Search results for: learning Maltese as a second language

Authors: Abdi Omar Shuriye

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A social business is a business designed to address socio-economic problems to enhance the welfare of the communities involved. Lately, social business, with its focus on innovative ideas, is capturing the interest of educational institutions, governments, and non-governmental organizations. Social business uses a business model to achieve a social goal, and in the last few decades, the idea of imbuing social business into the education system of higher learning institutions has spurred much excitement. This is due to the belief that it will lead to job creation and increased social resilience. One of the higher learning institutions which have invested immensely in the idea is Albukhari International University; it is a private education institution, on a state-of-the-art campus, providing an advantageous learning ecosystem. The niche area of this institution is social business, and it graduates job creators, not job seekers; this Malaysian institution is unique and one of its kind. The objective of this paper is to develop a work plan, direction, and milestone as well as the focus area for the infusion of social business into higher learning institutions with special reference to Al-Bukhari International University. The purpose is to develop a prototype and model full-scale to enable higher learning education institutions to construct the desired curriculum fermented with social business. With this model, major predicaments faced by these institutions could be overcome. The paper sets forth an educational plan and will spell out the basic tenets of social business, focusing on the nature and implementational aspects of the curriculum. It will also evaluate the mechanisms applied by these educational institutions. Currently, since research in this area remains scarce, institutions adopt the process of experimenting with various methods to find the best way to reach the desired result on the matter. The author is of the opinion that social business in education is the main tool to educate holistic future leaders; hence educational institutions should inspire students in the classroom to start up their own businesses by adopting creative and proactive teaching methods. This proposed model is a contribution in that direction.

Keywords: social business, curriculum, skills, university

Procedia PDF Downloads 78

Authors: Davoud Masoumi, Maryam Bourbour

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By characterizing children’s actions in the scaffolding process, which is often undermined and ignored in the studies reviewed, this study aimed to examine children’s different (re)actions in relation to the teachers’ actions in a context where digital technologies are used. Over five months, 22 children aged 4-6 with five preschool teachers were video observed. The study brought in rich details of the children’s actions in relation to the teacher’s actions in the scaffolding process. The findings of the study reveal thirteen (re)actions, including Giving short response; Explaining; Participating in the activities; Examining; Smiling and laughing; Pointing and showing; Working together; Challenging each other; Problem-solving skills; Developing vocabulary; Choosing the activity; Expressing of the emotions; and Identifying the similarities and differences. Our findings expanded and deepened the understanding of the scaffolding process, which can contribute to the notion of scaffolding and help us to gain further understanding about scaffolding of children’s learning. Characterizing the children’s (re)action in relation to teacher’s scaffolding actions further can contribute to ongoing discussions about how teachers can scaffold children’s learning using digital technologies in the learning process.

Keywords: children’ (re)actions, scaffolding process, technologies, preschools

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Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: S. AlBustan, B. AlGhannam

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This oral presentation discusses a proposal for a study that evaluates the usability of an evidence based application named ProxTalker App. The significance of this study will inform administration and faculty staff at the Department of Communication Sciences Disorders (CDS), College of Life Sciences, Kuwait University whether the app is a suitable tool to use for CDS students. A case study will be used involving a sample of CDS students taking practicum and internship courses during the academic year 2018/2019. The study will follow a process used by previous study. The process of calculating SUS is well documented and will be followed. ProxTalker App is an alternative and augmentative tool that speech language pathologist (SLP) can use to customize boards for their clients. SLPs can customize different boards using this app for various activities. A board can be created by the SLP to improve and support receptive and expressive language. Using technology to support therapy can aid SLPs to integrate this ProxTalker App as part of their clients therapy. Supported tools, games and motivation are some advantages of incorporating apps during therapy sessions. A quantitative methodology will be used. It involves the utilization of a standard tool that was the was adapted to the Arabic language to accommodate native Arabic language users. The tool that will be utilized in this research is the Arabic Standard Usability Scale (A-SUS) questionnaire which is an adoption of System Usability Scale (SUS). Standard usability questionnaires are reliable, valid and their process is properly documented. This study builds upon the development of A-SUS, which is a psychometrically evaluated questionnaire that targets Arabic native speakers. Results of the usability will give preliminary indication of whether the ProxTalker App under investigation is appropriate to be integrated within the practicum and internship curriculum of CDS. The results of this study will inform the CDS department of this specific app is an appropriate tool to be used for our specific students within our environment because usability depends on the product, environment, and users.

Keywords: A-SUS, communication disorders practicum, evidence based app, Standard Usability Scale

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Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method Web-App auto-generated twin data structure replication. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi" has been developed. A special login form has been developed with a special instance of data validation; this verification process secures the web application from its early stages. The system has been tested and validated, up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database

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Authors: Odigie Veronica

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The paper focused on the application of Information and Communication Technology (ICT) in effective service delivery in view of the ongoing COVID-19 experience. It adopted the exploratory research method with three research objectives captured. Consequently, the objectives were to ascertain the meaning of online education, understand the concept of COVID-19 and to determine the relevance of online education in effective service delivery in institutions of learning. It is evident from the findings that through ICT, online mode of learning can be adopted in schools which helps greatly in promoting continual education. Online mode of education is practiced online; it brings both the teacher and learners from different places together, without any physical boundary/contact (at least 75%); and has helped greatly in human development in countries where it has been practiced. It is also a welcome development owing to its many benefits such as exposure to digital learning, having access to works of great teachers and educationists such as Socrates, Plato, Dewey, R.S. Peters, J. J. Rosseau, Nnamdi Azikwe, Carol Gilligan, J. I. Omoregbe, Jane Roland Martin, Jean Piaget, among others; and the facilitation of uninterrupted learning for class promotion and graduation of students. Developing the learners all round is part of human development which helps in developing a nation. These and many more are some benefits online education offers which make ICT very relevant in our contemporary society

Keywords: online education, COVID-19 pandemic, effective service delivery, human development

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Authors: Patrizia Poscic, Sanja Candrlic, Danijela Jaksic

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The University of Rijeka, Department of Informatics participated in the Stand4Info project, co-financed by the European Union, with the main idea of an alignment of study programs with occupational and qualifications standards in the field of Informatics. A brief overview of our research methodology, goals and deliverables is shown. Our main research and project objectives were: a) development of occupational standards, qualification standards and study programs based on the Croatian Qualifications Framework (CROQF), b) higher education quality improvement in the field of information and communication sciences, c) increasing the employability of students of information and communication technology (ICT) and science, and d) continuously improving competencies of teachers in accordance with the principles of CROQF. CROQF is a reform instrument in the Republic of Croatia for regulating the system of qualifications at all levels through qualifications standards based on learning outcomes and following the needs of the labor market, individuals and society. The central elements of CROQF are learning outcomes - competences acquired by the individual through the learning process and proved afterward. The place of each acquired qualification is set by the level of the learning outcomes belonging to that qualification. The placement of qualifications at respective levels allows the comparison and linking of different qualifications, as well as linking of Croatian qualifications' levels to the levels of the European Qualifications Framework and the levels of the Qualifications framework of the European Higher Education Area. This research has made 3 proposals of occupational standards for undergraduate study level (System Analyst, Developer, ICT Operations Manager), and 2 for graduate (master) level (System Architect, Business Architect). For each occupational standard employers have provided a list of key tasks and associated competencies necessary to perform them. A set of competencies required for each particular job in the workplace was defined and each set of competencies as described in more details by its individual competencies. Based on sets of competencies from occupational standards, sets of learning outcomes were defined and competencies from the occupational standard were linked with learning outcomes. For each learning outcome, as well as for the set of learning outcomes, it was necessary to specify verification method, material, and human resources. The task of the project was to suggest revision and improvement of the existing study programs. It was necessary to analyze existing programs and determine how they meet and fulfill defined learning outcomes. This way, one could see: a) which learning outcomes from the qualifications standards are covered by existing courses, b) which learning outcomes have yet to be covered, c) are they covered by mandatory or elective courses, and d) are some courses unnecessary or redundant. Overall, the main research results are: a) completed proposals of qualification and occupational standards in the field of ICT, b) revised curricula of undergraduate and master study programs in ICT, c) sustainable partnership and association stakeholders network, d) knowledge network - informing the public and stakeholders (teachers, students, and employers) about the importance of CROQF establishment, and e) teachers educated in innovative methods of teaching.

Keywords: study program, qualification standard, occupational standard, higher education, informatics and computer science

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Authors: D. Kokt, T. F. Dreyer

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The main objective of the study was to design a mentoring programme aimed at developing the soft skills of mentors. The mentors are all employed by a multinational corporation. The company had a mentoring plan in place that did not yield the required results, especially related to the development of soft skills. This prompted the researchers to conduct an extensive literature review followed by a mixed methods approach to ascertain the best practices in developing the soft skills of mentors. The outcomes of the study led to the development of a structured mentoring programme using 25 modules to be completed by mentors. The design incorporated a blended modular approach using both face-to-face teaching and teaching supported by Information Communication Technology (ICT). Blended learning was ideal as the ICT component helped to minimise instructor-mentor physical contact as part of the health measures during the Covid-19 pandemic. The blended learning approach also allowed instructors and mentors an online or offline mode, so that mentors could have more time for creative and cooperative exercises. A range of delivery methodologies were spread out across the different modules to ensure mentor engagement and accelerate mentor development. This included concept development through in-person instructor-led training sessions, concept development through virtual instructor-led training sessions, simulations, case studies, e-learning, role plays, interactive learning using mentoring toolkits, and experiential learning through application. The mentor development journey included formal modular competency assessments. All modules contained post-competency assessment consisting of 10 questions (comprising of a combination of explanatory questions and multiple-choice questions) to ensure understanding and deal with identified competency gaps. The minimum pass mark for all modular competency assessments was 80%. Mentors were allowed to retake the assessment if they scored less than 80% until they demonstrated understanding at the required level.

Keywords: mentor, mentee, soft skills, mentor development, blended learning, modular approach

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Authors: Kenneth Philip Jones

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This dissertation investigates the potential of developing educational-based video games to motivate and engage African American males. The study employed a qualitative methodological approach by investigating African American males who are avid video game players and are currently enrolled at a college or university. The participants were individually and collectively video and audio recorded during the interviews and observations. Situated Learning theory analyzed how motivation and engagement can transfer from a video game to an educational context. The research aims to address the disparities in our educational systems when it comes to providing a culture, climate, and atmosphere that will enable the academic development of African American males. The primary objective of the findings is based on the participants’ responses and the data collected to provide recommendations to educators and scholars on how to address the issues that have demoralized African American males in education and provide a platform that will allow for equality in educational development and advancement.

Keywords: video games, motivation, behavioral, learning transfer

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Authors: Chek K. Loi

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The present study has two objectives. Firstly, it investigates the rhetorical strategies employed in the body paragraphs of ESL (English as a Second Language) undergraduate students’ English academic essays. Peacock’s (2002) model of the discussion section was used as the starting points in this study to investigate the rhetorical moves employed in the data. Secondly, it investigates the writing problems as perceived by these ESL students through an interview. Interview responses serve as accompanying data to the move analysis. Apart from this, students’ English academic writing problems are diagnosed. The findings have pedagogical implications in an EAP (English for Academic Purposes) classroom.

Keywords: academic essays, move analysis, pedagogical implication, rhetorical strategies

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Authors: Anochao Phetcharat

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This research aims to study problems of translation basic knowledge, particularly from English into Thai. The researcher used 38 2nd-year non-English speaking students of Suratthani Rajabhat University as samples. The samples were required to translate an A4-sized article from English into Thai assigned as a part of BEN0202 Translation for Business, a requirement subject for Business English Department, which was also taught by the researcher. After completion of the translation, numerous problems were found and the research grouped them into 4 major types. The normally occurred problems in English-Thai translation works are the lack of knowledge in terms of parts of speech, word-by-word translation employment, misspellings as well as the poor knowledge in English language structure. However, this research is currently under the process of data analysis and shall be completed by the beginning of August. The researcher, nevertheless, predicts that all the above-mentioned problems, will support the researcher’s hypothesizes, that are; 1) the lack of knowledge in terms of parts of speech causes the mistranslation problem; 2) employing word-by-word translation technique hugely results in the mistranslation problem; 3) misspellings yields the mistranslation problem; and 4) the poor knowledge in English language structure also brings about translation errors. The research also predicts that, of all the aforementioned problems, the following ones are found the most, respectively: the poor knowledge in English language structure, word-by-word translation employment, the lack of knowledge in terms of parts of speech, and misspellings.

Keywords: problem, student, Thai, translation

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Manik Sharma, Ganapathy Krishnamurthi

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The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.

Keywords: cellular images, genetic perturbations, deep-learning, explainability

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

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Authors: George Bocean

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In the mainstream academic spheres of thought, there is a tendency to associate the writings of Russian Marxists as being constantly against the practice of religion itself. Such arguments mainly stem from how the attitude of the Russian Marxists, specifically the Bolsheviks, towards the concept of religion supposedly originates from its own Marxist ideology. Although Marxism is critical of religion as an institution, the approach that Marxism would have on the question of religion is not as clear. Such aspect is specifically observed in the use of language of major leading Russian Marxist figures, such as Lenin and Trotsky, throughout the early 20th century, where the use of religious metaphors was widely used in their philosophical writings and speeches, as well as in propaganda posters of general left-wing movements in Russia as a whole. The methodology of the research will consist of a sociolinguistic and sociology of language approach within a sociohistorical framework of late Tsarist and early Soviet Russia, 1905-1926. The purpose of such approaches are not simply to point out the religious metaphors used in the writings and speeches of Marxists in Russia, but rather in order to analyse how the use of such metaphors represent an important socio-political connection with the context of Russia at the time. In other words, the use of religious metaphors was not only more akin to Russian culture at the time, but this also resonated and was more familiar with the conditions of the working class and peasantry. An example in this study can be observed in the writings of Lenin, where the theme of chudo (miracle) is often mentioned in his writings, and such a word is commonly associated with an idealist philosophy rather than a materialist one, which represents a common theme in Russian culture in regards to the principle of hope for a better life. A further and even more obvious example is Trotsky’s writings about how the revolution of 1905 “would be revived”, which not only resonates with the theme of resurrection, but also prophesises the “second coming” of a future revolution. Such metaphors are important in the writings of such authors, as they simultaneously contain Marxist ideas, as well as religious themes. In doing this research, this paper will demonstrate two aspects. Firstly, the paper will analyse the use of the metaphors by Russian Marxists as a whole in regards to a socio-political and ideological perspectives akin to those of Marxism. Secondly, it will also demonstrate the role that such metaphors have in regards to their impact on the left-wing movements within Russia itself, as well as their relation to the working class and peasantry of Russia within the historical context.

Keywords: language and politics, Marxism, Russian history, social history, sociology of language

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Authors: Willy Mbenza, Sho Kenjiro

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Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

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Authors: Shaheeb Abdul Azeez, Siong-Choy Chong

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Background: Talent retention is increasingly becoming a major challenge for many industries due to the high turnover rate. Public higher learning institutions in the Maldives have a similar situation with the turnover of their employees'. This paper is to identify whether Human Resource Management (HRM) practices have any impact on employee retention in public higher learning institutions in the Maldives. Purpose: This paper aims to identify the influence of HRM practices on employee retention in public higher learning institutions in the Maldives. A total of 15 variables used in this study; 11 HRM practices as independent variables (leadership, rewards, salary, employee participation, compensation, training and development, career development, recognition, appraisal system and supervisor support); job satisfaction and motivation as mediating variables; demographic profile as moderating variable and employee retention as dependent variable. Design/Methodology/Approach: A structured self-administered questionnaire was used for data collection. A total of 300 respondents were selected as the study sample, representing the academic and administrative from public higher learning institutions using a stratified random sampling method. AMOS was used to test the hypotheses constructed. Findings: The results suggest that there is no direct effect between the independent variable and dependent variable. Also, the study concludes that no moderate effects of demographic profile between independent and dependent variables. However, the mediating effects of job satisfaction and motivation in the relationship between HRM practices and employee retention were significant. Salary had a significant influence on job satisfaction, whilst both compensation and recognition have significant influence on motivation. Job satisfaction and motivation were also found to significantly influence employee retention. Research Limitations: The study consists of many variables more time consuming for the respondents to answer the questionnaire. The study is focussed only on public higher learning institutions in the Maldives due to no participation from the private sector higher learning institutions. Therefore, the researcher is unable to identify the actual situation of the higher learning industry in the Maldives. Originality/Value: To our best knowledge, no study has been conducted using the same framework throughout the world. This study is the initial study conducted in the Maldives in this study area and can be used as a baseline for future researches. But there are few types of research conducted on the same subject throughout the world. Some of them concluded with positive findings while others with negative findings. Also, they have used 4 to 7 HRM practices as their study framework.

Keywords: human resource management practices, employee retention, motivation, job satisfaction

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Authors: Meera Rajeev Kumar

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An overall social, emotional, and cultural development in a child is what a parent expects. There is no point in comparing the generations of 70’s or 80’s with that of the children of today as the trends are changing drastically. Technology has enabled them to become smart as well as over smart in one way or the other. Children today are quite ignorant of today’s values or ethics and are imbibing different cultures around them and ultimately confused on what to follow. The researcher has gained experience in transmitting or imparting the traditional culture through performing arts. It is understood that the children undergo a transformation from what they knew to what the truth is, through learning and experience. Through performing arts, the child develops an emotional, quick learning, abundant creativity, and ultimately self-realisation on what is right and wrong. The child also gains good organising skills, good decision making skills, therefore summing up to a holistic development. The sample study is 50, and a random sampling technique is adopted to differentiate between a normal child and a child learning an art. The study is conducted in Tamil Nadu, in India.

Keywords: creativity, cultural, emotional, empower

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Authors: Elisabeth Desiana Mayasari, Laurensia Aptik Evanjeli, Brigitta Erlita Tri Anggadewi

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The condition of the COVID-19 pandemic demands adaptation in various aspects of human life, including in the field of education. Teachers are expected to do distance learning or Learning From Home (LFH). The teacher said that he experienced stress, anxiety, feeling depressed, and afraid based on the interview. Learning adaptations and pandemic situations can impact the mental health of teachers, so the purpose of this study is to determine the mental health of teachers while teaching online. This research was conducted with a quantitative approach using a survey method. The subjects in this study were 330 elementary school teachers under the auspices of a foundation in Yogyakarta. Teachers' mental health was measured using the Indonesian version of The Mental Health Inventory (MHI-38), which has a reliability of 0.888. The results showed that the teachers generally had a good mental health condition marked by a lower negative aspect score than the positive aspect. In addition, the overall mental health aspect shows that some teachers have better mental health when compared to the average score, as well as higher positive aspect scores in all sub-aspects.

Keywords: mental health, teacher, COVID-19 pandemic, MHI-38

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Authors: Heichia Wang, Yalan Chao

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Social inequality is a persistent problem. One of the ways to solve this problem is through education. At present, vulnerable groups are often less geographically accessible to educational resources. However, compared with educational resources, communication equipment is easier for vulnerable groups. Now that information and communication technology (ICT) has entered the field of education, today we can accept the convenience that ICT provides in education, and the mobility that it brings makes learning independent of time and place. With mobile learning, teachers and students can start discussions in an online chat room without the limitations of time or place. However, because liquidity learning is quite convenient, people tend to solve problems in short online texts with lack of detailed information in a lack of convenient online environment to express ideas. Therefore, the ICT education environment may cause misunderstanding between teachers and students. Therefore, in order to better understand each other's views between teachers and students, this study aims to clarify the essays of the analysts and classify the students into several types of learning questions to clarify the views of teachers and students. In addition, this study attempts to extend the description of possible omissions in short texts by using external resources prior to classification. In short, by applying a short text classification, this study can point out each student's learning problems and inform the instructor where the main focus of the future course is, thus improving the ICT education environment. In order to achieve the goals, this research uses convolutional neural network (CNN) method to analyze short discussion content between teachers and students in an ICT education environment. Divide students into several main types of learning problem groups to facilitate answering student problems. In addition, this study will further cluster sub-categories of each major learning type to indicate specific problems for each student. Unlike most neural network programs, this study attempts to extend short texts with external resources before classifying them to improve classification performance. In short, by applying the classification of short texts, we can point out the learning problems of each student and inform the instructors where the main focus of future courses will improve the ICT education environment. The data of the empirical process will be used to pre-process the chat records between teachers and students and the course materials. An action system will be set up to compare the most similar parts of the teaching material with each student's chat history to improve future classification performance. Later, the function of short text classification uses CNN to classify rich chat records into several major learning problems based on theory-driven titles. By applying these modules, this research hopes to clarify the main learning problems of students and inform teachers that they should focus on future teaching.

Keywords: ICT education improvement, social equality, short text analysis, convolutional neural network

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Daniela Velichová

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Plenty of ideas on how to adopt active learning methods in education are available nowadays. Mathematics is a subject where the active involvement of students is required in particular in order to achieve desirable results regarding sustainable knowledge and deep understanding. The present article is based on the outcomes of an Erasmus+ project DrIVE-MATH, that was aimed at developing a novel and integrated framework to teach maths classes in engineering courses at the university level. It is fundamental for students from the early years of their academic life to have agile minds. They must be prepared to adapt to their future working environments, where enterprises’ views are always evolving, where all collaborate in teams, and relations between peers are thought for the well-being of the whole - workers and company profit. This reality imposes new requirements on higher education in terms of adaptation of different pedagogical methods, such as project-based and active-learning methods used within the course curricula. Active learning methodologies are regarded as an effective way to prepare students to meet the challenges posed by enterprises and to help them in building critical thinking, analytic reasoning, and insight to the solved complex problems from different perspectives. Fostering learning-by-doing activities in the pedagogical process can help students to achieve learning independence, as they could acquire deeper conceptual understanding by experimenting with the abstract concept in a more interesting, useful, and meaningful way. Clear information about learning outcomes and goals might help students to take more responsibility for their learning results. Active learning methods implemented by the project team members in their teaching practice, eduScrum and Jigsaw in particular, proved to provide better scientific and soft skills support to students than classical teaching methods. EduScrum method enables teachers to generate a working environment that stimulates students' working habits and self-initiative as they become aware of their responsibilities within the team, their own acquired knowledge, and their abilities to solve problems independently, though in collaboration with other team members. This method enhances collaborative learning, as students are working in teams towards a common goal - knowledge acquisition, while they are interacting with each other and evaluated individually. Teams consisting of 4-5 students work together on a list of problems - sprint; each member is responsible for solving one of them, while the group leader – a master, is responsible for the whole team. A similar principle is behind the Jigsaw technique, where the classroom activity makes students dependent on each other to succeed. Students are divided into groups, and assignments are split into pieces, which need to be assembled by the whole group to complete the (Jigsaw) puzzle. In this paper, analysis of students’ perceptions concerning the achievement of deeper conceptual understanding in mathematics and the development of soft skills, such as self-motivation, critical thinking, flexibility, leadership, responsibility, teamwork, negotiation, and conflict management, is presented. Some new challenges are discussed as brought by introducing active learning methods in the basic mathematics courses. A few examples of sprints developed and used in teaching basic maths courses at technical universities are presented in addition.

Keywords: active learning methods, collaborative learning, conceptual understanding, eduScrum, Jigsaw, soft skills

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Authors: Lorena Blasco-Arcas, Francesca Pucciarelli

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Business contexts have become globalised and digitalised, which requires that managers develop a strong sense of cross-cultural intelligence while working in geographically distant teams by means of digital technologies. How to better equip future managers on these kinds of skills has been put forward as a critical issue in Business Schools. In pursuing these goals, higher education is shifting from a passive lecture approach, to more active and experiential learning approaches that are more suitable to learn skills. For example, through the use of case studies, proposing plausible business problem to be solved by students (or teams of students), these institutions have focused for long in fostering learning by doing. Though, case studies are no longer enough as a tool to promote active teamwork and experiential learning. Moreover, digital advancements applied to educational settings have enabled augmented classrooms, expanding the learning experience beyond the class, which increase students’ engagement and experiential learning. Different authors have highlighted the benefits of digital engagement in order to achieve a deeper and longer-lasting learning and comprehension of core marketing concepts. Clickers, computer-based simulations and business games have become fairly popular between instructors, but still are limited by the fact that are fictional experiences. Further exploration of real digital platforms to implement real, live projects in the classroom seem relevant for marketing and business education. Building on this, this paper describes the development of an experiential learning activity in class, in which students developed a communication campaign in teams using the BuzzFeed platform, and subsequently implementing the campaign by using other social media platforms (e.g. Facebook, Instagram, Twitter…). The article details the procedure of using the project for a marketing module in a Bachelor program with students located in France, Italy and Spain campuses working on multi-campus groups. Further, this paper describes the project outcomes in terms of students’ engagement and analytics (i.e. visits achieved). the project included a survey in order to analyze and identify main aspects related to how the learning experience is influenced by the cultural competence developed through working in geographically distant and culturally diverse teamwork. Finally, some recommendations to use project-based social media tools while working with virtual teamwork in the classroom are provided.

Keywords: cultural competences, experiential learning, social media, teamwork, virtual group work

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Authors: P. J. Moore-Jones

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Emirati students studying at the University of the Emirates, one of three major public institutions of higher learning in the United Arab Emirates (UAE), have a wide demographic of faculty members teaching them an equally wide variety of courses. These faculty members bring with them their own cultural assumptions, methods, expectations, educational practices and use of language. The history of multiculturalism in the UAE coupled with the contemporary multiculturalism that exists in higher education Dubai create intriguing phenomena within the classroom. This study seeks to delve into students’ and faculty members’ perceptions of the social stratification that exist in this context. Data were collected via semi-structured interviews with both and analyzed from an interpretive perspective. Findings suggest the social stratification with is deeply-seeded in the multicultural history of the region and country are reflected in the everyday interworkings of education in modern day Dubai. The relevance of this research lies in that these findings can provide valuable insights into not only the attitudes and perceptions of these Emirati students might also be applicable to any of those student populations may exist.

Keywords: social stratification, intercultural competence, Dubai, United Arab Emirates

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural language processing in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis

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Authors: Frantisek Mosna

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E-learning has become an efficient and widespread means in process of education at all branches of human activities. Statistics is not an exception. Unfortunately the main focus in the statistics teaching is usually paid to the substitution to formulas. Suitable web-sites can simplify and automate calculation and provide more attention and time to the basic principles of statistics, mathematization of real-life situations and following interpretation of results. We introduce our own web-sites for hypothesis testing. Their didactic aspects, technical possibilities of individual tools for their creating, experience and advantages or disadvantages of them are discussed in this paper. These web-sites do not substitute common statistical software but significantly improve the teaching of the statistics at universities.

Keywords: e-learning, hypothesis testing, PHP, web-sites

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Authors: Shri Krishna Mishra, Badri Yadav

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Effect of collaborative learning on development of process skills and attitude towards science is It rightly said that the destiny of the nation is shaped inside its classroom. Classroom is a place where the pupil and teacher interact purposefully to gain knowledge. Teaching is the principal mode of education. It can be called a transaction between teacher and pupil, in which one transmits knowledge to other. The teaching learning process consists of three important components, the pupils, the teacher and the curriculum; the classroom is the collection of students of their own individual abilities and needs. In the present classroom teaching learners are either persuasive recipient or passive observant. The school environment leading to low-achievement we have to try better to develop in the young mind. Children are the sticks of dynamite, bundles of energy and potential power waiting to be ignited. Guide them carefully to a place where their potentialities and strength will be used to build a better world. Man’s future depends to large extent on scientific advances and development of productive activity. Science is considered as an important subject in school curricular. The education commission (1964-66) has suggested that science education is necessary for all children at school stage. It is essential to develop children’s logical and critical thinking. But these days thinking process and academic achievement of students have been suppressed by competitive environment of our schools. How the students perceive each other and interact with one another is a neglected aspect of instruction. In the constructivist perspective learning in a process of construction of knowledge. Learners actively construct their own knowledge by connecting new ideas to existing ideas on the basis of materials/ activities presented to them (experience).

Keywords: effect of collaborative learning, development of process skills, science education, attitude towards science

Procedia PDF Downloads 268