Search results for: self-regulated learning theory

Authors: Mohammad Tipu Sultan, Farzana Sharmin, Ke Xue

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Social media create a better opportunity for travelers to search for travel information, select destination and share their personal experiences of the travel. This study proposes a framework which describes the relationships between social media, and positive or negative tourism experience sharing impact on destination choice. To find out new trends of travelers behavioral intention, we propose an extended theoretical model, the Theory of Reasoned Action (TRA). We conducted a survey to analyze three external factors, subjective norms, and positive and negative experience influence on travel destination choice. Structural questionnaire analysis was employed to confirm the proposed research hypothesis within the relationship between consumer influences on the shared experience of social media. The results of the study confirm that sharing positive experiences influence the positive effect of destination choice, while negative experiences decrease the destination selection option. The results indicate that attitudes, subjective norms are passively influenced by shared experience. Moreover, we find that sharing live pictures of travel experiences through social media helps to reduce negative perceptions of the destination brand. This research contribution is useable to the research field as a new determination factor and the findings could be used by destination organization management (DMO) to enhancing their tourism promotion through social media.

Keywords: destination choice, tourism experience sharing, Theory of Reasoned Action, TRA, social media

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Authors: Xueyan Hu, Liwen Chen, Weilin He, Sujie Peng

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Writing is an important but challenging skill For English language learners. Due to the small amount of time allocated for writing classes at schools, students have relatively few opportunities to practice writing in the classroom. While the practice of integrating listening and speaking activates with writing instruction has been used for adult English language learners, its application for young English learners has seldom been examined due to the challenge of listening and speaking activities for young English language learners. The study attempted to integrating integrating listening and speaking activities with writing instruction for middle school English language learners so as to improving their writing achievements and writing abilities in terms of the word use, coherence, and complexity in their writings. Guided by Gagne's information processing learning theory and memetics, this study conducted a 8-week writing instruction with an experimental class (n=44) and a control class (n=48) . Students in the experimental class participated in a series of listening and retelling activities about a writing sample the teacher used for writing instruction during each period of writing class. Students in the control class were taught traditionally with teachers’ direction instruction using the writing sample. Using the ANCOVA analysis of the scores of students’ writing, word-use, Chinese-English translation and the text structure, this study showed that the experimental writing instruction can significantly improve students’ writing performance. Compared with the students in the control class, the students in experimental class had significant better performance in word use and complexity in their essays. This study provides useful enlightenment for the teaching of English writing for middle school English language learners. Teachers can skillfully use information technology to integrate listening, speaking, and writing teaching, considering students’ language input and output. Teachers need to select suitable and excellent composition templates for students to ensure their high-quality language input.

Keywords: wring instruction, retelling, English language learners, listening and speaking

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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: Mayantoinette F. Watson

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During such an unprecedented time of the largest public health crisis, the COVID-19 pandemic, nursing students are of the utmost concern regarding their psychological and physical well-being. Questions are emerging and circulating about what will happen to the nursing students and the long-term effects of the pandemic, especially now that hospitals are being overwhelmed with a significant need for nursing staff. Expectations, demands, change, and the fear of the unknown during this unprecedented time can only contribute to the many stressors that accompany nursing students through laborious clinical and didactic courses in nursing programs. The risk of psychological distress is at a maximum, and its effects can negatively impact not only nursing students but also nursing education and academia. The high exposures to interpersonal, economic, and academic demands contribute to the major health concerns, which include a potential risk for psychological distress. Achievement of educational success among nursing students is directly affected by the high exposure to anxiety and depression from experiences within the program. Working relationships and achieving academic success is imperative to positive student outcomes within the nursing program. The purpose of this study is to identify and establish influences and associations within multilevel factors, including the effects of the COVID-19 pandemic on psychological distress in nursing students. Neuman’s Systems Model Theory was used to determine nursing students’ responses to internal and external stressors. The research in this study utilized a mixed-methods, convergent study design. The study population included undergraduate nursing students from Southeastern U.S. The research surveyed a convenience sample of undergraduate nursing students. The quantitative survey was completed by 202 participants, and 11 participants participated in the qualitative follow-up interview surveys. Participants completed the Kessler Psychological Distress Scale (K6), the Perceived Stress Scale (PSS4), and the Dundee Readiness Educational Environment Scale (DREEM12) to measure psychological distress, perceived stress, and perceived educational environment. Participants also answered open-ended questions regarding their experience during the COVID-19 pandemic. Statistical tests, including bivariate analyses, multiple linear regression analyses, and binary logistics regression analyses were performed in effort to identify and highlight the effects of independent variables on the dependent variable, psychological distress. Coding and qualitative content analysis were performed to identify overarching themes within participants’ interviews. Quantitative data were sufficient in identifying correlations between psychological distress and multilevel factors of coping, marital status, COVID-19 stress, perceived stress, educational environment, and social support in nursing students. Qualitative data were sufficient in identifying common themes of students’ perceptions during COVID-19 and included online learning, workload, finances, experience, breaks, time, unknown, support, encouragement, unchanged, communication, and transmission. The findings are significant, specifically regarding contributing factors to nursing students’ psychological distress, which will help to improve learning in the academic environment.

Keywords: nursing education, nursing students, pandemic, psychological distress

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Authors: Damir Latypov

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A hybrid classical-quantum algorithm to solve boundary integral equations (BIE) arising in problems of electromagnetic and acoustic scattering is proposed. The quantum speed-up is due to a Quantum Linear System Algorithm (QLSA). The original QLSA of Harrow et al. provides an exponential speed-up over the best-known classical algorithms but only in the case of sparse systems. Due to the non-local nature of integral operators, matrices arising from discretization of BIEs, are, however, dense. A QLSA for dense matrices was introduced in 2017. Its runtime as function of the system's size N is bounded by O(√Npolylog(N)). The run time of the best-known classical algorithm for an arbitrary dense matrix scales as O(N².³⁷³). Instead of exponential as in case of sparse matrices, here we have only a polynomial speed-up. Nevertheless, sufficiently high power of this polynomial, ~4.7, should make QLSA an appealing alternative. Unfortunately for the QLSA, the asymptotic separability of the Green's function leads to high compressibility of the BIEs matrices. Classical fast algorithms such as Multilevel Fast Multipole Method (MLFMM) take advantage of this fact and reduce the runtime to O(Nlog(N)), i.e., the QLSA is only quadratically faster than the MLFMM. To be truly impactful for computational electromagnetics and acoustics engineers, QLSA must provide more substantial advantage than that. We propose a computational scheme which combines elements of the classical fast algorithms with the QLSA to achieve the required performance.

Keywords: quantum linear system algorithm, boundary integral equations, dense matrices, electromagnetic scattering theory

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Authors: Rania Mousa, Peterson Ozili

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A key agenda of policymakers in developed and developing countries is to increase the level of financial inclusion. Microlending institutions have been recognized as important agents of financial inclusion, which have the potential to achieve this objective and help move toward a more accessible, inclusive, and equitable path to financial sustainability. In that respect, this case study attempts to identify and assess the key initiatives undertaken by Grameen America as it responded to the COVID-19 pandemic within the framework of selected United Nations’ Sustainability Development Goals (UN’s SD Goals). This study goes beyond the stated objective by using the vulnerable group theory and special agent theory of financial inclusion to support the analysis of financial and non-financial information collected from Grameen America’s Annual Reports and audited financial statements. The study follows a qualitative content analysis method to precisely gauge the shift in Grameen’s strategy and focus, as well as to assess the impact of its initiatives on the small business community before and after the pandemic. The findings showcase that Grameen’s longstanding mission to alleviate poverty is in line with the UN’s Sustainability Development Goal 1. Furthermore, Grameen’s commitment to creating partnerships with external organizations to offer credit and non-credit services and support is consistent with UN’s Sustainability Development Goal 17. The study suggests that policymakers should foster the creation of more member-based financial and non-financial institutions which are ethically and morally responsible to their members in both good and bad times.

Keywords: COVID-19, financial inclusion, microfinance, sustainable development, microlending

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Authors: Sadullah Rahmani

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Legends, stories, beliefs and traditions in every nation represent the collective dreams, secrets and aspirations of a nation and on the other hand, the foundation of their collective memory; What generally forms the foundation of the culture of any nation has undergone changes and transformations due to the passage of time and changes in political, religious and social conditions. Afghanistan is one of the richest countries in terms of cultural diversity. This country is home to people of different languages, ethnicities and religions. The purpose of this article is to analyze the contrasts and cultural commonalities between two ethnic groups in Afghanistan, namely the Hazara and Uzbek peoples. This research was done with qualitative method and structured interview tool. The method of data analysis is content analysis. In order to explain the intercultural sensitivities of the two groups, Milton Bennett's intercultural sensitivities measures have been used. Based on the theory of intercultural sensitivities, the development of communication is an important factor in reducing intercultural sensitivities. In this research, 8 people from the Hazara and Uzbek tribes were interviewed. Various factors such as customs and manners, music, language, art, lifestyle, etc. have been examined in the article. These factors can contribute to cultural differences and commonalities between the Hazara and Uzbek peoples. The results of this research show that according to Bennett's theory, there are less cultural sensitivities between the Hazara and Uzbek peoples of Afghanistan, especially in matters of marriage, language, economic poverty, being discriminated against, and work relationships; But cultural sensitivities are more in many other cases such as education, religion and the formation of cultural communities.

Keywords: Keywords: Uzbek, language, culture, religion, Hazara.

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Authors: Louise Bunce, Jill Childs, Adam J. Lonsdale, Naomi King

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A major concern for the Social Work profession concerns the frequency of burn-out and high turnover of staff. The characteristic of resilience has been identified as playing a crucial role in social workers’ ability to have a satisfying and successful career. Thus a critical role for social work education is to develop resilience in social work students. We currently need to know more about how to train resilient social workers who will also increase the academic standing of the profession. The specific aim of this research was to quantify characteristics that may contribute towards resilience and academic success among student social workers in order to mitigate against the problems of burn-out and low academic standing. These three characteristics were competence (effectiveness at mastering the environment), autonomy (sense of control and free will), and relatedness (interacting and connecting with others), as specified in Self-Determination Theory (SDT). When these three needs are satisfied, we experience higher degrees of motivation to succeed and wellbeing. Thus when these three needs are met in social work students, they have the potential to raise academic standards and promote wellbeing characteristics that contribute to the development of resilience. The current study tested the hypothesis that higher levels of autonomy, competence, and relatedness, as defined by SDT, will predict levels of academic success and resilience in social work students. Two hundred and ten social work students studying at a number of universities completed well-established questionnaires to assess autonomy, competence, and relatedness, level of academic performance and resilience (The Brief Resilience Scale). In this scale, students rated their agreement with items e.g., ‘I bounce back quickly after hard times’ and ‘I usually come through difficult times with little struggle’. After controlling for various factors, including age, gender, ethnicity, and course (undergraduate or postgraduate) preliminary analysis revealed that the components of SDT provided useful predictive value for academic success and resilience. In particular, autonomy and competence provided a useful predictor of academic success while relatedness was a particularly useful predictor of resilience. This study demonstrated that SDT provides a valuable framework for helping to understand what predicts academic success and resilience among social work students. This is relevant because the psychological needs for autonomy, competence and relatedness can be affected by external social and cultural pressures, thus they can be improved by the right type of supportive teaching practices and educational environments. These findings contribute to the growing evidence-base to help build an academic and resilient social worker student body and workforce.

Keywords: education, resilience, self-determination theory, student social workers

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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: Jizhi Zhao, Qiliang Zhou, Muxuan Tao

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The calculation of the ultimate loading capacity of composite frame beams is an important step in the design of composite frame structural systems. Currently, the plastic limit theory is mainly used for this calculation in the codes adopted by many countries; however, the effective slab width recommended in most codes is based on the elastic theory, which does not accurately reflect the complex stress mechanism at the beam-column joints in the ultimate loading state. Therefore, the authors’ research group put forward the Compression-on-Column-Face mechanism and Tension-on-Transverse-Beam mechanism to explain the mechanism in the ultimate loading state. Formulae are derived for calculating the effective slab width in composite frames with rectangular/square-section columns under ultimate lateral loading. Moreover, this paper discusses the calculation method of the effective slab width for the beam-end flexural strength of composite frames with circular-section columns. The proposed design formula is suitable for exterior and interior joints. Finally, this paper compares the proposed formulae with available formulae in other literature, current design codes, and experimental results, providing the most accurate results to predict the effective slab width and ultimate loading capacity.

Keywords: composite frame structure, effective slab width, circular-section column, design formulae, ultimate loading capacity

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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: 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: Rui Liu, Klaus Greve

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The navigation information is a kind of dynamic geographic information, and the navigation information system is a kind of special geographic information system. At present, there are many researches on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing is not deeply applied into the research of navigation information service. And the imperfection of navigation target coordination and navigation information sharing mechanism under certain navigation tasks has greatly affected the reliability and scientificity of navigation service such as path planning. Considering this, the project intends to study the multi-source information fusion and multi-objective united navigation information interaction mechanism: first of all, investigate the actual needs of navigation users in different areas, and establish the preliminary navigation information classification and importance level model; and then analyze the characteristics of the remote sensing and GIS vector data, and design the fusion algorithm from the aspect of improving the positioning accuracy and extracting the navigation environment data. At last, the project intends to analyze the feature of navigation information of the land, sea and air navigation targets, and design the united navigation data standard and navigation information sharing model under certain navigation tasks, and establish a test navigation system for united navigation simulation experiment. The aim of this study is to explore the theory of united navigation service and optimize the navigation information service model, which will lay the theory and technology foundation for the united navigation of land, sea and air targets.

Keywords: information fusion, united navigation, dynamic path planning, navigation information visualization

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Authors: Dinamarie Fonzone

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Employer-sponsored health insurance (ESI) strategic decision-making processes rely on financial analysis to guide leadership in choosing plans that will produce optimal organizational spending outcomes. These financial decision-making methods have not abated ESI costs. Previously unrecognized external social determinants, the impact on ESI plan spending, and other organizational strategies are emerging and are important considerations for organizational decision-makers and change management practitioners. The purpose of thisstudy is to examine the relationship between the social determinants of health (SDoH), employer-sponsored health insurance (ESI) plans, andthe unintended consequence of health inequity. A quantitative research design using selectemployee records from an existing employer human capital management database will be analyzed. Statistical regressionmethods will be used to study the relationships between certainSDoH (employee income, neighborhood geographic living area, and health care access) and health plan utilization, cost, and chronic disease prevalence. The discussion will include an application of the social gradient of health theory to the study findings, organizational transformation through changes in ESI decision-making mental models, and the connection of ESI health inequity to organizational development and changediversity, equity, and inclusion strategies.

Keywords: employer-sponsored health insurance, social determinants of health, health inequity, mental models, organizational development, organizational change, social gradient of health theory

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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: 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: 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: Anna Drzewicz, Marzena Tykarska

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The chiral liquid crystal phases form the helicoidal structure, which is characterized by the helical pitch and the helical twist sense. In anticlinic smectic phase with antiferroelectric properties three types of helix temperature dependence have been obtained: increased helical pitch with temperature and right-handed helix, decreased helical pitch with temperature and left-handed helix and the inversion of both. The change of helical twist sense may be observed during the transition from one liquid crystal phase to another or within one phase for the same substance. According to Gray and McDonnell theory, the helical handedness depends on the absolute configuration of the assymetric carbon atom and its position related to the rigid core of the molecule. However, this theory does not explain the inversion of helical twist sense phenomenon. It is supposed, that it may be caused by the presence of different conformers with opposite handendess, which concentration may change with temperature. In this work, the inversion of helical twist sense in the chiral liquid crystals differing in the length of alkyl chain, in the substitution the benzene ring by fluorine atoms and in the type of helix handedness was tested by vibrational spectroscopy (infrared and raman spectroscopy) and by nuclear magnetic resonance spectroscopy. The results obtained from the vibrational spectroscopy confirm the presence of different conformers. Moreover, the analysis of nuclear magnetic resonance spectra is very useful to check, on which structural fragments the change of conformations are important for the change of helical twist sense.

Keywords: helical twist sense, liquid crystals, nuclear magnetic resonance spectroscopy, vibrational spectroscopy

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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

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