Search results for: student performance prediction

Authors: Amy Stringer, Resa Chandler

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High Intensity Interval Training (HIIT) involves a 3-10-minute circuit of various exercises which is a viable alternative to a traditional cardiovascular and strength training regimen. Research suggests that measures of health-related fitness can either be maintained or actually improve with the use of this training method. After conducting a 6-week HIIT research study with 10-14 year old children, considerations for using a daily HIIT workout are presented. Is the use of HIIT with children a reasonable consideration for physical education programs? The benefits and challenges of this type of an intervention are identified. This study is significant in that achieving fitness gains in a small amount of daily class time is an attractive concept – especially for physical education teachers who often do not have the time necessary to accomplish all of their curricular goals in the amount of class time assigned. Basic methodologies include students participating in a circuit of exercises for 7-10 minutes at 80-95% of max heart rate as measured by heart rate monitors. Student pre and post fitness test data were collected for cardio-vascular endurance, muscular endurance, and body composition. Research notes as well as commentary by the teachers and researchers who participated in the HIIT study contributed to the understanding of the cost-benefit analysis. Major findings of the study are that HIIT has limited effectiveness but is a good choice for limited class times. Student efficacy of their ability to complete the exercises and visible heart rate data were considered to be significant factors in success of the HIIT study. The effective use of technology promoting positive audience effect during the display of heart rate data was more important at the beginning of the study than at the end. Student ‘buy-in’ and motivation, teacher motivation and ‘buy-in’, the variety of activities in the circuit and the fitness level of the student at the beginning of the study were also findings influencing the fitness outcomes of the study. Concluding Statement: High intensity interval training can be used effectively in a secondary physical education program. It is not a ‘magic bullet’ to produce health-related fitness outcomes in every student but it is an effective tool to enhance student fitness in a limited time and contribute to the goals of the program.

Keywords: cardio vascular fitness, children, high intensity interval training, physical education

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Authors: Yusuf S. Dambatta, Ahmed A. D. Sarhan

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Fused deposition modelling (FDM) is one of the most prominent rapid prototyping (RP) technologies which is being used to efficiently fabricate CAD 3D geometric models. However, the process is coupled with many drawbacks, of which the surface quality of the manufactured RP parts is among. Hence, studies relating to improving the surface roughness have been a key issue in the field of RP research. In this work, a technique of modelling the surface roughness in FDM is presented. Using experimentally measured surface roughness response of the FDM parts, an ANFIS prediction model was developed to obtain the surface roughness in the FDM parts using the main critical process parameters that affects the surface quality. The ANFIS model was validated and compared with experimental test results.

Keywords: surface roughness, fused deposition modelling (FDM), adaptive neuro fuzzy inference system (ANFIS), orientation

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Authors: Mohammed Salem Alzahrani

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In this paper, student admission process is studied to optimize the assignment of vacant seats with three main objectives. Utilizing all vacant seats, satisfying all program of study admission requirements and maintaining fairness among all candidates are the three main objectives of the optimization model. Seat Assignment Method (SAM) is used to build the model and solve the optimization problem with help of Northwest Coroner Method and Least Cost Method. A closed formula is derived for applying the priority of assigning seat to candidate based on SAM.

Keywords: admission process model, assignment problem, Hungarian Method, Least Cost Method, Northwest Corner Method, SAM

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Authors: Amylyn F. Labasano

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A significant number of empirical studies are carried out to investigate factors affecting college students’ performance in the academic examination. With a wide-array of literature-and studies-supported findings, this study is limited only on the students’ probability of passing periodical exams which is associated with students’ gender, absences in the class, use of reference book, and hours of study. Binary logistic regression was the technique used in the analysis. The research is based on the students’ record and data collected through survey. The result reveals that gender, use of reference book and hours of study are significant predictors of passing an examination while students’ absenteeism is an insignificant predictor. Females have 45% likelihood of passing the exam than their male classmates. Students who use and read their reference book are 38 times more likely pass the exam than those who do not use and read their reference book. Those who spent more than 3 hours in studying are four (4) times more likely pass the exam than those who spent only 3 hours or less in studying.

Keywords: absences, binary logistic regression, gender, hours of study prediction-causation method, periodical exams, random sampling, reference book

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Authors: Aneta Oblouková, Eva Vítková

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The article deals with the issue of water and sewerage charge rate prices in the Czech Republic. The research is specifically focused on the analysis of the development of the average prices of water and sewerage charge rate in the Czech Republic in the years 1994-2021 and on the validation of the chosen methodology relevant for the prediction of the development of the average prices of water and sewerage charge rate in the Czech Republic. The research is based on data collection. The data for this research was obtained from the Czech Statistical Office. The aim of the paper is to validate the relevance of the mathematical linear trend estimate technique for the calculation of the predicted average prices of water and sewerage charge rates. The real values of the average prices of water and sewerage charge rates in the Czech Republic in the years 1994-2018 were obtained from the Czech Statistical Office and were converted into a mathematical equation. The same type of real data was obtained from the Czech Statistical Office for the years 2019-2021. Prediction of the average prices of water and sewerage charge rates in the Czech Republic in the years 2019-2021 were also calculated using a chosen method -a linear trend estimation technique. The values obtained from the Czech Statistical Office and the values calculated using the chosen methodology were subsequently compared. The research result is a validation of the chosen mathematical technique to be a suitable technique for this research.

Keywords: Czech Republic, linear trend estimation, price prediction, water and sewerage charge rate

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Authors: Malo Pocheau-Lesteven, Olivier Le Maître

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Engineering and optimisation of complex systems is often achieved through multi-disciplinary analysis of the system, where each subsystem is modeled and interacts with other subsystems to model the complete system. The coherence of the output of the different sub-systems is achieved through the use of compatibility constraints, which enforce the coupling between the different subsystems. Due to the complexity of some sub-systems and the computational cost of evaluating their respective models, it is often necessary to build surrogate models of these subsystems to allow repeated evaluation these subsystems at a relatively low computational cost. In this paper, gaussian processes are used, as their probabilistic nature is leveraged to evaluate the likelihood of satisfying the compatibility constraints. This paper presents infilling strategies to build accurate surrogate models of the subsystems in areas where they are likely to meet the compatibility constraint. It is shown that these infilling strategies can reduce the computational cost of building surrogate models for a given level of accuracy. An application of these methods to velocity prediction programs used in offshore racing naval architecture further demonstrates these method's applicability in a real engineering context. Also, some examples of the application of uncertainty quantification to field of naval architecture are presented.

Keywords: infilling strategy, gaussian process, multi disciplinary analysis, velocity prediction program

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Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

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With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation, pressure drop

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Authors: Roya Kelishadi, Mostafa Amini-Rarani, Mostafa Qorbani

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Introduction: As a health-related behavior, physical activity (PA) has an unequal distribution relating to individual's socioeconomic status. This study aimed to assess socioeconomic inequality in PA among Iranian students and their parents at national level and according to socioeconomic status (SES) of the living regions. Method: This study was conducted as part of a national surveillance program conducted among 14400 Iranian students and their parents. Non-linear principal component analysis was used to construct the households' socioeconomic status, and the concentration index approach was applied to measure inequality in father, mother, and student’s PA. Results: The data of 13313 students and their parents were complete for the current study. At national level and SES regions, students had more PA than their parents (except in the lowest SES region), and fathers have more PA than mothers. The lowest means of mother and student's PA were find in the highest SES region. At national level, the concentration indices of father and mother’s PA were -0.050 (95 % CI: -0.067 ~ -0.030) and -0.028 (95% CI: -0.044 ~ -0.012), respectively; indicating pro-poor inequality and, the CI value of student PA was nearly equal to zero (P > 0.05). At SES regions, father and mother's PA were more concentrated in the poor, except for lower middle region. Regional concentration indices for students reveal that inequality not statistically significant at all regions. Conclusion: This study suggests that reliable evidence that comparing different aspects of inequality of PA, based on socioeconomic status and residence areas of students and their parents, could be used for better planning for health promotion programs. Moreover, given the average of mother's and student’s PA in the richer regions were low, it can be suggested that richer focused-PA planning may further increase the level of PA across higher SES and, consequently, reduce inequality in PA. These findings can be applied in the health system services.

Keywords: concentration index, health system services, physical activity, socioeconomic inequality

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Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: Kathleen L. Seifert

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Students with special needs are expected to achieve the same academic standards as their general education peers, yet many students with special needs are pulled-out of general content instruction. Because of this, many students with special needs are denied content knowledge from a content expert and instead receive content instruction in a more restrictive setting. Collaborative teaching, where a general education and special education teacher work alongside each other in the same classroom, has become increasingly popular as a means to meet the diverse needs of students in America’s public schools. The idea behind co-teaching is noble; to ensure students with special needs receive content area instruction from a content expert while also receiving the necessary supports to be successful. However, in spite of this noble effort, the effects of co-teaching are not always positive. The reasons why have produced several hypotheses, one of which has to do with lack of proper training and implementation of effective evidence-based co-teaching practices. In order to examine the effects of co-teacher training, eleven teaching pairs from a small mid-western school district in the United States participated in a study. The purpose of the study was to examine the effects of co-teacher training on middle and high school student achievement in Math and Language Arts. A local university instructor provided teachers with training in co-teaching via a three-day workshop. In addition, co-teaching pairs were given the opportunity for direct observation and feedback using the Co-teaching Core Competencies Observation Checklist throughout the academic year. Data are in the process of being collected on both the students enrolled in the co-taught classes as well as on the teachers themselves. Student data compared achievement on standardized assessments and classroom performance across three domains: 1. General education students compared to students with special needs in co-taught classrooms, 2. Students with special needs in classrooms with and without co-teaching, 3. Students in classrooms where teachers were given observation and feedback compared to teachers who refused the observation and feedback. Teacher data compared the perceptions of the co-teaching initiative between teacher pairs who received direct observation and feedback from those who did not. The findings from the study will be shared with the school district and used for program improvement.

Keywords: collabortive teaching, collaboration, co-teaching, professional development

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Authors: Koe Han Beng, Khoo Boo Cheong

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The rising interest of stepped hull design has been led by the demand of more efficient high-speed boat. At the same time, the need of accurate prediction method for stepped planing hull is getting more important. By understanding the flow at high Froude number is the key in designing a practical step hull, the study surrounding stepped hull has been done mainly in the towing tank which is time-consuming and costly for initial design phase. Here the feasibility of predicting hydrodynamics of high-speed planing hull both with and without step using computational fluid dynamics (CFD) with the volume of fluid (VOF) methodology is studied in this work. First the flow around the prismatic body is analyzed, the force generated and its center of pressure are compared with available experimental and empirical data from the literature. The wake behind the transom on the keel line as well as the quarter beam buttock line are then compared with the available data, this is important since the afterbody flow of stepped hull is subjected from the wake of the forebody. Finally the calm water performance prediction of a conventional planing hull and its stepped version is then analyzed. Overset mesh methodology is employed in solving the dynamic equilibrium of the hull. The resistance, trim, and heave are then compared with the experimental data. The resistance is found to be predicted well and the dynamic equilibrium solved by the numerical method is deemed to be acceptable. This means that computational fluid dynamics will be very useful in further study on the complex flow around stepped hull and its potential usage in the design phase.

Keywords: planing hulls, stepped hulls, wake shape, numerical simulation, hydrodynamics

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Authors: Lavinia B. Dulla

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The exploration study of the fuzzy regression approach attempts to present that fuzzy regression can be used as a possible alternative to classical regression. It likewise seeks to assess the differences and characteristics of simple linear regression and fuzzy regression using the width of prediction interval, mean absolute deviation, and variance of residuals. Based on the simple linear regression model, the fuzzy regression approach is worth considering as an alternative to simple linear regression when the sample size is between 10 and 20. As the sample size increases, the fuzzy regression approach is not applicable to use since the assumption regarding large sample size is already operating within the framework of simple linear regression. Nonetheless, it can be suggested for a practical alternative when decisions often have to be made on the basis of small data.

Keywords: fuzzy regression approach, minimum fuzziness criterion, interval regression, prediction interval

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Authors: Yildirim Ortaoglan

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The attempt to make thought school-like by fitting it into various frameworks with the institutionalization of it is almost simultaneous with philosophy itself. What once sprouted in the “academia” of old has institutionalized under the enlightenment's light, becoming the fundamental space reflecting the spirit of its age. However, the shift from the thinking temple where truth's knowledge was sought to functional spaces where power/power relations are constructed indicates a significant rupture in the meaning of school. Therefore, a genealogical inquiry into the meaning of the school can provide us with a path toward understanding how it should be approached in contemporary times. From this perspective, it is essential to highlight how power/power relations operate in the school in terms of disciplinary practices, temporal management, and spatial organization to construct a distinct subjectivation. Recognizing that the changing and evolving nature of education is related to the structure of space can be understood by revealing how disciplinary power and bio-power, two fundamental aspects of genealogical research, operate. In disciplinary power, the relationship of the subject with discipline, temporal management, and space is about improvement and normalization, while in biopower, it manifests in maximizing utility, increasing free time, and constructing spaces that seem more vital. These indicators not only facilitate the formation of students as a subjectivation but also enable the condition of the possibility of power/power relations. Because power is not applied to subjects but used by them for passage, and behind this lies the idea that the individual is already one of the components of power. As one of the components of power, in terms of subjectivation type, the student is one of the primary targets of power relations. Therefore, conducting a genealogical inquiry of the student as a type of subjectivation and the school as its living area from the philosophical foundations of education may offer a new opportunity for thinking about the contemporary crisis of thought. Within the framework of this possibility, our investigation will consider which aspects of the school and the student, brought together for educational purposes, can be thought of within and beyond power/power relations.

Keywords: power, education, space, school, student, discipline

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Authors: Mariayee Doraisamy, Suhaimi bin Ibrahim, Mohd Naz’ri Mahrin

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There are several methods to monitor software projects and the objective for monitoring is to ensure that the software projects are developed and delivered successfully. A performance measurement is a method that is closely associated with monitoring and it can be scrutinized by looking at two important attributes which are efficiency and effectiveness both of which are factors that are important for the success of a software project. Consequently, a successful steering is achieved by monitoring and controlling a software project via the performance measurement criteria and metrics. Hence, this paper is aimed at identifying the performance measurement criteria and the metrics for monitoring the performance of a software project by using the Goal Question Metrics (GQM) approach. The GQM approach is utilized to ensure that the identified metrics are reliable and useful. These identified metrics are useful guidelines for project managers to monitor the performance of their software projects.

Keywords: component, software project performance, goal question metrics, performance measurement criteria, metrics

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Authors: Konstantinos Sofianos, Michael Stefanidakis

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Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in the field of education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at any time, in any place, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

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Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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Authors: Kaewkarn Phuangsombat, Arthit Phuangsombat, Anupun Terdwongworakul

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Hard seeds will not grow and can cause mold in sprouting process. Thus, the hard seeds need to be separated from the normal seeds. Near infrared hyperspectral imaging in a range of 900 to 1700 nm was implemented to develop a model by partial least squares discriminant analysis to discriminate the hard seeds from the normal seeds. The orientation of the seeds was also studied to compare the performance of the models. The model based on hilum-up orientation achieved the best result giving the coefficient of determination of 0.98, and root mean square error of prediction of 0.07 with classification accuracy was equal to 100%.

Keywords: mung bean, near infrared, germinatability, hard seed

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Authors: Ummu Salma Al Azizah, Herri Mulyono, Anisa Mauliata Suryana

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The significance of corporate governance regarding to the agency problem have been transparent. This study examine the impact of corporate governance on the performance of Islamic banking in Indonesia. By using fixed effect model and added some control variable, the current study try to explore the correlation between the theoretical framework on corporate governance, such as agency theory and risk management theory. The bank performance (Return on Asset and Return on Equity) which are operational performance and financial performance. And Corporate governance based on Board size, CEO duality, Audit committee and Shariah supervisory board. The limitation of this study only focus on the Islamic banks performance from year 2015 to 2020. The study fill the gap in the literature by addressing the issue of corporate governance on Islamic banks performance in Indonesia.

Keywords: corporate governance, financial performance, islamic banks, listed companies, Indonesia

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Authors: Mansour Abdi

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The aim of this study has been the investigation of coronavirus influence/impact on social adjustment and depression of Arak University students. The samples of study are 100 available female students at Arak University. They were assessed by the Bell Social Adjustment Questionnaire and Beck Depression. They were asked to answer two situations before the corona outbreak and the present. The result of evaluating/assessing the difference between social adjustment before and after coronavirus was not significant but, the averages indicate a decrease in the adjustment of students before and after the coronavirus. Meanwhile, there was no significant difference in depression findings but, in the present, the average amount of depression indicated an increase than its amount before the corona.

Keywords: depression, social adjustment student, coronavirus, student

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Authors: Sami Houry

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Complex systems exhibit universal characteristics as they near a tipping point. Among them are common generic early warning signals which precede critical transitions. These signals include: critical slowing down in which the rate of recovery from perturbations decreases over time; an increase in the variance of the state variable; an increase in the skewness of the state variable; an increase in the autocorrelations of the state variable; flickering between different states; and an increase in spatial correlations over time. The presence of the signals has management implications, as the identification of the signals near the tipping point could allow management to identify intervention points. Despite the applications of the generic early warning signals in various scientific fields, such as fisheries, ecology and finance, a review of literature did not identify any applications that address the program student withdrawal problem at the undergraduate distance universities. This area could benefit from the application of generic early warning signals as the program withdrawal rate amongst distance students is higher than the program withdrawal rate at face-to-face conventional universities. This research specifically assessed the generic early warning signals through an intensive case study of undergraduate program student withdrawal at a Canadian distance university. The university is non-cohort based due to its system of continuous course enrollment where students can enroll in a course at the beginning of every month. The assessment of the signals was achieved through the comparison of the incidences of generic early warning signals among students who withdrew or simply became inactive in their undergraduate program of study, the true positives, to the incidences of the generic early warning signals among graduates, the false positives. This was achieved through significance testing. Research findings showed support for the signal pertaining to the rise in flickering which is represented in the increase in the student’s non-pass rates prior to withdrawing from a program; moderate support for the signals of critical slowing down as reflected in the increase in the time a student spends in a course; and moderate support for the signals on increase in autocorrelation and increase in variance in the grade variable. The findings did not support the signal on the increase in skewness of the grade variable. The research also proposes a new signal based on the fractal-like characteristic of student behavior. The research also sought to extend knowledge by investigating whether the emergence of a program withdrawal status is self-similar or fractal-like at multiple levels of observation, specifically the program level and the course level. In other words, whether the act of withdrawal at the program level is also present at the course level. The findings moderately supported self-similarity as a potential signal. Overall, the assessment of the signals suggests that the signals, with the exception with the increase of skewness, could be utilized as a predictive management tool and potentially add one more tool, the fractal-like characteristic of withdrawal, as an additional signal in addressing the student program withdrawal problem.

Keywords: critical transitions, fractals, generic early warning signals, program student withdrawal

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Authors: Emily Jin, Harry Sharples, Anne Weist

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Introduction: NICE Evidence Search Student Champion Scheme is a peer-assisted learning scheme that aims to improve the routine use of evidence-based information by future health and social care staff. The focus is on the NICE evidence search portal that provides selected information from more than 800 reliable health, social care, and medicines sources, including up-to-date guidelines and information for the public. This paper aims to evaluate the effectiveness of the scheme when implemented in Liverpool School of Medicine and to understand the experiences of those attending. Methods: Twelve student champions were recruited and trained in February 2020 as peer tutors during a workshop facilitated by NICE. Cascade sessions were then organised and delivered on an optional basis for students, in small groups of < 10 to approximately 70 attendees. Surveys were acquired immediately before and 8-12 weeks after cascade sessions (n=47 and 45 respectively). Data from these surveys facilitated the analysis of the scheme. Results: Surveys demonstrated 74% of all attendees frequently searched for health and social care information online as a part of their studies. However, only 15% of attendees reported having prior formal training on searching for health information, despite receiving such training earlier on in the curriculum. After attending cascade sessions, students reported a 58% increase in confidence when searching for information using evidence search, from a pre-session a baseline of 36%. Conclusion: NICE Evidence Search Student Champion Scheme provided clear benefits for attending students, increasing confidence in searching for peer-reviewed, mainly secondary sources of health information. The lack of reported training represents the unmet need that the champion scheme satisfies, and this likely benefits student champions as well as attendees. Increasing confidence in searching for healthcare information online may support future evidence-based decision-making.

Keywords: evidence-based medicine, NICE, medical education, medical school, peer-assisted learning

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Authors: Kwong Yeung

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Theories about strategic purchasing and quality performance are underdeveloped. Understanding the evolving role of purchasing from reactive to proactive is a pressing strategic issue. Using survey responses from 176 manufacturing and electronics industry professionals, we study the relationships between strategic purchasing and supply chain partners’ quality performance to answer the following questions: Can transaction cost economics be used to elucidate the strategic purchasing-quality performance relationship? Is this strategic purchasing-quality performance relationship moderated by critical item analysis? The findings indicate that critical item analysis positively and significantly moderates the strategic purchasing-quality performance relationship.

Keywords: critical item analysis, moderation, quality performance, strategic purchasing, transaction cost economics

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Authors: M. Al-Jepoori, D. Bennett

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Teaching Object-Oriented Programming (OOP) as part of a Computing-related university degree is a very difficult task; the road to ensuring that students are actually learning object oriented concepts is unclear, as students often find it difficult to understand the concept of objects and their behavior. This problem is especially obvious in advanced programming modules where Design Pattern and advanced programming features such as Multi-threading and animated GUI are introduced. Looking at the students’ performance at their final year on a university course, it was obvious that the level of students’ understanding of OOP varies to a high degree from one student to another. Students who aim at the production of Games do very well in the advanced programming module. However, the students’ assessment results of the last few years were relatively low; for example, in 2016-2017, the first quartile of marks were as low as 24.5 and the third quartile was 63.5. It is obvious that many students were not confident or competent enough in their programming skills. In this paper, the reasons behind poor performance in Advanced OOP modules are investigated, and a suggested practice for teaching OOP based on a complex case study is described and evaluated.

Keywords: complex programming case study, design pattern, learning advanced programming, object oriented programming

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Authors: Farhad Shafiepour Motlagh, Narges Salehi

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Purpose: The purpose of this study was to support student strategies for virtual learning in the learning management system. Methodology: The research method was based on grounded theory. The statistical population included all the articles of the ten years 2022-2010, and the sampling method was purposeful to the extent of theoretical saturation (n=31 ). Data collection was done by referring to the authoritative scientific databases of Emerald, Springer, Elsevier, Google Scholar, Sage Publication, and Science Direct. For data analysis, open coding, axial coding, and selective coding were used. Results: The results showed that causal conditions include cognitive empowerment (comprehension, analysis, composition), emotional empowerment (learning motivation, involvement in the learning system, enthusiasm for learning), psychomotor empowerment (learning to master, internalizing learning skills, creativity in learning). Conclusion: Supporting students requires their empowerment in three dimensions: cognitive, emotional empowerment, and psychomotor empowerment. In such a way that by introducing them to enter the learning management system, the capacities of the system, the toolkit of learning in the system, improve the motivation to learn in them, and in such a case, by learning more in the learning management system, they will reach mastery learning.

Keywords: student support, virtual education, learning management system, electronic

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Authors: Kari M. Solomon

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Companies with a culture accepting of change management and performance excellence are better suited to determine their sustainability performance and impacts. A mature corporate culture supportive of performance excellence is better positioned to integrate sustainability management tools into their standard business strategy. Companies use various sustainability management tools and reporting standards to communicate levels of sustainability performance to their stakeholders, more often focusing on shareholders and investors. A research gap remains in understanding how companies adapt business excellence models to define corporate sustainability performance. A content analysis of medium-sized enterprises using corporate sustainability reports and business excellence models reveals the challenges and opportunities of reporting sustainability performance in the context of organizational excellence. The outcomes of this content analysis contribute knowledge on the resources needed for companies to build sustainability performance management systems integral to existing management systems. The findings of this research inform academic research areas of corporate sustainability performance, the business community contributing to sustainable development initiatives, and integrating sustainable development issues into business excellence models. There are potential research links between sustainability performance management and the alignment of the United Nations Sustainable Development Goals (UN SDGs) when organizations promote a culture of performance or business excellence.

Keywords: business excellence, corporate sustainability, performance excellence, sustainability performance

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Authors: Dixit Garg, S. Luthra, A. Haleem

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During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection among society. Organizations are trying to achieve the goals of improvement in environment, low cost, high quality, flexibility and more customer satisfaction. Performance measurement frameworks are very useful to monitor the performance of any organization. The basic goal of this paper is to identify performance measures and ranking of these performance measures of GSCM performance measurement towards sustainability framework. Five perspectives (Environment, Economic, Social, Operational and Cost performances) and nineteen performance measures of GSCM performance towards sustainability have been have been identified from extensive literature review. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of these performance perspectives and measures. All pair comparisons in AHP have been made on the basis on the experts’ opinions (selected from academia and industry). Ranking of these performance perspectives and measures will help to understand the importance of environmental, economic, social, operational performances, and cost performances in the supply chain.

Keywords: analytical hierarchy process, green supply chain management, performance measures, sustainability

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Authors: Kiana Williams

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The purpose of this case study was to examine beginning music teachers’ perspectives of cultural relevance in relation to music instruction in urban school settings within a large Southwestern city. Research questions focused on the role of student culture in beginning music teachers’ instruction. Data were collected based on Seidman’s (2013) three interview series, consisting of audio recordings from two semi-structured individual interviews for each participant, a 15-20-minute video recording from each participant teaching in their classroom, and an audio recording of one focus group interview. Participants included three beginning music teachers currently employed in urban schools in a major metropolitan city in the Southern United States. In this study, a teacher was considered a beginning teacher if they had zero to three years of experience teaching music in urban school settings. The results revealed three broad themes related to connectivity and relatability, concerts, and differentiated instruction. Implications for current music educators as well as music teacher educators in higher education are included in this study. Further research should consider examining the effect of culturally relevant pedagogy on student retention in urban school music programs.

Keywords: culture, instruction, music, pedagogy, teacher, urban

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

Abstract:

In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

Procedia PDF Downloads 127

Authors: Natacha Jesus-Silva, Carla S. Pereira, Natercia Durao, Maria Das Dores Formosinho, Cristina Costa-Lobo

Abstract:

Any assessment process, by its very nature, raises a wide range of doubts, uncertainties, and insecurities of all kinds. The evaluation process should be ethically irreproachable, treating each and every one of the evaluated according to a conduct that ensures that the process is fair, contributing to all recognize and feel well with the processes and results of the evaluation. This is a very important starting point and implies that positive and constructive conceptions and attitudes are developed regarding the evaluation of teaching performance, where students' responsibility is desired. It is not uncommon to find teachers feeling threatened at various levels, in particular as regards their autonomy and their professional dignity. Evaluation must be useful in that it should enable decisions to be taken to improve teacher performance, the quality of teaching or the learning climate of the school. This study is part of a research project whose main objective is to identify, select, evaluate and synthesize the available evidence on Quality Indicators in Higher Education. In this work, the 01 parameters resulting from pedagogical surveys in a Portuguese higher education institution in the north of the country will be presented, surveys for the 2015/2016 school year, presented to 1751 students, in a total of 11 degrees and 18 master's degrees. It has analyzed the evaluation made by students with respect to the performance of a group of 68 teachers working full time. This paper presents the lessons learned in the last three academic years, allowing for the identification of the effects on the following areas: teaching strategies and methodologies, capacity of systematization, learning climate, creation of conditions for active student participation. This paper describes the procedures resulting from the descriptive analysis (frequency analysis, descriptive measures and association measures) and inferential analysis (ANOVA one-way, MANOVA one-way, MANOVA two-way and correlation analysis).

Keywords: teaching performance, higher education, students responsibility, indicators of teaching management

Procedia PDF Downloads 265