Search results for: student performance prediction

Authors: Yun Chan Lee

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Background: End-of-life care is a large area of all nursing practice and student nurses are likely to meet dying patients in many placement areas. It is therefore important to understand the emotional responses and coping strategies of student nurses in order for nursing education systems to have some appreciation of how nursing students might be supported in the future. Methodology: This research used a qualitative phenomenological approach. Six student nurses understanding a degree-level adult nursing course were interviewed. Their responses to questions were analyzed using interpretative phenomenological analysis. Finding: The findings identified 3 main themes. First, the common experience of ‘unpreparedness’. A very small number of participants felt that this was unavoidable and that ‘no preparation is possible’, the majority felt that they were unprepared because of ‘insufficient input’ from the university and as a result of wider ‘social taboos’ around death and dying. The second theme showed that emotions were affected by ‘the personal connection to the patient’ and the important sub-themes of ‘the evoking of memories’, ‘involvement in care’ and ‘sense of responsibility’. The third theme, the coping strategies used by students, seemed to fall into two broad areas those ‘internal’ with the student and those ‘external’. In terms of the internal coping strategies, ‘detachment’, ‘faith’, ‘rationalization’ and ‘reflective skills’ are the important components of this part. Regarding the external coping strategies, ‘clinical staff’ and ‘the importance of family and friends’ are the importance of accessing external forms of support. Implication: It is clear that student nurses are affected emotionally by caring for dying patients and many of them have apprehension even before they begin on their placements but very often this is unspoken. Those anxieties before the placement become more pronounced during and continue after the placements. This has implications for when support is offered and possibly its duration. Another significant point of the study is that participants often highlighted their wish to speak to qualified nurses after their experiences of being involved in end-of-life care and especially when they had been present at the time of death. Many of the students spoke that qualified nurses were not available to them. This seemed to be due to a number of reasons. Because the qualified nurses were not available, students had to make use of family members and friends to talk to. Consequently, the implication of this study is not only to educate student nurses but also to educate the qualified mentors on the importance of providing emotional support to students.

Keywords: nursing students, coping strategies, end-of-life care, emotional responses

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Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

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large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

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Authors: Mohammed Nishat, Ahmad Ghazali

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This study empirically examines the corporate governance and firm performance, and tries to evaluate the governance, ownership and control related variables which are hypothesized to affect on firms performance. This study tries to evaluate the effectiveness of corporate governance mechanism to achieve high level performance among companies listed on the Karachi Stock Exchange (KSE) over the period from 2005 to 2008. To measure the firm performance level this research uses three measures of performance; Return on assets (ROA), Return on Equity (ROE) and Tobin’s Q. To link the performance of firms with the corporate governance three categories of corporate governance variables are tested which includes governance, ownership and control related variables. Fixed effect regression model is used to test the link between corporate governance and firm performance for 267 KSE listed Pakistani firms. The result shows that corporate governance variables such as percentage block holding by individuals have positive impact on firm performance. When CEO is also the chairperson of board then it is found that firm performance is adversely affected. Also negative relationship is found between share held by insiders and performance of firm. Leverage has negative impact on the performance of the firm and firm size is positively related with the firms performance.

Keywords: corporate governance, performance, agency cost, Karachi stock market

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Authors: Daniel Martinez, Tim de Leeuw, Stefan Haefliger

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The challenges of managing a large and geographically dispersed R&D organization have been further increasing during the past years, concentrating on the leverage of a geo-graphically dispersed body of knowledge in an efficient and effective manner. In order to reduce complexity and improve performance, firms introduce product modularity as one key element for global R&D network teams to develop their products and projects in collaboration. However, empirical studies on the effects of product modularity on innovation performance are really scant. Furthermore, some researchers have suggested that product modularity promotes innovation performance, while others argue that it inhibits innovation performance. This research fills this gap by investigating the impact of product modularity on various dimensions of innovation performance, i.e. effectiveness and efficiency. By constructing the theoretical framework, this study suggests that that there is an inverted U-shaped relationship between product modularity and innovation performance. Moreover, this research work suggests that the optimum of innovation performance efficiency will be at a higher level than innovation performance effectiveness at a given product modularity level.

Keywords: modularity, innovation performance, networks, R&D, collaboration

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Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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Authors: Babatunde Kasim Oladele

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This current study investigated students’ characteristics as factors that influence Mathematics Achievement of junior secondary school students. The study adopted a descriptive survey design. The population of the study was one hundred and twenty-three (123) JSS students of secondary schools in Ibadan North Local Government in Oyo State. A Mathematics achievement test and three questionnaires on student’s self-efficacy belief, attitude, and learning style were the instruments used. Prior to the administration of the constructed mathematics achievement test, 100-item mathematics was subjected to the expert review, and items analysis was carried out. Fifty items were retained. The Cronbach Alpha reliability coefficients of the instruments were 0.71, 0.76, and 0.83, respectively. Collected data were analysed using the frequency count, percentages, mean, standard deviation, and Path Analysis in Amos SPSS Version 20. Students characteristics: gender, age, self-efficacy, attitude and learning style had positive direct effects on students’ achievement in Mathematics as indicated by their respective beta weights (β = 0.36, 0.203, 0.92, 0.079, 0.69 p < 0.05). Consequently, the study concluded that student’s characteristics (Age, gender, and learning style) explained a significant part of the variability in students’ achievement in Mathematics.

Keywords: mathematics achievement, students’ characteristics, junior secondary school, Ibadan

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Authors: Abolaji Mayowa Akinyele

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The purpose of this study was to investigate student’s awareness, Knowledge and understanding of environmental issues for sustainable development. Findings revealed that; despite the positive attitude shown by students towards environmental education, a relatively low level of understanding of environmental concept was recorded in school settings regardless of efforts by government and other environmental agencies at creating awareness about environmental related issues. This brought about the investigation of students environmental education knowledge in high school settings. About 205 Students were randomly selected for data collection using validated instruments titled student’s knowledge and attitude questionnaire as well as student’s response to questions (interview) concerning global warming. T-test statistics, chi-square and simple percentage were the major statistical tools employed in data analysis. This study revealed that environment based-education (school curriculum) as well as efforts by government/environmental agencies (mass media) plays a major role in promoting students understanding, of environmental concepts, awareness of major environmental issues and positive attitude towards natural environment.

Keywords: environmental issues, sustainable development, students attitude, students knowledge

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Authors: Abrar Ajmal

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This quantitative study explored elementary school teachers' pedagogical content knowledge and effects on grade 8 students' achievement in Punjab, Pakistan. A teacher sample (N=100) rated competencies across inquiry-focused teaching, conceptual building, interaction practices and peer collaboration promotion. A student sample (N=120) self-reported academic abilities, intrinsic motivation, help-seeking and accountability. Findings reveal teachers highly endorse learner-centric strategies, although peer interaction promotion seems less common currently. Meanwhile, significant gender disparities in self-perceived expertise emerge, favouring female over male educators across all facets measured. Additionally, teachers' knowledge positively—and significantly—correlates with student achievement overall and for both genders, highlighting the importance of professional enrichment. However, female pupils demonstrate greater confidence, drive, utilization of academic support, and ownership over learning than male counterparts. Recommendations include ongoing teacher training, targeted competency building for male students and teachers, leveraging gender peer collaboration similarities, and holistic female support amid widening divides. Sustaining instructional quality through empowering, equitable practices that nurture disadvantaged and gifted learners alike can spur systemic improvements. Ultimately, the fire line confirms the interrelations between teachers' multifaceted knowledge and student success.

Keywords: pedagogical knowledge, academic achievement, teacher gender differences, student gender differences, empowering instruction

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Authors: Amanat Ali, Muhammad S. Al-Siyabi, Mostafa I. Waly, Hashem Al-Kilani

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In a cross-sectional research design, we assessed the nutrient intake, nutritional status, nutritional knowledge and dietary habits of Sultan Qaboos University (SQU) student athletes. A total of 71 (49 male and 22 female) student athletes with a mean age of 21.0 ± 1.81 and 19.32 ± 0.72 years and body mass index (BMI) of 22.51 ± 1.98 and 20.34 ± 2.97 kg/m2 for male and female respectively, participated in this study. A study questionnaire consisting of 2 sections was distributed to the participants. Section I included 18 questions regarding the demographic information, whereas the Section II consisted of 20 questions regarding the nutrition knowledge. The dietary intake of participants was collected by using a 7-days food diary identifying the frequency as well as the variety of food consumption. Significant differences (P < 0.05) were observed in the main sources of nutrition information used by the male and female athletes. Male athletes mainly had most of the nutrition information from friends (17%) whereas female athletes relied mainly on the family (20%). More female athletes (20%) were using TV as a source of nutrition information as compared to male athletes (15%). Both male and female athletes had the minimum nutrition information from dietitians and physicians. Significant (P < 0.05) differences were also observed in the nutritional knowledge and dietary habits scores of male and female athletes, which were 57 % and 49 %, respectively. Male athletes were classified to have fair nutritional knowledge and dietary habits, whereas the female athletes had poor nutritional knowledge and dietary habits. The average daily energy intake of male athletes was 2595 ± 358 kcal/day. Carbohydrate, fat, and protein contributed 64%, 22%, and 14%, of the total energy intake for the male athletes, respectively. The energy and macronutrients intake of male athletes was within the recommended dietary intake. The results indicated some gaps in the nutritional knowledge of SQU student athletes and suggest that there is a need for developing strategies in counseling and teaching the athletes to improve their nutritional knowledge and dietary habits.

Keywords: nutrient assessment, nutritional knowledge, dietary habits, Omani University athletes

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Authors: Brad Curabba

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Utilising active, process-based learning methods to improve critical thinking and writing skills of second language (L2) writers brings unique challenges. To comprehensively satisfy different learners' needs, when commenting on student work, instructors can embed multiple feedback methods so that the capstone of their abilities as writers can be achieved. This research project assesses faculty and student perceptions regarding the effectiveness of various feedback practices used in process-based writing classrooms with L2 students at the American University of Sharjah (AUS). In addition, the research explores the challenges encountered by faculty during the provision of feedback practices. The quantitative research findings are based on two concurrent electronically distributed anonymous surveys; one aimed at students who have just completed a process-based writing course, and the other at instructors who delivered these courses. The student sample is drawn from multiple sections of Academic Writing I and II, and the faculty survey was distributed among the Department of Writing Studies (DWS) faculty. Our findings strongly suggest that all methods of feedback are deemed equally important by both students and faculty. Students, in particular, find process writing and its feedback practices to have greatly contributed to their writing proficiency.

Keywords: process writing, feedback, formative feedback, composition, reflection

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Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed

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Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

Keywords: dissolved gas-in-oil analysis, fuzzy logic, power transformer, prediction

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Yasir E. Mohieldeen

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Qatar is one of the most water scarce countries in the World. In 2014, the average per capita rainfall was less than 29 m3/y/ca, while the global average is 6,000 m3/y/ca. However, the per capita water consumption in Qatar is among the highest in the World: more than 500 liters per person per day, whereas the global average is 160 liters per person per day. Since the early 2000s, Qatar has been relying heavily on desalinated water from the Arabian Gulf as the main source of fresh water. In 2009, about 99.9% of the total potable water produced was desalinated. Reliance on desalinated water makes Qatar very vulnerable to water related natural disasters, such as the red-tide phenomenon. Qatar’s strategic water reserve lasts for only 7 days. In case of red-tide outbreak, the country would not be able to desalinate water for days, let alone the months that this disaster would bring about (as it clogs the desalination equipment). The 2008-09 red-tide outbreak, for instance, lasted for more than eight months and forced the closure of desalination plants in the region for weeks. This study aims at identifying favorite conditions for red-tide outbreaks, using satellite data along with in-situ measurements. This identification would allow the prediction of these outbreaks and their hotspots. Prediction and monitoring of outbreaks are crucial to water security in the country, as different measures could be put in place in advance to prevent an outbreak and mitigate its impact if it happened. Red-tide outbreaks are detected using different algorithms for chlorophyll concentration in the Gulf waters. Vegetation indices, such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used along with Surface Algae Bloom Index (SABI) to detect known outbreaks. MODIS (or Moderate Resolution Imaging Spectroradiometer) bands are used to calculate these indices. A red-tide outbreaks atlas in the Arabian Gulf is being produced. Prediction of red-tide outbreaks ahead of their occurrences would give critical information on possible water-shortage in the country. Detecting known outbreaks in the past few decades and related parameters (e.g. water salinity, water surface temperature, nutrition, sandstorms, … etc) enables the identification of favorite conditions of red-tide outbreak that are key to the prediction of these outbreaks.

Keywords: Arabian Gulf, MODIS, red-tide detection, strategic water reserve, water desalination

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Authors: Dariush Jafari, S. Mostafa Nowee

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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.

Keywords: thermodynamic modeling, ANN, solubility, ternary electrolyte system

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Timothy J. Grebec

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This study investigated whether using a voice dictation software program (i.e., Google Voice Typing) has an impact on student writing quality. The research took place in a third-grade general education classroom in a suburban school setting. Because the study involved minors, all data was encrypted and deidentified before analysis. The students completed a series of writings prior to the beginning of the intervention to determine their thoughts and skill level with writing. During the intervention phase, the students were introduced to the voice dictation software, given an opportunity to practice using it, and then assigned writing prompts to be completed using the software. The prompts written by nineteen student participants and surveys of student opinions on writing established a baseline for the study. The data showed that using the dictation software resulted in a 34% increase in the response quality (compared to the Pennsylvania State Standardized Assessment [PSSA] writing guidelines). Of particular interest was the increase in students' proficiency in demonstrating mastery of the English language and conventions and elaborating on the content. Although this type of research is relatively no, it has the potential to reshape the strategies educators have at their disposal when instructing students on written language.

Keywords: educational technology, accommodations, students with disabilities, writing instruction, 21st century education

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Authors: Marinel Dayawon

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Student participation in classroom activities is vital in the teaching- learning the process as it develops self-confidence, social relationships and good academic performance of students. It is the teacher’s empathetic manner and creativity to create solutions that encourage teamwork and mutual support while dropping the academic competition within the class that hinder every shy student to walk with courage and talk with conviction because they consider their ideas, weak, as compared to the bright students. This study aimed to explore the different design thinking strategies that will change the mindset of shy students in classroom activities, maximizing their participation in all given tasks while sharing their views through ideation and providing them a wider world through compromise agreement within the members of the group, sensitivity to one’s idea, thus, arriving at a collective decision in the development of a prototype that indicates improvement in their classroom involvement. The study used the qualitative type of research. Triangulation is done through participant observation, focus group discussion and interview, documented through photos and videos. The respondents were the second- year Bachelor of Secondary Education students of the Institute of Teacher Education at Isabela State University- Cauayan City Campus. The result of the study revealed that reticent students when involved in game activities through a slap and tap method, writing their clustered ideas, using sticky notes is excited in sharing ideas as it doesn’t use oral communication. It is also observed after three weeks of using the design thinking strategies; shy students volunteer as secretary, rapporteur or group leader in the team- building activities as it represents the ideas of the heterogeneous group, removing the individual identity of the ideas. Superior students learned to listen to the ideas of the reticent students and involved them in the prototyping process of designing a remediation program for high school students showing reticence in the classroom, making their experience as a benchmark. The strategies made a 360- degrees transformation of the shy students, producing their journal log, in their journey to being open. Thus, faculty members are now adopting the design thinking approach.

Keywords: design thinking activities, qualitative, reticent students, Isabela, Philippines

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Authors: Nina Dzamashvili Fogelström

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This paper examines concepts of Game-Based Learning and Gamification. Conducted literature survey found an increased interest in the academia in these concepts, limited evidence of a positive effect on student motivation and academic performance, but also certain scepticism for adding games to traditional educational activities. A small-scale empirical study presented in this paper aims to evaluate student experience and usefulness of GameBased Learning and Gamification for a better understanding of the threshold concepts in software engineering project courses. The participants of the study were 22 second year students from bachelor’s program in software engineering at Blekinge Institute of Technology. As a part of the course instruction, the students were introduced to a digital game specifically designed to simulate agile software project. The game mechanics were designed as to allow manipulation of the agile concept of team velocity. After the application of the game, the students were surveyed to measure the degree of a perceived increase in understanding of the studied threshold concept. The students were also asked whether they would like to have games included in their education. The results show that majority of the students found the game helpful in increasing their understanding of the threshold concept. Most of the students have indicated that they would like to see games included in their education. These results are encouraging. Since the study was of small scale and based on convenience sampling, more studies in the area are recommended.

Keywords: agile development, gamification, game based learning, digital games, software engineering, threshold concepts

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Authors: Maria Da Glória Diniz De Almeida, Andreia M. P. Salgado

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This paper aims to present the creation of a mentoring program to be applied in developing future junior industrial engineers acting professionally. Its objective is to contribute to a better professional performance as engineers. It is a case-study for the RIP region (including the cities of Resende, Itatiaia and Porto Real), which is located in an industrial area in Rio de Janeiro State, in Brazil. As a result, 87% of mentors and mentees approved the program as efficient, based on the initial targets.

Keywords: mentoring program, mentors and mentees, student professional development, young engineers education

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Authors: Matthew Montebello

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Student engagement within a virtual learning environment generates masses of data points that can significantly contribute to the learning analytics that lead to decision support. Ideally, similar data is collected during student interaction with a physical learning space, and as a consequence, data is present at a large scale, even in relatively small classes. In this paper, we report of such an occurrence during classes held in a HiFlex modality as we investigate the advantages of adopting such a methodology. We plan to take full advantage of the learner-generated data in an attempt to further enhance the effectiveness of the adopted learning environment. This could shed crucial light on operating modalities that higher education institutions around the world will switch to in a post-COVID era.

Keywords: HiFlex, big data in higher education, learning analytics, virtual learning environment

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Authors: Deepak Raj Bhat, Ryuichi Yatabe

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In this study, a residual-state creep failure model was developed based on the residual-state creep test results of clayey soils. To develop the proposed model, the regression analyses were done by using the R. The model results of the failure time (tf) and critical displacement (δc) were compared with experimental results and found in close agreements to each others. It is expected that the proposed regression model for residual-state creep failure will be more useful for the prediction of displacement of different clayey soils in the future.

Keywords: regression model, residual-state creep failure, displacement prediction, clayey soils

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Authors: Faride Hashemiannejad, Shima Oloomi

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Imagination is one of the important elements of creative thinking which as a skill needs attention by the educational system. Although most students learn reading, writing, and arithmetic skills well, they lack high level thinking skills like creative thinking. Therefore, in the information age and in the beginning of entry to knowledge-based society, the educational system needs to think over its goals and mission, and concentrate on creativity-based curriculum. From among curriculum elements-goals, content, method and evaluation “method” is a major domain whose reform can pave the way for fostering imagination and creativity. The purpose of this study was examining the relationship between creativity development and curriculum. Research questions were: (1) is there a relationship between the cognitive-emotional structure of the classroom and creativity development? (2) Is there a relationship between the environmental-social structure of the classroom and creativity development? (3) Is there a relationship between the thinking structure of the classroom and creativity development? (4) Is there a relationship between the physical structure of the classroom and creativity development? (5) Is there a relationship between the instructional structure of the classroom and creativity development? Method: This research is a applied research and the research method is Correlational research. Participants: The total number of participants in this study included 894 students from High school through 11th grade from seven schools of seven zones in Mashad city. Sampling Plan: Sampling was selected based on Random Multi State. Measurement: The dependent measure in this study was: (a) the Test of Creative Thinking, (b) The researcher-made questionnaire includes five fragments, cognitive, emotional structure, environmental social structure, thinking structure, physical structure, and instructional structure. The Results Show: There was significant relationship between the cognitive-emotional structure of the classroom and student’s creativity development (sig=0.139). There was significant relationship between the environmental-social structure of the classroom and student’s creativity development (sig=0.006). There was significant relationship between the thinking structure of the classroom and student’s creativity development (sig=0.004). There was not significant relationship between the physical structure of the classroom and student’s creativity development (sig=0.215). There was significant relationship between the instructional structure of the classroom and student’s creativity development (sig=0.003). These findings denote if students feel secure, calm and confident, they can experience creative learning. Also the quality of coping with students’ questions, imaginations and risks can influence on their creativity development.

Keywords: imagination, creativity, curriculum, bioinformatics, biomedicine

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Edith Esparza-Young, Ángel M. Matos, Yaritza Gonzalez, Kirthana Sugunathevan

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Introduction: This research describes the existing medical school program which supports a multicultural setting and bilingualism. The rise of Spanish speakers in the United States has led to the recruitment of bilingual medical students who can serve the evolving demographics. This paper includes anecdotal evidence, narratives and the latest research on the outcomes of supporting a multilingual academic experience in medical school and beyond. People in the United States will continue to need health care from physicians who have experience with multicultural competence. Physicians who are bilingual and possess effective communication skills will be in high demand. Methodologies: This research is descriptive. Through this descriptive research, the researcher will describe the qualities and characteristics of the existing medical school programs, curriculum, and student services. Additionally, the researcher will shed light on the existing curriculum in the medical school and also describe specific programs which help to serve as safety nets to support diverse populations. The method included observations of the existing program and the implementation of the medical school program, specifically the Accelerated Review Program, the Language Education and Professional Communication Program, student organizations and the Global Health Institute. Concluding Statement: This research identified and described characteristics of the medical school’s program. The research explained and described the current and present phenomenon of this medical program, which has focused on increasing the graduation of bilingual and minority physicians. The findings are based on observations of the curriculum, programs and student organizations which evolves and remains innovative to stay current with student enrollment.

Keywords: bilingual, English, medicine, doctor

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Authors: Hassan Baji, Chun-Qing Li, Wei Yang

Abstract:

Water seepage is one of the most common causes of damage in tunnel structures, which can cause direct and indirect e.g. reinforcement corrosion and calcium leaching damages. Estimation of water seepage or inflow is one of the main challenges in probabilistic assessment of tunnels. The methodology proposed in this study is an attempt for mathematically modeling the water seepage in tunnel structures and further predicting its service life. Using the time-dependent reliability, water seepage is formulated as a failure mode, which can be used for prediction of service life. Application of the formulated seepage failure mode to a case study tunnel is presented.

Keywords: water seepage, tunnels, time-dependent reliability, service life

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Authors: Geng Xiangren, Liu Lei, Gui Ye-Wei, Tang Wei, Wang An-ling

Abstract:

The malfunction of thermal protection system (TPS) caused by aerodynamic heating is a latent trouble to aircraft structure safety. Accurately predicting the structure temperature field is quite important for the TPS design of hypersonic vehicle. Since Thornton’s work in 1988, the coupled method of aerodynamic heating and heat transfer has developed rapidly. However, little attention has been paid to the influence of structural deformation on aerodynamic heating and structural temperature field. In the flight, especially the long-endurance flight, the structural deformation, caused by the aerodynamic heating and temperature rise, has a direct impact on the aerodynamic heating and structural temperature field. Thus, the coupled interaction cannot be neglected. In this paper, based on the method of static aero-thermo-elasticity, considering the influence of aero-thermo-elasticity deformation, the aerodynamic heating and heat transfer coupled results of hypersonic vehicle wing model were calculated. The results show that, for the low-curvature region, such as fuselage or center-section wing, structure deformation has little effect on temperature field. However, for the stagnation region with high curvature, the coupled effect is not negligible. Thus, it is quite important for the structure temperature prediction to take into account the effect of elastic deformation. This work has laid a solid foundation for improving the prediction accuracy of the temperature distribution of aircraft structures and the evaluation capacity of structural performance.

Keywords: aerothermoelasticity, elastic deformation, structural temperature, multi-field coupling

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Authors: Fitri CaturLestari

Abstract:

According to National Population and Family Planning Board (BKKBN), demographic bonus will occur in 2025-2035, when the number of people within the productive age bracket is higher than the number of elderly people and children. This time will be a gold moment for Indonesia to achieve maximum productivity and prosperity. But it will be a demographic bomb if it isn’t balanced by economic and social aspect considerations. Therefore it is important to make a prediction mapping of all provinces in Indonesia whether in demographic bomb or bonus condition after 100 years Indonesian independence. The purpose of this research were to make the demographic mapping based on the economic and social aspects of the provinces in Indonesia and categorizing them into demographic bomb and bonus condition. The research data are gained from Statistics Indonesia (BPS) as the secondary data. The multiregional component method, regression and quadrant analysis were used to predict the number of people, economic growth, Human Development Index (HDI), and gender equality in education and employment. There were different characteristic of provinces in Indonesia from economic aspect and social aspect. The west Indonesia was already better developed than the east one. The prediction result, many provinces in Indonesia will get demographic bonus but the others will get demographic bomb. It is important to prepare particular strategy to particular provinces with all of their characteristic based on the prediction result so the demographic bomb can be minimalized.

Keywords: demography, economic growth, gender, HDI

Procedia PDF Downloads 336

Authors: Ermias Melake Tesfay

Abstract:

The importance of evaluation practice and feedback to student advancement and retention has gained importance in the literature over the past ten years. So many issues and cases have been raised about the quality and types of evaluation carried out in higher education and the quality and quantity of student feedback. The aim of this study was to explore the students’ perspectives on the quality of course evaluation practice and feedback in College of Education and College of Science. The study used both quantitative and qualitative methods to collect data. Data were collected from third-year and fourth-year students of 13 departments in the College of Education and College of Science in Eritrea. A modified Service Performance (SERVPERF) questionnaire and focus group discussions were used to collect the data. The sample population comprised of 135 third-year and fourth-year students’ from both Colleges. A questionnaire using a 5 point Likert-scale was administered to all respondents whilst two focus group discussions were conducted. Findings from survey data and focus group discussions showed that the majority of students hold a positive perception of the quality of course evaluation practice but had a negative perception of methods of awarding grades and administrators’ role in listening to the students complain about the course. Furthermore, the analysis from the questionnaire showed that there is no statistically significant difference between third-year and fourth-year students, College of Education and College of Science and male and female students on the quality of course evaluation practice and feedback. The study recommends that colleges improve the quality of fairness and feedback during course assessment.

Keywords: evaluation, feedback, quality, students' perception

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Authors: Senol Dogan, Gunay Karli

Abstract:

Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.

Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model

Procedia PDF Downloads 210