Search results for: EFL learning/ teaching

Authors: Sujeet Kumar

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Education has greater importance particularly in terms of increasing human capital and economic competitiveness. It plays a crucial role in terms of cognitive and skill development. Its plays a vital role in process of socialization, fostering social justice, and enhancing social cohesion. Policy related to education has been always a priority for developed countries, which is later adopted by developing countries also. The government of India has also brought change in education polices in line with recognizing change at national and supranational level. However, quality education is still not become an open door for every child in India and several reports are produced year to year about level of school education in India. This paper is concerned with schooling in India. Particularly, it focuses on two government and two private schools in Bihar, but reference has made to schools in Delhi especially around slum communities. The paper presents brief historical context and an overview of current school systems in India. Later, it focuses on analysis of current development in policy in reference with field observation, which is anchored around choice, diversity, market – orientation and gap between different groups of pupils. There is greater degree of difference observed at private and government school levels in terms of quality of teachers, method of teaching and overall environment of learning. The paper concludes that the recent policy development in education particularly Sarva Siksha Abhiyaan (SAA) and Right to Education Act (2009) has required renovating new approach to bridge the gap through broader consultation at grassroots and participatory approach with different stakeholders.

Keywords: education, public policy, participatory approach

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Authors: Owen Cegielski, Kristi Maida, Danny Morales, Sylvia L. Mendez

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This study explores the challenges and threats US secondary educators experience in incorporating culturally relevant education (CRE) practices in their classrooms. CRE is a social justice pedagogical practice used to connect student’s cultural references to academic skills and content, to promote critical reflection, to facilitate cultural competence, and to critique discourses of power and oppression. Empirical evidence on CRE demonstrates positive student educational outcomes in terms of achievement, engagement, and motivation. Additionally, due to the direct focus on uplifting diverse cultures through the curriculum, students experience greater feelings of belonging, increased interest in the subject matter, and stronger racial/ethnic identities. When these teaching practices are in place, educators develop deeper relationships with their students and appreciate the multitude of gifts they (and their families) bring to the classroom environment. Yet, educators regularly report being unprepared to incorporate CRE in their daily teaching practice and identify substantive gaps in their knowledge and skills in this area. Often, they were not exposed to CRE in their educator preparation program, nor do they receive adequate support through school- or district-wide professional development programming. Through a descriptive phenomenological research design, 20 interviews were conducted with a diverse set of secondary school educators to explore the challenges and threats they experience in incorporating CRE practices in their classrooms. The guiding research question for this study is: What are the challenges and threats US secondary educators face when seeking to incorporate CRE practices in their classrooms? Interviews were grounded by the theory of challenge and threat states, which highlights the ways in which challenges and threats are appraised and how resources factor into emotional valence and perception, as well as the potential to meet the task at hand. Descriptive phenomenological data analysis strategies were utilized to develop an essential structure of the educators’ views of challenges and threats in regard to incorporating CRE practices in their secondary classrooms. The attitude of the phenomenological reduction method was adopted, and the data were analyzed through five steps: sense of the whole, meaning units, transformation, structure, and essential structure. The essential structure that emerged was while secondary educators display genuine interest in learning how to successfully incorporate CRE practices, they perceive it to be a challenge (and not a threat) due to lack of exposure which diminishes educator capacity, comfort, and confidence in employing CRE practices. These findings reveal the value of attending to emotional valence and perception of CRE in promoting this social justice pedagogical practice. Findings also reveal the importance of appropriately resourcing educators with CRE support to ensure they develop and utilize this practice.

Keywords: culturally relevant education, descriptive phenomenology, social justice practice, US secondary education

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Authors: Stephen Grant Atkins

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Radical use of project-based learning (PBL) in a small New Zealand business school provides an opportunity to longitudinally examine its effects over a decade of pre-Covid data. Prior to this business school’s implementation of PBL, starting in 2012, the business pedagogy literature presented just one example of PBL replacing an entire core-set of courses. In that instance, a British business school merged four of its ‘degree Year 3’ accounting courses into one PBL semester. As radical as that would have seemed, to students aged 20-to-22, the PBL experiment conducted in a New Zealand business school was notably more extreme: 41 nationally-approved Learning Outcomes (L.O.s), these deriving from 8 separate core courses, were aggregated into one grand set of L.O.s, and then treated as a ‘full-year’/‘full-time’ single course. The 8 courses in question were all components of this business school’s compulsory ‘degree Year 1’ curriculum. Thus, the students involved were notably younger (…ages 17-to-19…), and no ‘part-time’ enrolments were allowed. Of interest are this PBL experiment’s effects on subsequent performance outcomes in ‘degree Years 2 & 3’ (….which continued to operate in their traditional ways). Of special interest is the quality of ‘group project’ outcomes. This is because traditionally, ‘degree Year 1’ course assessments are only minimally based on group work. This PBL experiment altered that practice radically, such that PBL ‘degree Year 1’ alumni entered their remaining two years of business coursework with far more ‘project group’ experience. Timeline-wise, thus of interest here, firstly, is ‘degree Year 2’ performance outcomes data from years 2010-2012 + 2016-2018, and likewise ‘degree Year 3’ data for years 2011-2013 + 2017-2019. Those years provide a pre-&-post comparative baseline for performance outcomes in students never exposed to this school’s radical PBL experiment. That baseline is then compared to PBL alumni outcomes (2013-2016….including’Student Evaluation of Course Quality’ outcomes…) to clarify ‘radical PBL’ effects.

Keywords: project-based learning, longitudinal mixed-methods, students criticism, effects-on-learning

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Authors: M. Kobylanski, D. Buskulic, P.-H. Duron, D. Revuz, F. Ruggieri, E. Sandier, C. Tijus

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In order to design a cooperative e-learning platform, we observed teams of Teacher [T], Computer Scientist [CS] and exerciser's programmer-designer [ED] cooperating for the conception of a self-correcting exercise, but without the use of such a device in order to catch the kind of interactions a useful platform might provide. To do so, we first run a task analysis on how T, CS and ED should be cooperating in order to achieve, at best, the task of creating and implementing self-directed, self-paced, repeatable self-correcting exercises (RSE) in the context of open educational resources. The formalization of the whole process was based on the “objectives, activities and evaluations” theory of educational task analysis. Second, using the resulting frame as a “how-to-do it” guide, we run a series of three contrasted Hackathon of RSE-production to collect data about the cooperative process that could be later used to design the collaborative e-learning platform. Third, we used two complementary methods to collect, to code and to analyze the adequate survey data: the directional flow of interaction among T-CS-ED experts holding a functional role, and the Means-End Problem Solving analysis. Fourth, we listed the set of derived recommendations useful for the design of the exerciser as a cooperative e-learning platform. Final recommendations underline the necessity of building (i) an ecosystem that allows to sustain teams of T-CS-ED experts, (ii) a data safety platform although offering accessibility and open discussion about the production of exercises with their resources and (iii) a good architecture allowing the inheritance of parts of the coding of any exercise already in the data base as well as fast implementation of new kinds of exercises along with their associated learning activities.

Keywords: editorialization, open educational resources, pedagogical alignment, produsage, repeatable self-correcting exercises, team roles

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Authors: Shraddha Jain Sharma, Ratnalata Gupta

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Predicting stock movements in the financial market is both difficult and rewarding. Analysts and academics are increasingly using advanced approaches such as machine learning techniques to anticipate stock price patterns, thanks to the expanding capacity of computing and the recent advent of graphics processing units and tensor processing units. Stock market prediction is a type of time series prediction that is incredibly difficult to do since stock prices are influenced by a variety of financial, socioeconomic, and political factors. Furthermore, even minor mistakes in stock market price forecasts can result in significant losses for companies that employ the findings of stock market price prediction for financial analysis and investment. Soft computing techniques are increasingly being employed for stock market prediction due to their better accuracy than traditional statistical methodologies. The proposed research looks at the need for soft computing techniques in stock market prediction, the numerous soft computing approaches that are important to the field, past work in the area with their prominent features, and the significant problems or issue domain that the area involves. For constructing a predictive model, the major focus is on neural networks and fuzzy logic. The stock market is extremely unpredictable, and it is unquestionably tough to correctly predict based on certain characteristics. This study provides a complete overview of the numerous strategies investigated for high accuracy prediction, with a focus on the most important characteristics.

Keywords: stock market prediction, artificial intelligence, artificial neural networks, fuzzy logic, accuracy, deep learning, machine learning, stock price, trading volume

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Authors: Preethi Sudarshanie Dassanayake, R. A. Sudath Weerasiri

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Objective: The objective of this study were to find out highest expectation and perception,highest gap between perception and expectation of service quality, and to find out such gaps between perception and expectation with regard to service quality dimensions were whether statistically significant. Methodology: This study carried out at the Out Patient Department (OPD) of the Veterinary Teaching Hospital (VTH), University of Peradeniya. Modified version of SERVQUAL with 22-pairs of items regarding expectation and perception of service quality in dimensions of tangible, reliability, responsiveness, assurance and empathy were included in Part 1 and the Part 2 of the questionnaire consisted of questions regarding socio-demographic factors. Sample size was 200 and sampling procedure was Systematic Random Sampling. Customers above 18 years of age, able to read, write and understand Sinhala or English language, visits more than twice in last six months and who willing to respond were selected. Findings: The analysis revealed customers expectations of service higher than the perceived for all 22- items of the SERVQUAL. This high expectation suggests that there is sufficient room for further improvement of service quality in all five dimensions. Originality/Value of the Paper: This study gave a new insight for poorly researched area of veterinary health service quality in Sri Lankan context. It provides hospital administrators and policy makers to develop strategies for further improvement of service quality according to customers' view.

Keywords: expectation, perception, service quality, SERVQUAL, veterinary health care

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Breno Barrreto Silva, Agnieszka Otwinowska, Katarzyna Kutylowska

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Research comparing lexical learning following the writing of sentences and longer texts with keywords is limited and contradictory. One possibility is that the recursivity of writing may enhance processing and increase lexical learning; another possibility is that the higher cognitive load of complex-text writing (e.g., essays), at least when timed, may hinder the learning of words. In our study, we selected 2 sets of 10 academic keywords matched for part of speech, length (number of characters), frequency (SUBTLEXus), and concreteness, and we asked 90 L1-Polish advanced-level English majors to use the keywords when writing sentences, timed (60 minutes) or untimed essays. First, all participants wrote a timed Control essay (60 minutes) without keywords. Then different groups produced Timed essays (60 minutes; n=33), Untimed essays (n=24), or Sentences (n=33) using the two sets of glossed keywords (counterbalanced). The comparability of the participants in the three groups was ensured by matching them for proficiency in English (LexTALE), and for few measures derived from the control essay: VocD (assessing productive lexical diversity), normed errors (assessing productive accuracy), words per minute (assessing productive written fluency), and holistic scores (assessing overall quality of production). We measured lexical learning (depth and breadth) via an adapted Vocabulary Knowledge Scale (VKS) and a free association test. Cognitive load was measured in the three essays (Control, Timed, Untimed) using normed number of errors and holistic scores (TOEFL criteria). The number of errors and essay scores were obtained from two raters (interrater reliability Pearson’s r=.78-91). Generalized linear mixed models showed no difference in the breadth and depth of keyword knowledge after writing Sentences, Timed essays, and Untimed essays. The task-based measurements found that Control and Timed essays had similar holistic scores, but that Untimed essay had better quality than Timed essay. Also, Untimed essay was the most accurate, and Timed essay the most error prone. Concluding, using keywords in Timed, but not Untimed, essays increased cognitive load, leading to more errors and lower quality. Still, writing sentences and essays yielded similar lexical learning, and differences in the cognitive load between Timed and Untimed essays did not affect lexical acquisition.

Keywords: learning academic words, writing essays, cognitive load, english as an L2

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Authors: Peter R. Reuter

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Health professionals play important roles in helping patients use Complementary and Alternative Medicine (CAM) practices safely and accurately. Consequently, it is important for future health professionals to learn about CAM practices during their time in undergraduate and graduate programs. To satisfy this need for education, teaching CAM in nursing and medical schools and other health professions programs is becoming more prevalent. Our study was the first to look specifically at the knowledge of, and attitude toward CAM of undergraduate health professions students at a university in the U.S. Students were invited to participate in one of two anonymous online surveys depending on whether they were pre-health professions students or graduating health professions seniors. Of the 763 responses analyzed, 71.7% were from pre-health professions students, and 28.3% came from graduating seniors. The overall attitude of participants toward and interest in learning about CAM practices was generally fairly positive with graduating seniors being more positive than pre-health professions students. Yoga, meditation, massage therapy, aromatherapy, and chiropractic care were the practices most respondents had personal experience with. Massage therapy, yoga, chiropractic care, meditation, music therapy, and diet-based therapy received the highest ratings from respondents. Three-quarters of respondents planned on including aspects of holistic medicine in their future career as a health professional. The top five practices named were yoga, meditation, massage therapy, diet-based therapy, and music therapy. The study confirms the need to educate health professions students about CAM practices to give them the background information they need to select or recommend the best practices for their patients' needs.

Keywords: CAM education, health professions, health professions students, pre-health professions students

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Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori

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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.

Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing

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Authors: F. Ruiz-Fuster

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Arnold’s redefinition of human motives can sustain a psychology of education which emphasizes the beauty of knowledge and the exercise of intellectual functions. Thus, education instead of focusing on skills and learning by doing would be centered on ‘the widest reaches of the human spirit’. One way to attain it is by developing children’s inherent interest. Arnold takes into account the fact that the desire to know is the inherent interest which leads students to explore and learn. She also emphasizes the need of exercising human functions as thinking, judging and reasoning. According to Arnold, the influence of psychological theories of motivation in education has derived in considering that all learning and school tasks should derive from children’s needs and impulses. The desire to know and the curiosity have not been considered as basic and active as any instinctive drive or basic need, so there has been an attempt to justify and understand how biological drives guide student’s learning. However, understanding motives and motivation not as a drive, an instinct or an impulse guided by our basic needs, but as a want that leads to action can help to understand, from a psychological perspective, how teachers can motivate students to learn, strengthening their desire and interest to reason and discover the whole new world of knowledge.

Keywords: academic motivation, interests, desire to know, educational psychology, intellectual functions

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Li Wang

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The explosive of technology advances has opened up many avenues of career options for engineering graduates. Hence, how relevant their learning at university is very much dependent on their actual jobs. Bridging the gap between education and industrial practice is important, but it also becomes evident how both engineering education and industrial training can be leveraged at the same time and balance between what students should grasp at university and what they can be continuously trained at the working environment. Through a case study of developing a commercial product, this paper presents the required level of depth of technical knowledge and skills for some typical engineering jobs (for mechanical/materials engineering). It highlights the necessary collaboration for industry, university, and accreditation bodies to work together to nurture the next generation of engineers.

Keywords: leverage, collaboration, career, industry, engineering education

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Authors: Jonathan A. Sánchez Muñoz, Gustavo Flores Eraña, Juan M. Silva

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Mexican Mezcal industry has reached attention during the last decade due to it has been a popular beverage demanded by North American and European markets, reaching popularity due to its crafty character. Despite its wide demand, productive processes are still made with rudimentary equipment, and there is a lack of evidence to improve kiln energy efficiency. Tec21 is a challenge-based learning curricular model implemented by Tecnológico de Monterrey since 2019, where each formation unit requires an industrial partner. “Problem processes solution” is a formation unity designed for mechatronics engineers, where students apply the acquired knowledge in thermofluids and apply electronic. During five weeks, students are immersed in an industrial problem to obtain a proper level of competencies according to formation unit designers. This work evaluates the competencies acquired by the student through qualitative research methodology. Several evaluation instruments (report, essay, and poster) were selected to evaluate etic argumentation, principles of sustainability, implemented actions, process modelling, and redesign feasibility.

Keywords: applied electronic, challenge based learning, competencies, mezcal industry, thermofluids

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Authors: Wendi Dunham, Kimberly Floyd

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The constructivist approach to learning is a theoretical orientation that posits that individuals create their own understanding and knowledge of the world through their experiences and interactions. This approach emphasizes that learning is an active process and that individuals are not passive recipients when constructing their understanding of their world. When used concurrently with trauma-informed practices, a constructivist approach can inform the development of a framework for students and teachers that supports their social, emotional, and mental health in addition to enabling academic success. This framework can be applied to teachers and students. When applied to teachers, it can be used to achieve purposeful coping mechanisms through restorative justice and dispositional mindfulness. When applied to students, the framework can implement proactive, student-based practices such as Response to Intervention (RtI) and the 4 Rs to connect resiliency and intervention to academic learning. Using a constructivist, trauma-informed framework can provide students with a greater sense of control and agency over their trauma experiences and impart confidence in achieving school success.

Keywords: trauma, trauma informed practices in education, constructivist theory framework, school responses to trauma, trauma informed supports for teachers, trauma informed strategies for students, restorative justice, mindfulness, response to intervention, the 4 R's, resiliency

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: Iman Al Khalidi

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Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

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Authors: Iman Al Khalidi

Abstract:

Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead a meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently, they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi-methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying, and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

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Authors: Naomi Weiner-Levy

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The Mofet Institute of Research, established a School of Professional Development, the only one of its kind in Israel and throughout the world. It offers specialized programs for teacher educators, providing them with the professional knowledge and skills. The studies aim at updating teachers about rapidly changing knowledge and skills. Teacher educators are conceptualized as shifting from first order practitioners (school teachers) to second order practitioners. Those who train teachers are referred to as third order practitioners. The instructors in the School of Professional Development are third-order practitioners – teacher educators specializing in teaching their colleagues. Collegial guidance by teachers’ college staff members is no simple task: Tutors must be expert in their field of specialization, as well as in instruction. Moreover, although colleagues, they have to position themselves within the group as authoritative figures in terms of instruction and knowledge. To date, the role and professional identity of these third-order practitioners, has not been studied. To understand the nature and development of professional identity, a qualitative study was conducted in which 12 tutors of various subjects were interviewed. These were analyzed by categorical content analysis. The findings, assessed professional identity through a post-modern prism, while examining the interplay among events that tutors experienced, the knowledge they acquired and the structuring of their professional identity. The Tutors’ identity transformed through negotiating with ‘self’ and ‘other’ in the class, and constructed by their mutual experiences as tutors and learners. Understanding the function and identity of tutors facilitates comprehension of this unique training process for teacher educators.

Keywords: professional development, professional identity, teacher education, tutoring

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Maho Komura

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The purpose of this study was to determine from a questionnaire survey of teachers the status of implementation of individualized support for the pupils with suspected developmental disabilities in regular elementary school classes in Japan. In inclusive education, the goal is for all pupils to learn in the same place as much as possible by receiving the individualized support they need. However, in the Japanese school culture, strong "homogeneity" sometimes surfaces, and it is pointed out that it is difficult to provide individualized support from the viewpoint of formal equality. Therefore, we decided to conduct this study in order to examine whether there is a difference in the frequency of implementation depending on the content of individualized support and to consider the direction of future individualized support. The subjects of the survey were 196 public elementary school teachers who had been in charge of regular classes within the past five years. In the survey, individualized support was defined as individualized consideration including rational consideration, and did not include support for the entire class or all pupils enrolled in the class (e.g., reducing the amount of homework for pupils who have trouble learning, changing classroom rules, etc.). (e.g., reducing the amount of homework for pupils with learning difficulties, allowing pupils with behavioral concerns to use the library or infirmary when they are unstable). The respondents were asked to choose one answer from four options, ranging from "very much" to "not at all," regarding the degree to which they implemented the nine individual support items that were set up with reference to previous studies. As a result, it became clear that the majority of teachers had pupils with developmental disabilities or pupils who require consideration in terms of learning and behavior, and that the majority of teachers had experience in providing individualized support to these pupils. Investigating the content of the individualized support that had been implemented, it became clear that the frequency with which it was implemented varied depending on the individualized support. Individualized support that allowed pupils to perform the same learning tasks was implemented more frequently, but individualized support that allowed different learning tasks or use of places other than the classroom was implemented less frequently. It was suggested that flexible support methods tailored to each pupil may not have been considered.

Keywords: inclusive education, ndividualized support, regular class, elementary school

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Authors: Popoola Sulaimon Akorede, Muinat A. Agbabiaka-Mustapha

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The Quranic / piazza school where the rudiments of Islam are being imparted from the teaching of Arabic/ Quranic alphabets which later metamorphosized to higher fundamental principles of Islam is the major determinant of the existence of Islam in any part of south western Nigeria. In other words, one can successfully say that where there is a few or non-existence of such schools in that part of the country, the practice of the religion of Islam would be either very low or not existing at all. However, it has been discovered in the modern worlds that several challenges are militating against the development of these schools and among these challenges are poor admission policy, inadequate facilities such as learning environment and instructional materials, curriculum inadequacy and the management and the administration of the schools which failed to change in order to meet the modern contemporary Educational challenges. The focus of this paper therefore is to improve the conditions of these basic Islamic schools through the introduction of quality assurance and integrating accreditation Exercise to improve their status in order to enhance economic empowerment and to further their educational career in the future so that they will be able to compete favourably among the graduates of conventional universities. The scope of this study is limited to only seven (7) states of yorubaland and with only three (3) proprietors/ schools from each state which are Lagos, Oyo, Ogun, Osun, Ekiti, Ondo and parts of Kwara State. The study revealed that quality assurance as well as accreditation exercise are lacking in all the local Arabic/Quranic schools. Suggestions are proffered towards correcting the anomalies in these schools so that they can meet the modern Educational standard.

Keywords: accreditation, quality assurance, Quranic schools, South-western Nigeria

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Authors: Martha E. Aguiar-Barrera, Humberto Gutierrez-Pulido, Veronica Vargas-Alejo

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Identifying and modeling random phenomena is a fundamental cognitive process to understand and transform reality. Recognizing situations governed by chance and giving them a scientific interpretation, without being carried away by beliefs or intuitions, is a basic training for citizens. Hence the importance of generating teaching-learning processes, supported using technology, paying attention to model creation rather than only executing mathematical calculations. In order to develop the student's knowledge about basic probability distributions and decision making; in this work a model eliciting activity (MEA) is reported. The intention was applying the Model and Modeling Perspective to design an activity related to civil engineering that would be understandable for students, while involving them in its solution. Furthermore, the activity should imply a decision-making challenge based on sample data, and the use of the computer should be considered. The activity was designed considering the six design principles for MEA proposed by Lesh and collaborators. These are model construction, reality, self-evaluation, model documentation, shareable and reusable, and prototype. The application and refinement of the activity was carried out during three school cycles in the Probability and Statistics class for Civil Engineering students at the University of Guadalajara. The analysis of the way in which the students sought to solve the activity was made using audio and video recordings, as well as with the individual and team reports of the students. The information obtained was categorized according to the activity phase (individual or team) and the category of analysis (sample, linearity, probability, distributions, mechanization, and decision-making). With the results obtained through the MEA, four obstacles have been identified to understand and apply the binomial distribution: the first one was the resistance of the student to move from the linear to the probabilistic model; the second one, the difficulty of visualizing (infering) the behavior of the population through the sample data; the third one, viewing the sample as an isolated event and not as part of a random process that must be viewed in the context of a probability distribution; and the fourth one, the difficulty of decision-making with the support of probabilistic calculations. These obstacles have also been identified in literature on the teaching of probability and statistics. Recognizing these concepts as obstacles to understanding probability distributions, and that these do not change after an intervention, allows for the modification of these interventions and the MEA. In such a way, the students may identify themselves the erroneous solutions when they carrying out the MEA. The MEA also showed to be democratic since several students who had little participation and low grades in the first units, improved their participation. Regarding the use of the computer, the RStudio software was useful in several tasks, for example in such as plotting the probability distributions and to exploring different sample sizes. In conclusion, with the models created to solve the MEA, the Civil Engineering students improved their probabilistic knowledge and understanding of fundamental concepts such as sample, population, and probability distribution.

Keywords: linear model, models and modeling, probability, randomness, sample

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Authors: Jennifer Wallbrown

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It’s not uncommon in the US to see news article headlines about public school teachers being scrutinized for what they are teaching or see the general public weighing in on whether or not they think certain controversial subjects should be addressed in the classroom- such as LGBTQ+ or multicultural literature. Even though this is a subject that has been written about and discussed for years, it continues to be a relevant topic in education as it continues to be a struggle to implement more diverse texts. Although it is valid for teachers to fear controversy when they attempt to create a more diverse or inclusive curriculum, it is a fight worth fighting because of the benefits students can gain from being exposed to a wide range of texts. This paper is different from others of its kind because it addresses many of the counterarguments often made to implementing LGBTQ+ or multicultural literature in secondary classrooms. It not only encourages educators to try to include more diverse texts, but it gives them the tools to address common concerns and be sound in their reasoning for choosing these texts. This can be of interest to those educators who are not English teachers because a truly diverse and inclusive curriculum would include other subjects as well- including history, art, and more. By the end of my proposed paper, readers will feel encouraged to choose more diverse and inclusive texts for their classrooms. They can also be confident that if met with opposition or controversy, as is sometimes common when implementing new texts, that they have sound arguments and reasoning for why they chose to include these texts. This reasoning is that, based on the research, studies have found there are benefits to students studying texts about those different from themselves, because it teaches them empathy and helps fight prejudice.

Keywords: education, diverse, inclusive, multicultural, lgbtq+, pedagogy

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Felipa M. Rico

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Linguistic oral competence plays a vital role in attaining effective communication. Since the English language is considered as universally used language and has a high demand skill needed in the work-place, mastery is the expected output from learners. To achieve this, learners should be given integrated differentiated tasks which help them develop and strengthen the expected skills. This study aimed to develop speaking instructional supplementary material to enhance the English linguistic competence of Grade 9 students in areas of pronunciation, intonation and stress, voice projection, diction and fluency. A descriptive analysis was utilized to analyze the speaking level of performance of the students in order to employ appropriate strategies. There were two sets of respondents: 178 Grade 9 students selected through a stratified sampling and chosen at random. The other set comprised English teachers who evaluated the usefulness of the devised teaching materials. A teacher conducted a speaking test and activities were employed to analyze the speaking needs of students. Observation and recordings were also used to evaluate the students’ performance. The findings revealed that the English pronunciation of the students was slightly unclear at times, but generally fair. There were lapses but generally they rated moderate in intonation and stress, because of other language interference. In terms of voice projection, students have erratic high volume pitch. For diction, the students’ ability to produce comprehensible language is limited, and as to fluency, the choice of vocabulary and use of structure were severely limited. Based on the students’ speaking needs analyses, the supplementary material devised was based on Nunan’s IM model, incorporating context of daily life and global work settings, considering the principle that language is best learned in the actual meaningful situation. To widen the mastery of skill, a rich learning environment, filled with a variety instructional material tends to foster faster acquisition of the requisite skills for sustained learning and development. The role of IM is to encourage information to stick in the learners’ mind, as what is seen is understood more than what is heard. Teachers say they found the IM “very useful.” This implied that English teachers could adopt the materials to improve the speaking skills of students. Further, teachers should provide varied opportunities for students to get involved in real life situations where they could take turns in asking and answering questions and share information related to the activities. This would minimize anxiety among students in the use of the English language.

Keywords: diction, fluency, intonation, instructional materials, linguistic competence

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Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

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This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

Procedia PDF Downloads 135