Online-Journals.org (International Association of Online Engineering)
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Secondary School Teachers’ Attitudes Towards Online Learning Tools: Teachers’ Behaviour in Distance Education
Get PDFSecondary school teachers’ attitudes towards online learning tools have been modified by systemic measures adopted in the school network as a result of COVID-19. This unexpected crisis situation forced schools to quickly implement digital infrastructure and look for optimal methods of online education. The aim of this study is to investigate on which factors (gender, age and subject area taught) the use of online tools for teaching activities depends. The aim is also to explore the subjective emotional experience of teachers when using online tools and the reasons of their perceived stress in distance education in the Covid era. The factors influencing the use of online tools for teaching, teachers’ subjective emotional experiences of using online tools, and the reasons for teachers’ perceived burden in distance education in the COVID era are analyzed using Welch’s ANOVA test and Games-Howell’s Post-Hoc test. The correlation values focused on teachers’ perceived feelings using online teaching tools are calculated by Pearson’s correlation coefficient. The results are directed towards the level of teachers’ emotional experience in the context of using online tools for the respective activity. Satisfaction and well-being are experienced by teachers when explaining, activating students, assigning written work, and providing information resources. The study identified a major problem in education, which is the use of online tools for oral examinations. Another problem is the integration of homework into online education. The study has practical impact on the integration of teachers’ digital competences. A holistic approach should be developed in teacher training, seeking to fully integrate digital competences, and social and health aspects should also be taken into account
Students’ Perception towards Online Learning across Multiple Disciplinary Courses in India—A Qualitative Analysis
Get PDFOnline learning has become essential to the teaching and learning approach during the pandemic. Due to its enormous benefits, online or e-learning can be sustained. The acceptability of online or e-learning depends on the student’s perception and the availability of infrastructure. Data from various streams and age groups has been collected from students in different institutions. After collecting the data, this research incorporates descriptive statistics for a thorough analysis and utilizes the Chi-square test to provide scientific evidence. This study finds that the majority of final-year undergraduate and postgraduate students support online education. The student’s economic status affects their preference for online or e-learning. Having a smart device and internet access also influence the decision to pursue online or e-learning. Gender is positively associated with access to Internet facilities and has a cascading effect on preferences for online or e-learning. Female students prefer online classes but require additional internet resources. Higher education institutions could enhance their online course offerings by targeting specific groups, such as female students for postgraduate programs, if they could better understand their preferences. Even though some existing studies in the literature have examined the Indian scenario to understand the factors influencing the adoption of online education, none of these studies have considered the fundamental need for online or e-learning. Moreover, the preferences were not studied based on different demographics. This research work has collected and utilized data from various educational disciplines across multiple institutes, marking the first endeavor of its kind in the literature
A Practical Approach of Data Visualization from Geographic Information Systems by Using Mobile Technologies
Get PDFThe purpose of this paper is to demonstrate a practical approach to data visualization by using mobile technologies and desktop geographic information systems. To do that, we analyze public data for Black Sea water pollution on Varna’s beaches by using real data in real time. Geographic information systems (GISs) are used for visualization, and statistical software is used for correlation analysis. In our approach, the use of open-source software products is essential, namely QGIS and PSPP software. The methodology includes using one dataset, and after extract-transform-load procedures, additional analysis is conducted. Mobile technologies are used to demonstrate the results of the correlation analysis to a wide audience, and data visualization helps for better understanding. A similar visualization approach may be conducted for other subjects and fields of interest
A State Table SPHIT Approach for Modified Curvelet-based Medical Image Compression
Get PDFMedical imaging plays a significant role in clinical practice. Storing and transferring a large volume of images can be complex and inefficient. This paper presents the development of a new compression technique that combines the fast discrete curvelet transform (FDCvT) with state table set partitioning in the hierarchical trees (STS) encoding scheme. The curvelet transform is an extension of the wavelet transform algorithm that represents data based on scale and position. Initially, the medical image was decomposed using the FDCvT algorithm. The FDCvT algorithm creates symmetrical values for the detail coefficients, and these coefficients are modified to improve the efficiency of the algorithm. The curvelet coefficients are then encoded using the STS and differential pulse-code modulation (DPCM). The greatest amount of energy is contained in the coarse coefficients, which are encoded using the DPCM method. The finest and modified detail coefficients are encoded using the STS method. A variety of medical modalities, including computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI), are used to verify the performance of the proposed technique. Various quality metrics, including peak signal-to-noise ratio (PSNR), compression ratio (CR), and structural similarity index (SSIM), are used to evaluate the compression results. Additionally, the computation time for the encoding (ET) and decoding (DT) processes is measured. The experimental results showed that the PET image obtained higher values of the PSNR and CR. The CT image provides high quality for the reconstructed image, with an SSIM value of 0.96 and the fastest ET of 0.13 seconds. The MRI image has the shortest DT, which is 0.23 seconds
We Can Rely on ChatGPT as an Educational Tutor: A Cross-Sectional Study of its Performance, Accuracy, and Limitations in University Admission Tests
Get PDFThe aim of this research was to evaluate the performance of ChatGPT in answering multiple-choice questions without images in the entrance exams to the National University of Engineering (UNI) and the Universidad Nacional Mayor de San Marcos (UNMSM) over the past five years. In this prospective exploratory study, a total of 1182 questions were gathered from the UNMSM exams and 559 questions from the UNI exams, encompassing a wide range of topics including academic aptitude, reading comprehension, humanities, and scientific knowledge. The results indicate a significant (p < 0.001) and higher proportion of correct answers for UNMSM, with 72% (853/1182) of questions answered correctly. In contrast, there is no significant difference (p = 0.168) in the proportion of correct and incorrect answers for UNI, with 52% (317/552) of questions answered correctly. Similarly, in the World History course (p = 0.037), ChatGPT achieved its highest performance at a general level, with an accuracy of 91%. However, this was not the case in the language course (p = 0.172), where it achieved the lowest score of 55%. In conclusion, to fully harness the potential of ChatGPT in the educational setting, continuous evaluation of its performance, ongoing feedback to enhance its accuracy and minimize biases, and tailored adaptations for its use in educational settings are essential
Developing Future Teachers’ Academic Writing and Critical Thinking Skills Using ChatGPT
Get PDFPreparing future teachers to meet the demands of an increasingly dynamic world is a paramount challenge. Academic writing and critical thinking skills influence foreign language teachers’ professional growth, shaping their students’ cognitive development. This paper explores the integration of ChatGPT (generative pre-trained transformer) as a tool to augment future foreign language teachers’ academic writing and critical thinking skills. Through engagement with ChatGPT, future foreign language teachers have the opportunity to interact with a large language model that can provide targeted feedback, prompt thought-provoking discussions, and assist in refining professionally oriented competencies. This study examines the impact of ChatGPT on skills development through a comprehensive analysis of empirical data, pedagogical frameworks, and student experiences. A qualitative study conducted with 35 students enrolled in a foreign languages master’s program utilized focus group interviews and thematic analysis. The findings highlight ChatGPT’s limitations in content generation while also recognizing its potential to reduce research labor and assist in formatting and referencing tasks. The study underscores the importance of informed usage of ChatGPT, with students and educators recognizing the necessity of verifying information and maintaining academic integrity
A Systematic Review of Software for Learning Analytics in Higher Education
Get PDFLearning analytics (LA) is an important area of study in technology-enhanced learning that has emerged during the last decade. In earlier years, several systematic reviews have been conducted that focused on the theories behind LA or on empirical studies that utilized LA-based methods to improve learning and teaching processes in higher education. However, to date, there has been no systematic review of papers that have adopted a software perspective to report on the many forms of learning analytics software (LAS) that have been developed, despite these being used more frequently than before in higher education to support learning and teaching processes. To fill this gap, this paper presents a systematic review of LAS with the aim of critically scrutinizing the ways in which the use of interactive software in real-world settings may both support students in improving their academic performance and assist teachers in various pedagogical practices. A thematic analysis of 75 articles was conducted, resulting in the identification of three categories of LAS: at-risk student identification (ARSI) software; self-regulation software; and collaborative learning software. For each of these categories, we analyzed (i) the embedded functionality; (ii) the stakeholder (teacher and student) for which the functionality is intended; (iii) the analytical and visualization approaches implemented; and (iv) the limitations of the software that require future attention. Based on the findings of our review, we propose future directions for the development of learning analytics software
Looking into Students’ Cognitive Processes in an Online Collaborative Learning Environment
Get PDFThe primary aim of this study was to examine how students’ cognitive interactions in an online collaborative environment influence the formation and recognition processes of unconscious cognitive mechanisms appearing in the learning of mathematical concepts at the university level. The data analyzed was collected from a population of undergraduate students. The implemented methodology was supported by a qualitative approach. The study occurred in two phases: in the first phase, students answered three questionnaires, and in the second phase, stimulated recall interviews involving the verbalization of the cognitive processes were conducted retrospectively through the online collaborative environment provided by Zoom. The selection of pairs of students participating in these interviews was made after analyzing their responses, considering their richness in terms of differences and variations. Through the study, rich insights were gained into the cognitive processes examined. The analysis showed metacognitive processes through which students’ unconscious misconceptions were examined through self-reflection on previously acquired inadequate schemas. Cognitive and metacognitive interactions during the interviews progressively led to an adequate understanding of mathematical concepts. The findings confirm the results of a similar study that states stimulated recall data gathered in collaborative environments could be useful in revealing relatively higher-level cognitive and metacognitive processes
Enhancing Student Engagement: Technology Acceptance in Higher Education During Covid-19
Get PDFCOVID-19 has caused institutions across the sector to transition from conventional teaching and learning environments into virtual environments. Amidst this paradigm shift, academics have adopted a range of technology-based strategies to support the online learner. However, low attendance, engagement, and participation continue to challenge the execution of eLearning across the higher education (HE) sector. Within this narrative, there has been an interest in understanding the acceptance and adoption of technologies in education from the learners’ perspective. As a result, there has been an increased focus on technology acceptance models as a theoretical lens to unpack attitudes and beliefs relating to eLearning. Motivated by these environmental shifts, this study aims to capture themes and perspectives considered in educational literature worldwide to present future considerations for studied and practitioners as we emerge from the pandemic. By systematically reviewing global educational literature, the study aims to provide valuable insights and future considerations for both studied and practitioners as the HE sectors transitions out of the pandemic. The study is guided by the central study question: What influences the learners’ acceptance and continuation of use of education technologies during forced emergency conditions such as the COVID-19 pandemic? Based on these findings, we then share recommendations for education technology adoption in the HE sector
Impact of Augmented Reality via Mobile Technology on Student Performance in Physics Practicals Work
Get PDFThe current study was conducted to investigate the effect of using augmented reality (AR) via mobile devices on students’ performance in practical physics work. The study involved 108 second-year bachelor students specializing in physics and chemistry at the Higher Normal School of Abdelmalek Essaadi University. In this experimental study, the students were divided into two groups: an experimental group and a control group. The results indicate that using AR via mobile devices positively impacts students’ performance in practical physics work and significantly reduces the time required for the experimental group to complete various experiments