Search results for: onsite and online learning

Authors: Yahia A. M. AlKhoudary

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This Study presents the outcome of an investigation to evaluate the importance of autonomous learning as a means of motivation. However, very little research done in this field. Thus, the aims of this study are to ascertain the needs of the learners and to investigate their attitudes and motivation towards the mode of learning. Various suggestions made on how to improve learners’ participation in the learning process. A survey conducted on a sample group of 60 Omani College students. Self-report questionnaires and retrospective interviews conducted to find out their material-type preferences in a self-access learning context. Achieving autonomous learning system, which learners is one of the Ministry of Education goals in the Sultanate of Oman. As a result, this study presents the outcome of an investigation to evaluate the students’ performance in English as a Foreign Language (EFL). It focuses on the effect of autonomous learning that encourages students to learn English, a research conducted at Buraimi city, the Sultanate of Oman. The procedure of this investigation based on four dimensions: (1) sixty students are selected and divided into two groups, (2) pre and posttest projects are given to them, and (3) questionnaires are administered to both students who are involved in the experiment and 50 teachers (25 males and 25 females) to collect accurate data, (4) an interview with students and teachers to find out their attitude towards autonomous learning. Analysis of participants’ responses indicated that autonomous learning motivates students to learn English independently and increase the intrinsic rather than extrinsic motivation to improve their English language as a long-life active learning. The findings of this study show that autonomous learning approach is the best remedy to empower the students’ skills and overcome all relevant difficulties. They also show that secondary school teachers can fully rely on this learning approach that encourages language learners to monitor their progress, increase both learners and teachers’ motivation and ameliorate students’ behavior in the classroom. This approach is also an ongoing process, which takes time, patience and support to be lifelong learning.

Keywords: Omani, autonomous learning system, English as a Foreign Language (EFL), learning approach

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Authors: Z. Tasir, S. N. Kew, D. West, Z. Abdullah, D. Toohey

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Research on Learning Analytics is progressively developing in the higher education field by concentrating on the process of students' learning. Therefore, a research project between Malaysian and Australian Universities was initiated in 2015 to look at the use of Learning Analytics to support the development of teaching practice. The focal point of this article is to discuss and share the experiences of Malaysian and Australian universities in the process of developing the collaborative research on Learning Analytics. Three aspects of this will be discussed: 1) Establishing an international research project and team members, 2) cross-cultural understandings, and 3) ways of working in relation to the practicalities of the project. This article is intended to benefit other researchers by highlighting the challenges as well as the strategies used in this project to ensure such collaborative research succeeds.

Keywords: academic research project, collaborative research, cross-cultural understanding, international research project

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Authors: Vine Petzer, Mirna Nel

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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.

Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting

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Authors: Giovanni Gonzalez Araujo, Michael Kyrilov, Angelo Kyrilov

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STEAMplug is a web-based innovative educational platform which makes teaching easier and learning more effective. It requires no setup, eliminating the barriers to entry, allowing students to focus on their learning throughreal-world development environments. The student-centric tools enable easy collaboration between peers and teachers. Analyzing user interactions with the system enables us to predict student performance and identify at-risk students, allowing early instructor intervention.

Keywords: plagiarism detection, identifying at-Risk Students, education technology, e-learning system, collaborative development, learning and teaching with technology

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Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Ibrahim Garba

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This research involved the use of word distributions and morphological knowledge by speakers of Arabic learning English connected different allomorphs in order to realize how the morphology and syntax of English gives meaning through using interactive crossword puzzles (ICP). Fifteen chapters covered with a class of nine learners over an academic year of an intensive English program were reviewed using the ICP. Learners were questioned about how the use of this gaming element enhanced and motivated their learning of English. The findings were positive indicating a successful implementation of ICP both at creational and user levels. This indicated a positive role technology had when learning and teaching English through adopting an interactive gaming element for learning English.

Keywords: distribution, gaming, interactive-crossword-puzzle, morphology

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Hadi Manjiri, Mahdyeh Bakhshi, Ali Jafari, Maryam Salati

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This study investigates the influence of e-learning on teacher-student instructional interactions through the mediating role of computer literacy among elementary school teachers in Tehran. The research method is a survey that was conducted among elementary school students in Tehran. A sample size of 338 was determined based on Morgan's table. A stratified random sampling method was used to select 228 women and 110 men for the study. Bagherpour et al.'s computer literacy questionnaire, Elahi et al.'s e-learning questionnaire, and Lourdusamy and Khine's questionnaire on teacher-student instructional interactions were used to measure the variables. The data were analyzed using SPSS and LISREL software. It was found that e-learning affects teacher-student instructional interactions, mediated by teachers' computer literacy. In addition, the results suggest that e-learning predicts a 0.66 change in teacher-student instructional interactions, while computer literacy predicts a 0.56 change in instructional interactions between teachers and students.

Keywords: e-learning, instructional interactions, computer literacy, students

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Authors: Kashi Raj Pandey

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Transformative learning is a form of learning rooted in learners' life experiences and their inherent love for learning. It emphasizes the importance of incorporating students' everyday work through the use of learning diaries and reflective journals. It encourages learners to take a proactive role in their own improvement, fostering creativity and promoting informed discussions about the learning process. Reflecting on the personal experience with English language learning in a rural village in Nepal where rote memorization was the prevailing teaching method, this traditional approach hindered a deeper understanding of the language, prompting the author to recognize the need for more effective pedagogy. In this study, the author delved into the cultural contextualization of English language learning, taking into account learners' backgrounds. The study’s findings highlighted the importance of equity, inclusion, mutuality, and social justice in the classroom, emphasizing the significance of integrating students' lived experiences into the pedagogical approach. This, in turn, can encourage students to engage in profound and collaborative learning practices within the realm of English language education. Upon successfully implementing the research findings, including the eight key conditions of transformative learning, in multiple classrooms, the author collaborated with international educationists and government stakeholders in Nepal. The purpose was to disseminate the research findings, conduct teacher training workshops, and systematically enhance Nepali students’ English language learning. These methods have already demonstrated a significant improvement in student engagement within the same school where the author once learned English as a child. This study aims to explore teachers’ decision-making process regarding the transition from traditional teaching methods to interactive ones, which have gained national recognition within the ESL/EFL teaching community in Nepal. By sharing these experiences, it is expected that other teachers will also contemplate adopting transformative learning pedagogy in their own classrooms.

Keywords: reflection, student engagement, pedagogy, transformative learning

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Authors: Issa Qabaja, Fadi Thabtah

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Email phishing classification is one of the vital problems in the online security research domain that have attracted several scholars due to its impact on the users payments performed daily online. One aspect to reach a good performance by the detection algorithms in the email phishing problem is to identify the minimal set of features that significantly have an impact on raising the phishing detection rate. This paper investigate three known feature selection methods named Information Gain (IG), Chi-square and Correlation Features Set (CFS) on the email phishing problem to separate high influential features from low influential ones in phishing detection. We measure the degree of influentially by applying four data mining algorithms on a large set of features. We compare the accuracy of these algorithms on the complete features set before feature selection has been applied and after feature selection has been applied. After conducting experiments, the results show 12 common significant features have been chosen among the considered features by the feature selection methods. Further, the average detection accuracy derived by the data mining algorithms on the reduced 12-features set was very slight affected when compared with the one derived from the 47-features set.

Keywords: data mining, email classification, phishing, online security

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Authors: Sirimanee Banjong

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This study aimed to 1) develop pre-service teachers’ leadership skills through camp-based learning, and 2) develop pre-service teachers’ teamwork skills through camp-based learning. An applied research methodology was used. The target group was derived from a purposive selection. It involved 32 fourth-year students in Early Childhood Education Program enrolling in a course entitled Seminar in Early Childhood Education provided during the second semester of the academic year 2013. The treatment was camp-based learning activities which applied a PDCA process including four stages: 1) plan, 2) do, 3) check, and 4) act. Research instruments were a learning camp program, a camp-based learning management plan, a 5-level assessment form for leadership skills and a 5-level assessment form for assessing teamwork skills. Data were analyzed using descriptive statistics. Results were: 1) pre-service teachers’ leadership skills yielded the before treatment average score at ¯("x" )=3.4, S.D.= 0.62 and the after-treatment average score at ¯("x" ) 4.29, S.D.=0.66 pre-service teachers’ teamwork skills yielded the before-treatment average score at ¯("x" )=3.31, S.D.= 0.60 and the after-treatment average score at ¯("x" )=4.42, S.D.= 0.66. Both differences were statistically significant at the .05 level. Thus, the pre-service teachers’ leadership and teamwork skills were significantly improved through the camp-based learning approach.

Keywords: learning camp, leadership skills, teamwork skills, pre-service teachers

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

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

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

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Authors: Elisabeth Unterfrauner, Christian Voigt

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Since the foundation of the first Fab Lab by the Massachusetts Institute of Technology about 17 years ago, the Maker movement has spread globally with the foundation of maker spaces and Fab Labs worldwide. In these workshops, citizens have access to digital fabrication technologies such as 3D printers and laser cutters to develop and test their own ideas and prototypes, which makes it an attractive place for start-up companies. Know-How is shared not only in the physical space but also online in diverse communities. According to the Horizon report, the Maker movement, however, will also have an impact on educational settings in the following years. The European project ‘DOIT - Entrepreneurial skills for young social innovators in an open digital world’ has incorporated key elements of making to develop an early entrepreneurial education program for children between the age of six and 16. The Maker pedagogy builds on constructive learning approaches, learning by doing principles, learning in collaborative and interdisciplinary teams and learning through trial and error where mistakes are acknowledged as learning opportunities. The DOIT program consists of seven consecutive elements. It starts with a motivation phase where students get motivated by envisioning the scope of their possibilities. The second step is about Co-design: Students are asked to collect and select potential ideas for innovations. In the Co-creation phase students gather in teams and develop first prototypes of their ideas. In the iteration phase, the prototype is continuously improved and in the next step, in the reflection phase, feedback on the prototypes is exchanged between the teams. In the last two steps, scaling and reaching out, the robustness of the prototype is tested with a bigger group of users outside of the educational setting and finally students will share their projects with a wider public. The DOIT program involves 1,000 children in two pilot phases at 11 pilot sites in ten different European countries. The comprehensive evaluation design is based on a mixed method approach with a theoretical backbone on Lackeus’ model of entrepreneurship education, which distinguishes between entrepreneurial attitudes, entrepreneurial skills and entrepreneurial knowledge. A pre-post-test with quantitative measures as well as qualitative data from interviews with facilitators, students and workshop protocols will reveal the effectiveness of the program. The evaluation results will be presented at the conference.

Keywords: early entrepreneurial education, Fab Lab, maker education, Maker movement

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Authors: Khadija Al Farei, Prakash Kumar, Vikas Rao Naidu

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Games are being developed with different genres for different age groups, for many decades. In many places, educational games are playing a vital role for active classroom environment and better learning among students. Currently, the educational games have assumed an important place in children and teenagers lives. The role of educational games is important for improving the learning capability among the students especially of this generation, who really live among electronic gadgets. Hence, it is now important to make sure that in our educational system, we are updated with all such advancement in technologies. Already much research is going on in this area of edutainment. This research paper will review around ten different research papers to find the relation between the education learning techniques and games. The result of this review provides guidelines for enhanced teaching and learning solutions in education. In-house developed educational games proved to be more effective, compared to the one which is readily available in the market.

Keywords: education, education game, educational technology, edutainment, game genres, gaming in education

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Authors: Khadija Bouzaachane, El Mahdi El Guarmah

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The classification of low-resolution satellite images has been a worthwhile and fertile field that attracts plenty of researchers due to its importance in monitoring geographical areas. It could be used for several purposes such as disaster management, military surveillance, agricultural monitoring. The main objective of this work is to classify efficiently and accurately low-resolution satellite images by using novel technics of deep learning and reinforcement learning. The images include roads, residential areas, industrial areas, rivers, sea lakes, and vegetation. To achieve that goal, we carried out experiments on the sentinel-2 images considering both high accuracy and efficiency classification. Our proposed model achieved a 91% accuracy on the testing dataset besides a good classification for land cover. Focus on the parameter precision; we have obtained 93% for the river, 92% for residential, 97% for residential, 96% for the forest, 87% for annual crop, 84% for herbaceous vegetation, 85% for pasture, 78% highway and 100% for Sea Lake.

Keywords: classification, deep learning, reinforcement learning, satellite imagery

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Authors: Una Carthy

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A recent study of third level institutions in Ireland reveals that both age and aptitude can be overcome by teaching methodologies to motivate second language learners. This PhD investigation gathered quantitative and qualitative data from 14 Institutes of Technology over a three years period from 2011 to 2014. The fundamental research question was to establish the impact of institutional language policy on attitudes towards language learning. However, other related issues around second language acquisition arose in the course of the investigation. Data were collected from both lectures and students, allowing interesting points of comparison to emerge from both datasets. Negative perceptions among lecturers regarding language provision were often associated with the view that language learning belongs to primary and secondary level and has no place in third level education. This perception was offset by substantial data showing positive attitudes towards adult language learning. Lenneberg’s Critical Age Theory postulated that the optimum age for learning a second language is before puberty. More recently, scholars have challenged this theory in their studies, revealing that mature learners can and do succeed at learning languages. With regard to aptitude, a preoccupation among lecturers regarding poor literacy skills among students emerged and was often associated with resistance to second language acquisition. This was offset by a preponderance of qualitative data from students highlighting the crucial role which teaching approaches play in the learning process. Interestingly, the data collected regarding learning disabilities reveals that, given the appropriate learning environments, individuals can be motivated to acquire second languages, and indeed succeed at learning them. These findings are in keeping with other recent studies regarding attitudes towards second language learning among students with learning disabilities. Both sets of findings reinforce the case for language policies in the Institute of Technology (IoTs). Supportive and positive learning environments can be created in third level institutions to motivate adult learners, thereby overcoming perceived obstacles relating to age and aptitude.

Keywords: age, aptitude, second language acquisition, teaching methodologies

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

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Authors: Tharntip Tawnie Chutikulrungsee, Oliver Kisalay Burmeister, Maumita Bhattacharya, Dragana Calic

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Sharing on social network sites (SNSs) has rapidly emerged as a new social norm and has become a global phenomenon. Billions of users reveal not only their own information (self disclosure) but also information about others (other-generated disclosure), resulting in a risk and a serious threat to either personal or informational privacy. Self-disclosure (SD) has been extensively researched in the literature, particularly regarding control of individual and existing privacy management. However, far too little attention has been paid to other-generated disclosure (OGD), especially by insiders. OGD has a strong influence on self-presentation, self-image, and electronic word of mouth (eWOM). Moreover, OGD is more credible and less likely manipulated than SD, but lacks privacy control and legal protection to some extent. This article examines OGD in depth, ranging from motivation to both online and offline impacts, based upon lived experiences from both ‘the disclosed’ and ‘the discloser’. Using purposive sampling, this phenomenological study involves an online survey and in-depth interviews. The findings report the influence of peer disclosure as well as users’ strategies to mitigate privacy issues. This article also calls attention to the challenge of OGD privacy and inadequacies in the law related to privacy protection in the digital domain.

Keywords: facebook, online privacy, other-generated disclosure, social networks sites (SNSs)

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Authors: Nanyombi Lubimbi, Josette Niyokindi

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Background: As in many other developing countries in Africa, Rwanda suffers from a chronic shortage of skilled Health Care professionals including Clinical Instructors. This shortage negatively affects the clinical instruction quality therefore impacting student-learning outcomes. Due to poor clinical supervision, it is often noted that students have no structure or consistent guidance in their learning process. The Clinical Educators and the Rwandan counterparts identified the need to create a favorable environment for learning. Description: During orientation the expectations of the student learning process, collaboration of the clinical instructors with the nurses and Clinical Educators is outlined. The ward managers facilitate structured learning by helping the students identify a maximum of two patients using the school’s objectives to guide the appropriate selection of patients. Throughout the day, Clinical Educators with collaboration of Clinical Instructors when present conduct an ongoing assessment of learning and provide feedback to the students. Post-conference is provided once or twice a week to practice critical thinking skills of patient cases that they have been taking care of during the day. Lessons Learned: The students are found to be more confident with knowledge and skills gained during rotations. Clinical facility evaluations completed by students at the end of their rotations highlight the student’s satisfaction and recommendation for continuation of structured learning. Conclusion: Based on the satisfaction of both students and Clinical Instructors, we have identified need for structured learning during clinical rotations. We acknowledge that more evidence-based practice is necessary to effectively address the needs of nursing and midwifery students throughout the country.

Keywords: Rwanda, clinical rotation, structured learning, critical thinking skills, post-conference

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Authors: M. Dakshayini, P. Jayarekha

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In traditional output-based education system, class room lecture and laboratory are the traditional delivery methods used during the course. Written examination and lab examination have been used as a conventional tool for evaluating student’s performance. Hence, there are certain apprehensions that the traditional education system may not efficiently prepare the students for competent professional life. This has led for the change from Traditional output-based education to Outcome-Based Education (OBE). OBE first sets the ideal programme learning outcome consecutively on increasing degree of complexity that students are expected to master. The core curriculum, teaching methodologies and assessment tools are then designed to achieve the proposed outcomes mainly focusing on what students can actually attain after they are taught. In this paper, we discuss a promising applications based learning and evaluation component involving industry collaboration to improve the quality of teaching and student learning process. Incorporation of this component definitely improves the quality of student learning in engineering education and helps the student to attain the competency as per the graduate attributes. This may also reduce the Industry-academia gap.

Keywords: outcome-based education, programme learning outcome, teaching-learning process, evaluation, industry collaboration

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Authors: F. Zarrabi, J. R. Brown

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Although English is not a second language in Iran, it has become an inseparable part of many Iranian people’s lives and is becoming more and more widespread. This high demand has caused a significant increase in the number of private English language institutes in Iran. Although English is a compulsory course in schools and universities, the majority of Iranian people are unable to communicate easily in English. This paper reviews the current state of teaching and learning English as an international language in Iran. Attitudes and motivations about learning English are reviewed. Five different aspects of using English within the country are analysed, including: English in public domain, English in Media, English in organizations/businesses, English in education, and English in private language institutes. Despite the time and money spent on English language courses in private language institutes, the majority of learners seem to forget what has been learned within months of completing their course. That is, when they are students with the support of the teacher and formal classes, they appear to make progress and use English more or less fluently. When this support is removed, their language skills either stagnant or regress. The findings of this study suggest that a dependant approach to learning is potentially one of the main reasons for English language learning problems and this is encouraged by English course books and approaches to teaching.

Keywords: English in Iran, English language learning, English language teaching, evaluation

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Authors: Abdulmajeed Almansour

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Learning a foreign language with the assistant of technological tools has become an interest of learners and educators. Increased use of smartphones among undergraduate students has made them popular for not only social communication but also for entertainment and educational purposes. Smartphones have provided remarkable advantages in language learning process. Learning vocabulary is an important part of learning a language. The use of smartphone applications for English vocabulary learning provides an opportunity for learners to improve vocabulary knowledge beyond the classroom wall anytime anywhere. Recently, various smartphone applications were created specifically for vocabulary learning. This paper aims to explore the use of smartphone application Memrise designed for vocabulary learning to enhance academic vocabulary among undergraduate students. It examines whether the use of a Memrise smartphone application designed course enhances the academic vocabulary learning among ESL learners. The research paradigm used in this paper followed a mixed research model combining quantitative and qualitative research. The study included two hundred undergraduate students randomly assigned to the experimental and controlled group during the first academic year at the Faculty of English Language, Imam University. The research instruments included an attitudinal questionnaire and an English vocabulary pre-test administered to students at the beginning of the semester whereas post-test and semi-structured interviews administered at the end of the semester. The findings of the attitudinal questionnaire revealed a positive attitude towards using smartphones in learning vocabulary. The post-test scores showed a significant difference in the experimental group performance. The results from the semi-structure interviews showed that there were positive attitudes towards Memrise smartphone application. The students found the application enjoyable, convenient and efficient learning tool. From the study, the use of the Memrise application is seen to have long-term and motivational benefits to students. For this reason, there is a need for further research to identify the long-term optimal effects of learning a language using smartphone applications.

Keywords: second language vocabulary learning, academic vocabulary, mobile learning technologies, smartphone applications

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Authors: Ahmad Khachan, Ahmet Ozmen

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This study aims to introduce a mobile bite-sized learning concept, a mobile application with social networks motivation factors that will encourage students to practice critical thinking, improve analytical skills and learn knowledge sharing. We do not aim to propose another e-learning or distance learning based tool like Moodle and Edmodo; instead, we introduce a mobile learning tool called Interactive M-learning Application. The tool reconstructs and strengthens the bonds between educators and learners and provides a foundation for integrating mobile devices in education. The application allows learners to stay connected all the time, share ideas, ask questions and learn from each other. It is built on Android since the Android has the largest platform share in the world and is dominating the market with 74.45% share in 2018. We have chosen Google-Firebase server for hosting because of flexibility, ease of hosting and real time update capabilities. The proposed m-learning tool was offered to four groups of university students in different majors. An improvement in the relation between the students, the teachers and the academic institution was obvious. Student’s performance got much better added to better analytical and critical skills advancement and moreover a willingness to adopt mobile learning in class. We have also compared our app with another tool in the same class for clarity and reliability of the results. The student’s mobile devices were used in this experimental study for diversity of devices and platform versions.

Keywords: education, engineering, interactive software, undergraduate education

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Authors: G. Valentis, Q. Berthelot

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Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

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Authors: Fabrice Setephin Atedjio, Jean-Pierre Lienou, Frederica F. Nelson, Sachin S. Shetty

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Malicious users exploit vulnerabilities in computer systems, significantly disrupting their performance and revealing the inadequacies of existing protective solutions. Even machine learning-based approaches, designed to ensure reliability, can be compromised by adversarial attacks that undermine their robustness. This paper addresses two critical aspects of enhancing model reliability. First, we focus on improving model performance and robustness against adversarial threats. To achieve this, we propose a strategy by harnessing deep reinforcement learning. Second, we introduce an approach leveraging generative adversarial networks to counter adversarial attacks effectively. Our results demonstrate substantial improvements over previous works in the literature, with classifiers exhibiting enhanced accuracy in classification tasks, even in the presence of adversarial perturbations. These findings underscore the efficacy of the proposed model in mitigating intrusions and adversarial attacks within the machine learning landscape.

Keywords: machine learning, reliability, adversarial attacks, deep-reinforcement learning, robustness

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Rajiv Kumar, Amit Sachan, Arindam Mukherjee

Abstract:

Government agencies around the world, including India, are incorporating digital technologies and processes into their day-to-day operations to become more efficient. Despite low internet penetration (around 34.8% of total population) in India, Government of India has made some public services mandatory to access online (e.g. passport, tax filing).This is insisting citizens to access mandatory public services online. However, due to digital divide, all citizens do not have equal access to internet. In light of this, it is an interesting topic to explore how citizens are able to access mandatory online public services. It is important to understand how citizens are adopting these mandatory e-government services and how the adoption behavior of these mandatory e-government services is different or similar to adoption behavior of non-mandatory e-government services. The purpose of this research is to investigate the factors that influence adoption of mandatory and non-mandatory e-government services in India. A quantitative technique is employed in this study. A conceptual model has been proposed by integrating the influencing factors to adopt e-government services from previous studies. The proposed conceptual model highlights a comprehensive set of potential factors influencing the adoption of e-government services. The proposed model has been validated by keeping in view the local context of Indian society. Online and paper based survey was administered, collected data was analyzed and results have been discussed. A total of 463 valid responses were received and further the responses were analyzed. The research reveals that the influencing factors to adopt e-government services are not same for both mandatory and non-mandatory e-government services. There are some factors that influence adoption of both mandatory and non-mandatory e-government services but there are some which are relevant for either of mandatory and non-mandatory e-government services. The research findings may help government or concerned agencies in successfully implementing e-government services.

Keywords: adoption, e-government, India, mandatory, non-mandatory

Procedia PDF Downloads 317

Authors: Eyup Bayram Guzel

Abstract:

There have been growing awareness that technology offers unique and promising advantages by offering up-to-data educational materials in promoting teaching and learning materials, new strategies for building enhanced communication environment for people with disabilities and specifically for this study concentrated on the students with deafness and hearing impairments. Creating e-learning environment where teachers and students work in collaboration to develop better educational outcomes is the foremost reason of conducting this research. This study examined the perspectives of special education teachers’ regarding an application of e-learning software called Multimedia Builder on the students with deafness and hearing impairments. Initial and follow up interviews were conducted with 15 special education teachers around the scope of qualitative case study. Grounded approach has been used to analyse and interpret the data. The research results revealed that application of Multimedia Builder software were influential on reading, sign language, vocabulary improvements, computer and ICT usage developments and on audio-visual learning achievements for the advantages of students with deafness and hearing impairments. The implications of the study encouraged the ways of using e-learning tools and strategies to promote unique and comprehensive learning experiences for the targeted students and their teachers.

Keywords: e-learning, special education, deafness and hearing impairment, computer-ICT usage.

Procedia PDF Downloads 437

Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

Abstract:

Teaching and learning occupy a significant position globally, as the sustainable development of all sectors is intrinsically linked to the improvement of the educational system. The COVID-19 pandemic demonstrated that the integration of Information and Communication Technology (ICT) in the learning process is not optional but essential, and that proficiency in computer tools is an asset that will enhance pedagogy and ensure the continuity of learning under any circumstances. The objective of our study is to evaluate the impact of introducing computer tools on the quality of learning and the realization of conceptual change in learners. To this end, a learning situation was meticulously prepared, targeting first-year baccalaureate students in experimental sciences at a public high school, "Khadija Oum Almouminin," focusing on the chapter on glycemia regulation in the Moroccan Life and Earth Sciences (LES) curriculum. The learning situation was implemented with a pilot group that utilized computer tools and a control group that studied the same chapter without using ICT. The analysis and comparison of the results allowed us to verify the research question posed and to propose perspectives to ensure conceptual change in learners.

Keywords: information and communication technology, conceptual change, continuity of learning, life and earth sciences, glycemia regulation

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Authors: Ahmed Al-Adaileh

Abstract:

Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

Procedia PDF Downloads 199