Search results for: self-regulated learning theory

Authors: Danjuma Bawa

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This paper aimed at exploring the capabilities of Location-Allocation model in complementing the strides of the existing physical planning models in the location and distribution of facilities for regional consumption. The paper was designed to provide a blueprint to the Nigerian government and other donor agencies especially the Fertilizer Distribution Initiative (FDI) by the federal government for the revitalization of the terrorism ravaged regions. Theoretical underpinnings of central place theory related to spatial distribution, interrelationships, and threshold prerequisites were reviewed. The study showcased how Location-Allocation Model (L-AM) alongside Central Place Theory (CPT) was applied in Geographic Information System (GIS) environment to; map and analyze the spatial distribution of settlements; exploit their physical and economic interrelationships, and to explore their hierarchical and opportunistic influences. The study was purely spatial qualitative research which largely used secondary data such as; spatial location and distribution of settlements, population figures of settlements, network of roads linking them and other landform features. These were sourced from government ministries and open source consortium. GIS was used as a tool for processing and analyzing such spatial features within the dictum of CPT and L-AM to produce a comprehensive spatial digital plan for equitable and judicious location and distribution of fertilizer deports in the study area in an optimal way. Population threshold was used as yardstick for selecting suitable settlements that could stand as service centers to other hinterlands; this was accomplished using the query syntax in ArcMapTM. ArcGISTM’ network analyst was used in conducting location-allocation analysis for apportioning of groups of settlements around such service centers within a given threshold distance. Most of the techniques and models ever used by utility planners have been centered on straight distance to settlements using Euclidean distances. Such models neglect impedance cutoffs and the routing capabilities of networks. CPT and L-AM take into consideration both the influential characteristics of settlements and their routing connectivity. The study was undertaken in two terrorism ravaged Local Government Areas of Adamawa state. Four (4) existing depots in the study area were identified. 20 more depots in 20 villages were proposed using suitability analysis. Out of the 300 settlements mapped in the study area about 280 of such settlements where optimally grouped and allocated to the selected service centers respectfully within 2km impedance cutoff. This study complements the giant strides by the federal government of Nigeria by providing a blueprint for ensuring proper distribution of these public goods in the spirit of bringing succor to these terrorism ravaged populace. This will ardently at the same time help in boosting agricultural activities thereby lowering food shortage and raising per capita income as espoused by the government.

Keywords: central place theory, GIS, location-allocation, network analysis, urban and regional planning, welfare economics

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: Mohammad Mirzaei

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The term "modernism" is at the heart of debates about 20th-century literature and critical theory. Astradur Eysteinsson argues here that the notion of modernity does not emerge directly from the literature it encompasses but is actually a product of critical practices related to non-traditional literature. By intervening in and relating them to modernist works and contemporary literary theories, Esteinsson takes a comprehensive look at the idea of modernity. Eysteinsson critically examines various expressions of modernism in the rich spectrum of American, British, and European literature, criticism, and theory. He first explored a number of modernist paradigms and found a conflict between modernism's potential for cultural subversion and its relatively conservative status as a formalist project. In turn, he sees these paradigms as interpretations and inventions of literary history. Seen in this way, modernism presents both a historical change in the literary scene and the context of this change. Imbued with the connotations of tradition and modernity, modernity fulfills its primary function. Highlights and defines the complex relationship between history and post-realist literature. Eysteinsson focuses on how concepts of modernism guide our understanding of literature and literary history and how they influence the evaluation of experimental and 3post realist works in literature and art. He discusses in detail the relationship between modernism and the key terms postmodernism, avant-garde, and realism. In staging a crisis of subject and reference, modernity is not a form of discourse but its subversion, the "other" that may reveal important aspects of our social and linguistic experience in Western culture.

Keywords: literature, modernism, western cultures, postmodernism

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Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty

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A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.

Keywords: abstractive summarization, deep learning, natural language Processing, patent document

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Authors: Narendra Babu Bommenahalli Veerabhadrappa

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Teaching sustainability concepts along with profit maximizing philosophy of business in management education is a challenge. This paper explores and evaluates various learning models to inculcate sustainability concepts in management education. The paper explains about a new pedagogy that was tested in a business management school (Indus Business Academy, Bangalore, India) to teach sustainability. The pedagogy was designed by intertwining concepts related to sustainability with digital marketing concepts. As part of this experimental method, students (in groups) were assigned with various topics of sustainability and were asked to work with concepts of digital marketing and thus market the concepts of sustainability. The paper explains as a case study as to how sustainability was integrated with digital marketing tools and how learning towards sustainability was facilitated. It also explains the outcomes of this pedagogical method, in terms of inculcating sustainability concepts amongst management students as well as marketing and proliferation of sustainability concepts to bring about the behavioral changes amongst target audience towards sustainability.

Keywords: management-education, pedagogy, sustainability, behavior

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Authors: Muhammad Shakeel Rehman Hissam

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This study aims at analyzing gender in Othello by applying Judith Butler’s Post-Structural theory of gender and gender performance. The analysis of the play provides us context by which we can examine what kinds of effects the drama have on understanding of the researchers regarding gender identity. The study sets out to examine that, is there any evidence or ground in Shakespearean selected work which leads to challenge the patriarchal taken for granted prescribed roles of gender? This would be the focal point in study of Othello that actions and performances of characters determine their gender identity rather than their sexuality. It argues that gender of Shakespearean characters has no constant, fixed and structural impression. On the contrary, they undergo consistent variations in their behavior and performance which impart fluidity and volatility to them. The focal point of the present study is Butler’s prominent work; Gender Trouble: Feminism and subversion of Identity and her post structural theory of Gender performativity as the theoretical underpinning of the text. It analyzes the selected play in Post-Structural gender perspective. The gender-centric plot of the play is riddled with fluidity of gender. The most fascinating aspect of the play is the transformations of genders on the basis of performances by different characters and through these transformations; gender identity is revealed and determined. The study reconstructs the accepted gender norms by challenging the traditional concept of gender that is based on sexual differences of characters.

Keywords: post structural, gender, performativity, socio-cultural gender norms, binaries, Othello, Butler, identity

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Authors: Jacopo Baboni Schilingi

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We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

Keywords: algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Ma Chaoyang

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This article starts from the perspective of environmental justice theory and analyzes the accessibility and regional equity of park green spaces in the central urban area of Chengdu in 2022 based on the improved Gaussian 2SFCA analysis method and Gini coefficient method. Then, according to the relevant analysis model, it further explores the correlation between the spatial distribution of park green spaces and the socio-economic conditions of residents in order to provide a reference for the construction and research of Chengdu's park city under the guidance of fairness and justice. The results show that: (1) Overall, the spatial distribution of parks and green spaces in Chengdu shows a significantly uneven distribution of extreme core edge, with a certain degree of unfairness; that is, there is an environmental injustice pattern. (2) The spatial layout of urban parks and green spaces is subject to strong guiding interference from the socio-economic level; that is, there is a high correlation between housing prices and the tendency of parks. (3) Green space resources Gini coefficient analysis shows that residents of the three modes of transportation in the study area have unequal opportunities to enjoy park and green space services, and the degree of unfairness in walking is much greater than that in cycling and cycling.

Keywords: parks and green spaces, environmental justice, two step mobile search method, Gini coefficient, spatial distribution

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Guinevere Servis

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This paper hypothesizes that withdrawal from positive self-awareness, and the increase of counterfactual-thinking and self-handicapping can help provide ample justification for an individual before, during and/or after committing a crime. The understanding of who someone is, one’s perspective on the world, and why they think the way they do is key to therapy in preventing recidivism. Developing habits to escape self-awareness, by using self-handicapping and counterfactual ideologies, may provide the necessary thinking patterns to decide disobeying the law is a worthy act to pursue. An increase in self-awareness is hypothesized to decrease the likelihood of recidivism, and ways of thinking that withdraw from self awareness can increase the likelihood of it. Especially for those who have been disadvantaged in life and disobeyed the law, self-handicapping and counterfactual thinking can also help to justify one's wrongdoing. The understanding of how a criminal views their disadvantages in the world, and one’s thinking patterns are hypothesized to help one better understand the entire scope on why a crime was committed and thus reduce the likelihood of recidivism. Utilizing therapy for prisoners to increase self-awareness of both thought and action can lead to a healthy, happier life and reduce the likelihood of reoffending. By discussing the terms associated with self-awareness theory and other psychological topics such as self-handicapping, counterfactual thinking, this paper argues the actions towards increasing positive self-awareness can help decrease likelihood of recidivism. Adversely, hypothesizing that increasing the ways of thinking that withdraw one from self-awareness, through counterfactual thinking and self-handicapping, can inherently increase the likelihood of recidivism. Evaluating these findings to further understand the needed changes in correctional institutions is fundamental to reducing crime, benefiting the criminal, the victim(s) and their family, and the state.

Keywords: crime, self-awareness theory, correctional institutions, self-regulate, counterfactual thinking, recidivism

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Authors: Bharatendra Rai

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The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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Authors: S. Odabasi Cimer, A. Cimer

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Recently, the poor quality of education, low achieving students, low international exam performances and little or no effect of the education reforms on the teaching in the classrooms are the main problems of education discussed in Turkey. Research showed that the quality of an education system can not exceed the quality of its teachers and teaching. Therefore, in-service training (INSET) courses are important to improve teacher quality, thereby, the quality of education. However, according to the research conducted on the evaluation of the INSET courses in Turkey, they are not effective in improving the quality of teaching in the classroom. The main reason for this result is because INSET courses are conducted and delivered in limited time and presented theoretically, which does not meet the needs of teachers and as a result, the knowledge and skills taught are not used in the classrooms. Recently, developed countries have been using Critical Friends Groups (CFGs) successfully for the purpose of school-based training of teachers. CFGs are the learning groups which contain 6-10 teachers aimed at fostering their capacities to undertake instructional and personal improvement and schoolwide reform. CFGs have been recognized as a critical feature in school reform, improving teaching practice and improving student achievement. In addition, in the USA, teachers have named CFGs one of the most powerful professional development activities in which they have ever participated. Whereas, in Turkey, the concept is new. This study aimed to investigate the implications of application, evaluation, and promotion of CFGs which has the potential to contribute to teacher development and student learning in schools in Turkey. For this purpose, the study employed a qualitative approach and case study methodology to implement the model in high schools. The research was conducted in two schools and 13 teachers working in these schools participated. The study lasted two years and the data were collected through various data collection tools including interviews, meeting transcripts, questionnaires, portfolios, and diaries. The results of the study showed that CFGs contributed professional development of teachers and their students’ learning. It also contributed to a culture of collaborative work in schools. A number of barriers and challenges which prevent effective implementation were also determined.

Keywords: critical friends group, education reform, science learning, teacher education

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Authors: Caiwei Zhu, Remke Klapwijk

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Spatial thinking, a way of thinking based on the understanding and reasoning of spatial concepts and representations, is embedded in science, technology, engineering, arts, and mathematics (STEAM) learning. Aside from many studies that successfully used targeted training to improve students’ spatial thinking skills, few have closely examined how spatial thinking can be trained in classroom settings. Design and technology education, which receives increasing attention towards its integration into formal curriculums, inherently encompasses a wide range of spatial activities, such as constructing mental representations of design ideas, mentally transforming objects and materials to form designs, visually communicating design plans through annotated drawings, and creating 2D and 3D design artifacts. Among different design topics, biomimicry offers a unique avenue for students to recognize and analyze the shapes and structures in nature. By mapping the forms of plants and animals onto functions, students gain inspiration to solve human design challenges. This study is one of the first to highlight opportunities for training spatial thinking in a biomimicry design project for primary school students. Embracing methodological principles of educational design-based research, this case study is conducted along with iterations in the design of the intervention and collaboration with teachers. Data are harvested from small groups of 10- to 12-year-olds at an international school in the Netherlands. Classroom videos, semi-structured interviews with students, design drawings and artifacts, formative assessment, and the pre- and post-intervention spatial test triangulate evidence for students' spatial thinking. In addition to contributing to a theory of integrating spatial thinking in the primary curriculum, mechanisms underlying such improvement in spatial thinking are explored and discussed.

Keywords: biomimicry, design and technology education, primary education, spatial thinking

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Authors: Nadeesha Sewwandi, Dilini Shashikala, R. Kanapathy, S. Viyasan, R. M. S. Kumara, Duminda Guruge

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Early childhood development is important to the emotional, social, and physical development of young children and it has a direct effect on their overall development and on the adult they become. Play is so important to optimal child developments including skill development, social development, imagination, creativity and it fulfills a baby’s inborn need to learn. So, health promotion approach empowers people about the development of early childhood. Play area is a new concept and this study focus how this play areas helps to the development of early childhood of children in rural villages in Sri Lanka. This study was conducted with a children society in a rural village called Welankulama in Sri Lanka. Survey was conducted with children society about emotional, social and physical development of young children (Under age eight) in this village using questionnaires. It described most children under eight years age have poor level of emotional, social and physical development in this village. Then children society wanted to find determinants for this problem and among them they prioritized determinants like parental interactions, learning environment and social interaction and address them using an innovative concept called play area. In this village there is a common place as play area under a big tamarind tree. It consists of a playhouse, innovative playing toys, mobile library, etc. Twice a week children, parents, grandparents gather to this nice place. Collective feeding takes place in this area once a week and it was conducted by several mothers groups in this village. Mostly grandparents taught about handicrafts and this is a very nice place to share their experiences with all. Healthy competitions were conducted in this place through playing to motivate the children. Happy calendar (mood of the children) was marked by children before and after coming to the play area. In terms of results qualitative changes got significant place in this study. By learning about colors and counting through playing the thinking and reasoning skills got developed among children. Children were widening their imagination by means of storytelling. We observed there were good developments of fine and gross motor skills of two differently abled children in this village. Children learn to empathize with other people, sharing, collaboration, team work and following of rules. And also children gain knowledge about fairness, through role playing, obtained insight on the right ways of displaying emotions such as stress, fear, anger, frustration, and develops knowledge of how they can manage their feelings. The reading and writing ability of the children got improved by 83% because of the mobile library. The weight of children got increased by 81% in the village. Happiness was increased by 76% among children in the society. Playing is very important for learning during early childhood period of a person. Health promotion interventions play a major role to the development of early childhood and it help children to adjust to the school setting and even to enhance children’s learning readiness, learning behaviors and problem solving skills.

Keywords: early childhood development, health promotion approach, play and learning, working with children

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Authors: Malak Alqaydhi

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A problem in the Saudi Arabia education system is that there is a lack of curriculum- based Social, emotional learning (SEL) teaching practices with the pedagogical concept of SEL yet to be practiced in the Kingdom of Saudi Arabia (KSA). Furthermore, voices of teachers and parents have not been captured regarding the use of SEL, particularly in preschools. The importance of this research is to help determine, with the input of teachers and mothers of preschoolers, the efficacy of a culturally adapted SEL program. The purpose of this research is to determine the most appropriate SEL intervention method to appropriately apply in the cultural context of the Saudi preschool classroom setting. The study will use a mixed method exploratory sequential research design, applying qualitative and quantitative approaches including semi-structured interviews with teachers and parents of preschoolers and an experimental research approach. The research will proceed in four phases beginning with a series of interviews with Saudi preschool teachers and mothers, whose voices and perceptions will help guide the second phase of selection and adaptation of a suitable SEL preschool program. The third phase will be the implementation of the intervention by the researcher in the preschool classroom environment, which will be facilitated by the researcher’s cultural proficiency and practical experience in Saudi Arabia. The fourth and final phase will be an evaluation to assess the effectiveness of the trialled SEL among the preschool student participants. The significance of this research stems from its contribution to knowledge about SEL in culturally appropriate Saudi preschools and the opportunity to support initiatives for Saudi early childhood educators to consider implementing SEL programs. The findings from the study may be useful to inform the Saudi Ministry of Education and its curriculum designers about SEL programs, which could be beneficial to trial more widely in the Saudi preschool curriculum.

Keywords: social emotional learning, preschool children, saudi Arabia, child behavior

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Authors: Ezeabasili Chibuike Patrick

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The complex situation of construction industries in Nigeria and the risk of failures involved includes cost overrun, time overrun, Corruption, Government influence, Subcontractor challenges, Political influence and Instability, Cultural differences, Human resources deficiencies, cash flow Challenges, foreign exchange issues, inadequate design, Safety, low productivity, late payment, Quality control issues, project management issues, Environmental issues, Force majeure Competition amongst others has made the industry prone to risk and failures. Good project management remains effective in improving decision-making, which minimizes these risk events. This study was done to address these project risks and good decision-making to avert them. A mixed-method approach to research was used to do this study. Data collected by questionnaires and interviews on thirty-two (32) construction professionals was used in analyses to aid the knowledge and management of risks that were identified. The study revealed that there is no good risk management expertise in Nigeria. Also, that the economic/political situation and the recent COVID-19 pandemic has added to the risk and poor management strategies. The contingency theory and cost has therefore surfaced to be the most strategic management method used to reduce these risk issues and they seem to be very effective.

Keywords: strategies, risk management, contingency theory, Nigeria

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Authors: Nouzha Yasmina Soulimane-Benhabib

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Language is a medium of communication and a means of expression that is why today the learning of foreign languages especially the English language has become a basic necessity for every student who is ambitious. It is known that culture and language are inseparable and complementary, however, in the process of teaching a foreign language, teachers used to focus mainly on preparing adequate syllabi for ESP students, yet, some parameters should be considered. For instance; the culture of the target language may play an important role since students attitudes towards a foreign language enhance their learning or vice versa. The aim of this study is to analyse how culture could influence the teaching of a foreign language, we have taken the example of the English language as it is considered as the second foreign language in Algeria after French. The study is conducted at the Preparatory School of Sciences and Techniques, Tlemcen where twenty-five students participated in this research. The reasons behind learning the English language are various, and since English is the most widely-spoken language in the world, it is the language of research and education and it is used in many other fields, we have to take into consideration one important factor which is the social distance between the culture of the Algerian learner and the culture of the target language, this gap may lead to a culture shock. Two steps are followed in this research: The first one is to collect data from those students who are studying at the Preparatory School under the form of questionnaire and an interview is submitted to six of them in order to reinforce our research and get effective and precise results, and the second step is to analyse these data taking into consideration the diversity of the learners within this institution. The results obtained show that learners’ attitudes towards the English community and culture are mixed and it may influence their curiosity and attention to learn. Despite of big variance between Algerian and European cultures, some of the students focused mainly on the benefits of the English language since they need it in their studies, research and a future carrier, however, the others manifest their reluctance towards this language and this is mainly due to the profound impact of the English culture which is different from the Algerian one.

Keywords: Algeria, culture, English, impact

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Authors: Bernice Badal

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This article addresses a persistent challenge related to teacher agency in knowledge acquisition in professional development (PD) workshops in contexts of educational change, given that scholarship identifies a need for more teacher involvement and amplification of teacher's voices. Theoretical concepts are drawn from Bandura’s Social cognitive theory, incorporating the triadic causation model of agency to examine the reciprocal nature of the context, teacher characteristics, and systemic influences that shape how knowledge is transmitted and acquired in PD workshops. This qualitative study, using a mix of classroom observations and interviews, explored the political, contextual, and personal characteristics of teacher agency in PD through an analysis of data extracted from a PhD study. The narratives of six teachers from three township schools are examined to show how PD efforts in South Africa have failed to take account of the holistic development of teacher agency in knowledge dissemination and how this shapes teacher self-efficacy beliefs about being able to masterfully apply the tenets of the reform. Agency, teacher voice, and contextual considerations were used as markers of the quality of the training provided to understand how knowledge is acquired and meaning is made. The findings suggest that systemic influences of institutionally imposed PD offer partial understandings of the reform, which is offered in traditional formats that do not consider teacher empowerment in knowledge production and the development of teacher agency. Common in all the participants’ responses is the need for more information and training on the prescribed approach for teaching English as a second language; however, this paper holds the view that more information may not solve teachers’ dilemmas. Accordingly, it recommends a restructuring of the programme with facilitators being more cognisant of teacher agency for the development of transformative teachers. The findings of the study contribute to the field of teacher knowledge, teacher training, and professional development in the context of educational reforms.

Keywords: teacher professional development, teacher voice, teacher agency, educational reforms, teacher knowledge

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Authors: Rebecca Laycock

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Many Urban Agriculture (UA) initiatives, including community/allotment gardens, Community Supported Agriculture, and community/social farms, depend on volunteers. However, initiatives supported or run by volunteers are often faced with a high turnover of labour as a result of the involvement of episodic volunteers (a term describing ad hoc, one-time, and seasonal volunteers), leading to challenges with maintaining project continuity and retaining skills/knowledge within the initiative. This is a notable challenge given that food growing is a knowledge intensive activity where the fruits of labour appear months or sometimes years after investment. Participatory Action Research (PAR) is increasingly advocated for in the field of UA as a solution-oriented approach to research, providing concrete results in addition to advancing theory. PAR is a cyclical methodological approach involving researchers and stakeholders collaboratively 'identifying' and 'theorising' an issue, 'planning' an action to address said issue, 'taking action', and 'reflecting' on the process. Through iterative cycles and prolonged engagement, the theory is developed and actions become better tailored to the issue. The demand for PAR in UA research means that understanding how to use PAR with episodic volunteers is of critical importance. The aim of this paper is to explore (1) the challenges of doing PAR in UA initiatives with episodic volunteers, and (2) how PAR can be harnessed to advance sustainable development of UA through theoretically-informed action. A 2.5 year qualitative PAR study on three English case study student-led food growing initiatives took place between 2014 and 2016. University UA initiatives were chosen as exemplars because most of their volunteers were episodic. Data were collected through 13 interviews, 6 workshops, and a research diary. The results were thematically analysed through eclectic coding using Computer-Assisted Qualitative Data Analysis Software (NVivo). It was found that the challenges of doing PAR with transient participants were (1) a superficial understanding of issues by volunteers because of short term engagement, resulting in difficulties ‘identifying’/‘theorising’ issues to research; (2) difficulties implementing ‘actions’ given those involved in the ‘planning’ phase often left by the ‘action’ phase; (3) a lack of capacity of participants to engage in research given the ongoing challenge of maintaining participation; and (4) that the introduction of the researcher acted as an ‘intervention’. The involvement of a long-term stakeholder (the researcher) changed the group dynamics, prompted critical reflections that had not previously taken place, and improved continuity. This posed challenges for providing a genuine understanding the episodic volunteering PAR initiatives, and also challenged the notion of what constitutes an ‘intervention’ or ‘action’ in PAR. It is recommended that researchers working with episodic volunteers using PAR should (1) adopt a first-person approach by inquiring into the researcher’s own experience to enable depth in theoretical analysis to manage the potentially superficial understandings by short-term participants; and (2) establish safety mechanisms to address the potential for the research to impose artificial project continuity and knowledge retention that will end when the research does. Through these means, we can more effectively use PAR to conduct solution-oriented research about UA.

Keywords: community garden, continuity, first-person research, higher education, knowledge retention, project management, transience, university

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Authors: Matthias Haenisch, Katharina Hermann, Marc Godau, Verena Weidner

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Over the past two decades, international music education has been characterized by a growing interest in informal learning for formal contexts and a "compositional turn" that has moved from closed to open forms of composing. This change occurs under social and technological conditions that permeate 21st-century musical practices. This forms the background of Musical Communities in the (Post)Digital Age (MusCoDA), a four-year joint research project of the University of Erfurt (UE) and the University of Education Karlsruhe (PHK), funded by the German Federal Ministry of Education and Research (BMBF). Both explore songwriting processes as an example of collective creativity in (post)digital communities, one in formal and the other in informal learning contexts. Collective songwriting will be studied from a network perspective, that will allow us to view boundaries between both online and offline as well as formal and informal or hybrid contexts as permeable and to reconstruct musical learning practices. By comparing these songwriting processes, possibilities for a pedagogical-didactic interweaving of different educational worlds are highlighted. Therefore, the subproject of the University of Erfurt investigates school music lessons with the help of interviews, videography, and network maps by analyzing new digital pedagogical and didactic possibilities. In the first step, the international literature on songwriting in the music classroom was examined for design development. The analysis focused on the question of which methods and practices are circulating in the current literature. Results from this stage of the project form the basis for the first instructional design that will help teachers in planning regular music classes and subsequently reconstruct musical learning practices under these conditions. In analyzing the literature, we noticed certain structural methods and concepts that recur, such as the Building Blocks method and the pre-structuring of the songwriting process. From these findings, we developed a deck of cards that both captures the current state of research and serves as a method for design development. With this deck of cards, both teachers and students themselves can plan their individual songwriting lessons by independently selecting and arranging topic, structure, and action cards. In terms of science communication, music educators' interactions with the card game provide us with essential insights for developing the first design. The overall goal of MusCoDA is to develop an empirical model of collective musical creativity and learning and an instructional design for teaching music in the postdigital age.

Keywords: card game, collective songwriting, community of practice, network, postdigital

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Authors: Amani Hamdan

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A post-workshop of higher-order thinking skills (HOTS), for faculty from diverse academic disciplines, was conducted and the researcher surveyed the participants’ intentions and plans to include HOTS as a goal, as learning and teaching task in their practices. Follow-up interviews with a random sample of participants were used to determine if they fulfilled their intentions three 3 months after the workshop. The degree of planned and enacted HOTS then was analyzed against the post-workshop HOT ability and knowledge. This is one topic that has not been adequately explored in faculty professional development literature where measuring the effect of learning on their ability to use what they learned. This qualitative method study explored a group of male and female faculty members (n=85) enrolled in HOTS 2 day workshop. The results showed that 89% of faculty members although were mostly enthused to apply what they learned after a 3 months period they were caught up with routine presentations and lecturing.

Keywords: higher education, faculty development, Saudi Arabia, higher order thinking skills

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Authors: Sara Blanc, José V. Benlloch-Dualde, Laura Grindei, Ana C. Torres, Angélica Monteiro

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This paper presents a study that leads a new experience by introducing digital learning applied to a case study focused on primary and secondary school garden-based education. The approach represents an example of interaction among different education and research agents at different countries and levels, such as universities, public and private research, and schools, to get involved in the implementation of education for sustainable development that will make students become more sensible to natural environment, more responsible for their consumption, more aware about waste reduction and recycling, more conscious of the sustainable use of natural resources and, at the same time, more ‘digitally competent’. The experience was designed attending to the European digital education context and OECD directives in transversal skills education. The paper presents the methodology carried out in the study as well as outcomes obtained from experience.

Keywords: school gardens, primary education, secondary education, science technology and innovation in education, digital learning, sustainable development goals, university, knowledge transference

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: Wenwen Lei, David R. Mckenzie

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Recent findings of anomalously high gas flow rates in carbon nanotubes show smooth hydrophobic walls can increase specular reflection of molecules and reduce the tangential momentum accommodation coefficient (TMAC). Here we report the first measurements of water vapor flows in microtubes over a wide humidity range and show that for hydrophobic silica there is a range of humidity over which an adsorbed water layer reduces TMAC and accelerates flow. Our results show that this association between hydrophobicity and accelerated moisture flow occurs in readily available materials. We develop a hierarchical theory that unifies Maxwell’s ideas on TMAC with Langmuir’s ideas on adsorption. We fit the TMAC data as a function of humidity with the hierarchical theory based on two stages of Langmuir adsorption and derive total adsorption isotherms for water on hydrophobic silica that agree with direct observations. We propose structures for each stage of the water adsorption, the first reducing TMAC by a passivation of adsorptive patches and a smoothing of the surface, the second resembling bulk water with large TMAC. We find that leak testing of moisture barriers with an ideal gas such as helium may not be accurate enough for critical applications and that direct measurements of the water leak rate should be made.

Keywords: water vapor flows, silica microtubes, TMAC, enhanced flow rates

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Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

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Authors: Yosra Ben Mhamed

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Most previous research that investigates the importance of earnings volatility for a firm’s value has focused on the effects of earnings volatility on the cost of capital. Many study illustrate that earnings volatility can reduce the firm’s value by enhancing the cost of capital. However, a few recent studies directly examine the relation between earnings volatility and subsequent earnings levels. In our study, we further explore the role of volatility in forecasting. Our study makes two primary contributions to the literature. First, taking into account the level of current firm’s performance, we provide causal theory to the link between volatility and earnings predictability. Nevertheless, previous studies testing the linearity of this relationship have not mentioned any underlying theory. Secondly, our study contributes to the vast body of fundamental analysis research that identifies a set of variables that improve valuation, by showing that earnings volatility affects the estimation of future earnings. Projections of earnings are used by valuation research and practice to derive estimates of firm value. Since we want to examine the impact of volatility on earnings predictability, we sort the sample into three portfolios according to the level of their earnings volatility in ascending order. For each quintile, we present the predictability coefficient. In a second test, each of these portfolios is, then, sorted into three further quintiles based on their level of current earnings. These yield nine quintiles. So we can observe whether volatility strongly predicts decreases on earnings predictability only for highest quintile of earnings. In general, we find that earnings volatility has an inverse relationship with earnings predictability. Our results also show that the sensibility of earnings predictability to ex-ante volatility is more pronounced among profitability firms. The findings are most consistent with overinvestment and persistence explanations.

Keywords: earnings volatility, earnings predictability, earnings persistence, current profitability

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Authors: Vijaya K. Narne, Gerard Loquet, Tobias Piechowiak, Dorte Hammershoi, Jesper H. Schmidt

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BEAR, which stands for better hearing rehabilitation is a large-scale project in Denmark designed and executed by three national universities, three hospitals, and the hearing aid industry with the aim to improve hearing aid fitting. A total of 1963 hearing impaired people were included and were segmented into subgroups based on hearing-loss, demographics, audiological and questionnaires data (i.e., the speech, spatial and qualities of hearing scale [SSQ-12] and the International Outcome Inventory for Hearing-Aids [IOI-HA]). With the aim to provide a better hearing-aid fit to individual patients, we applied modern machine learning techniques with traditional audiograms rule-based systems. Results show that age, speech discrimination scores, and audiogram configurations were evolved as important parameters in characterizing sub-population from the data-set. The attempt to characterize sub-population reveal a clearer picture about the individual hearing difficulties encountered and the benefits derived from more individualized hearing aids.

Keywords: hearing loss, audiological data, machine learning, hearing aids

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Authors: Scott Andersen

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Perhaps simply and rather unadornedly, consciousness is having multiple goals for action and the continuously adjudication of such goals to implement action, referred to as the Maps of Meaning (MoM) Consciousness Theory. The MoM theory triangulates through three parallel corollaries, action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains a fluid, nested goals. These goals are not intentionality, but intersectionality, embodiment meeting the world. i.e., Darwinian inclusive fitness or randomization, then survival of the fittest. These goals form via gradual descent under inclusive fitness, the goals being the abstraction of a ‘match’ between the evolutionary environment and organism. Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience crystallize efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary, but determine the operation and level of one’s consciousness, termed extreme thrownness. Since inclusive fitness drives efficiencies in physiologic mechanism, morphology and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as its the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. Perception is the operant process of consciousness and is the consciousness’ de facto goal adjudication process. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception isn’t a ‘frame rate,’ but Bayesian priors of efficiency based on one’s extreme thrownness. Consciousness and human consciousness is a modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as emergent phenomena at various modularities, like stratified factors in factor analysis). The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

Keywords: consciousness, perception, prospection, embodiment

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Authors: O. V. Vyazovska

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Behavioral efficiency is one of the main principles to be successful in nature. Accuracy of visual discrimination is determined by the attention, learning experience, and memory. In the experimental condition, pigeons’ responses to visual stimuli presented on the screen of the monitor are behaviorally manifested by pecking or not pecking the stimulus, by the number of pecking, reaction time, etc. The higher the probability of rewarding is, the more likely pigeons will respond to the stimulus. We trained 8 pigeons (Columba livia) on a stagewise go/no-go visual discrimination task.16 visual stimuli were created from all possible combinations of four binary dimensions: brightness (dark/bright), size (large/small), line orientation (vertical/horizontal), and shape (circle/square). In the first stage, we presented S+ and 4 S-stimuli: the first that differed in all 4-dimensional values from S+, the second with brightness dimension sharing with S+, the third sharing brightness and orientation with S+, the fourth sharing brightness, orientation and size. Then all 16 stimuli were added. Pigeons rejected correctly 6-8 of 11 new added S-stimuli at the beginning of the second stage. The results revealed that pigeons’ behavior at the beginning of the second stage was controlled by probabilities of rewarding for 4 dimensions learned in the first stage. More or fewer mistakes with dimension discrimination at the beginning of the second stage depended on the number S- stimuli sharing the dimension with S+ in the first stage. A significant inverse correlation between the number of S- stimuli sharing dimension values with S+ in the first stage and the dimensional learning rate at the beginning of the second stage was found. Pigeons were more confident in discrimination of shape and size dimensions. They made mistakes at the beginning of the second stage, which were not associated with these dimensions. Thus, the received results help elucidate the principles of dimensional stimulus control during learning compound multidimensional visual stimuli.

Keywords: visual go/no go discrimination, selective attention, dimensional stimulus control, pigeon

Procedia PDF Downloads 128