Search results for: Socio-cultural context for learning

Authors: Laura Zizka, Gaby Probst

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The Covid-19 pandemic has affected the way Higher Education Institutions (HEIs) have given their courses. From emergency remote where all students and faculty were immediately confined to home teaching and learning, the continuing evolving sanitary situation obliged HEIs to adopt other methods of teaching and learning from blended courses that included both synchronous and asynchronous courses and activities to hy-flex models where some students were on campus while others followed the course simultaneously online. Each semester brought new challenges for HEIs and, subsequently, additional emotional reactions. This paper investigates the affective side of teaching and learning in various online modalities and its toll on students and faculty members over the past three semesters. The findings confirm that students and faculty who have more self-efficacy, flexibility, and resilience reported positive emotions and embraced the opportunities that these past semesters have offered. While HEIs have begun a new semester in an attempt to return to ‘normal’ face-to-face courses, this paper posits that there are lessons to be learned from these past three semesters. The opportunities that arose from the challenge of the pandemic should be considered when moving forward by focusing on a greater emphasis on the affective aspect of teaching and learning in HEIs worldwide.

Keywords: effective teaching and learning, higher education, engagement, interaction, motivation

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Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Robert H. Bradley, Robert F. Corwyn

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There is abundant research showing that socio-economic status is implicated in parenting. However, additional factors such as family context, parent personality, parenting history and child behavior also help determine how parents enact the role of caregiver. Each of these factors not only helps determine how a parent will act in a given situation, but each can serve to moderate the influence of the other factors. Personality has long been studied as a factor that influences parental behavior, but it has almost never been considered as a moderator of family contextual factors. For this study, relations between three maternal personality characteristics (agreeableness, extraversion, neuroticism) and four aspects of parenting (harshness, sensitivity, stimulation, learning materials) were examined when children were 6 months, 36 months, and 54 months old and again at 5th grade. Relations between these three aspects of personality and the overall home environment were also examined. A key concern was whether maternal personality characteristics moderated relations between household income and the four aspects of parenting and between household income and the overall home environment. The data for this study were taken from the NICHD Study of Early Child Care and Youth Development (NICHD SECCYD). The total sample consisted of 1364 families living in ten different sites in the United States. However, the samples analyzed included only those with complete data on all four parenting outcomes (i.e., sensitivity, harshness, stimulation, and provision of learning materials), income, maternal education and all three measures of personality (i.e., agreeableness, neuroticism, extraversion) at each age examined. Results from hierarchical regression analysis showed that mothers high in agreeableness were more likely to demonstrate sensitivity and stimulation as well as provide more learning materials to their children but were less likely to manifest harshness. Maternal agreeableness also consistently moderated the effects of low income on parental behavior. Mothers high in extraversion were more likely to provide stimulation and learning materials, with extraversion serving as a moderator of low income on both. By contrast, mothers high in neuroticism were less likely to demonstrate positive aspects of parenting and more likely to manifest negative aspects (e.g., harshness). Neuroticism also served to moderate the influence of low income on parenting, especially for stimulation and learning materials. The most consistent effects of parent personality were on the overall home environment, with significant main and interaction effects observed in 11 of the 12 models tested. These findings suggest that it may behoove professional who work with parents living in adverse circumstances to consider parental personality in helping to better target prevention or intervention efforts aimed at supporting parental efforts to act in ways that benefit children.

Keywords: home environment, household income, learning materials, personality, sensitivity, stimulation

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Authors: Mark Shiu-kee Shum, Dan Shi

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The paper aims to introduce the ‘Reading to Learn, Learning to Write’ (R2L) pedagogy and its application in teaching reading and writing to non-Chinese speaking (NCS) students in Hong Kong. Guided by the teaching and learning cycles accentuated in R2L pedagogy, sufficient scaffolding was provided for students with an explicit teaching method in literacy education. To understand the influence of using R2L pedagogy on students’ reading and writing abilities across different genres, quantitative data were collected by pre- and post-test of reading and writing tasks in the two different genres of narration and explanation. The pre-test and post-test were used to assess students’ writing performance based on the three textual components of context, discourse, and graphic features, while the reading abilities were assessed at the literal, inferred and interpretive levels of reading comprehension to measure the effectiveness of R2L pedagogy on their literacy improvement. The findings show the use of R2L pedagogy has been proven more effective in improving NCS students’ writing abilities than developing their reading capacity. It is hoped that the R2L-based pedagogic practices can serve as teaching references and pedagogic rationale for L1 language teachers and raise their metalinguistic awareness in teaching Chinese to non-Chinese speaking students in Hong Kong and beyond.

Keywords: pedagogical inclusiveness, literacy education, ethnic minority, reading and writing

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Authors: Chathurika Sewwandi Kannangara, Jerome Carson

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The objective of this research is to identify strengths among the individuals with dyslexia and design a positive psychology intervention to support such individuals. Dyslexia is a combination of abilities and difficulties that affect the learning process in areas as such reading, spelling and writing. It is a persistent condition. The research aims to adapt positive psychology techniques to support individuals with dyslexia. Population of the research will be undergraduate and college level students with dyslexia. First phase of the study will be conducted on a sample of undergraduate and college level students with dyslexia in Bolton, UK. The concept of treatment in positive psychology is not only to fix the component just what is wrong, instead it is also to develop and construct on what is right in the individual. The first phase of the research aims to identify the signature strengths among the individuals with dyslexia using Interviews, Descriptions on personal experiences on ‘My life with Dyslexia’, and Values in Action (VIA) strength survey. In order to conduct the survey for individuals with dyslexia, the VIA survey has been hosted in a website which is solely developed in the form of dyslexia friendly context. Dyslexia friendly website for surveys had designed and developed following the British Dyslexia Association guidelines. The findings of the first phase would be utilized for the second phase of the research to develop the positive psychology intervention.

Keywords: dyslexia, signature strengths, positive psychology, qualitative study, learning difficulties

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Authors: Caroline Labib

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This paper reports on a qualitative study exploring the approaches teachers used to integrate computers or smart tablets into their program planning. Their aim was to integrate ICT into children’s play, thereby supporting children’s learning and development. Data was collected in preschool settings in Melbourne in 2016. Interviews with teachers, observations of teacher interactions with children and copies of teachers’ planning and observation documents informed the study. The paper looks closely at findings from two early childhood settings and focuses on exploring the differing approaches two EC teachers have adopted when integrating iPad or computers into their settings. Data analysis revealed three key approaches which have been labelled: free digital play, guided digital play and teacher-led digital use. Importantly, teacher decisions were influenced by the interplay between the opportunities that the ICT tools offered, the teachers’ prior knowledge and experience about ICT and children’s learning needs and contexts. This paper is a snapshot of two early childhood settings, and further research will encompass data from six more early childhood settings in Victoria with the aim of exploring a wide range of motivating factors for early childhood teachers trying to integrate ICT into their programs.

Keywords: early childhood education (ECE), digital play, information and communication technologies (ICT), play, and teachers' interaction approaches

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Authors: Julianne Mullen-Williams

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This paper will provide an overview of a three year mixed methods research project that explores if methods from the supervision of dramatherapy can augment the occupational psychology of newly qualified secondary school teachers. It will consider how creativity and the use of metaphor, as applied in the supervision of dramatherapists, can be translated to an educational context in order to explore the explicit / implicit dynamics between the teacher trainee/ newly qualified teacher and the organisation in order to support the super objective in training for teaching; how to ‘be a teacher.’ There is growing evidence that attrition rates among teachers are rising after only five years of service owing to too many national initiatives, an unmanageable curriculum and deteriorating student discipline. The fieldwork conducted entailed facilitating a reflective space for Newly Qualified Teachers from all subject areas, using methods from the supervision of dramatherapy, to explore the social and emotional aspects of teaching and learning with the ultimate aim of improving the occupational psychology of teachers. Clinical supervision is a formal process of professional support and learning which permits individual practitioners in frontline service jobs; counsellors, psychologists, dramatherapists, social workers and nurses to expand their knowledge and proficiency, take responsibility for their own practice, and improve client protection and safety of care in complex clinical situations. It is deemed integral to continued professional practice to safeguard vulnerable people and to reduce practitioner burnout. Dramatherapy supervision incorporates all of the above but utilises creative methods as a tool to gain insight and a deeper understanding of the situation. Creativity and the use of metaphor enable the supervisee to gain an aerial view of the situation they are exploring. The word metaphor in Greek means to ‘carry across’ indicating a transfer of meaning form one frame of reference to another. The supervision support was incorporated into each group’s induction training programme. The first year group attended fortnightly one hour sessions, the second group received two one hour sessions every term. The existing literature on the supervision and mentoring of secondary school teacher trainees calls for changes in pre-service teacher education and in the induction period. There is a particular emphasis on the need to include reflective and experiential learning, within training programmes and within the induction period, in order to help teachers manage the interpersonal dynamics and emotional impact within a high pressurised environment

Keywords: dramatherapy supervision, newly qualified secondary school teachers, professional development, teacher education

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Authors: Wen-Chao Tang, Tang-Yi Liu, Ming Gao, Gang Xu, Hua-Yuan Yang

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This study developed a method for teaching acupuncture manipulation in small groups optimized with the theory of motor learning. Sixty acupuncture students and their teacher participated in our research. Motion videos were recorded of their manipulations using the lifting-thrusting method. These videos were analyzed using Simi Motion software to acquire the movement parameters of the thumb tip. The parameter velocity curves along Y axis was used to generate small teaching groups clustered by a self-organized map (SOM) and K-means. Ten groups were generated. All the targeted instruction based on the comparative results groups as well as the videos of teacher and student was provided to the members of each group respectively. According to the theory and research of motor learning, the factors or technologies such as video instruction, observational learning, external focus and summary feedback were integrated into this teaching method. Such efforts were desired to improve and enhance the effectiveness of current acupuncture teaching methods in limited classroom teaching time and extracurricular training.

Keywords: acupuncture, group teaching, video instruction, observational learning, external focus, summary feedback

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Authors: Estevan B. Costa, Armando M. Toda, Marcell A. A. Mesquita, Jacques D. Brancher

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The advances in technology in the last five years allowed an improvement in the educational area, as the increasing in the development of educational software. One of the techniques that emerged in this lapse is called Gamification, which is the utilization of video game mechanics outside its bounds. Recent studies involving this technique provided positive results in the application of these concepts in many areas as marketing, health and education. In the last area there are studies that cover from elementary to higher education, with many variations to adequate to the educators methodologies. Among higher education, focusing on IT courses, data structures are an important subject taught in many of these courses, as they are base for many systems. Based on the exposed this paper exposes the development of an interactive web learning environment, called DSLEP (Data Structure Learning Platform), to aid students in higher education IT courses. The system includes basic concepts seen on this subject such as stacks, queues, lists, arrays, trees and was implemented to ease the insertion of new structures. It was also implemented with gamification concepts, such as points, levels, and leader boards, to engage students in the search for knowledge and stimulate self-learning.

Keywords: gamification, Interactive learning environment, data structures, e-learning

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Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

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Authors: Jenjira Chinnawong, Phusit Phukamchanoad

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The objective of this study is to explore the guidelines for the development of community classroom for research and academic services in Ranong province. By interviewing leaders involved in the development of learning resources, research, and community services, it was found that the leaders' perceptions in the development of learning resources, research, and community services in Ranong, was at the highest level. They perceived at every step on policies of community classroom implementation, research, and community services in Ranong. Leaders' perceptions were at the moderate level in terms of analysis of problems related to procedures of community classroom management, research and community services in Ranong especially in the planning and implementation of the examination, improvement, and development of learning sources to be in good condition and ready to serve the visitors. Their participation in the development of community classroom, research, and community services in Ranong was at a high level, particularly in the participation in monitoring and evaluation of the development of learning resources as well as in reporting on the result of the development of learning resources. The most important thing in the development of community classroom, research and community services in Ranong is the necessity to integrate the three principles of knowledge building in teaching, research and academic services in order to create the identity of the local and community classroom for those who are interested to visit to learn more about the useful knowledge. As a result, community classroom, research, and community services were well-known both inside and outside the university.

Keywords: community classroom, learning resources, development, participation

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Authors: Aabha Chaubey, Bani Bhattacharya

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Evaluation of the quality of teaching in engineering education in India needs to be conducted on a continuous basis to achieve the best teaching quality in technical education. Quality teaching is an influential factor in technical education which impacts largely on learning outcomes of the students. Present study is not exclusively theory-driven, but it draws on various specific concepts and constructs in the domain of technical education. These include teaching and learning in higher education, teacher effectiveness, and teacher evaluation and performance management in higher education. Student Evaluation of Education Quality (SEEQ) was proposed as one of the evaluation instruments of the quality teaching in engineering education. SEEQ is one of the popular and standard instrument widely utilized all over the world and bears the validity and reliability in educational world. The present study was designed to evaluate the teaching quality through SEEQ in the context of technical education in India, including its validity and reliability based on the collected data. The multiple dimensionality of SEEQ that is present in every teaching and learning process made it quite suitable to collect the feedback of students regarding the quality of instructions and instructor. The SEEQ comprises of 9 original constructs i.e.; learning value, teacher enthusiasm, organization, group interaction, and individual rapport, breadth of coverage, assessment, assignments and overall rating of particular course and instructor with total of 33 items. In the present study, a total of 350 samples comprising first year undergraduate students from Indian Institute of Technology, Kharagpur (IIT, Kharagpur, India) were included for the evaluation of the importance of SEEQ. They belonged to four different courses of different streams of engineering studies. The above studies depicted the validity and reliability of SEEQ was based upon the collected data. This further needs Confirmatory Factor Analysis (CFA) and Analysis of Moment structure (AMOS) for various scaled instrument like SEEQ Cronbach’s alpha which are associated with SPSS for the examination of the internal consistency. The evaluation of the effectiveness of SEEQ in CFA is implemented on the basis of fit indices such as CMIN/df, CFI, GFI, AGFI and RMSEA readings. The major findings of this study showed the fitness indices such as ChiSq = 993.664,df = 390,ChiSq/df = 2.548,GFI = 0.782,AGFI = 0.736,CFI = 0.848,RMSEA = 0.062,TLI = 0.945,RMR = 0.029,PCLOSE = 0.006. The final analysis of the fit indices presented positive construct validity and stability, on the other hand a higher reliability was also depicted which indicated towards internal consistency. Thus, the study suggests the effectivity of SEEQ as the indicator of the quality evaluation instrument in teaching-learning process in engineering education in India. Therefore, it is expected that with the continuation of this research in engineering education there remains a possibility towards the betterment of the quality of the technical education in India. It is also expected that this study will provide an empirical and theoretical logic towards locating a construct or factor related to teaching, which has the greatest impact on teaching and learning process in a particular course or stream in engineering education.

Keywords: confirmatory factor analysis, engineering education, SEEQ, teaching and learning process

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Authors: Michael McMahon

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The use of media (video/animation/graphics) has long been used by athletes, coaches, and sports scientists to analyse and improve performance in technical skills and team tactics. Sports educators are increasingly open to the use of technology to support coach and learner development. However, an overreliance is a concern., This paper is part of a larger Ph.D. study looking into these new challenges for Sports Educators. Most notably, how to exploit the deep-learning potential of Digital Media among expert learners, how to instruct sports educators to create effective media content that fosters deep learning, and finally, how to make the process manageable and cost-effective. Central to the study is Richard Mayers Cognitive Theory of Multimedia Learning. Mayers Multimedia Learning Theory proposes twelve principles that shape the design and organization of multimedia presentations to improve learning and reduce cognitive load. For example, the Prior Knowledge principle suggests and highlights different learning outcomes for Novice and Non-Novice learners, respectively. Little research, however, is available to support this principle in modified domains (e.g., sports tactics and strategy). As a foundation for further research, this paper compares and contrasts a range of contemporary multimedia sports coaching content and assesses how they perform as learning tools for Strategic and Tactical Play Acquisition among elite sports practitioners. The stress tests applied are guided by Mayers's twelve Multimedia Learning Principles. The focus is on the elite athletes and whether current coaching digital media content does foster improved sports learning among this cohort. The sport of Gaelic Football was selected as it has high strategic and tactical play content, a wide range of Practitioner skill levels (Novice to Elite), and also a significant volume of Multimedia Coaching Content available for analysis. It is hoped the resulting data will help identify and inform the future instructional content design and delivery for Sports Practitioners and help promote best design practices optimal for different levels of expertise.

Keywords: multimedia learning, e-learning, design for learning, ICT

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Authors: Ruthanne Tobin

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The shift to a personalized learning (PL) curriculum in Canada represents an innovative approach to teaching and learning that is also evident in various initiatives across the 32-nation OECD. The premise behind PL is that empowering individual learners to have more input into how they access and construct knowledge, and express their understanding of it, will result in more meaningful school experiences and academic success. In this paper presentation, the author reports on a document analysis of the new curriculum in the province of British Columbia. Three theoretical frameworks are used to analyze the new curriculum. Framework 1 focuses on five dominant aspects (FDA) of PL at the classroom level. Framework 2 focuses on conceptualizing and enacting personalized learning (CEPL) within three spheres of influence. Framework 3 focuses on the integration of three types of knowledge (content, technological, and pedagogical). Analysis is ongoing, but preliminary findings suggest that the new curriculum addresses framework 1 quite well, which identifies five areas of personalized learning: 1) assessment for learning; 2) effective teaching and learning; 3) curriculum entitlement (choice); 4) school organization; and 5) “beyond the classroom walls” (learning in the community). Framework 2 appears to be less well developed in the new curriculum. This framework speaks to the dynamics of PL within three spheres of interaction: 1) nested agency, comprised of overarching constraints [and enablers] from policy makers, school administrators and community; 2) relational agency, which refers to a capacity for professionals to develop a network of expertise to serve shared goals; and 3) students’ personalized learning experience, which integrates differentiation with self-regulation strategies. Framework 3 appears to be well executed in the new PL curriculum, as it employs the theoretical model of technological, pedagogical content knowledge (TPACK) in which there are three interdependent bodies of knowledge. Notable within this framework is the emphasis on the pairing of technologies with excellent pedagogies to significantly assist students and teachers. This work will be of high relevance to educators interested in innovative school reform.

Keywords: curriculum reform, K-12 school change, innovations in education, personalized learning

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Mamatha Hosapatna, Anne D. Souza, Antony Sylvan Dsouza, Vrinda Hari Ankolekar

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Our study intends to know the effect of the overall teaching program of Anatomy on a students learning. The advancement of various teaching methodologies in the present era has led to progressive changes in education. A student should be able to correlate well between the theory and practical knowledge attained even in the early years of their education in medicine and should be able to implement the same in patient care. The present study therefore aims to assess the impact the current anatomy teaching program has on a students learning and to what extent is it successful in making the learning program effective. Specific objectives of our study to assess the impact of overall teaching program of Anatomy in a students’ learning. Description of process proposed: A questionnaire will be constructed and the students will be asked to put forth their views regarding the Anatomy teaching program and its method of assessment. Suggestions, if any will also be encouraged to be put forth. Type of study is cross sectional observations. Target population is the first year MBBS students and sample size is 250. Assessment plan is to obtaining students responses using questionnaire. Calculating percentages of the responses obtained. Tabulation of the results will be done.

Keywords: anatomy, observational study questionnaire, observational study, M.B.B.S students

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: M.J. Seddighi, Moradchelleh, M. Keyvan

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The ultimate goal in building a city is to provide pleasant, comfortable and nurturing environment as a context of public life. City environment establishes strong connection with people and their surrounding habitant, acting as relevance in social interactions between citizens itself. Urban environment and appropriate municipal facilities are the only way for proper communication between city and citizens and also citizens themselves.There is a need for complement elements between buildings and constructions to settling city life through which the move, comfort, reactions and anxiety will adjust and reflect the spirit to the city. In the surging development of society, urban’ spaces are encountered evolution, sometimes causing the symbols to fade and waste, and as a result, leading to destroy belongs among humans and their physical liquidate. Houses and living spaces exhibit materialistic reflection of life style. In the other words, way of life makes the symbolic essence of living spaces. In addition, it is of sociocultural factor of lifestyle, consisting the concepts and culture, morality, worldview, and national character. Culture is responsible for some crucial meaningful needs which can be wide because they depend on various causes such as perception and interpretation of believes, philosophy of life, interaction with neighbors and protection against climate and enemies. The bi-lateral relationship between human and nature is the main factor that needs to be properly addressed. It is because of the fact that the approach which is taken against landscape and nature has a pertinent influence on creation and shaping the structure of a house. The first response of human in tackling the environment is to build a “shelter” and place as dwelling. This has been a crucial factor in all time periods. In the proposed study, dwelling in Khorasgan’ Stream, as an area located in one of the important historical city of Iran, has been studied. Khorasgan’ Stream is the basic constituent elements of the present architectural form of Isfahan. The influence of Islamic spiritual culture and neighborhood with the historical elements on the dwelling of the selected location, subsequently on other regions of the town are presented.

Keywords: dwelling, neighborhood, historical, Islamic, architectural elements

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Authors: Ann P. Daunic, Nancy Corbett

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Background and Significance: Researchers emphasize the role that motivation, self-esteem, and self-regulation play in children’s early adjustment to the school culture, including skills such as identifying their own feelings and understanding the feelings of others. As social-emotional growth, academic learning, and successful integration within culture and society are inextricably connected, the Social-Emotional Learning Foundations (SELF) curriculum was designed to integrate social-emotional learning (SEL) instruction within early literacy instruction (specifically, reading) for Kindergarten and first-grade students at risk for emotional and behavioral difficulties. Storybook reading is a typically occurring activity in the primary grades; thus SELF provides an intervention that is both theoretically and practically sound. Methodology: The researchers will report on findings from the first two years of a three-year study funded by the US Department of Education’s Institute of Education Sciences to evaluate the effects of the SELF curriculum versus “business as usual” (BAU). SELF promotes the development of self-regulation by incorporating instructional strategies that support children’s use of SEL related vocabulary, self-talk, and critical thinking. The curriculum consists of a carefully coordinated set of materials and pedagogy designed specifically for primary grade children at early risk for emotional and behavioral difficulties. SELF lessons (approximately 50 at each grade level) are organized around 17 SEL topics within five critical competencies. SELF combines whole-group (the first in each topic) and small-group lessons (the 2nd and 3rd in each topic) to maximize opportunities for teacher modeling and language interactions. The researchers hypothesize that SELF offers a feasible and substantial opportunity within the classroom setting to provide a small-group social-emotional learning intervention integrated with K-1 literacy-related instruction. Participating target students (N = 876) were identified by their teachers as potentially at risk for emotional or behavioral issues. These students were selected from 122 Kindergarten and 100 first grade classrooms across diverse school districts in a southern state in the US. To measure the effectiveness of the SELF intervention, the researchers asked teachers to complete assessments related to social-emotional learning and adjustment to the school culture. A social-emotional learning related vocabulary assessment was administered directly to target students receiving small-group instruction. Data were analyzed using a 3-level MANOVA model with full information maximum likelihood to estimate coefficients and test hypotheses. Major Findings: SELF had significant positive effects on vocabulary, knowledge, and skills associated with social-emotional competencies, as evidenced by results from the measures administered. Effect sizes ranged from 0.41 for group (SELF vs. BAU) differences in vocabulary development to 0.68 for group differences in SEL related knowledge. Conclusion: Findings from two years of data collection indicate that SELF improved outcomes related to social-emotional learning and adjustment to the school culture. This study thus supports the integration of SEL with literacy instruction as a feasible and effective strategy to improve outcomes for K-1 students at risk for emotional and behavioral difficulties.

Keywords: Socio-cultural context for learning, social-emotional learning, social skills, vocabulary development

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Authors: Audrey Romero-Pelaez, Juan Carlos Morocho-Yunga

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The increasing amount of open educational resources (OER) published on the web for consumption in teaching and learning environments also generates a growing need to ensure the quality of these resources. The low level of OER discovery is one of the most significant drawbacks when faced with its reuse, and as a consequence, high-quality educational resources can go unnoticed. Metadata enables the discovery of resources on the web. The purpose of this study is to lay the foundations for open educational resources to achieve their first quality star within the Quality4OER Framework. In this study, we evaluate the quality of OER metadata and establish the main guidelines on metadata quality in this context.

Keywords: open educational resources, OER quality, quality metadata

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Authors: Celeste Labuschagne, Sam Ramaila, Thasmai Dhurumraj

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Although formative assessment is acknowledged as crucial for teachers to gauge students’ understanding of subject content, applying formative assessment in an online context is more challenging than in a traditional Physical Sciences classroom. This study examines challenges experienced by Grade 10 Physical Sciences teachers when enacting online formative assessment. The empirical investigation adopted a generic qualitative design and involved three purposively selected Grade 10 Physical Sciences teachers from three different schools and quintiles within the Tshwane North District in South Africa. Data were collected through individual and focus group interviews. Technological, pedagogical, and content knowledge (TPACK) was utilised as a theoretical framework underpinning the study. The study identified a myriad of challenges experienced by Grade 10 Physical Sciences teachers when enacting online formative assessment. These challenges include the utilisation of Annual Teaching Plans, lack of technological knowledge, and internet connectivity. The Department of Basic Education faces the key imperative to provide continuous teacher professional development and concomitant online learning materials that can facilitate meaningful enactment of online formative assessment in various educational settings.

Keywords: COVID-19, challenges, online formative assessment, physical sciences, TPACK

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Authors: Taghreed Alghamdi, Wendy Hall, David Millard

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Massive Open Online Courses (MOOCs) have recently gained widespread interest in the academic world, starting a wide range of discussion of a number of issues. One of these issues, using MOOCs in teaching and learning in the higher education by integrating MOOCs’ contents with traditional face-to-face activities in blended learning format, is called blended MOOCs (bMOOCs) and is intended not to replace traditional learning but to enhance students learning. Most research on MOOCs has focused on students’ perception and institutional threats whereas there is a lack of published research on academics’ experiences and practices. Thus, the first aim of the study is to develop a classification of blended MOOCs models by conducting a systematic literature review, classifying 19 different case studies, and identifying the broad types of bMOOCs models namely: Supplementary Model and Integrated Model. Thus, the analyses phase will emphasize on these different types of bMOOCs models in terms of adopting MOOCs by lecturers. The second aim of the study is to improve the understanding of lecturers’ acceptance of bMOOCs by investigate the factors that influence academics’ acceptance of using MOOCs in traditional learning by distributing an online survey to lecturers who participate in MOOCs platforms. These factors can help institutions to encourage their lecturers to integrate MOOCs with their traditional courses in universities.

Keywords: acceptance, blended learning, blended MOOCs, higher education, lecturers, MOOCs, professors

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Authors: S. Alfalah, J. Falah, T. Alfalah, M. Elfalah, O. Falah

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The field of education is an ever-evolving area constantly enriched by newly discovered techniques provided by active research in all areas of technologies. The recent years have witnessed the introduction of a number of promising technologies and applications to enhance the teaching and learning experience. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing education in many fields. VR creates an artificial environment, using computer hardware and software, which is similar to the real world. This simulation provides a solution to improve the delivery of materials, which facilitates the teaching process by providing a useful aid to instructors, and enhances the learning experience by providing a beneficial learning aid. In order to assure future utilization of such systems, students’ perceptions were examined toward utilizing VR as an educational tool in the Faculty of Information Technology (IT) in The University of Jordan. A questionnaire was administered to IT undergraduates investigating students’ opinions about the potential opportunities that VR technology could offer and its implications as learning and teaching aid. The results confirmed the end users’ willingness to adopt VR systems as a learning aid. The result of this research forms a solid base for investing in a VR system for IT education.

Keywords: information, technology, virtual reality, education

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Authors: Elena Valionienė, Genutė Kalvaitienė

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The issue of resilience of an individual, an organisation, or an entire ecosystem of organisations has recently become an integral part of the education system, where the uncertainties that lead to societal development in the short term create economic, social, and psycho-emotional instability. The Maritime Transport Sector (MTS) is no exception, and the aim of the article is to model the possibilities of enhancing the professional, sociocultural, and psycho-emotional resilience of MTS specialists to proactively respond to crises caused by uncertainties. The research consists of theoretical model creation that helps to identify general maritime business resilience factors and critical success factors. This can develop high resilience and achieve business excellence in a highly volatile, uncertain, complex, and ambiguous (VUCA) environment.

Keywords: maritime transport sector, resilience, uncertainties, VUCA

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Bryony Pound

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This study investigated how views of green or urban space affect learning performance. It provides evidence of the value of visual access to greenspace in work and learning environments, and builds on the extensive research into the cognitive and learning-related benefits of access to green and natural spaces, particularly in learning environments. It demonstrates that benefits of visual access to natural spaces whilst learning can produce statistically significant faster responses than those facing urban views after only 5 minutes. The primary hypothesis of this research was that a greenspace view would improve short-term learning. Participants were randomly assigned to either a view of parkland or of urban buildings from the same room. They completed a psychological test of two stages. The first stage consisted of a presentation of words from eight different categories (four manmade and four natural). Following this a 2.5 minute break was given; participants were not prompted to look out of the window, but all were observed doing so. The second stage of the test involved a word recognition/false memory test of three types. Type 1 was presented words from each category; Type 2 was non-presented words from those same categories; and Type 3 was non-presented words from different categories. Participants were asked to respond with whether they thought they had seen the words before or not. Accuracy of responses and reaction times were recorded. The key finding was that reaction times for Type 2 words (highest difficulty) were significantly different between urban and green view conditions. Those with an urban view had slower reaction times for these words, so a view of greenspace resulted in better information retrieval for word and false memory recognition. Importantly, this difference was found after only 5 minutes of exposure to either view, during winter, and with a sample size of only 26. Greenspace views improve performance in a learning task. This provides a case for better visual access to greenspace in work and learning environments.

Keywords: benefits, greenspace, learning, restoration

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Authors: Nahla Khatib

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This study investigated several learning difficulties that affected the classroom learning experience of preservice students who are studying general science and methods of teaching science students at Faculty of Educational Studies at the Arab Open University (AOU) in Amman, Jordan. The focus questions for this study were to find answers for the following: 1. What are the main areas of learning difficulty among preservice students towards science education? 2. What are the main aspects of reducing obstacles towards success in science education? To achieve this goal, the researcher prepared a questionnaire which included 30 items to point out the learning difficulties among preservice students towards science education. The questionnaire was distributed among students enrolled in the general science courses 1&2 and methods of teaching science courses at the beginning of the spring semester of year (2013-2014). After collecting the filled questionnaire a descriptive statistical analysis was carried out (means and standard deviation) for the items of the questionnaire. After analyzing the data statistically our findings showed that student control–factors as well as course controlled factor, factors related to the nature of science, and factors related to the role of instructor affected student success toward science education. The study was concluded with a number of recommendations.

Keywords: nature of science, preservice teachers, science education, learning difficulties

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Hahido Samaras

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In many cases, especially with the pandemic playing a major role in fast-tracking the growth of the digital industry, online learning has become a necessity or even a standard educational model nowadays, reliably overcoming barriers such as location, time and cost and frequently combined with a face-to-face format (e.g., in blended learning). This being the case, it is evident that students in many parts of the world, as well as their parents, will increasingly need to become aware of the pros and cons of online versus traditional courses. This fast-growing mode of learning, accelerated during the years of the pandemic, presents an abundance of exciting options especially matched for a large number of secondary school students in remote places of the world where access to stimulating educational settings and opportunities for a variety of learning alternatives are scarce, adding advantages such as flexibility, affordability, engagement, flow and personalization of the learning experience. However, online learning can also present several challenges, such as a lack of student motivation and social interactions in natural settings, digital literacy, and technical issues, to name a few. Therefore, educational researchers will need to conduct further studies focusing on the benefits and weaknesses of online learning vs. traditional learning, while instructional designers propose ways of enhancing student motivation and engagement in virtual environments. Similarly, teachers will be required to become more and more technology-capable, at the same time developing their knowledge about their students’ particular characteristics and needs so as to match them with the affordances the technology offers. And, of course, schools, education programs, and policymakers will have to invest in powerful tools and advanced courses for online instruction. By developing digital courses that incorporate intentional opportunities for community-building and interaction in the learning environment, as well as taking care to include built-in design principles and strategies that align learning outcomes with learning assignments, activities, and assessment practices, rewarding academic experiences can derive for all students. This paper raises various issues regarding the effectiveness of online learning on students by reviewing a large number of research studies related to the usefulness and impact of online learning following the COVID-19-induced digital education shift. It also discusses what students, teachers, decision-makers, and parents have reported about this mode of learning to date. Best practices are proposed for parties involved in the development of online learning materials, particularly for secondary school students, as there is a need for educators and developers to be increasingly concerned about the impact of virtual learning environments on student learning and wellbeing.

Keywords: blended learning, online learning, secondary schools, virtual environments

Procedia PDF Downloads 96