Search results for: student performance prediction

Authors: Erica Cochran Hameen, Bobuchi Ken-Opurum, Shalini Priyadarshini, Berangere Lartigue, Sadhana Anath-Pisipati

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School districts throughout the United States are constantly seeking measures to improve test scores, reduce school absenteeism and improve indoor environmental quality. It is imperative to identify key building investments which will provide the largest benefits to schools in terms of improving the aforementioned factors. This study uses Analysis of Variance (ANOVA) tests to statistically evaluate the impact of a school building’s mechanical and plumbing characteristics on a child’s educational performance. The educational performance is measured via three indicators, i.e. test scores, suspensions, and absenteeism. The study investigated 125 New York City school facilities to determine the potential correlations between 50 mechanical and plumbing variables and the performance indicators. Key findings from the tests revealed that elementary schools with pneumatic systems in “good” condition have 48.8% lower percentages of students scoring at the minimum English Language Arts (ELA) competency level compared with those with no pneumatic system. Additionally, elementary schools with “unit heaters/cabinet heaters” in “good to fair” conditions have 1.1% higher attendance rates compared to schools with no “unit heaters/cabinet heaters” or those in inferior condition. Furthermore, elementary schools with air conditioning have 0.6% higher attendance rates compared to schools with no air conditioning, and those with interior floor drains in “good” condition have 1.8% higher attendance rates compared to schools with interior drains in inferior condition.

Keywords: academic attendance and performance, mechanical and plumbing systems, schools, student health

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Authors: Leonardo Juan Ramírez López, Javier Oswaldo Rodriguez Velasquez

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We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.

Keywords: attractor , cardiac, entropy, holter, mathematical , prediction

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Authors: Thuy T. T. Tran, Hamish Coates, Sophie Arkoudis

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Evaluation instruments of teaching are abundant; however, these do not prompt any enhancement in the quality of teaching, not least because these instruments are framed only by teacher-centered conceptions of teaching. There is a need for more sophisticated teaching evaluation measures that focus on student learning and multi-stakeholder involvement. This study aims to develop such an evaluation instrument for Vietnamese higher education. The study uses several kinds of methods. The instrument was initially drafted through in-depth review of research, paying close attention to Vietnamese higher education. Draft evaluation instruments were produced and reviewed by 34 experts. The outcomes of this qualitative and quantitative data reveal an instrument that highlights the value of a multisource student-centered approach, and the rich integration of contextual and cultural traits where Confucian values are emphasized. The validation affirms that evaluating teaching in such way will facilitate the continuous learning growth of all stakeholders involved.

Keywords: multi stakeholders, quality teaching, student learning, teaching evaluation

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Authors: Rita A. Sunday-Kanu

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This article reports on an evaluation of lunch hour concert and its effectiveness in improving undergraduate performance ability. In particular, it examines the aptitude of students in classroom applied music and their reaction/responses to true life concert situations. It further investigated factors affecting students’ confidence during performances, the relationship between stage fright and confidence building in regular concert participation. The Department of Music, University of Port Harcourt runs monthly lunch our concerts which are coordinated by undergraduates for the university community. Forty music students who have participated in or coordinated lunch hour concerts were chosen for this survey. Eight music lecturers who have supervised the monthly lunch hour concert were also chosen for this study. The attitude and view on the effectiveness of lunch hour concert in enhancing students’ performance skills were gotten through questionnaires survey, in-depth interview and participant observation to determine if classroom based applied music alone is as successful in grooming performance genius as the lunch hour concert. Result indicated that students’ participation in lunch hour concert did indeed broaden and strengthened their performance experiences. This observation led to a recommendation that regular community based concerts be considered as a standard for performance practices in the university curriculum since it serves as a preparatory platform for acquiring professional performance skills before graduation.

Keywords: lunch hour concert, performance, performing skill, community concert

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Authors: Theresa Marie Miller, Ma. Nympha Joaquin

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The aim of this study was to check the predictive power of social-oriented and individual-oriented achievement motivation on student engagement and collaborative problem-solving skills in mathematics. A sample of 277 fourth year high school students from the Philippines were selected. Surveys and videos of collaborative problem solving activity were used to collect data from respondents. The mathematics teachers of the participants were interviewed to provide qualitative support on the data. Systemaitc correlation and regression analysis were employed. Results of the study showed that achievement motivations−SOAM and IOAM− linearly predicted student engagement but was not significantly associated to the collaborative problem-solving skills in mathematics. Student engagement correlated positively with collaborative problem-solving skills in mathematics. The results contribute to theorizing about the predictive power of achievement motivations, SOAM and IOAM on the realm of academic behaviors and outcomes as well as extend the understanding of collaborative problem-solving skills of 21st century learners.

Keywords: achievement motivation, collaborative problem-solving skills, individual-oriented achievement motivation, social-oriented achievement motivation, student engagement

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Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

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Authors: Rosemary Saidu, Taiyelolu Martins Ogunjirin

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The study examines the teaching environment and instructional materials on the performance of students in the English Language in selected secondary schools in Ogun State and its implication for counselling. Two research questions guided the study were developed. The study adopted a descriptive survey design. A multi-stage sampling technique was employed for the study. Samples of 100 students of Senior Secondary School Two (SSS11) were drawn. Purposive sampling technique was to select the five schools. Additionally, the instruments known as Teaching Environment and Instructional Materials on Students Performance in English Inventory (TEIMEI) and Student Achievement Scores (SAS) were used to elicit information. Thereafter, inferential statistics and the non-parametric chi-square statistics at 0.05 alpha levels and 3 degree of freedom were adopted as analytical tools. From the study, it was discovered among others that teaching environment and instructional materials significantly contributed to the performance of students in the English language. From the findings, it was recommended that among others functional language laboratory in the schools, counselors to regularly give guidance talk on the importance of the subject.

Keywords: performance, English language, teaching environment, instructional materials

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Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

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Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar

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Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.

Keywords: data mining, defect prediction, missing requirements, software quality

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Authors: Ngozi Claribelle Nwogu, Mohammed Nasir Kajama, Oyoh Kechinyere, Edward Gobina

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Atmospheric carbon dioxide emissions are considered as the greatest environmental challenge the world is facing today. The challenges to control the emissions include the recovery of CO2 from flue gas. This concern has been improved due to recent advances in materials process engineering resulting in the development of inorganic gas separation membranes with excellent thermal and mechanical stability required for most gas separations. This paper therefore evaluates the performance of a highly selective inorganic membrane for CO2 recovery applications. Analysis of results obtained is in agreement with experimental literature data. Further results show the prediction performance of the membranes for gas separation and the future direction of research. The materials selection and the membrane preparation techniques are discussed. Method of improving the interface defects in the membrane and its effect on the separation performance has also been reviewed and in addition advances to totally exploit the potential usage of this innovative membrane.

Keywords: carbon dioxide, gas separation, inorganic ceramic membrane, permselectivity

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Irshana Muhamadhu Razmy

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Education is one of the main necessities for a modern society to access wealth as well as to achieve social well-being. Education contributes to enhancing as well as developing the social and economic status of an individual and building a vibrant community within a strong nation. The student dropout problem refers to students who enrolled in a school and are later unable to complete their grade education due to multiple factors). In Sri Lanka, the tea plantation sector is a prominent sector. The tea plantation sector is different from other plantation sectors such as palm oil, rubber, and coconut. Therefore, the present study particularly focuses on the influencing factors of student dropout in the tea plantation sector in Sri Lanka by conducting research in the Labookellie estate in Nuwera Eliya District. this research has opted to use both qualitative and quantitative methods. This study examines the factors associated with student dropout namely the family, school, and the social by the characteristic (gender, grade, and ethnicity) in the plantation area in the Labookellie estate.

Keywords: student dropout, school, plantation settlement, social environmental

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Authors: Sadiq Habiba Alhaji

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This is a descriptive survey design intended to determine the level of usage of the learner centred methods by student teachers of Federal College of Education Kontagora, Niger State, Nigeria. The study was guided by two null hypotheses formulated by the researcher. The population of the study are students of Federal College of Education, Kontagora. The Target Population consisted of one hundred Teaching practice students drawn from sciences, Arts, and humanities who were posted to various schools practicing different teaching methods. The student teachers were supervised using the checklist designed by the researcher to determine their level of usage of learner centred methods. Data collected was analysed using t test of independent variables. It was recommended that pre service and in service teachers should be equipped with the skills of using learner centred methods.

Keywords: assessment, usage, learner centred, methods, student teachers

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Deepa Idnani

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Attendance is an important factor in school success among children. Studies show that better attendance is related to higher academic achievement for students of all backgrounds, but particularly for children with lower socio-economic status. Beginning from the early years, students who attend school regularly score higher on tests than their peers who are frequently absent. The present study in different types of School In Delhi tries to highlight the impact of student absenteeism and the challenges it poses for the students. The study relies on Lewin ‘Model of Exclusion’ and tries to focus on the analysis of children with special needs and the inclusion and exclusion of students in the school.

Keywords: student absenteeism, pedagogy, learning, right to education act, exclusion

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Authors: M. K. Wijayarathna, S. M. Buddika Harshanath

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Monitoring student engagement has become a crucial part of the educational process and a reliable indicator of the capacity to retain information. As online learning classrooms are now more common these days, students' attention levels have become increasingly important, making it more difficult to check each student's concentration level in an online classroom setting. To profile student attention to various gradients of engagement, a study is a plan to conduct using machine learning models. Using a convolutional neural network, the findings and confidence score of the high accuracy model are obtained. In this research, convolutional neural networks are using to help discover essential emotions that are critical in defining various levels of participation. Students' attention levels were shown to be influenced by emotions such as calm, enjoyment, surprise, and fear. An improved virtual learning system was created as a result of these data, which allowed teachers to focus their support and advise on those students who needed it. Student participation has formed as a crucial component of the learning technique and a consistent predictor of a student's capacity to retain material in the classroom. Convolutional neural networks have a plan to implement the platform. As a preliminary step, a video of the pupil would be taken. In the end, researchers used a convolutional neural network utilizing the Keras toolkit to take pictures of the recordings. Two convolutional neural network methods are planned to use to determine the pupils' attention level. Finally, those predicted student attention level results plan to display on the graphical user interface of the System.

Keywords: HTML5, JavaScript, Python flask framework, AI, graphical user

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Authors: Svitov David, Alyamkin Sergey

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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax

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Authors: Kh. Alaa, Sh. Sarah, J. Khowlah, S. Liyakathunsia

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Education has become very important nowadays and with the rapidly increasing number of student, taking the attendance manually is getting very difficult and time wasting. In order to solve this problem, an automated solution is required. An effective automated system can be implemented to manage student attendance in different ways. This research will discuss a unique class attendance system which integrates both Face Recognition and RFID technique. This system focuses on reducing the time spent on submitting of the lecture and the wastage of time on submitting and getting approval for the absence excuse and sick leaves. As a result, the suggested solution will enhance not only the time, also it will also be helpful in eliminating fake attendance.

Keywords: attendance system, face recognition, RFID, process model, cost, time

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Edwaldo R. B. Monteiro, Patricia D. M. Plentz, Edson R. De Pieri

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Mobile robotics is gaining an increasingly important role in modern society. Several potentially dangerous or laborious tasks for human are assigned to mobile robots, which are increasingly capable. Many of these tasks need to be performed within a specified period, i.e., meet a deadline. Missing the deadline can result in financial and/or material losses. Mechanisms for predicting the missing of deadlines are fundamental because corrective actions can be taken to avoid or minimize the losses resulting from missing the deadline. In this work we propose a simple but reliable deadline missing prediction mechanism for mobile robots through the use of historical data and we use the Pioneer 3-DX robot for experiments and simulations, one of the most popular robots in academia.

Keywords: deadline missing, historical data, mobile robots, prediction mechanism

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Authors: Chang Su Woo, Hyun Sung Park

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Useful lifetime evaluations of rail-pads were very important in design procedure to assure the safety and reliability. It is, therefore, necessary to establish a suitable criterion for the replacement period of rail pads. In this study, we performed properties and accelerated heat aging tests of rail pads considering degradation factors and all environmental conditions including operation, and then derived a lifetime prediction equation according to changes in hardness, thickness, and static spring constants in the Arrhenius plot to establish how to estimate the aging of rail pads. With the useful lifetime prediction equation, the lifetime of e-clip pads was 2.5 years when the change in hardness was 10% at 25°C; and that of f-clip pads was 1.7 years. When the change in thickness was 10%, the lifetime of e-clip pads and f-clip pads is 2.6 years respectively. The results obtained in this study to estimate the useful lifetime of rail pads for high speed trains can be used for determining the maintenance and replacement schedule for rail pads.

Keywords: rail pads, accelerated test, Arrhenius plot, useful lifetime prediction, mechanical engineering design

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Authors: Siddiq Ahmed

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The current study aimed to investigate the effectiveness of a Peer-Mediated Intervention (PMI) on writing skills for a student with autism spectrum disorders in inclusive classrooms. The participants in this study were two students, one as a tutor and another as a tutee who was diagnosed with autism spectrum disorder (ASD). The target participant struggled with writing skills and was paired with a student with high academic outcomes. The Tutor had a readiness to act as a tutor for his peer and was trained on how to assist his peer and how to identify and guide his peer’s writing mistakes. Multiple baseline design across behaviors was implemented to monitor the student’s progress in writing skills. The results of the present study showed that PMI yielded significant improvements in academic achievements for the target student. This study suggests that further studies should replicate the current study with an intensive focus on other academic skills such as reading comprehension, writing social stories, and math.

Keywords: peer tutoring, writing skills, autism, inclusion

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Authors: Susanna Asatryan

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The author will introduce the Language Portfolio for master course student-teachers of Yerevan Brusov State University of Languages and Social Sciences The overall aim of the Portfolio is to serve as a visual didactic tool for the pedagogical internship of master students in specialization “A Foreign Language Teacher of High Schools and Professional Educational Institutions”, based on the principles and fundamentals of the EPOSTL. The author will present the parts of the Portfolio, including the programme, goal and objectives of student-teacher’s internship, content and organization, expected outputs and the principles of the student’s self-assessment, based on Can-do philosophy suggested by the EPOSTL. The Language Portfolio for master course student-teachers outlines the distinctive stages of their scientific-pedagogical internship. In Lesson Observation and Teaching section student teachers present thematic planning of the syllabus course, including individual lesson plan-description and analysis of the lesson. In Realization of the Scientific-Pedagogical Research section student-teachers introduce the plan of their research work, its goal, objectives, steps of procedure and outcomes. In Educational Activity section student-teachers analyze the educational sides of the lesson, they introduce the plan of the extracurricular activity, provide psycho-pedagogical description of the group or the whole class, and outline extracurricular entertainments. In the Dossier the student-teachers store up the entire instructional “product” during their pedagogical internship: e.g. samples of surveys, tests, recordings, videos, posters, postcards, pupils’ poems, photos, pictures, etc. The author’s presentation will also cover the Self Assessment Checklist, which highlights the main didactic competences of student-teachers, extracted from the EPOSTL. The Self Assessment Checklist is introduced with some innovations, taking into consideration the local educational objectives that Armenian students come across with. The students’ feedback on the use of the Portfolio will also be presented.

Keywords: internship, lesson observation, can-do philosophy, self-assessment

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Authors: Mehmet Oren, Susan Pedersen, Sevket C. Cetin

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Despite the frequently criticized disadvantages of the traditional used paper and pencil assessment, it is the most frequently used method in our schools. Although assessments do an acceptable measurement, they are not capable of measuring all the aspects and the richness of learning and knowledge. Also, many assessments used in schools decontextualize the assessment from the learning, and they focus on learners’ standing on a particular topic but do not concentrate on how student learning changes over time. For these reasons, many scholars advocate that using simulations and games (S&G) as a tool for assessment has significant potentials to overcome the problems in traditionally used methods. S&G can benefit from the change in technology and provide a contextualized medium for assessment and teaching. Furthermore, S&G can serve as an instructional tool rather than a method to test students’ learning at a particular time point. To investigate the potentials of using educational games as an assessment and teaching tool, this study presents the implementation and the validation of an automated embedded assessment (AEA), which can constantly monitor student learning in the game and assess their performance without intervening their learning. The experiment was conducted on an undergraduate level engineering course (Digital Circuit Design) with 99 participant students over a period of five weeks in Spring 2016 school semester. The purpose of this research study is to examine if the proposed method of AEA is valid to assess student learning in a 3D Educational game and present the implementation steps. To address this question, this study inspects three aspects of the AEA for the validation. First, the evidence-centered design model was used to lay out the design and measurement steps of the assessment. Then, a confirmatory factor analysis was conducted to test if the assessment can measure the targeted latent constructs. Finally, the scores of the assessment were compared with an external measure (a validated test measuring student learning on digital circuit design) to evaluate the convergent validity of the assessment. The results of the confirmatory factor analysis showed that the fit of the model with three latent factors with one higher order factor was acceptable (RMSEA < 0.00, CFI =1, TLI=1.013, WRMR=0.390). All of the observed variables significantly loaded to the latent factors in the latent factor model. In the second analysis, a multiple regression analysis was used to test if the external measure significantly predicts students’ performance in the game. The results of the regression indicated the two predictors explained 36.3% of the variance (R2=.36, F(2,96)=27.42.56, p<.00). It was found that students’ posttest scores significantly predicted game performance (β = .60, p < .000). The statistical results of the analyses show that the AEA can distinctly measure three major components of the digital circuit design course. It was aimed that this study can help researchers understand how to design an AEA, and showcase an implementation by providing an example methodology to validate this type of assessment.

Keywords: educational video games, automated embedded assessment, assessment validation, game-based assessment, assessment design

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Authors: Christine Okello

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Physical Education (PE) curriculum provides school age students to explore issues that are likely to impact on health, safety, and well-being. The current curriculum includes the physical activity component, intended to improve physical fitness, social skills as well as building confidence. While this viewpoint is vital, there are challenges and stigma attached when specific issues are either ignored, inadequately addressed, or not seen to be important. The department stipulates that students attend a school that is closest to their home, to access available government transportation to and from school. Equivalently, parents of students with a disability decide where their children attend school. A choice between a regular classroom, mainstream Special Unit classroom, or a School for Specific Purposes (SSP). Parents who take their children to regular schools may be oblivious of the details of the curriculum. Physical Education outcomes does not stipulate the extent to which a student must perform or expected to perform. It is therefore due to the classroom teacher to adjust their teaching goals or outcomes to suit all students in their classroom. A student who can run a hundred meters race in 20 seconds may belong in the same classroom as a student in a wheelchair. While these students are challenged because of a lack of performance, teachers are challenged to effectively teach successful PE lessons, and on the other hand students without a disability may not be able to attain their optimum. This paper will identify areas of need, address the challenges, and explore a possible solution.

Keywords: special needs, disability, challenges, physical education

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Authors: A. Yacob, N. Hj. Ali, M. H. Yusoff, M. Y. MohdSaman, W. M. A. F. W. Hamzah

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Personalized learning becomes increasingly popular which not is restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability. The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT, it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores. Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.

Keywords: assessment, item response theory, cognitive load theory, learning, motivation, performance

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Frazer McDonald Ng'oma

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Online Learning in Malawi has only immersed in recent years due to the need to increase access to higher education, the need to accommodate upgrading students who wish to study on a part time basis while still continuing their work, and the COVID-19 pandemic, which forced the closure of schools resulting in academic institutions seeking alternative modes of teaching and Learning to ensure continued teaching and Learning. Realizing that this mode of Learning is becoming a norm, institutions of higher Learning have started pioneering online post-graduate programs from which they can draw lessons before fully implementing it in undergraduate programs. Online learning pedagogy has not been fully grasped and institutions are still experimenting with this mode of Learning until online Learning guiding policies are created and its standards improved. This single case descriptive qualitative research study sought to investigate online postgraduate students’ perceptions and experiences with Student to student interactive pedagogy in their programs. The results of the study are to inform institutions and educators how to structure their programs to ensure that their students get the full satisfaction. 25 Masters students in 3 recently introduced online programs at Kamuzu University of Health Sciences (KUHES), were engaged; 19 were interviewed and 6 responded to questionnaires. The findings from the students were presented and categorized in themes and subthemes that emerged from the qualitative data that was collected and analysed following Colaizzi’s framework for data analysis that resulted in themes formulation. Findings revealed that Student to student interactions occurred in the online programme during live sessions, on class Whatsapp group, in discussion boards as well as on emails. Majority of the students (n=18) felt the level of students’ interaction initiated by the institution was too much, referring to mandatory interactions activities like commenting in discussion boards and attending to live sessons. Some participants (n=7) were satisfied with the level of interaction and also pointed out that they would be fine with more program-initiated student–to–student interactions. These participants attributed having been out of school for some time as a reason for needing peer interactions citing that it is already difficult to get back to a traditional on-campus school after some time, let alone an online class where there is no physical interaction with other students. In general, majority of the participants (n=18) did not value Student to student interaction in online Learning. The students suggested that having intensive student-to-student interaction in postgraduate online studies does not need to be a high priority for the institution and they further recommended that if a lecturer decides to incorporate student-to-student activities into a class, they should be optional.

Keywords: online learning, interactions, student interactions, post graduate students

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Authors: Dadang Gunawan, I. Dewa Ketut Kertawidana, Lufthi Noorfitriyani

Abstract:

For the last 5 years, there is the never-ending violent act and increased cases regarding aggressive behavior among high school students in Bogor, Indonesia. Those cases caused harm to many people, even death, and lead to the continuation circle of violence. This research was conducted to evaluate the effect of using peace education and media literacy in enhancing student’s understanding about aggression, as an effort to prevent aggressive behavior. In terms of methodology, this research was done by quasi-experiment with one group pretest and post-test design. A number of 38 students who were at risk of aggressive behavior from 3 vocational high school were involved to receive a 10 learning session about peace and media literacy. The aggression questionnaire was used to identify participants, supported by student’s record in school. To collect data, the questionnaire for measuring understanding about aggression has been developed and was used after the validity and reliability of this questionnaire tested. Post-test was carried out after the session ended. Data were analyzed using t-test. The finding result showed that the mean score of student’s understanding of aggression was increased, therefore learning session of peace education and media literacy is significantly effective to enhance student’s understanding of aggression. It also showed a meaningful difference of understanding between male and female student’s whereas female students have a better understanding of aggression.

Keywords: aggressive behavior prevention, aggression, media literacy, peace education, peacebuilding

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Authors: H. A. Mansour

Abstract:

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

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

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