Online-Journals.org (International Association of Online Engineering)
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Predicting Preservice Teachers' Intentions to Integrate AI-Based Mobile Applications in Special Education: Examining the Role of Technology Self-Efficacy and Attitudes
Get PDFGrounded in the Theory of Reasoned Action, this study aims to examine how technology self-efficacy and attitudes toward AI-based mobile applications predict preservice special education teachers’ (SETs) intentions to integrate these applications into teaching students with learning disabilities (SWLD). A stepwise multiple regression analysis assessed the impact of these variables on preservice teachers’ intentions. Data were collected from 173 preservice SETs. The results revealed that preservice teachers exhibited moderate levels of technology self-efficacy, intentions to integrate AI-based mobile applications, and attitudes toward these applications. Furthermore, attitudes toward AI-based mobile applications emerged as the strongest predictor of teachers’ intentions to integrate these technologies (r = 0.878, p < 0.05), while technology self-efficacy also had a significant effect (r = 0.698, p < 0.05). Together, these variables accounted for 76% of the variance in intentions (R2 = 0.77). These findings underscore the important role of technology self-efficacy and positive attitudes in affecting teachers’ adoption of AI-based mobile applications. This study addresses the gap in the literature on integrating AI technologies in special education and emphasizes their potential to enhance teaching practices for SWLD. Based on the findings, the study recommends training and support to improve preservice teachers’ self-efficacy and attitudes toward AI-based mobile applications, facilitating their integration into special education settings
Effects of Augmented Reality-Based Digital Mobile Game-Based Learning on the Engagement of Students
Get PDFAugmented reality, or AR, has become increasingly popular over the past ten years, particularly in education. Only a small number of publications, meanwhile, have thoroughly examined the research trends in the application of AR to mathematics education. Globally, two trends that are being implemented in education are AR and digital game-based mobile learning. It is still important to monitor the consequences of implementing both trends simultaneously in inclusive learning, though. We have created an inclusive AR video game to teach mathematical logic skills. To highlight the patterns in this study’s emphasis, eight themes were identified from the analysis of these literary works: learning challenges, testing strategies, benefits of AR for mathematics, different kinds of AR apps, tools for developing AR apps, research contribution categories, and math subtopics. Additionally, by providing researchers and educators with a synthesized review of learning mathematics through AR, this study may open up new research directions. Our study demonstrated that children with varying needs perform similarly when playing. The findings and the teaching staff’s input indicate that DGBL and AR should permit the inclusion of kids with disabilities in the instruction procedure
Interactive Mobile English Translation Proficiency Model Based on Particle Swarm Optimisation and Neural Network for Teaching
Get PDFThis paper studies an interactive mobile English translation ability analysis model based on particle swarm optimisation (PSO) and neural networks (NNs) and explores its application potential in mobile translation teaching. By integrating the global search capability of PSO algorithm and the powerful learning capability of NN, the model aims to optimise the translation quality assessment process and improve the accuracy and efficiency of translation capability analysis. By training NNs to recognise language features, style and accuracy in translated texts, and fine-tuning NN parameters with PSO algorithm, this paper constructs a model that can effectively evaluate and interactively improve mobile English translation ability. The results show that the interactive mobile English translation ability analysis model based on PSO and NN has significant teaching application value, and brings new possibilities to the field of translation education, especially mobile learning scenarios
The Role of Mobile Technology in Enhancing Classroom Interaction for Accounting Instructors in Higher Vocational Education
Get PDFThe rapid advancement of mobile technology has introduced new opportunities to enhance classroom interaction, particularly in higher vocational accounting education, where theory and practices are closely integrated. Traditional interaction modes often limit student engagement and participation due to constraints of time, space, and format. This study addresses the gap in research on the interactive behaviors of accounting instructors under mobile network environments, focusing on two key aspects: (1) analyzing the effectiveness and influencing factors of mobile technology in facilitating instructor-student interactions in various teaching contexts, and (2) developing a predictive model using data mining techniques to forecast instructor interaction behaviors. By providing data-driven insights and a theoretical foundation, this study aims to optimize classroom interaction, improve teaching quality, and contribute to educational reform in accounting education
An Innovative Translation Teaching Model Based on Mobile Technology: A Case Study of Translation Major Classrooms
Get PDFWith the rapid development of information technology, the application of mobile technology in education has become increasingly widespread, particularly in language learning and translation teaching. In translation major classrooms, traditional teaching methods are gradually failing to meet the demands of training translation professionals in the new era. Existing studies have predominantly focused on the use of individual translation tools or basic translation support technologies, lacking systematic and in-depth discussions. Particularly in the context of real-time bilingual translation in teaching scenarios, how mobile technology and advanced machine translation algorithms can be integrated to improve translation efficiency and quality in the classroom remains an unresolved issue. A new innovative translation teaching model based on mobile technology was proposed in this study, with two core aspects being examined. First, to address the need for real-time bilingual translation in translation major classrooms, a hybrid tensor train decomposition (HTTD) method was introduced, which optimizes the flow of information and computational processes in translation tasks through efficient model decomposition and multi-dimensional data fusion. Second, based on HTTD, a lightweight machine translation model was developed, aiming to reduce the computational complexity and resource consumption during the translation process, ensuring the real-time performance and responsiveness of the translation system on mobile devices. This study not only provides a new technical support model for translation teaching but also offers innovative insights for the optimization and application of machine translation systems, holding significant theoretical and practical value
Students’ Motivation in the Artificial Intelligence Environment: A Systematic Review
Get PDFStudents’ motivation affects several educational variables related to students’ learning, including the learning outcomes. Artificial intelligence tools are flourishing in educational contexts. Research related to artificial intelligence contexts needs to address the various aspects of students’ motivation in these contexts. The present research intended to perform a systematic review of research papers that addressed students’ motivation in the artificial intelligence context. Specifically, it intended to examine the types of such motivation in terms of four aspects: description, factors influencing the motivation type, factors influenced by the motivation type, and the type as a mediator between other educational variables. To look for appropriate papers, we used the terms ‘artificial intelligence’ and ‘students’ motivation’ as keys used to search appropriate papers in Scopus, Web of Science and ‘Scholar; and afterword’s we added terms as ‘influence’ or ‘impact’ and ‘mediator; The results of the review showed that not all four aspects were realized in the literature arrived at as a result of the collecting data process. The four aspects were found for some of the motivation types, such as intrinsic motivation, while other types did not have the four aspects, such as extrinsic motivation. We recommend that educational researchers address each one of the four aspects of the different motivation types in the artificial intelligence context. This approach would give educators means for understanding how to encourage students’ motivation to learn and thus their learning outcomes in the new educational context
An Interactive Mobile Technology-Based Flipped Classroom Model for Japanese Language Instruction in Higher Education
Get PDFWith the continuous advancement of information technology, the application of mobile technologies in education has expanded considerably, particularly in the domain of foreign language learning. As a key foreign language, Japanese instruction has been influenced by various factors, including learning time, instructional methods, and educational tools. Traditional classroom-based models have increasingly failed to meet the individualized and diversified learning needs of contemporary students. Consequently, the flipped classroom model, supported by interactive mobile technologies, has emerged as a focal point of foreign language pedagogy research. While existing studies have predominantly concentrated on the design and implementation of flipped classrooms, limited attention has been given to the influence of learners’ circadian rhythms on learning effectiveness. In addition, Japanese learning module delivery systems have generally lacked personalization and interactivity. To address these gaps, this study aims to investigate optimal learning time period alignment for Japanese language acquisition using the dynamic time warping (DTW) algorithm and deliver personalized Japanese learning modules through interactive mobile technologies, thereby enhancing learning outcomes and fostering greater learner engagement
Multi-Model Approach for Tongue Image Classification in Traditional Thai Medicine
Get PDFNowadays, complementary medicine is gaining widespread acceptance and is widely accepted, particularly within traditional Thai medicine (TTM). Tongue inspection is a primary method for diagnosing health conditions, as it reflects organ functionality. However, diagnostic results can vary depending on the expertise of TTM practitioners. In this work, we propose methods that incorporate transfer learning (TL) from deep learning (DL), machine learning (ML), and statistical models, using various tongue features. We introduced a collected dataset for evaluation. Experimental results demonstrated that the DenseNet121 model, trained on tongue images pre-processed with histogram equalisation (HE), achieved the best performance, with accuracy, sensitivity, and specificity of 0.89, 0.83, and 0.92, respectively. Model ensembling and paired t-tests were used to analyse the results. Finally, we identified the best approach and models for potential clinical use to assist in the pre-diagnostic analysis of tongue images for TTM practitioners and general users via our web application at http:// bioservices.sci.psu.ac.th/
Unveiling the Clinical Significance of Microsatellite Instability in Colorectal Cancer: Deep Learning and the Segment Anything Model for Accurate Segmentation and Classification
Get PDFMicrosatellite instability (MSI) is crucial for colorectal cancer (CRC) diagnosis and prognosis. Accurate differentiation between MSI and microsatellite stability (MSS) tumors is essential for personalized treatment. This paper introduces a novel approach combining the segment anything model (SAM), Yolov8, and convolutional neural networks (CNNs) for precise segmentation and classification of histopathological images. SAM employs a prompt-based mechanism for segmenting tumor regions like invasive margins, tumor-infiltrating lymphocytes (TILs), and necrotic areas. Integrating SAM’s segmentation with CNN-based classification achieves high-accuracy MSI-H/MSS subtyping by focusing on key histopathological features. Tested on TCGA-CRC data, this approach outperformed traditional methods in segmentation and classification accuracy, enhancing MSI/MSS diagnostic potential and enabling efficient high-throughput analysis in clinical and research settings
Use of Massive Open Online Courses (MOOC) by Teachers of Ukrainian Universities: Survey Results
Get PDFThe research analyzes the results of a survey of university teachers on the use of massive open online courses (MOOC) in the educational process and for personal self-development. 2,824 respondents from 155 universities located throughout Ukraine took part in the survey. The authors’ questionnaire was created with Google Forms. The analysis of responses has revealed that 88.8% of respondents use MOOC. The most famous Ukrainian online platform among teachers is Prometheus (54.7% of respondents). The most famous foreign platform is Coursera (31.2% of teachers). In addition to quantitative analysis of simple responses, we used a hierarchical clustering method to analyze extended responses, and we made a list of 82 standardized responses (SR). It was found that the use of MOOC had increased the amount of teachers’ knowledge and their practical experience. The most important advantages of using MOOC in the educational process are additional learning material, experience in non-formal education, etc. As for weaknesses, these are low-quality connection, low quality of some online courses, lack of motivation among teachers. The obtained results expanded the list of advantages and disadvantages of MOOC, and the formed list of SR can become the basis for further research where we plan to study the ways of increasing teacher motivation to use MOOC in the educational process