Search results for: personalized learning paths

Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: Brenda Ravenscroft, Ulemu Luhanga, Bev King

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A comprehensive evaluation of online learning needs to include a blend of educational design, technology use, and online instructional practices that integrate technology appropriately for developing and delivering quality online courses. Research shows that classroom-based evaluation tools do not adequately capture the dynamic relationships between content, pedagogy, and technology in online courses. Furthermore, studies suggest that using classroom evaluations for online courses yields lower than normal scores for instructors, and may affect faculty negatively in terms of administrative decisions. In 2014, the Faculty of Arts and Science at Queen’s University responded to this evidence by seeking an alternative to the university-mandated evaluation tool, which is designed for classroom learning. The Faculty is deeply engaged in e-learning, offering large variety of online courses and programs in the sciences, social sciences, humanities and arts. This paper describes the process by which a new student survey instrument for online courses was developed and piloted, the methods used to analyze the data, and the ways in which the instrument was subsequently adapted based on the results. It concludes with a critical reflection on the challenges of evaluating e-learning. The Student Evaluation of Online Teaching Effectiveness (SEOTE), developed by Arthur W. Bangert in 2004 to assess constructivist-compatible online teaching practices, provided the starting point. Modifications were made in order to allow the instrument to serve the two functions required by the university: student survey results provide the instructor with feedback to enhance their teaching, and also provide the institution with evidence of teaching quality in personnel processes. Changes were therefore made to the SEOTE to distinguish more clearly between evaluation of the instructor’s teaching and evaluation of the course design, since, in the online environment, the instructor is not necessarily the course designer. After the first pilot phase, involving 35 courses, the results were analyzed using Stobart's validity framework as a guide. This process included statistical analyses of the data to test for reliability and validity, student and instructor focus groups to ascertain the tool’s usefulness in terms of the feedback it provided, and an assessment of the utility of the results by the Faculty’s e-learning unit responsible for supporting online course design. A set of recommendations led to further modifications to the survey instrument prior to a second pilot phase involving 19 courses. Following the second pilot, statistical analyses were repeated, and more focus groups were used, this time involving deans and other decision makers to determine the usefulness of the survey results in personnel processes. As a result of this inclusive process and robust analysis, the modified SEOTE instrument is currently being considered for adoption as the standard evaluation tool for all online courses at the university. Audience members at this presentation will be stimulated to consider factors that differentiate effective evaluation of online courses from classroom-based teaching. They will gain insight into strategies for introducing a new evaluation tool in a unionized institutional environment, and methodologies for evaluating the tool itself.

Keywords: evaluation, online courses, student survey, teaching effectiveness

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Authors: Mohamad Abdullah

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Recent Advancements in technology have stimulated deep change in the language learning classroom. Flipped classroom as a new pedagogical method is at the center of this change. It turns the classroom into a student-centered environment and promotes interactive and autonomous learning. The present study is an attempt to examine the effectiveness of the Flipped Classroom Model (FCM) on students’ motivation level in English speaking performance. This study was carried out with 27 undergraduate female English majors who enrolled in the course of Advanced Communication Skills (ENGL 154) at Buraimi University College (BUC). Data was collected through Motivation in English Speaking Performance Questionnaire (MESPQ) which has been distributed among the participants of this study pre and post the implementation of FCM. SPSS was used for analyzing data. The Paired T-Test which was carried out on the pre-post of (MESPQ) showed a significant difference between them (p < .009) that revealed participants’ tendency to increase their motivation level in English speaking performance after the application of FCM. In addition, respondents of the current study reported positive views about the implementation of FCM.

Keywords: english speaking performance, motivation, flipped classroom model, learner-contentedness

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Authors: Eman Mohamed Abdelwahab, Badreyya Alkhanbooli

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This study focuses on exploring the challenges encountered by English language teachers in same-ability English language classrooms in the United Arab Emirates public schools. This qualitative study uses open-ended questions for data collection from teacher participants. The study sample includes the participation of 60 English language teachers from 8 public schools across 4 emirates/cities in the United Arab Emirates. The study results highlight a number of challenges that are mostly encountered by English language teachers in their classrooms while teaching in same-ability classrooms, including lack of diversity in abilities, class-time limitation, difficulty in engaging all students (especially lower-achieving students), limited opportunities for peer learning and limited linguistic diversity. A set of suggestions is to be provided by participating teachers and researchers to improve the same-ability teaching and learning experience in English language classrooms.

Keywords: English language teaching, same ability grouping, ESL, English language learners

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Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

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Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Farzaneh Sarbandi Farahani

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Drought and decrease in the level of lakes in recent years due to global warming and excessive use of water resources feeding lakes are of great importance, and this research has provided a structure to investigate this issue. First, the information required for simulating lake drought is provided with strong references and necessary assumptions. Entity-Component-System (ECS) structure has been used for simulation, which can consider assumptions flexibly in simulation. Three major users (i.e., Industry, agriculture, and Domestic users) consume water from groundwater and surface water (i.e., streams, rivers and lakes). Lake Mead has been considered for simulation, and the information necessary to investigate its drought has also been provided. The results are presented in the form of a scenario-based design and optimal strategy selection. For optimal strategy selection, a deep reinforcement algorithm is developed to select the best set of strategies among all possible projects. These results can provide a better view of how to plan to prevent lake drought.

Keywords: drought simulation, Mead lake, entity component system programming, deep reinforcement learning

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Authors: Fakieh Alrabai

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This paper presents an experimental study designed to explore some of the learner’s individual and interpersonal factors (e.g. persistence, interest, regulation, satisfaction, appreciation, etc.) that Saudi learners experience when learning English as a Foreign Language and how learners’ perceptions of these factors influence various aspects of their motivation to learn English language. As part of the study, a 27-item structured survey was administered to a randomly selected sample of 105 Saudi learners from public schools and universities. Data collected through the survey were subjected to some basic statistical analyses, such as "mean" and "standard deviation". Based on the results from the analysis, a number of generalizations and conclusions are made in relation to how these inherent factors affect Saudi learners’ motivation to learn English as a foreign language. In addition, some recommendations are offered to Saudi academics on how to effectively make use of such factors, which may enable Saudi teachers and learners of English as a foreign language to achieve better learning outcomes in an area widely associated by Saudis with lack of success.

Keywords: persistence, interest, appreciation, satisfaction, SL/FL motivation

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Authors: Gokcen Akyurek, Hulya Kayihan, Deniz Yuce, Selen Yilmaz

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The stigma towards mental illness is still very rooted in our society, despite the number of studies, campaigns, and anti-stigma programs developed in recent years. Stigma represents a serious obstacle to recovery and social integration for people who experience a mental illness, affecting directly their well-being and quality of life. It implies that these persons have to deal with many other barriers apart from the disease symptoms (1-5). Convergent, recent literature suggests that less positive attitudes by mental health professionals interfere with the self-determination and recovery process (4-10).The aim of this study was to translate the Attribution Questionnaire-27 (AQ-27) to the Turkish language (AQ-27-T), and to examine the reliability and validity of this new Turkish version. Cultural adaptation was implemented according to the internationally suggested method. To determine the understandability and appropriateness of this measure for the Turkish culture, a pretest was administered and the final form was generated. Then, 424 randomly chosen people took part in the study. Participant’s mean age was 36.9±12.7 years and %52 of them female. Cronbach's alpha and intra-class coefficients were used to estimate instrument reliability. The AQ-27-T was assessed again 14 days later for test retest reliability. The AQ-27-T demonstrated acceptable internal consistency, with a Cronbach's alpha of 0.88 for the total scale and ranging between 0.86 and 0.89 for the items. The test-retest reliability was good, with Pearson correlation coefficients of 0.79 for the total scale and ranging between 0.35 and 0.77 for the items (p<0.05). Correlation between subscales was moderate-good, with Pearson correlation coefficients of 0.18-0.88 (p<0.05). Fit indices of the model supported the factor structure and paths. The AQ-27-T is a reliable measure to assess stigmatizing attitudes in Turkish.

Keywords: attribution questionnaire, validity, reliability, stigma

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Authors: A. Marais

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A challenging aspect of teaching cello to novice adult learners is finding adequate lesson material and applying relevant teaching methodologies. It could play a crucial role in adult learners' decision to commence or stop taking music lessons. This study contributes to the theory and practises of continuing education. This study is important to lifelong learning, especially with the focus on adult teaching and learning and the difficulties concerning these themes. The research problem identified for this study is we are not aware of adults' life stories; thus, cello lesson material is not always relevant for adult's specific needs for motivation and goals for starting cello lessons. In my experience, an adult does not necessarily want to play children songs when they learn a new instrument. They want material and lessons fitted to adult learners. Adults also learn differently from younger beginners. Adults ask questions such as how and why, while children more readily accept what is being taught. This research creates awareness of adults' musical needs and learning methods. If every adult shares their own story for commencing and continuing with cello lessons, material should be created, revised, or adapted for more individually appropriate lessons. A number of studies show that adults taking music lessons experience a decrease in feelings of loneliness and isolation. It gives adults a sense of wellbeing and can help improve immune systems. The purpose of this research study will be to discover the life stories of adult amateur cellists. At this stage in the research, the life stories of amateur cellists can generally be defined as personal reflections of their motivations for and experiences of commencing and continuing with individual lessons. The findings of this study will contribute to the development of cello lesson material for adult beginners based on their stories. This research could also encourage adults to commence with music lessons and could, in that way, contribute to their quality of life. Music learners become aware of deep spiritual, emotional, and social values incorporated or experienced through musical learning. This will be a qualitative study with a narrative approach making use of oral history. The chosen method will encapsulate the stories of amateur individual adults starting and continuing with cello lessons. The narrative method entails experiences as expressed in lived and told stories of individuals. Oral history is used as part of the narrative method and entails gathering of personal reflections of events and their cause and effects from an individual or several individuals. These findings from this study will contribute to adult amateur cellists' motivations to continue with music lessons and inspire others to commence. The inspiring life stories of the amateur cellists would provide insight into finding and creating new cello lesson material and enhance existing teaching methodologies for adult amateur cellists.

Keywords: adult, amateur, cello, education, learning, music, stories

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Authors: Andrew Gryguć, Seyed Behzad Behravesh, Hamid Jahed, Mary Wells, Wojciech Macek, Bruce Williams

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This extended abstract investigates the influence of the multiaxial loading on the fatigue behavior of forged magnesium through quantitative analysis of its fracture surface topography and mesoscopic cracking orientation. Fatigue tests were performed on hollow tubular sample geometries extracted from closed-die forged AZ80 Mg components, with three different multiaxial strain paths (axial/shear), proportional, 45° out of phase, and 90° out of phase. Regardless of the strain path, fatigue cracks are initiated at the outer surface of the specimen where the combined stress state is largest. Depending on the salient mode of deformation, distinctive features in the fracture surface manifested themselves with different topographic amplitudes, surface roughness, and mesoscopic cracking orientation in the vicinity of the initiation site. The dominant crack propagation path was in the circumferential direction of the hollow tubular specimen (i.e., cracking transverse to the sample axis, with little to no branching), which is congruent with previous findings of low to moderate shear strain energy density (SED) multiaxial loading. For proportional loading, the initiation zone surface morphology was largely flat and striated, whereas, at phase angles of 45° and 90°, the initiation surface became more faceted and inclined. Overall, both a qualitative and quantitative link was developed between the fracture surface morphology and the level of non-proportionality in the loading providing useful insight into the fracture mechanics of forged magnesium as a relevant focus for future study.

Keywords: fatigue, fracture, magnesium, forging, fractography, anisotropy, strain energy density, asymmetry, multiaxial fatigue

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Authors: Pantaleon Lutta, Mohamed Sedky, Mohamed Hassan

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The inability of organizations to put in place management control measures for Internet of Things (IoT) complexities persists to be a risk concern. Policy makers have been left to scamper in finding measures to combat these security and privacy concerns. IoT forensics is a cumbersome process as there is no standardization of the IoT products, no or limited historical data are stored on the devices. This paper highlights why IoT forensics is a unique adventure and brought out the legal challenges encountered in the investigation process. A quadrant model is presented to study the conflicting aspects in IoT forensics. The model analyses the effectiveness of forensic investigation process versus the admissibility of the evidence integrity; taking into account the user privacy and the providers’ compliance with the laws and regulations. Our analysis concludes that a semi-automated forensic process using machine learning, could eliminate the human factor from the profiling and surveillance processes, and hence resolves the issues of data protection (privacy and confidentiality).

Keywords: cloud forensics, data protection Laws, GDPR, IoT forensics, machine Learning

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Authors: Cina Mosito, Toyin Mary Adewumi, Charlene Nissen

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One of the goals of inclusive education is to provide learners with suitable learning environments and prospects to best attain their potential. This study sought to determine the experiences of studying inclusive education on pre-service teachers’ teaching within the South African education context. A purposeful sample comprising 6 pre-service teachers was selected from a university of technology located in the Western Cape South Africa. Data were collected using open-ended questionnaires, which were exploratory in nature and analyzed thematically. The findings supported significant proportions of experiences as self-reported by pre-service teachers. The pre-service teachers’ experiences of studying inclusive education included inclusive education as an “eye-opener” to the fact that learners experiencing various barriers to learning can be accommodated in the regular classrooms, exposure to some aspects of inclusive education, such as diversity, learners’ rights, and curriculum differentiation. It was also revealed that studying inclusive education made pre-service teachers love and enjoy teaching more. The study shows that awareness of inclusive education has influenced pre-service teachers in South African schools.

Keywords: experience, inclusive education, pre-service teacher, South Africa

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Authors: Anne Marie Morrin

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This paper will focus on the design, delivery and assessment of a transdisciplinary STEAM (Science, Technology, Engineering, Arts, and Mathematics) education initiative in a college of education in Ireland. The project explores a transdisciplinary approach to supporting STEAM education where the concepts, methodologies and assessments employed derive from visual art sessions within initial teacher education. The research will demonstrate that the STEAM Education approach is effective when visual art concepts and methods are placed at the core of the teaching and learning experience. Within this study, emphasis is placed on authentic collaboration and transdisciplinary pedagogical approaches with the STEAM subjects. The partners included a combination of teaching expertise in STEM and Visual Arts education, artists, in-service and pre-service teachers and children. The inclusion of all stakeholders mentioned moves towards a more authentic approach where transdisciplinary practice is at the core of the teaching and learning. Qualitative data was collected using a combination of questionnaires (focused and open-ended questions) and focus groups. In addition, the data was collected through video diaries where students reflected on their visual journals and transdisciplinary practice, which gave rich insight into participants' experiences and opinions on their learning. It was found that an effective program of STEAM education integration was informed by co-teaching (continuous professional development), which involved a commitment to adaptable and flexible approaches to teaching, learning, and assessment, as well as the importance of continuous reflection-in-action by all participants. The delivery of a transdisciplinary model of STEAM education was devised to reconceptualizatise how individual subject areas can develop essential skills and tackle critical issues (such as self-care and climate change) through data visualisation and technology. The success of the project can be attributed to the collaboration, which was inclusive, flexible and a willingness between various stakeholders to be involved in the design and implementation of the project from conception to completion. The case study approach taken is particularistic (focusing on the STEAM-ED project), descriptive (providing in-depth descriptions from varied and multiple perspectives), and heuristic (interpreting the participants’ experiences and what meaning they attributed to their experiences).

Keywords: collaboration, transdisciplinary, STEAM, visual arts education

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language is one of the most important and the most demanding skills to be mastered by non-native speakers. Traditionally, the EAP writing instruction at the tertiary level encompasses the teaching of academic genre knowledge, more specifically, the disciplinary writing conventions, the rhetorical functions, and specific linguistic features. However, one of the main sources of challenges in English academic writing for L2 students at the tertiary level can still be found in proficiency in academic discourse, especially vocabulary, academic register, and organization. Data-Driven Learning (DDL) is defined as “a pedagogical approach featuring direct learner engagement with corpus data”. In the past two decades, the rising popularity of the application of the data-driven learning (DDL) approach in the field of EAP writing teaching has been noticed. Such a combination has not only transformed traditional pedagogy aided by published DDL guidebooks in classroom use but also triggered global research on corpus use in EAP classrooms. This study endeavors to delineate a systematic review of research in the intersection of DDL and EAP writing instruction by conducting a systematic literature review on both indirect and direct DDL practice in EAP writing instructional settings in China. Furthermore, the review provides a synthesis of significant discoveries emanating from prior research investigations concerning Chinese university students’ perception of Data-Driven Learning (DDL) and the subsequent impact on their academic writing performance following corpus-based training. Research papers were selected from Scopus-indexed journals and core journals from two main Chinese academic databases (CNKI and Wanfang) published in both English and Chinese over the last ten years based on keyword searches. Results indicated an insufficiency of empirical DDL research despite a noticeable upward trend in corpus research on discourse analysis and indirect corpus applications for material design by language teachers. Research on the direct use of corpora and corpus tools in DDL, particularly in combination with genre-based EAP teaching, remains a relatively small fraction of the whole body of research in Chinese higher education settings. Such scarcity is highly related to the prevailing absence of systematic training in English academic writing registers within most Chinese universities' EAP syllabi due to the Chinese English Medium Instruction policy, where only English major students are mandated to submit English dissertations. Findings also revealed that Chinese learners still held mixed attitudes towards corpus tools influenced by learner differences, limited access to language corpora, and insufficient pre-training on corpus theoretical concepts, despite their improvements in final academic writing performance.

Keywords: corpus linguistics, data-driven learning, EAP, tertiary education in China

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Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Maimuna Akram, Khadija Zia, Sohaib Naseer

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Pedagogical objectives and the nature of the course content may lead instructors to take varied approaches to selecting a student for the cold call, specifically in a studio setup where students work on different projects independently and show progress work time to time at scheduled critiques. Cold-calling often proves to be an effective tool in eliciting a response without enforcing judgment onto the recipients. While there is a mixed range of behavior exhibited by students who are cold-called, a classification of responses from anxiety-provoking to inspiring may be elicited; there is a need for a greater understanding of utilizing the exchanges in bringing about fruitful and engaging outcomes of studio discussions. This study aims to unravel the dimensions of utilizing the cold-call approach in a didactic exchange within studio pedagogy. A questionnaire survey was conducted in an undergraduate class at Arts and Design School. The impact of cold calling on students’ participation was determined through various parameters, including course choice, participation frequency, students’ comfortability, and teaching methodology. After analyzing the surveys, specific classroom teachers were interviewed to provide a qualitative perspective of the faculty. It was concluded that cold-calling increases students’ participation frequency and also increases preparation for class. Around 67% of students responded that teaching methods play an important role in learning activities and students’ participation during class discussions. 84% of participants agreed that cold calling is an effective way of learning. According to research, cold-calling can be done in large numbers without making students uncomfortable. As a result, the findings of this study support the use of this instructional method to encourage more students to participate in class discussions.

Keywords: active learning, class discussion, class participation, cold calling, pedagogical methods, student engagement

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Authors: Ayperi̇ Haspolat Özcan, Meltem Anafarta Şendağ

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This study aimed to establish a model in the light of current approaches for understanding the mediating role of early maladaptive schemas in the relationship between attachment and anger. Accordingly, the proposed mediation model was tested by mediation with bootstrapping technique, considering gender and attachment figure differences. The university students (N= 444) with ages ranging from 17 to 28 participated in the study. Participants filled out Parental and Peer Attachment Scale Short Form, Young Schema Questionnaire - Short Form 3, Trait Anger and Anger Expression Scales. The mediating role of early maladaptive schemas (impaired autonomy, disconnection and rejection, unrelenting standards, other-directedness, and impaired limits) in the relationship between attachment (mother and father) and anger aspects (trait anger, anger in, anger out and anger control) were found to be significant for both male and female participants. Separate mediation analyses for both genders and different attachment figures have also drawn attention to noticeable differences in the results. Specifically, for females, various paths were discovered in predicting various aspects of anger (anger in, anger out, anger control, and trait anger). On the other hand, for males only anger directed inwards was found to be predicted by any source of attachment through disconnection and rejection schema only. These obvious gender differences in understanding the mechanism of anger are discussed in the light of cultural gender roles and the social acceptance of anger in males. In the area of application, the study of various aspects of anger with particular attention to attachment and early maladaptive schemas as well as the importance of distinguishing the gender differences are emphasized as important points.

Keywords: anger expression, attachment, early maladaptive schemas, trait anger

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Authors: Candela Contero Urgal

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Using realia to teach English for Specific Purposes (ESP) is a must, as it is thought to be designed to meet the students’ real needs in their professional life. Teachers are then expected to offer authentic materials and set students in authentic contexts where their learning outcomes can be highly meaningful. One way of engaging students is using social networks as a way to bridge the gap between their everyday life and their ESP learning outcomes. It is in ESP, particularly in Business English teaching, that our study focuses, as the ongoing process of digitalization is leading firms to use social media to communicate with potential clients. The present paper is aimed at carrying out a case study in which different digital tools are employed as a way to offer a collection of formats businesses are currently using so as to internationalize and advertise their products and services. A secondary objective of our study will then be to progress on the development of multidisciplinary competencies students are to acquire during their degree. A two-phased study will be presented. The first phase will cover the analysis of course tasks accomplished by undergraduate students at the University of Cadiz (Spain) in their third year of the Degree in Business Management and Administration by comparing the results obtained during the years 2019 to 2021. The second part of our study will present a survey conducted to these students in 2021 and 2022 so as to verify their interest in learning new ways to digitalize as well as internationalize their future businesses. Findings will confirm students’ interest in working with updated realia in their Business English lessons, as a consequence of their strong belief in the necessity to have authentic contexts and didactic resources. Despite the limitations social media can have as a means to teach business English, students will still find it highly beneficial since it will foster their familiarisation with the digital tools they will need to use when they get to the labour market.

Keywords: English for specific purposes, business English, internationalization of higher education, foreign language teaching

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Authors: Milan N. A. Van Der Kuil, Anne M. A. Visser-Meily, Andrea W. M. Evers, Ineke J. M. Van Der Ham

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Navigation ability is essential for autonomy and mobility in daily life. In patients with acquired brain injury, navigation impairment is frequently impaired; however, in this study, we tested the effectiveness of a serious gaming training protocol as a tool for cognitive rehabilitation to reduce navigation impairment. In total, 38 patients with acquired brain injury and subjective navigation complaints completed the experiment, with a partially blind, randomized control trial design. An objective navigation test was used to construct a strengths and weaknesses profile for each patient. Subsequently, patients received personalized compensation training that matched their strengths and weaknesses by addressing an egocentric or allocentric strategy or a strategy aimed at minimizing the use of landmarks. Participants in the experimental condition received psychoeducation and a home-based rehabilitation game with a series of exercises (e.g., map reading, place finding, and turn memorization). The exercises were developed to stimulate the adoption of more beneficial strategies, according to the compensatory approach. Self-reported navigation ability (wayfinding questionnaire), participation level, and objective navigation performance were measured before and after 1 and 4 weeks after completing the six-week training program. Results indicate that the experimental group significantly improved in subjective navigation ability both 1 and 4 weeks after completion of the training, in comparison to the score before training and the scores of the control group. Similarly, goal attainment showed a significant increase after the first and fourth week after training. Objective navigation performance was not affected by the training. This navigation training protocol provides an effective solution to address navigation impairment after acquired brain injury, with clear improvements in subjective performance and goal attainment of the participants. The outcomes of the training should be re-examined after implementation in a clinical setting.

Keywords: spatial navigation, cognitive rehabilitation, serious gaming, acquired brain injury

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Authors: Alex Elentukh

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The paper is based on data collected from final exams administered during five years of teaching the graduate course in software engineering. The visualization instrument with four distinct personas has been used to improve the effectiveness of each class. The study offers a plethora of clues toward students' behavioral preferences. Diversity among students (professional background, physical proximity) is too significant to assume a single face of a learner. This is particularly true for a body of online graduate students in computer science. Conclusions of the study (each learner is unique, and each class is unique) are extrapolated to demystify the notion of an 'average software engineer.' An immediate direction for an educator is to ensure a course applies to a wide audience of very different individuals. On the other hand, a student should be clear about his/her abilities and preferences - to follow the most effective learning path.

Keywords: K.3.2 computer and information science education, learner profiling, adaptive learning, software engineering

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Authors: Chris Procter

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There is a significant debate on the role of University education in developing or teaching employability skills. Should higher education attempt to do this? Is it the best place? Is it able to do so? Different views abound, but the question is wrongly posed – one of the reasons that previous employability initiatives foundered (e.g., in the UK). Our role is less to teach than to guide, less to develop and more to help articulate: “the mind is not a vessel to be filled, but a fire to be lit” (Plutarch). This paper then addresses how this can be achieved taking into account criticism of employability initiatives as well as relevant learning theory. It discusses the experience of a large module which involved students being assessed on all stages of application for a live job description together with reflection on their professional development. The assessment itself adopted a Patchwork Text approach as a vehicle for learning. Students were guided to evaluate their strengths and areas to be developed, articulate their competencies, and reflect upon their development, moving on to new Thresholds of Employability. The paper uses the student voices to express the progress they made. It concludes that employability can and should be an effective part of the higher education curriculum when designed to encourage students to confidently articulate their competencies and take charge of their own professional development.

Keywords: competencies, employability, patchwork assessment, threshold concepts

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Authors: Mohammad Haghighi, Amineh Akhondi, Leila Jahangard, Mohammad Ahmadpanah, Masoud Ansari

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Background: According to the recent estimation, approximately 4%-12% percent of Iranians have difficulty in learning to read and spell possibly as a result of developmental dyslexia. The study was planned to investigate spelling error patterns among Persian children with developmental dyslexia and compare that with the errors exhibited by control groups Participants: 90 students participated in this study. 30 students from Grade level five, diagnosed as dyslexics by professionals, 30 normal 5th Grade readers and 30 younger normal readers. There were 15 boys and 15 girls in each of the groups. Qualitative and quantitative methods for analysis of errors were used. Results and conclusion: results of this study indicate similar spelling error profiles among dyslexics and the reading level matched groups, and these profiles were different from age-matched group. However, performances of dyslexic group and reading level matched group were different and inconsistent in some cases.

Keywords: spelling, error types, developmental dyslexia, Persian, writing system, learning disabilities, processing

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Authors: Zehra Buyuktuncer, Aylin H. Büyükkaragöz, Tuğçe N. Balcı, Nevin Ergun

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Background: Undergoing rigid dietary habits for enhancing athletic performance could lead to eating disorders. High prevalence of eating disorders among female athletes has been already reported. However, the risk of disordered eating among disabled athletes is not known. A better knowledge of the different eating behaviors and their prevalence in disabled athletes would be helpful to understand interactions between eating and health. This study aimed to examine the cognitive restraint, uncontrolled eating and emotional eating behaviors in a disabled athlete population. Method: A total of 70 disabled Turkish national athletes (33 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball) were involved in the study. The cognitive restraint, uncontrolled eating and emotional eating behaviors were assessed using the revised version of Three Factor Eating Questionnaire-R18 (TFEQ-R18). The questionnaires were conducted by dietitian during the preparation camps of athletes. Body weight, height and waist circumference (WC) were measured; and body composition was analyzed by bioelectrical impedance analysis method. Results: The TFEQ scales showed a cognitive dietary restraint score of 13.9±4.2, uncontrolled eating score of 17.7±5.8 and emotional eating score of 4.9±2.5. The mean score of total TFEQ-R18 was 36.5±8.62. Neither total TFEQ-R18 score nor subscale scores differed significantly by gender or sport branches (p>0.05, for each). The scores were also similar in BMI groups (n=63; p>0.05). Total TFEQ, uncontrolled eating and emotional eating scores were significantly higher among the athletes with congenital disabilities compared to the scores of the athletes with acquired disabilities (p<0.05, for each). Moreover, the cognitive dietary restraint score was significantly high in athletes who would like to lose weight (p=0.009). Conclusion: Disabled athletes might have a risk of disordered eating. The different eating behaviors among disabled athletes should be assessed using validated tools to develop personalized nutritional strategies for those athletes.

Keywords: disabled athletes, eating behaviour, three-factor eating questionnaire-r18, body composition

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Authors: Zarah M. Bello, Nathan Baddoo, Mariana Lilley, Paul Wernick

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In this paper, we present findings from a multi-part study to evaluate candidate elements reflecting the level of digital capability maturity (DCM) in higher education and the relationship between these elements. We will use these findings to propose a model of DCM for educational institutions. We suggest that the success of learning in higher education is dependent in part on the level of maturity of digital capabilities of institutions as well as the abilities of learners and those who support the learning process. It is therefore important to have a good understanding of the elements that underpin this maturity as well as their impact and interactions in order to better exploit the benefits that technology presents to the modern learning environment and support its continued improvement. Having identified ten candidate elements of digital capability that we believe support the level of a University’s maturity in this area as well as a number of relevant stakeholder roles, we conducted two studies utilizing both quantitative and qualitative research methods. In the first of these studies, 85 electronic questionnaires were completed by various stakeholders in a UK university, with a 100% response rate. We also undertook five in-depth interviews with management stakeholders in the same university. We then utilized statistical analysis to process the survey data and conducted a textual analysis of the interview transcripts. Our findings support our initial identification of candidate elements and support our contention that these elements interact in a multidimensional manner. This multidimensional dynamic suggests that any proposal for improvement in digital capability must reflect the interdependency and cross-sectional relationship of the elements that contribute to DCM. Our results also indicate that the notion of DCM is strongly data-centric and that any proposed maturity model must reflect the role of data in driving maturity and improvement. We present these findings as a key step towards the design of an operationalisable DCM maturity model for universities.

Keywords: digital capability, elements, maturity, maturity framework, university

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Authors: Keundong Lee, Dongha Yoo, Youngbin Tchoe, Gyu-Chul Yi

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Light emitting diode (LED) array is an ideal optical stimulation tool for optogenetics, which controls inhibition and excitation of specific neurons with light-sensitive ion channels or pumps. Although a fiber-optic cable with an external light source, either a laser or LED mechanically connected to the end of the fiber-optic cable has widely been used for illumination on neural tissue, a new approach to use micro LEDs (µLEDs) has recently been demonstrated. The LEDs can be placed directly either on the cortical surface or within the deep brain using a penetrating depth probe. Accordingly, this method would not need a permanent opening in the skull if the LEDs are integrated with miniature electrical power source and wireless communication. In addition, multiple color generation from single µLED cell would enable to excite and/or inhibit neurons in localized regions. Here, we demonstrate flexible and color tunable µLEDs for the optogenetic device applications. The flexible and color tunable LEDs was fabricated using multifaceted gallium nitride (GaN) nanorod arrays with GaN nanorods grown on InxGa1−xN/GaN single quantum well structures (SQW) anisotropically formed on the nanorod tips and sidewalls. For various electroluminescence (EL) colors, current injection paths were controlled through a continuous p-GaN layer depending on the applied bias voltage. The electric current was injected through different thickness and composition, thus changing the color of light from red to blue that the LED emits. We believe that the flexible and color tunable µLEDs enable us to control activities of the neuron by emitting various colors from the single µLED cell.

Keywords: light emitting diode, optogenetics, graphene, flexible optoelectronics

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Authors: Francesca Perri

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This paper describes a proposal for a teachers’ training course, focused on the introduction of corpora in the EFL didactics (English as a foreign language) of some Italian secondary schools. The training course is conceived as a part of a TEDD participant’s five months internship. TEDD (Technologies for Education: diversity and devices) is an advanced course held by the Department of Engineering and Information Technology at the University of Trento, Italy. Its main aim is to train a selected, heterogeneous group of graduates to engage with the complex interdependence between education and technology in modern society. The educational approach draws on a plural coexistence of various theories as well as socio-constructivism, constructionism, project-based learning and connectivism. TEDD educational model stands as the main reference source to the design of a formative course for EFL teachers, drawing on the digitalization of didactics and creation of learning interactive materials for L2 intermediate students. The training course lasts ten hours, organized into five sessions. In the first part (first and second session) a series of guided and semi-guided activities drive participants to familiarize with corpora through the use of a digital tools kit. Then, during the second part, participants are specifically involved in the realization of a ML (Mistakes Laboratory) where they create, develop and share digital activities according to their teaching goals with the use of corpora, supported by the digital facilitator. The training course takes place into an ICT laboratory where the teachers work either individually or in pairs, with a computer connected to a wi-fi connection, while the digital facilitator shares inputs, materials and digital assistance simultaneously on a whiteboard and on a digital platform where participants interact and work together both synchronically and diachronically. The adoption of good ICT practices is a fundamental step to promote the introduction and use of Corpus Linguistics in EFL teaching and learning processes, in fact dealing with corpora not only promotes L2 learners’ critical thinking and orienteering versus wild browsing when they are looking for ready-made translations or language usage samples, but it also entails becoming confident with digital tools and activities. The paper will explain reasons, limits and resources of the pedagogical approach adopted to engage EFL teachers with the use of corpora in their didactics through the promotion of digital practices.

Keywords: digital didactics, education, language learning, teacher training

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Authors: Ka Lei Au

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The Dalcroze method has been emerging in music classrooms, and music teachers are encouraged to integrate music and movement in their teaching. Music programs in colleges in Hong Kong have been introducing method courses such as Orff and Dalcroze method in music teaching as teacher’s education program. Since the targeted students of the course are music teachers who are making the decision of what approach to use in their classroom, their perception is significantly valued to identify how this approach is applicable in their teaching in regards to the teaching and learning culture and environment. This qualitative study aims to explore how the Dalcroze method as a teacher’s education course is perceived by music teachers from three aspects: 1) application in music teaching, 2) self-enhancement, 3) expectation. Through the lens of music teachers, data were collected from 30 music teachers who are taking the Dalcroze method course in music teaching in Hong Kong by the survey. The findings reveal the value and their intention of the Dalcroze method in Hong Kong. It also provides a significant reference for better development of such courses in the future in adaption to the culture, teaching and learning environment and teacher’s, student’s and parent’s perception of this approach.

Keywords: Dalcroze method, music teaching, perception, self-enhancement, teacher’s education

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Authors: Leah Ning

Abstract:

This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

Procedia PDF Downloads 91