Search results for: learning strategies

Authors: Yousef Sahari, Eisa Asiri

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Hollywood films are produced in an open and liberal context, and when subtitling for a more conservative and closed society such as an Arabic society, religious words can pose a thorny challenge for subtitlers. Using a corpus of 90 Hollywood films released between 2000 and 2018 and applying insights from Descriptive Translation Studies (Toury, 1995, 2012) and the dichotomy of domestication and foreignization, this paper investigates three main research questions: (1) What are the dominant religious terms and functions in the English subtitles? (2) What are the dominant translation strategies used in the translation of religious words? (3) Do these strategies tend to be SL-oriented or TL-oriented (domesticating or foreignising)? To answer the research questions above, a quantitative and qualitative analysis of the corpus is conducted, in which the researcher adopts a self-designed, parallel, aligned corpus of ninety films and their Arabic subtitles. A quantitative analysis is performed to compare the frequencies and distribution of religious words, their functions, and the translation strategies employed by the subtitlers of ninety films, with the aim of identifying similarities or differences in addition to identifying the impact of functions of religious terms on the use of subtitling strategies. Based on the quantitative analysis, a qualitative analysis is performed to identify any translational patterns in Arabic translations of religious words and the possible reasons for subtitlers’ choices. The results show that the function of religious words has a strong influence on the choice of subtitling strategies. Also, it is found that foreignization strategies are applied in about two-thirds of the total occurrences of religious words.

Keywords: religious terms, subtitling, audiovisual translation, modern standard arabic, subtitling strategies, english-arabic subtitling

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Authors: Hussah M. AlShayea

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This study aimed to identify the potential of cloud computing, "Google Drive" in overcoming the problems of collective learning from the viewpoint of Princess Noura University students. The study included (92) students from the College of Education. To achieve the goal of the study, several steps have been taken. First, the most important problems of collective learning were identified from the viewpoint of the students. After that, a survey identifying the potential of cloud computing "Google Drive" in overcoming the problems of collective learning was distributed among the students. The study results showed that the students believe that the use of Google Drive contributed to overcoming these problems. In the light of those results, the researcher presented a set of recommendations and proposals, including: encouraging teachers and learners to employ cloud computing to overcome the problems and constraints of collective learning.

Keywords: cloud computing, collective learning, Google drive, Princess Noura University

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Authors: Kennedy Efosa Ehimwenma, Sujatha Krishnamoorthy, Safiya Al‑Sharji

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The probability computation of events is in the interval of [0, 1], which are values that are determined by the number of outcomes of events in a sample space S. The probability Pr(A) that an event A will never occur is 0. The probability Pr(B) that event B will certainly occur is 1. This makes both events A and B a certainty. Furthermore, the sum of probabilities Pr(E₁) + Pr(E₂) + … + Pr(Eₙ) of a finite set of events in a given sample space S equals 1. Conversely, the difference of the sum of two probabilities that will certainly occur is 0. This paper first discusses Bayes, the complement of probability, and the difference of probability for occurrences of learning-events before applying them in the prediction of learning objects in student learning. Given the sum of 1; to make a recommendation for student learning, this paper proposes that the difference of argMaxPr(S) and the probability of student-performance quantifies the weight of learning objects for students. Using a dataset of skill-set, the computational procedure demonstrates i) the probability of skill-set events that have occurred that would lead to higher-level learning; ii) the probability of the events that have not occurred that requires subject-matter relearning; iii) accuracy of the decision tree in the prediction of student performance into class labels and iv) information entropy about skill-set data and its implication on student cognitive performance and recommendation of learning.

Keywords: complement of probability, Bayes’ rule, prediction, pre-assessments, computational education, information theory

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Authors: Raziel Felix-Aguelo

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Language competencies refer to the knowledge and abilities to use English in four inter-related skills: Speaking, listening, reading, and writing. Cooperative learning is a type of instruction where learners are grouped together to work on an assignment, project, or task. To become competent in second language, one needs to actively use English in each of four modalities. Learning English is challenging to second language learners. Sometimes, some students feel demotivated and scared to use English during class discussions and recitations. This paper explores the students’ attitude and perception towards cooperative learning in enhancing their language competencies. The primary method for this research is case study. Thirty-two grade 9 students within a single selected class are used as sample. The instruments used in data collection were questionnaire and semi-structured interviews. The finding shows that collaborative learning activities enhance the four skills of the students. The participants consider this approach motivational as they engage and interact with others. This indicates that students develop their language competencies as they rely to one another in doing meaningful language activities.

Keywords: language competencies, collaborative learning, motivation, language activities

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Authors: M. Novak, E. Munoz, A. Jana, M. Nelemans

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Cities and local governments the world over are interested to employ circular strategies as a means to bring about food security, create employment and increase resilience. The selection and implementation of circular strategies is facilitated by modeling the effects of strategies locally and understanding the impacts such strategies have had in other (comparable) cities and how that would translate locally. Urban areas are heterogeneous because of their geographic, economic, social characteristics, governance, and culture. In order to better understand the effect of circular strategies on urban systems, we create a dataset for over 300 cities around the world designed to facilitate circular strategy scenario modeling. This new dataset integrates data from over 20 prominent global national and urban data sources, such as the Global Human Settlements layer and International Labour Organisation, as well as incorporating employment data from over 150 cities collected bottom up from local departments and data providers. The dataset is made to be reproducible. Various clustering techniques are explored in the paper. The result is sets of clusters of cities, which can be used for further research, analysis, and support comparative, regional, and national policy making on circular cities.

Keywords: data integration, urban innovation, cluster analysis, circular economy, city profiles, scenario modelling

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Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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Authors: Samson T. Obafemi, Seraphin D. Eyono-Obono

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Information and Communication Technologies (ICTs) are pervasive nowadays, including in education where they are expected to improve the performance of learners. However, the hope placed in ICTs to find viable solutions to the problem of poor academic performance in schools in the developing world has not yet yielded the expected benefits. This problem serves as a motivation to this study whose aim is to examine the perceptions of educators on the advantages and disadvantages of e-learning. This aim will be subdivided into two types of research objectives. Objectives on the identification and design of theories and models will be achieved using content analysis and literature review. However, the objective on the empirical testing of such theories and models will be achieved through the survey of educators from different schools in the Pinetown District of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after assessing the validity and the reliability of the data. The main hypothesis driving this study is that there is a relationship between the demographics of educators’ and their adherence to learning theories on one side, and their perceptions on the advantages and disadvantages of e-learning on the other side, as argued by existing research; but this research views these learning theories under three perspectives: educators’ adherence to self-regulated learning, to constructivism, and to progressivism. This hypothesis was fully confirmed by the empirical study except for the demographic factor where teachers’ level of education was found to be the only demographic factor affecting the perceptions of educators on the advantages and disadvantages of e-learning.

Keywords: academic performance, e-learning, learning theories, teaching and learning

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Authors: Esther Kelechi Soyele

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Job satisfaction is the expression of an organisation's fulfillment of work output. In order to achieve effective job satisfaction, the motivation of employees is very essential in stimulating their obligation towards their work. The study examined the motivational strategies, job satisfaction as a correlation of library service delivery in some selected tertiary institutions in southwest Nigeria. The study adopted a descriptive survey research design. A simple random sampling method was employed to select 200 library staff consisting of both library professionals and para-professionals. Two hundred (200) questionnaires were given out, but only one hundred and twenty-nine 129 (96% response rate) were used for the study. Both simple percentage and one and two way ANOVA was used for data analysis. Findings revealed that 60.4% of the respondents were males while 39.6% were female; most of the respondents’ relatively belong to the age group of 31-40 and 41-50, 93.3% were within the age range of 21-50 years, and 43.2 % were M.Sc degree holders. The result revealed a (p < 0.05) significant relationship between work motivational strategies and library service delivery. The results also revealed that motivational development program strategies and job satisfaction have (p < 0.05) a positive significant relationship with library service delivery. It was concluded that work motivation strategies are essential for job satisfaction which is very important in any organization in the attainment of its goals and objectives and helps in maintaining a high standard. The study recommended that more incentive plans that will enhance job satisfaction should be put in place to encourage employees to be more active in carrying out their job effectively.

Keywords: job satisfaction, library, library services, motivational strategies

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: Robyn Moloney, HuiLing Xu

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Many countries wish to produce Asia-literate citizens, through language education. International contexts of Chinese language education are seeking pedagogical innovation to meet local contextual factors frequently holding back learner success. In multicultural Australia, innovative pedagogy is urgently needed to support motivation in sustained study, with greater strategic integration of technology. This research took a qualitative approach to identify need and solutions. The paper analyses strategies that three secondary school teachers are adopting to meet specific challenges in the Australian context. The data include teacher interviews, classroom observations and student interviews. We highlight the use of task-based learning and differentiated teaching for multilevel classes, and the role which digital technologies play in facilitating both areas. The strategy examples are analysed in reference both to a research-based framework for describing quality teaching, and to current understandings of motivation in language learning. The analysis of data identifies learning featuring deep knowledge, higher-order thinking, engagement, social support, utilisation of background knowledge, and connectedness, all of which work towards the learners having a sense of autonomy and an imagination of becoming an adult Chinese language user.

Keywords: Chinese pedagogy, digital technologies, motivation, secondary school

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Authors: Kai Yip Michael Tsang

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Science writing has played a crucial part in science assessments. This paper reports a study in an area that has received little research attention – how Language across the Curriculum (LAC, i.e. science language and literacy) learning activities in science lessons can increase the science knowledge development of English as a foreign language (EFL) students in Hong Kong. The data comes from a school-based interventional study in chemistry classrooms, with written data from questionnaires, assessments and teachers’ logs and verbal data from interviews and classroom observations. The effectiveness of the LAC teaching and learning activities in various chemistry classrooms were compared and evaluated, with discussion of some implications. Students in the treatment group with lower achieving students received LAC learning and teaching activities while students in the control group with higher achieving students received conventional learning and teaching activities. After the study, they performed better in control group in formative assessments. Moreover, they had a better attitude to learning chemistry content with a richer language support. The paper concludes that LAC teaching and learning activities yielded positive learning outcomes among chemistry learners with low English ability.

Keywords: science learning and teaching, content and language integrated learning, language across the curriculum, English as a foreign language

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Authors: Sami M. Alshareef

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The rapid growth of smart grid technology has brought significant advancements to the power industry. However, with the increasing interconnectivity and reliance on information and communication technologies, smart grids have become vulnerable to cyber-attacks, posing significant threats to the reliable operation of power systems. Among the critical components of smart grids, the Automatic Generation Control (AGC) system plays a vital role in maintaining the balance between generation and load demand. Therefore, protecting the AGC system from cyber threats is of paramount importance to maintain grid stability and prevent disruptions. Traditional security measures often fall short in addressing sophisticated and evolving cyber threats, necessitating the exploration of innovative approaches. Machine learning, with its ability to analyze vast amounts of data and learn patterns, has emerged as a promising solution to enhance AGC system security. Therefore, this research proposal aims to address the challenges associated with detecting and mitigating cyber-attacks on AGC in smart grids by leveraging machine learning techniques on automatic generation control of two-area power systems. By utilizing historical data, the proposed system will learn the normal behavior patterns of AGC and identify deviations caused by cyber-attacks. Once an attack is detected, appropriate mitigation strategies will be employed to safeguard the AGC system. The outcomes of this research will provide power system operators and administrators with valuable insights into the vulnerabilities of AGC systems in smart grids and offer practical solutions to enhance their cyber resilience.

Keywords: machine learning, cyber-attacks, automatic generation control, smart grid

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Authors: Delowar Hossain, Genci Capi

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This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: deep learning, genetic algorithm, object recognition, robot grasping

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Authors: Adi Gielgun-Katz, Alina S. Rusu

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In the last two decades, education systems worldwide have integrated new pedagogical methods and strategies in lesson plans, such as innovative technologies, social-emotional learning (SEL), gamification, mixed learning, multiple literacies, and many others. Visual language, such as photographs, is known to transcend cultures and languages, and it is commonly used by youth to express positions and affective states in social networks. Therefore, visual language needs more educational attention as a linguistic and communicative component that can create connectedness among the students and their teachers. Nowadays, when SEL is gaining more and more space and meaning in the area of academic improvement in relation to social well-being, and taking and sharing pictures is part of the everyday life of the majority of people, it becomes natural to add the visual language to SEL approach as a reinforcement strategy for connecting education to the contemporary culture and language of the youth. This article presents a program conducted in a high school class in Israel, which combines the five SEL with photography techniques, i.e., Social-Emotional Learning Visual Empowerments (SELVEs) program (experimental group). Another class of students from the same institution represents the control group, which is participating in the SEL program without the photography component. The SEL component of the programs addresses skills such as: troubleshooting, uncertainty, personal strengths and collaboration, accepting others, control of impulses, communication, self-perception, and conflict resolution. The aim of the study is to examine the effects of programs on the level of the five SEL aspects in the two groups of high school students: Self-Awareness, Social Awareness, Self-Management, Responsible Decision Making, and Relationship Skills. The study presents a quantitative assessment of the SEL programs’ impact on the students. The main hypothesis is that the students’ questionnaires' analysis will reveal a better understanding and improvement of the five aspects of the SEL in the group of students involved in the photography-enhanced SEL program.

Keywords: social-emotional learning, photography, education program, adolescents

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Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez

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It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.

Keywords: education, evolutionary algorithms, evolution strategies, interactive learning applications

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Authors: Seree Chadcham, Niphon Sukvilai

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This study is the research and development which is intended to: 1) design of the Intelligent Scaffolding Learning Management System (ISLMS) for vocational education, 2) assess the suitability of the Design of Intelligent Scaffolding Learning Management System for Vocational Education. Its methods are divided into 2 phases. Phase 1 is the design of the ISLMS for Vocational Education and phase 2 is the assessment of the suitability of the design. The samples used in this study are work done by 15 professionals in the field of Intelligent Scaffolding, Learning Management System, Vocational Education, and Information and Communication Technology in education selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. The results showed that the ISLMS for vocational education consists of 2 main components which are: 1) the Intelligent Learning Management System for Vocational Education, 2) the Intelligent Scaffolding Management System. The result of the system suitability assessment from the professionals is in the highest range.

Keywords: intelligent, scaffolding, learning management system, vocational education

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Authors: Maryam Savari, Mohamad Nizam Ayub, Ainuddin Wahid Abdul Wahab

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Game-based Learning (GBL) is an alternative that provides learners with an opportunity to experience a volatile environment in a safe and secure place. A volatile environment requires a different technique to facilitate learning and prevent injury and other hazards. Subjects involving elasticity are always considered hazardous and can cause injuries,for instance a bouncing ball. Elasticity is a topic that necessitates hands-on practicality for learners to experience the effects of elastic objects. In this paper the scope is to investigate the natural interaction between learners and elastic objects in a safe environment using GBL. During interaction, the potentials of natural contact in the process of learning were explored and gestures exhibited during the learning process were identified. GBL was developed using Kinect technology to teach elasticity to primary school children aged 7 to 12. The system detects body gestures and defines the meanings of motions exhibited during the learning process. The qualitative approach was deployed to constantly monitor the interaction between the student and the system. Based on the results, it was found that Natural Interaction GBL (Ni-GBL) is engaging for students to learn, making their learning experience more active and joyful.

Keywords: elasticity, Game-Based Learning (GBL), kinect technology, natural interaction

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Authors: Lucie Côté, Martin Lauzier, Guy Beauchamp, France Guertin

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Stress causes deleterious effects to the physical, psychological and organizational levels, which highlight the need to use effective coping strategies to deal with it. Several coping models exist, but they don’t integrate the different strategies in a coherent way nor do they take into account the new research on the emotional coping and acceptance of the stressful situation. To fill these gaps, an integrative model incorporating the main coping strategies was developed. This model arises from the review of the scientific literature on coping and from a qualitative study carried out among workers with low or high levels of stress, as well as from an analysis of clinical cases. The model allows one to understand under what circumstances the strategies are effective or ineffective and to learn how one might use them more wisely. It includes Specific Strategies in controllable situations (the Modification of the Situation and the Resignation-Disempowerment), Specific Strategies in non-controllable situations (Acceptance and Stubborn Relentlessness) as well as so-called General Strategies (Wellbeing and Avoidance). This study is intended to undertake and present the process of development and validation of an instrument to measure coping strategies based on this model. An initial pool of items has been generated from the conceptual definitions and three expert judges have validated the content. Of these, 18 items have been selected for a short form questionnaire. A sample of 300 students and employees from a Quebec university was used for the validation of the questionnaire. Concerning the reliability of the instrument, the indices observed following the inter-rater agreement (Krippendorff’s alpha) and the calculation of the coefficients for internal consistency (Cronbach's alpha) are satisfactory. To evaluate the construct validity, a confirmatory factor analysis using MPlus supports the existence of a model with six factors. The results of this analysis suggest also that this configuration is superior to other alternative models. The correlations show that the factors are only loosely related to each other. Overall, the analyses carried out suggest that the instrument has good psychometric qualities and demonstrates the relevance of further work to establish predictive validity and reconfirm its structure. This instrument will help researchers and clinicians better understand and assess coping strategies to cope with stress and thus prevent mental health issues.

Keywords: acceptance, coping strategies, stress, validation process

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Authors: Amani Hamdan

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

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

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Authors: R. M. Bashir, Sabo Elizabeth

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Electronic learning is an increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. An investigation on the assessment of e-learning facilities and information need by open and distance learning students in Jalingo, Nigeria was conducted. Structured questionnaires were administered to 70 students of the university. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Information on assessment of e-learning facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women, a large proportion of the respondents are married and there are more matured students. A high proportion of the students obtained qualifications higher than the secondary school certificate. The proportion of computer literate students was higher compared with those students that owned a computer. Inadequate e-books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities. Inadequate computer facilities caused delay in examination schedule at the study center. Open and distance learning students required to a high extent information on university timetable and schedule of activities, books (hard and e-books) and reference materials and contact with course coordinators via internet for better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

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Authors: Sathapath Kilaso

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Attendance checking in the classroom for student is object to record the student’s attendance in order to support the learning activities in the classroom. Despite the teaching trend in the 21st century is the student-center learning and the lecturer duty is to mentor and give an advice, the classroom learning is still important in order to let the student interact with the classmate and the lecturer or for a specific subject which the in-class learning is needed. The development of the system prototype by applied the microcontroller technology and embedded system with the “internet of thing” trend and the web socket technique will allow the lecturer to be alerted immediately whenever the data is updated.

Keywords: arduino, embedded system, classroom, raspberry PI

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Authors: Shu-Chen Wu

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This paper will present a study by the author which investigates Chinese teachers’ perspectives on learning at play and their teaching activities in the designed play activities. It asks the question of how Chinese teachers understand learning at play and how they design play activities in the classroom. Six kindergarten teachers in Hong Kong were invited to select and record exemplary play episodes which contain the largest amount of learning elements in their own classrooms. Applying video-stimulated interview, eight teachers in two focus groups were interviewed to elicit their perspectives on designing play activity and their teaching activities. The findings reveal that Chinese teachers have a very structured representation of learning at play, and the phenomenon of uniformity of teachers’ act was found. The contributions of which are important and useful for professional practices and curricular policies.

Keywords: learning at play, teacher involvement, video-stimulated interview, uniformity

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Authors: Vasanthi Muniasamy, Intisar Magboul Ejalani, M.Anandhavalli, K. Gauthaman

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Social Media (SM) are websites increasingly popular and built to allow people to express themselves and to interact socially with others. Most SMT are dominated by youth particularly college students. The proliferation of popular social media tools, which can accessed from any communication devices has become pervasive in the lives of today’s student life. Connecting traditional education to social media tools are a relatively new era and any collaborative tool could be used for learning activities. This study focuses (i) how the social media tools are useful for the learning activities of the students of faculty of medicine in King Khalid University (ii) whether the social media affects the collaborative learning with interaction among students, among course instructor, their engagement, perceived ease of use and perceived ease of usefulness (TAM) (iii) overall, the students satisfy with this collaborative learning through Social media.

Keywords: social media, Web 2.0, perceived ease of use, perceived usefulness, collaborative Learning

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Authors: Abdullah Abu-Tineh, Carol Murphy, Nigel Calder, Nasser Mansour

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This paper reports on an aspect of e-learning in developing inquiry-based learning (IBL). We present data on the views of teachers and students in Qatar following a professional development programme intended to help teachers implement IBL in their science and mathematics classrooms. Key to this programme was the use of WebQuests. Views of the teachers and students suggested that WebQuests helped students to develop technical skills, work collaboratively and become independent in their learning. The use of WebQuests also enabled a combination of digital and non-digital tools that helped students connect ideas and enhance their understanding of topics.

Keywords: digital technology, inquiry-based learning, mathematics and science education, professional development

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Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharrazi

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When we teach, we have two critical elements at our disposal to help students: learning styles as well as testing styles. There are many different ways in which educators can effectively teach their students; verbal learning and experience-based learning. Lecture as a form of verbal learning style is a traditional arrangement in which teachers are more active and share information verbally with students. In experienced-based learning as the process of through, students learn actively through hands-on learning materials and observing teachers or others. Meanwhile, standard testing or assessment is the way to determine progress toward proficiency. Teachers and instructors mainly use essay (requires written responses), multiple choice questions (includes the correct answer and several incorrect answers as distractors), or open-ended questions (respondents answers it with own words). The current study focused on exploring an effective teaching style and testing methods as the function of age over school ages. In the present study, totally 410 participants were selected randomly from four grades (2ⁿᵈ, 4ᵗʰ, 6ᵗʰ, and 8ᵗʰ). Each subject was tested individually in one session lasting around 50 minutes. In learning tasks, the participants were presented three different instructions for learning materials (learning by doing, learning by observing, and learning by listening). Then, they were tested via different standard assessments as free recall, cued recall, and recognition tasks. The results revealed that generally students remember more of what they do and what they observe than what they hear. The age effect was more pronounced in learning by doing than in learning by observing, and learning by listening, becoming progressively stronger in the free-recall, cued-recall, and recognition tasks. The findings of this study indicated that learning by doing and free recall task is more age sensitive, suggesting that both of them are more strategic and more affected by developmental differences. Pedagogically, these results denoted that learning by modeling and engagement in program activities have the special role for learning. Moreover, the findings indicated that the multiple-choice questions can produce the best performance for school-aged children but is less age-sensitive. By contrast, the essay as essay can produce the lowest performance but is more age-sensitive. It will be very helpful for educators to know that what types of learning styles and test methods are most effective for students in each school grade.

Keywords: experience-based learning, learning style, school-aged children, testing methods, verbal learning

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Prachya Kamonphet

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The purposes of this research were to study the learning motivation factors for Pre-cadets in Armed Forces Academies Preparatory School, Ministry of Defense. The subjects were 320 Pre-cadets (from all 3-year classes of Pre-cadets, the academic year 2015). The research instruments were questionnaires. The collected data were analyzed by means of Descriptive Statistic and One-Way Analysis of Variance. The results of this study were as follows: The relation between the Pre-cadets’ average grade and the motivation in studying was significance.In the aspect of the environment related to Pre-cadets’ families and the motivation in studying.In the aspect of the environment related to Pre-cadets’ studying, it was found that teaching method, learning place, educational media, relationship between teachers and Pre-cadets, relationship between Pre-cadets and their friends, and relationship between Pre-cadets and the commanders were significant.

Keywords: learning motivation factors, learning motivation, armed forces academies preparatory school, learning

Procedia PDF Downloads 234

Authors: H. Weigelt-Marom

Abstract:

Over the years and up to the arousal of the COVID-19 pandemic, deaf or hard of hearing students studying in higher education institutions, participated lectures on campus using hearing aids and strategies adapted for frontal learning in a classroom. Usually, these aids were well known to them from their earlier study experience in school. However, the transition to online lessons, due to the latest pandemic, led deaf or hard of hearing students to study outside of their physical, well known learning environment. The change of learning environment and structure rose new challenges for these students. The present study examined the learning experience, limitations, challenges and benefits regarding learning online with lecture and classmates via the “Zoom” video conference program, among deaf or hard of hearing students in academia setting. In addition, emotional and social aspects related to learning in general versus the “Zoom” were examined. The study included 18 students diagnosed as deaf or hard of hearing, studying in various higher education institutions in Israel. All students had experienced lessons on the “Zoom”. Following allocation of the group study by the deaf and hard of hearing non-profit organization “Ma’agalei Shema”, and receiving the participants inform of consent, students were requested to answer a google form questioner and participate in an interview. The questioner included background information (e.g., age, year of studying, faculty etc.), level of computer literacy, and level of hearing and forms of communication (e.g., lip reading, sign language etc.). The interviews included a one on one, semi-structured, in-depth interview, conducted by the main researcher of the study (interview duration: up to 60 minutes). The interviews were held on “ZOOM” using specific adaptations for each interviewee: clear face screen of the interviewer for lip and face reading, and/ or professional sign language or live text transcript of the conversation. Additionally, interviewees used their audio devices if needed. Questions regarded: learning experience, difficulties and advantages studying using “Zoom”, learning in a classroom versus on “Zoom”, and questions concerning emotional and social aspects related to learning. Thematic analysis of the interviews revealed severe difficulties regarding the ability of deaf or hard of hearing students to comprehend during ”Zoom“ lessons without adoptive aids. For example, interviewees indicated difficulties understanding “Zoom” lessons due to their inability to use hearing devices commonly used by them in the classroom (e.g., FM systems). 80% indicated that they could not comprehend “Zoom” lessons since they could not see the lectures face, either because lectures did not agree to open their cameras or, either because they did not keep a straight forward clear face appearance while teaching. However, not all descriptions regarded learning via the “zoom” were negative. For example, 20% reported the recording of “Zoom” lessons as a main advantage. Enabling then to repeatedly watch the lessons at their own pace, mostly assisted by friends and family to translate the audio output into an accessible input. These finding and others regarding the learning experience of the group study on the “Zoom”, as well as their recommendation to enable deaf or hard of hearing students to study inclusively online, will be presented at the conference.

Keywords: deaf or hard of hearing, learning experience, Zoom, qualitative research

Procedia PDF Downloads 112

Authors: Denise Levy, Anna Lucia C. H. Villavicencio

Abstract:

In a rapid-changing world, science teachers face considerable challenges. In addition to the basic curriculum, there must be included several transversal themes, which demand creative and innovative strategies to be arranged and integrated to traditional disciplines. In Brazil, nuclear science is still a controversial theme, and teachers themselves seem to be unaware of the issue, most often perpetuating prejudice, errors and misconceptions. This article presents the authors’ experience in the development of an interdisciplinary pedagogical proposal to include nuclear science in the basic curriculum, in a transversal and integrating way. The methodology applied was based on the analysis of several normative documents that define the requirements of essential learning, competences and skills of basic education for all schools in Brazil. The didactic materials and resources were developed according to the best practices to improve learning processes privileging constructivist educational techniques, with emphasis on active learning process, collaborative learning and learning through research. The material consists of an illustrated book for students, a book for teachers and a manual with activities that can articulate nuclear science to different disciplines: Portuguese, mathematics, science, art, English, history and geography. The content counts on high scientific rigor and articulate nuclear technology with topics of interest to society in the most diverse spheres, such as food supply, public health, food safety and foreign trade. Moreover, this pedagogical proposal takes advantage of the potential value of digital technologies, implementing QR codes that excite and challenge students of all ages, improving interaction and engagement. The expected results include the education of the educators for nuclear science communication in a transversal and integrating way, demystifying nuclear technology in a contextualized and significant approach. It is expected that the interdisciplinary pedagogical proposal contributes to improving attitudes towards knowledge construction, privileging reconstructive questioning, fostering a culture of systematic curiosity and encouraging critical thinking skills.

Keywords: science education, interdisciplinary learning, nuclear science, scientific literacy

Procedia PDF Downloads 127

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

Procedia PDF Downloads 224