Search results for: task based learning

Authors: Hsin-Yu Lee, Ming-Zhong Li, Wen-Hsi Chiu, Su-Fen Cheng, Shwu-Wen Lin

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Background: The use of medical terminology is essential to professional nurses on clinical practice. However, most nursing students consider traditional lecture-based teaching of medical terminology as boring and overly conceptual and lack motivation to learn. It is thus an issue to be discussed on how to enhance nursing students’ self-directed learning and improve learning outcomes of medical terminology. Digital game-based learning is a learner-centered way of learning. Past literature showed that the most common game-based learning for language education has been immersive games and teaching games. Thus, this study selected role-playing games (RPG) and digital puzzle games for observation and comparison. It is interesting to explore whether digital game-based learning has positive impact on nursing students’ learning of medical terminology and whether students can adapt well on this type of learning. Results can be used to provide references for institutes and teachers on teaching medical terminology. These instructions give you guidelines for preparing papers for the conference. Use this document as a template if you are using Microsoft Word. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at WASET. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column. Page margins are 1,78 cm top and down; 1,65 cm left and right. Each column width is 8,89 cm and the separation between the columns is 0,51 cm. Objective: The purpose of this research is to explore respectively the impact of RPG and puzzle game on nursing students’ self-directed learning and technology acceptance. The study further discusses whether different game types bring about different influences on students’ self-directed learning and technology acceptance. Methods: A quasi-experimental design was adopted in this study so that repeated measures between two groups could be conveniently conducted. 103 nursing students from a nursing college in Northern Taiwan participated in the study. For three weeks of experiment, the experiment group (n=52) received “traditional teaching + RPG” while the control group (n=51) received “traditional teaching + puzzle games”. Results: 1. On self-directed learning: For each game type, there were significant differences for the delayed tests of both groups as compared to the pre and post-tests of each group. However, there were no significant differences between the two game types. 2. On technology acceptance: For the experiment group, after the intervention of RPG, there were no significant differences concerning technology acceptance. For the control group, after the intervention of puzzle games, there were significant differences regarding technology acceptance. Pearson-correlation coefficient and path analysis conducted on the results of the two groups revealed that the dimension were highly correlated and reached statistical significance. Yet, the comparison of technology acceptance between the two game types did not reach statistical significance. Conclusion and Recommend: This study found that through using different digital games on learning, nursing students have effectively improved their self-directed learning. Students’ technology acceptances were also high for the two different digital game types and each dimension was significantly correlated. The results of the experimental group showed that through the scenarios of RPG, students had a deeper understanding of medical terminology, which reached the ‘Understand’ dimension of Bloom’s taxonomy. The results of the control group indicated that digital puzzle games could help students memorize and review medical terminology, which reached the ‘Remember’ dimension of Bloom’s taxonomy. The findings suggest that teachers of medical terminology could use digital games to assist their teaching according to their goals on cognitive learning. Adequate use of those games could help improve students’ self-directed learning and further enhance their learning outcome on medical terminology.

Keywords: digital game-based learning, medical terminology, nursing education, self-directed learning, technology acceptance model

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Authors: Eny Syatriana, Ardiansyah

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The purpose of recent study was to develop a learning model on writing, based on the reading texts which will be read by the students using reflection strategy. The strategy would allow the students to read the text and then they would write back the main idea and to develop the text by using their own sentences. So, the writing practice was begun by reading an interesting text, then the students would develop the text which has been read into their writing. The problem questions are (1) what kind of learning model that can develop the students writing ability? (2) what is the achievement of the students of STKIP YPUP through reflection strategy? (3) is the using of the strategy effective to develop students competence In writing? (4) in what level are the students interest toward the using of a strategy In writing subject? This development research consisted of some steps, they are (1) need analysis (2) model design (3) implementation (4) model evaluation. The need analysis was applied through discussion among the writing lecturers to create a learning model for writing subject. To see the effectiveness of the model, an experiment would be delivered for one class. The instrument and learning material would be validated by the experts. In every steps of material development, there was a learning process, where would be validated by an expert. The research used development design. These Principles and procedures or research design and development .This study, researcher would do need analysis, creating prototype, content validation, and limited empiric experiment to the sample. In each steps, there should be an assessment and revision to the drafts before continue to the next steps. The second year, the prototype would be tested empirically to four classes in STKIP YPUP for English department. Implementing the test greatly was done through the action research and followed by evaluation and validation from the experts.

Keywords: learning model, reflection, strategy, reading, writing, development

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Authors: Youmen Chaaban, Abdallah Abu-Tineh

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This article examines the development of a professional development (PD) model for educator growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge, and skills of both school leadership and teachers in an attempt to improve students’ learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents the results of a qualitative study examining the perceptions of nineteen instructional coaches about the strengths of the PD program, the challenges they face in their day-to-day implementation of the program, and their suggestions for the betterment of the program’s implementation and outcomes. Data were collected from the instructional coaches through open-ended surveys followed by focus group interviews. The instructional coaches reported several strengths, which were compatible with the literature on effective PD. However, the challenges they faced were deeply rooted within the structure of the program, in addition to external factors operating at the school and Ministry of Education levels. Thus, a general consensus on the way the program should ultimately develop was reached.

Keywords: situated professional development, school reform, instructional coach, school based support program

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Horng-Jyh Chen, Yi-Fang Chen, Chien-Liang Lin

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In this paper, the authors try to investigate the determinants of behavioral intention of the blended e-learning course for senior students at the Active Ageing University in Taiwan. Due to lower proficiency in the use of computers and less experience on learning styles of the blended e-learning course for senior students will be expected quite different from those for most young students. After more than five weeks course for two years the questionnaire survey is executed to collect data for statistical analysis in order to understand the determinants of the behavioral intention for senior students. The object of this study is at one of the Active Ageing University in Taiwan total of 84 senior students in the blended e-learning for the ceramics teaching course. The research results show that only the perceived usefulness of the blended e-learning course has significant positive relationship with the behavioral intention.

Keywords: Active Aging University, blended e-learning, ceramics teaching course, behavioral intention

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Authors: Sigal Gat-Lazer, Ronny Geva, Dan Ramon, Eitan Gur, Daniel Stein

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Introduction: Eating disorders (ED) are common psychopathologies which involve distorted body image and eating disturbances. Binge-purge eating disorders (B/P ED) are characterized by repetitive events of binge eating followed by purges. Patients with B/P ED behavior may be seen as impulsive especially when relate to food stimulation and affective conditions. The current study included innovative modification of the day-night task targeted to assess inhibitory control among patients with B/P ED. Methods: This prospective study included 50 patients with B/P ED during acute phase of illness (T1) upon their admission to specialized ED department in tertiary center. 34 patients repeated the study towards discharge to ambulatory care (T2). Treatment effect was evaluated by BMI and emotional questionnaires regarding depression and anxiety by the Beck Depression Inventory and State Trait Anxiety Inventory questionnaires. Control group included 36 healthy controls with matched demographic parameters who performed both T1 and T2 assessments. The current modification is based on the emotional day-night task (EDNT) which involves five emotional stimulation added to the sun and moon pictures presented to participants. In the current study, we designed the food-emotional modification day night task (F-EDNT) food stimulations of egg and banana which resemble the sun and moon, respectively, in five emotional states (angry, sad, happy, scrambled and neutral). During this computerized task, participants were instructed to push on “day” bottom in response to moon and banana stimulations and on “night” bottom when sun and egg were presented. Accuracy (A) and reaction time (RT) were evaluated and compared between EDNT and F-EDNT as a reflection of participants’ inhibitory control. Results: Patients with B/P ED had significantly improved BMI, depression and anxiety scores on T2 compared to T1 (all p<0.001). Task performance was similar among patients and controls in the EDNT without significant A or RT differences in both T1 and T2. On F-EDNT during T1, B/P ED patients had significantly reduced accuracy in 4/5 emotional stimulation compared to controls: angry (73±25% vs. 84±15%, respectively), sad (69±25% vs. 80±18%, respectively), happy (73±24% vs. 82±18%, respectively) and scrambled (74±24% vs. 84±13%, respectively, all p<0.05). Additionally, patients’ RT to food stimuli was significantly faster compared to neutral ones, in both cry and neutral emotional stimulations (356±146 vs. 400±141 and 378±124 vs. 412±116 msec, respectively, p<0.05). These significant differences between groups as a function of stimulus type were diminished on T2. Conclusion: Having to process food related content, in particular in emotional context seems to be impaired in patients with B/P ED during the acute phase of their illness and elicits greater impulsivity. Innovative modification using such procedures seem to be sensitive to patients’ illness phase and thus may be implemented during screening and follow up through the clinical management of these patients.

Keywords: binge purge eating disorders, day night task modification, eating disorders, food related stimulations

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Authors: Thi Chang Duyen Can

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Althoughthe COVID-19 epidemic is under control, online education technology in Vietnam will still thrive in the learner-centered trend. Most of the Vietnamese students are now ready to familiarize themselves with and access to online learning. Even in some cases, online learning, if combined with new tools, is far more effective and exciting for students than some traditional instruction. However, little research has been conducted to explore Vietnamese teachers’ difficulties in moderating learner-centered E-learning. Therefore, the study employed the mixed method (n=9) to (i) uncover the challenges faced by Vietnamese teachers in English language online classes using learner-centred approach and (ii) propose the recommendations to improve the quality of online training in universities.

Keywords: learner-centered e-learning, english language classes, teachers' challenges, online learning

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Authors: Wei Zhang

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With the rapid development of deep learning, neural network and deep learning algorithms play a significant role in various practical applications. Due to the high accuracy and good performance, Convolutional Neural Networks (CNNs) especially have become a research hot spot in the past few years. However, the size of the networks becomes increasingly large scale due to the demands of the practical applications, which poses a significant challenge to construct a high-performance implementation of deep learning neural networks. Meanwhile, many of these application scenarios also have strict requirements on the performance and low-power consumption of hardware devices. Therefore, it is particularly critical to choose a moderate computing platform for hardware acceleration of CNNs. This article aimed to survey the recent advance in Field Programmable Gate Array (FPGA)-based acceleration of CNNs. Various designs and implementations of the accelerator based on FPGA under different devices and network models are overviewed, and the versions of Graphic Processing Units (GPUs), Application Specific Integrated Circuits (ASICs) and Digital Signal Processors (DSPs) are compared to present our own critical analysis and comments. Finally, we give a discussion on different perspectives of these acceleration and optimization methods on FPGA platforms to further explore the opportunities and challenges for future research. More helpfully, we give a prospect for future development of the FPGA-based accelerator.

Keywords: deep learning, field programmable gate array, FPGA, hardware accelerator, convolutional neural networks, CNN

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Glenn A. Palmer, Lorenzo Bowman, Juanita Johnson-Bailey

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The ubiquitous economic upheaval that has gripped the global environment in the past few years displaced many workers through unemployment or underemployment. Globally, this disruption has caused many adult workers to seek additional education or skills to remain competitive, and acquire the ability and options to find gainful employment. While many learners have availed themselves of some opportunities to be retrained and retooled at locations within their communities, others have explored those options through the online learning environment. This paper examines the empirical research that explores the various strategies that are used in the adult online learning community that could also foster transformative learning.

Keywords: online learning, transformational learning, adult education, economic crisis, unemployment

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: distributed control, game theory, multi-agent learning, reinforcement learning

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Authors: Meiju Chen, Chaoyu Guo, Chia Wei Tang

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The present study's purpose is twofold: first, to construct indicators for learning-oriented school education and, second, to conduct a survey to examine how learning-oriented education has been implemented in junior high schools after the launch of the 12-year compulsory curriculum. For indicator system construction, we compiled relevant literature to develop a preliminary indicator list model and then conducted two rounds of a questionnaire survey to gain comprehensive feedback from experts to finalize our indicator model. In the survey's first round, 12 experts were invited to evaluate the indicators' appropriateness. Based on the experts' consensus, we determined our final indicator list and used it to develop the Fuzzy Delphi questionnaire to finalize the indicator system and each indicator's relative value. For the fact-finding survey, we collected 454 valid samples to examine how the concept of learning-oriented education is adopted and implemented in the junior high school context. We also used this data in our importance-performance analysis to explore the strengths and weaknesses of school education in Taiwan. The results suggest that the indicator system for learning-oriented school education must consist of seven dimensions and 34 indicators. Among the seven dimensions, 'student learning' and 'curriculum planning and implementation' are the most important yet underperforming dimensions that need immediate improvement. We anticipate that the indicator system will be a useful tool for other countries' evaluation of schools' performance in learning-oriented education.

Keywords: learning-oriented education, school education, fuzzy Delphi method, importance-performance analysis

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Authors: Yi-Chuan Cheng, Li-Chi Huang, Yu-Shan Chang

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Introduction: The main purpose of this study was to explore the relationship between the learning number, care knowledge, care skills and maternal confidence in preterm infant care in Taiwan. Background: Preterm infants care has been stressful for mother caring at home. Many programs have been applied for improving the infant care maternal confident. But less to know the learning behavior in mothers of preterm infant. Methods: The sample consisted of 55 mothers with preterm infants were recruited in a neonatal intermediate unit at a medical center in central Taiwan. The self-reported questionnaires including knowledge and skills of preterm infant care scales and maternal confidence scale were used to evaluation, which were conducted during hospitalization, before hospital discharge, and one month after discharge. We performed by using Pearson correlation of the collected data using SPSS 18. Results: The study showed that the learning number and knowledge in preterm infant care was a significant positive correlation (r = .40), and the skills and confidence preterm infant care was positively correlated (r = .89). Conclusions: Study results showed the mother had more learning number in preterm infant care will be stronger knowledge, and the skills and confidence in preterm infant care were also positively correlated. Thus, we found the learning behavior change significant care knowledge. And the maternal confidence change significant with skill on preterm infant’s care. But bondage still needs further study and develop the participation in hospital-based instructional programs, which could lead to greater long-term retention of learning.

Keywords: learning behavior, care knowledge, care skills, maternal confidence

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Authors: Huixuan Xu

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The present study was set out to investigate the extent to which and how service-learning fostered a sample of 138 Hong Kong undergraduates’ interpersonal competence and cooperative orientation development. Interpersonal competence is presented when an individual shows empathy with others, provides intelligent advice to others and has practical judgment. Cooperative orientation reflects individuals’ willingness to work with others to achieve common goals. A quality service-learning programme may exhibit the features of provision of meaningful service, close link to curriculum, continuous reflection, youth voice, and diversity. Mixed methods were employed in the present study. Pre-posttest survey was administered to capture individual undergraduates’ development of interpersonal competence and cooperative orientation over a period of four months. The respondents’ evaluation of service-learning elements was administered in the post-test survey. Focus groups were conducted after the end of the service-learning to further explore how the certain service-learning elements promoted individual undergraduates’ development of interpersonal competence and cooperative orientation. Three main findings were reported from the study. (1) The scores of interpersonal competence increased significantly from the pretest to the posttest, while the change of cooperative orientation was not significant. (2) Cooperative orientation and interpersonal competence were correlated positively with the overall course quality respectively, which suggested that the more a service-learning course complied with quality practice, the students became more competent in interpersonal competence and cooperative orientation. (3) The following service-learning elements showed higher impacts: (a) direct contact with service recipients, which engaged students in practicing interpersonal skills; (b) individual participants’ being exposed to a situation that required communication and dialogue with people from diverse backgrounds with different views; (c) experiencing interpersonal conflicts among team members and having the conflicts solved; (d) students’ taking a leading role in a project-based service. The present study provides compelling evidence about what elements in a service-learning program may foster undergraduates’ development of cooperative orientation and interpersonal competence. Implications for the design of service-learning programmes are provided.

Keywords: undergraduates, interpersonal competence, cooperation orientation, service-learning

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Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

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Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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Authors: Sharapat Sharapat

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English language is perceived as cultural capital in many non-native English-speaking countries, and minority groups in these social contexts seem to invest in the language to be empowered and reposition themselves from the imbalanced power relation with the dominant group. This study is devoted to explore how English learning influence minority Kazakh students’ identity (re)construction at Chinese universities from the scope of ‘imagined community, investment, and identity’ theory of Norton (2013). To this end the three research questions were designed as follows: 1) Kazakh minority students’ English learning experiences at Chinese universities; 2) Kazakh minority students’ views about benefits and opportunities of English learning; 3) the influence of English learning on Kazakh minority students’ identity (re)construction. The study employs an interview-based qualitative research method by interviewing nine Kazakh minority students in universities in Xinjiang and other inland cities in China. The findings suggest that through English learning, some students have reconstructed multiple identities as multicultural and global identities, which created ‘a third space’ to break limits of their ethnic and national identities and confused identity as someone in-between. Meanwhile, most minority students were empowered by the English language to resist inferior or marginalized positions and reconstruct imagined elite identity. However, English learning disempowered students who have little previous English education in school and placed them on unequal footing with other students, which further escalated the educational inequities.

Keywords: minority in China, identity construction, multilingual education, language empowerment

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Authors: Jayati Bhattacharjee

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Teaching is a very dynamic profession. Teaching Science is as much challenging as Learning the subject if not more. For instance teaching of Chemistry. From the introductory concepts of subatomic particles to atoms of elements and their symbols and further presenting the chemical equation and so forth is a challenge on both side of the equation Teaching Learning. This paper combines the Neuroscience of Learning and memory with the knowledge of Learning style (VAK) and presents an effective tool for the teacher to authenticate Learning. The model of ‘Working Memory’, the Visio-spatial sketchpad, the central executive and the phonological loop that transforms short-term memory to long term memory actually supports the psychological theory of Learning style i.e. Visual –Auditory-Kinesthetic. A closer examination of David Kolbe’s learning model suggests that learning requires abilities that are polar opposites, and that the learner must continually choose which set of learning abilities he or she will use in a specific learning situation. In grasping experience some of us perceive new information through experiencing the concrete, tangible, felt qualities of the world, relying on our senses and immersing ourselves in concrete reality. Others tend to perceive, grasp, or take hold of new information through symbolic representation or abstract conceptualization – thinking about, analyzing, or systematically planning, rather than using sensation as a guide. Similarly, in transforming or processing experience some of us tend to carefully watch others who are involved in the experience and reflect on what happens, while others choose to jump right in and start doing things. The watchers favor reflective observation, while the doers favor active experimentation. Any lesson plan based on the model of Prescriptive design: C+O=M (C: Instructional condition; O: Instructional Outcome; M: Instructional method). The desired outcome and conditions are independent variables whereas the instructional method is dependent hence can be planned and suited to maximize the learning outcome. The assessment for learning rather than of learning can encourage, build confidence and hope amongst the learners and go a long way to replace the anxiety and hopelessness that a student experiences while learning Science with a human touch in it. Application of this model has been tried in teaching chemistry to high school students as well as in workshops with teachers. The response received has proven the desirable results.

Keywords: working memory model, learning style, prescriptive design, assessment for learning

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Authors: Guizella Rocabado, Cassidy Wilkes

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It is well known that chemistry is one of the most feared courses in college. Although many students enjoy learning about science, most of them perceive that chemistry is “too difficult”. These perceptions of chemistry result in many students not considering Science, Technology, Engineering, and Mathematics (STEM) majors because they require chemistry courses. Ultimately, these perceptions are also thought to be related to high attrition rates of students who begin STEM majors but do not persist. Students perceived costs of a chemistry class can be many, such as task effort, loss of valued alternatives, emotional, and others. These costs might be overcome by students’ interests and goals, yet the level of perceived costs might have a lasting impact on the students’ overall perception of chemistry and their desire to pursue chemistry and other STEM careers in the future. In this mixed methods study, we investigated task effort and emotional cost, as well as a mastery or performance goal orientation, and the impact these constructs may have on achievement in general chemistry classrooms. Utilizing cluster analysis as well as student interviews, we investigated students’ profiles of perceived cost and goal orientation as it relates to their final grades. Our results show that students who are well prepared for general chemistry, such as those who have taken chemistry in high school, display less negative perceived costs and thus believe they can master the material more fully. Other interesting results have also emerged from this research, which has the potential to have an impact on future instruction of these courses.

Keywords: chemistry education, motivation, affect, perceived costs, goal orientations

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Authors: Ivy Rose Mathew

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The purpose of this study is to outline the efficacy of technology and the opportunities it can bring to implement a successful delivery model in Distance Learning. Distance Learning has proliferated over the past few years across the world. Some of the current challenges faced by current students of distance education include lack of motivation, a sense of isolation and a need for greater and improved communication. Hence the author proposes a creative technology supported model for distance learning exactly mirrored on the traditional face to face learning that can be adopted by distance learning providers. This model suggests the usage of a range of technologies and social networking facilities, with the aim of creating a more engaging and sustaining learning environment to help overcome the isolation often noted by distance learners. While discussing the possibilities, the author also highlights the complexity and practical challenges of implementing such a model. Design/methodology/approach: Theoretical issues from previous research related to successful models for distance learning providers will be considered. And also the analysis of a case study from one of the largest private tertiary institution in Botswana, Botho University will be included. This case study illustrates important aspects of the distance learning delivery model and provides insights on how curriculum development is planned, quality assurance is done, and learner support is assured for successful distance learning experience. Research limitations/implications: While some of the aspects of this study may not be applicable to other contexts, a number of new providers of distance learning can adapt the key principles of this delivery model.

Keywords: distance learning, efficacy, learning experience, technology supported model

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Authors: Adisorn Bansong, Walai Isarankura Na Ayudhaya, Aumporn Makanong

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A Development of an Instructional Model for Health Education was the aim to develop and study the effectiveness of an instructional model for health education to enhance self-regulation and learning achievement of lower secondary school students. It was the Quasi-Experimental Designs, used a Single-group Interrupted Time-series Designs, conducted by 2 phases: 1. To develop an instructional model based on Social Cognitive Theory and Strategic Life Planning. 2. To trial and evaluate effectiveness of an instructional model. The results as the following: i. An Instructional Model for Health Education consists of five main components: a) Attention b) Forethought c) Tactic Planning d) Execution and e) Reflection. ii. After an Instructional Model for Health Education has used for a semester trial, found the 4.07 percent of sample’s Self-Regulation higher and learning achievement on post-test were significantly higher than pre-test at .05 levels (p = .033, .000).

Keywords: social cognitive theory, strategic life planning, self-regulation, learning achievement

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Authors: Khadija Mushtaq, Mian Saqib Mehmood

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This paper attempts to determine the impact of leadership style and learning orientation on organizational performance in Pakistan. A sample of 158 middle managers selected from sports and surgical factories from Sialkot. The empirical estimation is based on a multiple linear regression analysis of the relationship between leadership style, learning orientation and organizational performance. Leadership style is measure through transformational leadership and transactional leadership. The transformational leadership has insignificant impact on organizational performance. The transactional leadership has positive and significant relation with organizational performance. Learning orientation also has positive and significant relation with organizational performance. Linear regression used to estimate the relation between dependent and independent variables. This study suggests top manger should prefer continuous process for improvement for any change in system rather radical change.

Keywords: transformational leadership, transactional leadership, learning orientation, organizational performance, Pakistan

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Shamshuddin K., Nagaraj Vannal, Diwakar Kulkarni, Raghavendra Nakod

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In most of the universities and colleges Operating System (OS) course is treated as theoretical and usually taught in a classroom using conventional teaching methods. In this paper we are presenting a new approach of teaching OS through experiential learning, the course is designed to suit the requirement of undergraduate engineering program of Instrumentation Technology. This new approach has benefited us to improve our student’s programming skills, presentation skills and understanding of the operating system concepts.

Keywords: pedagogy, interactive learning, experiential learning, OS, C, UNIX

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Authors: Joseph Osodo, Motsa Thobekani Phila

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The study investigated the impact of e-learning on the performance of history learners in Eswatini general certificate of secondary education in the Manzini region of Eswatini. The study was guided by the theory of connectivism. The study had three objectives which were to find out the significance of e-learning during the COVID-19 era in learning History subject; challenges faced by history teachers’ and learners’ in e-learning; and how the challenges were mitigated. The study used a qualitative research approach and descriptive research design. Purposive sampling was used to select eight History teachers and eight History learners from four secondary schools in the Manzini region. Data were collected using face to face interviews. The collected data were analyzed and presented in thematically. The findings showed that history teachers had good knowledge on what e-learning was, while students had little understanding of e-learning. Some of the forms of e-learning that were used during the pandemic in teaching history in secondary schools included TV, radio, computer, projectors, and social media especially WhatsApp. E-learning enabled the continuity of teaching and learning of history subject. The use of e-learning through the social media was more convenient to the teacher and the learners. It was concluded that in some secondary school in the Manzini region, history teacher and learners encountered challenges such as lack of finances to purchase e-learning gadgets and data bundles, lack of skills as well as access to the Internet. It was recommended that History teachers should create more time to offer additional learning support to students whose performance was affected by the COVID-19 pandemic effects.

Keywords: e-learning, performance, COVID-19, history, connectivism

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Authors: Ahasanul Haque, Abdullah Sarwar, Khaliq Ahmed

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Networking is important among students to achieve better understanding. Social networking plays an important role in the education. Realizing its huge potential, various organizations, including institutions of higher learning have moved to the area of social networks to interact with their students especially through Facebook. Therefore, measuring the effectiveness of Facebook as a learning tool has become an area of interest to academicians and researchers. Therefore, this study tried to integrate and propose new theoretical and empirical evidences by linking the western idea of adopting Facebook as an alternative learning platform from a Malaysian perspective. This study, thus, aimed to fill a gap by being among the pioneering research that tries to study the effectiveness of adopting Facebook as a learning platform across other cultural settings, namely Malaysia. Structural equation modelling was employed for data analysis and hypothesis testing. This study findings have provided some insights that would likely affect students’ awareness towards using Facebook as an alternative learning platform in the Malaysian higher learning institutions. At the end, future direction is proposed.

Keywords: Learning Management Tool, social networking, education, Malaysia

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Authors: Ida Srdić, Luka Mandić, LidijaMandić

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Digitization and intensive use of tablets, smartphones, the internet, mobile, and web applications have massively disrupted our habits, and the way audiences (especially youth) consume content. To introduce educational content in games and animations, and at the same time to keep it interesting and compelling for kids, is a challenge. In our work, we are comparing the different possibilities and potentials that digital games could provide to successfully mitigate direct connection with education. We analyze the main directions and educational methods in game-based learning and the possibilities of interactive modeling through questionnaires for user experience and requirements. A pre and post-quantitative survey will be conducted in order to measure levels of objective knowledge as well as the games perception. This approach enables quantitative and objective evaluation of the impact the game has on participants. Also, we will discuss the main barriers to the use of games in education and how games can be best used for learning.

Keywords: Bloom’s taxonomy, epistemic games, learning objectives, virtual learning environments

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Tahzeeb Mahreen

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Distance education refers to giving instruction in which students are remote from the institution and once in a while go to formal demonstration classes, and teaching sessions. Segments of media, for example, radio, TV, PC and Internet and so on are the assets and method for correspondence being utilized as a part of learning material by many open and distance learning institutions. Media has a great part in maximizing the learning opportunities thus enabling distance education, a mode of increased literacy rate of the country. This study goes for analyzing how media had affected distance education through its different mediums. The objectives of the study were (i) to determine the direct impact of media on distance education? (ii) To know how media effects distance education pedagogy (iii) To find out how media works to increase student’s achievement. Literature-based methodology was used, and books, peer-reviewed articles, press reports and internet-based materials were studied as a result. By using descriptive qualitative research analysis, the researcher has interpreted that distance education programs are progressively utilizing mixes of media to convey training that has a positive impact on learning along with a few challenges. In addition, the perception of the researcher varied depending on the programs of distance learning but generally believed that electronic media were moderately more supportive in enhancing the overall performance of the learners. It was concluded that the intellectual style, identity qualities, and self-expectations are the three primary enhanced areas in a student’s educational life in distance education programs. It was portrayed that a comprehension of how individual learners approach learning may make it workable for the distance educator to see an example of learning styles and arrange or modify course presentations through media. Moreover, it is noticed that teaching in distance education address the developing role of the instructor, the requirement for diminishing resistance as conventional teachers utilize remove conveyance frameworks lastly, staff state of mind toward the utilization of innovation. Furthermore, the results showed that media had assumed its part to make distance learning educators more dynamic, capable and concerned about their individual works. The study also indicated a high positive relationship between the media available at study centers and media used by the distance education. The challenge pointed out by the researcher was the clash of distance and time with communication as the life situations of every learner are varied. Recommendations included the realization of the duty of distance learning instructor to help students understand the effective use of media for their study lessons and also to develop online learning communities to be in instant connection with the students.

Keywords: distance education, education, media, teaching and learning

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