faculty development, analytics, course design

Procedia PDF Downloads 35

Authors: Azza Taha Zaki

Abstract:

Technology-enhanced teaching has been in the limelight since the 90s when educators started investigating and experimenting with using computers in the classroom as a means of building 21^st. century skills and motivating students. The concept of technology-enhanced strategies in education is kaleidoscopic! It has meant different things to different educators. For the purpose of this paper, however, it will be used to refer to the diverse technology-based strategies used to support and enrich the flipped learning process, in the classroom and outside. The paper will investigate how technology is put in the service of teaching and learning to improve the students’ learning experience as manifested in students’ attendance and engagement, achievement rates and finally, students’ projects at the end of the semester. The results will be supported by a student survey about relevant specific aspects of their learning experience in the modules in the study.

Keywords: attendance, British University, Egypt, flipped, student achievement, student-centred, student engagement, students’ projects

Procedia PDF Downloads 98

Authors: Anne-Lena Kampen, Øivind Kure

Abstract:

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

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

Procedia PDF Downloads 124

Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

Abstract:

Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

Procedia PDF Downloads 299

Authors: Gunasekaran Raja, Rajakumar Arul, Kottilingam Kottursamy, Ramkumar Jayaraman, Sathya Pavithra, Swaminathan Venkatraman

Abstract:

Wireless Interoperability for Microwave Access (WiMAX) utilizes the IEEE 802.1X mechanism for authentication. However, this mechanism incurs considerable delay during handoffs. This delay during handoffs results in service disruption which becomes a severe bottleneck. To overcome this delay, our article proposes a key caching mechanism based on user path prediction. If the user mobility follows that path, the user bypasses the normal IEEE 802.1X mechanism and establishes the necessary authentication keys directly. Through analytical and simulation modeling, we have proved that our mechanism effectively decreases the handoff delay thereby achieving fast authentication.

Keywords: authentication, authorization, and accounting (AAA), handoff, mobile, user path prediction (UPP) and user pattern

Procedia PDF Downloads 367

Authors: Kaoutar Abbahaddou, Mohammed Salah Chiadmi

Abstract:

The need to find a relevant way to predict the next-day price of a stock index is a real concern for many financial stakeholders and researchers. We have known across years the proliferation of several methods. Nevertheless, among all these methods, the most controversial one is a machine learning algorithm that claims to be reliable, namely neural networks. Thus, the purpose of this article is to study the prediction power of neural networks in the particular case of Islamic finance as it is an under-looked area. In this article, we will first briefly present a review of the literature regarding neural networks and Islamic finance. Next, we present the architecture and principles of artificial neural networks most commonly used in finance. Then, we will show its empirical application on two Islamic stock indexes. The accuracy rate would be used to measure the performance of the algorithm in predicting the right price the next day. As a result, we can conclude that artificial neural networks are a reliable method to predict the next-day price for Islamic indices as it is claimed for conventional ones.

Keywords: Islamic finance, stock price prediction, artificial neural networks, machine learning

Procedia PDF Downloads 201

Authors: P. V. Pramila , V. Mahesh

Abstract:

Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

Procedia PDF Downloads 281

Authors: Justice Dadzie, Stacy H. Surman, Ruth K. Annan-Brew, Ifesinachi J. Ezugwu, Evans Addison

Abstract:

This study aimed to explore the correlation between students' performance in educational statistics and research methods in education, as well as investigate potential differences in performance based on their undergraduate programs. A cross-sectional design was employed, and data was collected from 170 students enrolled in master of philosophy programs in the department of education and psychology. The correlation analysis revealed a strong positive correlation between students' performance in intermediate statistics in education and research methods in education. This indicates a close relationship between the two domains. The MANOVA analysis showed no significant differences in the linear combination of intermediate statistics in education and research methods in education scores across the different undergraduate programs. The tests of between-subjects effects further confirmed that the student's performance in intermediate statistics in education and research methods in education did not differ significantly across the different undergraduate programs. These findings contribute to the existing literature by providing insights into the correlation between educational statistics and research methods, and the influence of undergraduate program backgrounds on students' performance in these domains. The strong positive correlation between intermediate statistics and research methods highlights the importance of a solid foundation in statistics for understanding and applying research methods. Moreover, the consistent relationship across different academic backgrounds emphasizes the need for targeted interventions and support systems to enhance graduate students' competencies in these critical areas.

Keywords: educational statistics, research methods, undergraduate programs, students performance

Procedia PDF Downloads 24

Authors: Jefferson S. Galanza, Jewel An Mischelle R.Camcam, Alyssa Karryl C. Co, Stephanie P. De Guzman, Jet Jet K. Dongui-is, Rodolfo Dane C. Frias, Ovelle C. Jueco, Harvey L. Matbagan, Victoria Luzette T. Rillon, Christelle Romyna H. Saruca, Jeanette Roma M. Villasper

Abstract:

Background: Amidst numerous studies conducted on learning styles of students from a variety of courses, levels and school, a recent study recommended a great need for research on learning styles of student nurses. Moreover, related literatures have not been found exploring both the learning and teaching style of student nurses. Aims: The study aimed to determine the learning and teaching styles of student nurses and if there is an association between them. It also intended to discover whether student nurses are unimodal or multimodal in their styles and identified which faculty teaching style affords maximum outcome for student’s learning styles. Methods: Quantitative Descriptive-Correlational design was used. Participants were randomly selected 312 student nurses at School of Nursing X, Baguio City, Philippines. The questionnaire utilized a modified version of an adopted tool from Fleming’s VARK learning style version 7.2 (Visual, Auditory, Reader/Writer, Kinaesthetic) and Grasha’s teaching styles (Formal Authority, Demonstrator, Facilitator, Delegator). SPSS 19 was used for statistical treatment of data, where Chi square was used for the correlation of unimodal learning and teaching styles. Results/Finding: Majority of student nurses’ learning style is Kinesthetic and their teaching style is Demonstrator, which was also found to be significantly associated. Moreover, 8 out of 10 students are Unimodal in their learning and teaching modalities. In general, their preferred faculty teaching style is similar to their teaching style, which supports the concept, that teachers teach the way they learn. Conclusion: Study concludes that student nurses’ learning styles and teaching styles are varied, which exemplifies the uniqueness of every learner.This diversity in styles provided more evidence that a variety of mode of teaching and learning should be used by faculty and students to increase learning outcome and academic achievement. Recommendation: Future studies could be carried out in various schools of nursing utilizing faculty as respondents. Conduct assessment of learning style at the onset of classes/clinical placements so that faculty will become aware of the diversity of learners leading them to deliver diverse teaching methods.

Keywords: learning, learning styles, teaching styles, student nurses

Procedia PDF Downloads 515

Authors: Khalid Soussi

Abstract:

Implementing innovative teaching and learning methods is of pivotal importance for student motivation and teaching quality. At the center of such quality are teaching competencies. The present paper investigates three teachers’ core competencies related to their innovative teaching performance: educational/pedagogical competency, teaching competency, and social competency. The paper also attempts to describe the influence of social factors on innovation in higher education. Many recent studies highlight the technological competency as an independent one, but it is believed in this study that the latter makes part of the pedagogical competency. A Likert scale questionnaire was used to measure teachers’ judgements of core competencies role in innovative teaching performance. The study also attempted to demarcate the social variables that may affect innovative teaching in higher education. The findings indicate that teachers’ educational competency and teaching competency were generally confirmed to be either important or very important for innovation in teaching performance. Regarding social competency, the study also shows that satisfaction from job, daily working hours, amount of workload, flexibility in the functioning and the quality of students are the main factors that have a large effect on teachers’ innovative teaching performance.

Keywords: higher education, innovative teaching, teaching competencies, teaching performance

Procedia PDF Downloads 117

Authors: Muhammad Afzal Malik

Abstract:

Traditional Learning & Distance based learning are the two systems prevailing in Pakistan. These systems affect the level of education standard. The purpose of this study was to compare the traditional classroom learning and distance learning in Pakistan: (a) To explore the effectiveness of the traditional to Distance learning in Pakistan; (b) To identify the factors that affect traditional and distance learning. This review found that, on average, students in traditional classroom conditions performed better than those receiving education in and distance learning. The difference between student outcomes for traditional Classroom and distance learning classes —measured as the difference between treatment and control means, divided by the pooled standard deviation— was larger in those studies contrasting conditions that blended elements of online and face-to-face instruction with conditions taught entirely face-to-face. This research was conducted to highlight the impact of distance learning education system on education standard. The education standards were institutional support, course development, learning process, student support, faculty support, evaluation and assessment. A well developed questionnaire was administered and distributed among 26 faculty members of GCET, H-9 and Virtual University of Pakistan from each. Data was analyzed through correlation and regression analysis. Results confirmed that there is a significant relationship and impact of DLE system on education standards. This will also provide baseline for future research. It will add value to the existing body of knowledge.

Keywords: distance learning education, higher education, education standards, student performance

Procedia PDF Downloads 256

Authors: Van Thien NGO

Abstract:

The purpose of the study is to examine the effect of student response systems in computer-based formative assessment on learning outcomes. The backward design course is a tool to be applied for collecting necessary assessment evidence. The quasi-experimental research design involves collecting pre and posttest data on students assigned to the control group and the experimental group. The sample group consists of 150 college students randomly selected from two of the eight classes of electrical and electronics students at Cao Thang Technical College in Ho Chi Minh City, Vietnam. Findings from this research revealed that the experimental group, in which student response systems were applied, got better results than the controlled group, who did not apply them. Results show that using student response systems for technology-based formative assessment is vital and meaningful not only for teachers but also for students in the teaching and learning process.

Keywords: student response system, computer-based formative assessment, learning outcome, backward design course

Procedia PDF Downloads 112

Authors: Catherine Omole

Abstract:

Examination malpractice includes acts that temper with collecting accurate results during the conduct of an examination, thereby giving undue advantage to a student over his colleagues. Even though examination malpractice has been a lingering problem, examinations may not be easy to do away with completely as it is an important feedback tool in the learning process with several other functions e.g for the purpose of selection, placement, certification and promotion. Examination malpractice has created a lot of problems such as a relying on a weak work force based on false assessment results. The question is why is this problem still persisting, despite measures that have been taken to curb this ugly trend over the years? This opinion paper has identified modifications that could help relieve the student of the examination stress and thus increase the student’s effort towards effective learning and discourage examination malpractice in the long run.

Keywords: assessment, examination malpractice, learning, science classroom

Procedia PDF Downloads 236

Authors: Kiyoumars Roushangar, Saeid Sadaghian

Abstract:

Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

Procedia PDF Downloads 473

Authors: Wahid Ahmad Dar, Irshad Ahmad Najar

Abstract:

The influence of social media is percolating to every corner of our social life. It is also changing the social sphere of the classroom in particular and education in general. This paper tries to explore the ways in which social media is influencing student-teacher relationship. Differences have been found in student’s ability to draw benefits from using ICT. Besides digital divides in access and usage, there are attitudinal differences among students towards ICT aligned with traditional forms of social differences. The paper particularly focusses on how students from diverse backgrounds are using social media to interact with their teachers and how such interactions differ on the basis of social class, gender and residential background of students. A qualitative research methodology has been used for answering these questions. Open-ended questionnaire has been designed and administered to a sample of postgraduate students from University of Kashmir drawn purposively ensuring optimum number of subjects from all backgrounds. The data were analyzed by content analysis, deciphering general patterns in the data.

Keywords: social media, student-teacher relationship, social class, gender

Procedia PDF Downloads 217

Authors: Ting Shen

Abstract:

Whether resource matters to school has been a topic of intense debate since 1960s. Educational researchers and policy makers have been particularly interested in knowing the return or payoff of Per-Pupil Expenditure (PPE) on improving students’ achievement. However, the evidence on the effect of PPE has been mixed and the size of the effect is also unknown. With regard to the methods, it is well-known that meta-analysis study is superior to individual study and it is also preferred to vote counting method in terms of scientifically weighting the evidence by the sample size. This meta-analysis study aims to provide a synthesized evidence on the correlation between PPE and student academic achievement using recent study data from 1990s to 2010s. Meta-analytical approach of fixed- and random-effects models will be utilized in addition to a meta regression with predictors of year, location, region and school type. A preliminary result indicates that by and large there is no statistically significant relationship between per pupil expenditure and student achievement, but location seems to have a mediating effect.

Keywords: per pupil expenditure, student academic achievement, multilevel model, meta-analysis

Procedia PDF Downloads 222

Authors: Mary Isobelle Mullaney

Abstract:

The purpose of this research was to explore the attitudes of student Art and Design teachers (n=79) and their cooperating teachers in the Republic of Ireland (n=83) as to their interpretation of the role in teacher education. The role is outlined in terms of how the Teaching Council defines the role and then how the students and teachers see it being fulfilled. While overall teachers rated themselves as fulfilling the role expected of them, the interpretation varied greatly, with considerable deficits reported regarding guidance given in planning, observation of the student teacher, and feedback given. Overall, students saw teachers as fulfilling their role effectively, though there was considerable variation reported in experiences. A focus group was conducted in order to arrive at a more comprehensive understanding of the underlying factors influencing these discrepancies.

Keywords: Irish post primary teaching, cooperating teacher, student teacher, teacher education

Procedia PDF Downloads 29

Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

Abstract:

Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

Procedia PDF Downloads 182

Authors: Danladi Ali, Abdullahi Mukaila

Abstract:

In this work, GSM signal strength (power) was monitored in an indoor environment. Samples of the GSM signal strength was measured on mobile equipment (ME). One-dimensional multilevel wavelet is used to predict the fading phenomenon of the GSM signal measured and neural network clustering to determine the average power received in the study area. The wavelet prediction revealed that the GSM signal is attenuated due to the fast fading phenomenon which fades about 7 times faster than the radio wavelength while the neural network clustering determined that -75dBm appeared more frequently followed by -85dBm. The work revealed that significant part of the signal measured is dominated by weak signal and the signal followed more of Rayleigh than Gaussian distribution. This confirmed the wavelet prediction.

Keywords: decomposition, clustering, propagation, model, wavelet, signal strength and spectral efficiency

Procedia PDF Downloads 428

Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

Abstract:

Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

Procedia PDF Downloads 90

Authors: Etienne Alain Feukeu, L. W. Snyman

Abstract:

Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably.

Keywords: water scarcity, water estimation, water prediction, water forecast.

Procedia PDF Downloads 170

Authors: Kaycee L. Bills

Abstract:

Adolescents and youth who are members of a minority group are more likely to experience higher rates of bullying in comparison to other student demographics. Specifically, adolescents with intellectual disabilities are a minority population that is more susceptible to experience unfair treatment in social settings. This study employs the 2015 Wave of the National Crime Victimization Survey – School Crime Supplement (NCVS/SCS) longitudinal dataset to explore bullying rates experienced among adolescents with intellectual disabilities. This study uses chi-square testing and a logistic regression to analyze if having a disability influences the likelihood of being bullied in comparison to other student demographics. Results of the chi-square testing and the logistic regression indicate that adolescent students who were identified as having a disability were approximately four times more likely to experience higher bullying rates in comparison to all other majority and minority student populations. Thus, it means having a disability resulted in higher bullying rates in comparison to all student groups.

Keywords: disability, bullying, social work, school bullying

Procedia PDF Downloads 111

Authors: Athira M., Prakasha G. S.

Abstract:

The rising prevalence of academic entitlement among school and college students necessitates a comprehensive investigation. This study focuses on discovering gender differentials in academic entitlement and their nexus with diverse grade negotiation behaviors within the undergraduate (UG) student cohort. Grade negotiation behaviors, encompassing a range from amicable discussions to more assertive tactics, are influenced by students' perceptions of their academic entitlement. The research delves into the broader significance of academic entitlement, considering its implications for student-teacher conflicts and the dynamics it introduces into the educational field. Employing a quantitative research approach, data from UG students is meticulously analyzed. Mann-Whitney U tests unveil pronounced gender difference in academic entitlement, with females demonstrating higher entitlement levels. Furthermore, the study unearths significant correlations between academic entitlement and specific negotiation styles, notably yielding and forcing strategies, albeit with minimal impact on academic performance. These findings provide a foundational understanding for educators and institutions to foster equitable learning environments and formulate effective conflict resolution strategies, ultimately elevating the quality of the educational experience. Moreover, this study opens avenues for future research, exploring interventions to enhance negotiation skills and diving deeper into the intricate dimensions of academic entitlement within academic life.

Keywords: academic entitlement, grade negotiation, negotiation styles, student-teacher conflict

Procedia PDF Downloads 23

Authors: Francis Mark A. Fernandez, Chelca Ubay, Armithan Suguitan

Abstract:

Regions or provinces in a definite state certainly contribute to the economy of their mainland. These regions or provinces are the ones supplying the mainland with different resources and assets. Thus, with a certain region separating from the mainland would indeed impinge the heart of an entire state to develop and expand. With these, the researchers decided to study on the effects of the separation of one’s region to its mainland and the consequences that will take place if the mainland would rule out the region to separate from them. The researchers wrote this paper to present the causes of the separation of Catalonia from Spain and the prediction regarding the pursuance of this region to revolt from its mainland, Spain. In conducting this research, the researchers utilized two analyses, namely: qualitative and quantitative. In qualitative, numerous of information regarding the existing experiences of the citizens of Catalonia were gathered by the authors to give certainty to the prediction of the researchers. Besides this undertaking, the researchers will also gather needed information and figures through books, journals and the published news and reports. In addition, to further support this prediction under qualitative analysis, the researchers intended to operate the Phenomenological research in which the examiners will exemplify the lived experiences of each citizen in Catalonia. Moreover, the researchers will utilize one of the types of Phenomenological research which is hermeneutical phenomenology by Van Manen. In quantitative analysis, the researchers utilized the regression analysis in which it will ascertain the causality in an underlying theory in understanding the relationship of the variables. The researchers assigned and identified different variables, wherein the dependent variable or the y which represents the prediction of the researchers, the independent variable however or the x represents the arising problems that grounds the partition of the region, the summation of the independent variable or the ∑x represents the sum of the problem and finally the summation of the dependent variable or the ∑y is the result of the prediction. With these variables, using the regression analysis, the researchers will be able to show the connections and how a single variable could affect the other variables. From these approaches, the prediction of the researchers will be specified. This research could help different states dealing with this kind of problem. It will further help certain states undergoing this problem by analyzing the causes of these insurgencies and the effects on it if it will obstruct its region to consign their full-pledge autonomy.

Keywords: autonomy, liberty, prediction, separation

Procedia PDF Downloads 230