Search results for: learning text

Authors: Yen-Hui Lu

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In the past two decades, in order to increase university visibility and internationalization, English as a medium of instruction (EMI) has become one of the main language policies in higher education institutions where English is not a dominant language. However, given the complex, discipline-embedded nature of academic communication, academic literacy does not come with students’ everyday language experience, and it is a challenge for all students. Particularly, to engage students in the effective learning process of discipline concepts in the EMI classrooms, teachers need to provide explicit academic language instruction to assist students in deep understanding of discipline concepts. To bridge the gap between academic language development and discipline learning in the EMI classrooms, the researcher incorporates academic language strategies and key elements of project-based learning (PBL) into an Academic Language Strategy driven PBL (ALS-PBL) model. With clear steps and strategies, the model helps EMI teachers to scaffold students’ academic language development in the EMI classrooms. ALS-PBL model includes three major stages: preparation, implementation, and assessment. First, in the preparation stage, ALS-PBL teachers need to identify learning goals for both content and language learning and to design PBL topics for investigation. Second, during the implementation stage, ALS-PBL teachers use the model as a guideline to create a lesson structure and class routine. There are five important elements in the implementation stage: (1) academic language preparation, (2) connecting background knowledge, (3) comprehensible input, (4) academic language reinforcement, and (5) sustained inquiry and project presentation. Finally, ALS-PBL teachers use formative assessments such as student learning logs, teachers’ feedback, and peer evaluation to collect detailed information that demonstrates students’ academic language development in the learning process. In this study, ALS-PBL model was implemented in an interdisciplinary course entitled “Science is Everywhere”, which was co-taught by five professors from different discipline backgrounds, English education, civil engineering, business administration, international business, and chemical engineering. The purpose of the course was to cultivate students’ interdisciplinary knowledge as well as English competency in disciplinary areas. This study used a case-study design to systematically investigate students’ learning experiences in the class using ALS-PBL model. The participants of the study were 22 college students with different majors. This course was one of the elective EMI courses in this focal university. The students enrolled in this EMI course to fulfill the school language policy, which requires the students to complete two EMI courses before their graduation. For the credibility, this study used multiple methods to collect data, including classroom observation, teachers’ feedback, peer assessment, student learning log, and student focus-group interviews. Research findings show four major successful aspects of implementing ALS-PBL model in the EMI classroom: (1) clear focus on both content and language learning, (2) meaningful practice in authentic communication, (3) reflective learning in academic language strategies, and (4) collaborative support in content knowledge.This study will be of value to teachers involved in delivering English as well as content lessons to language learners by providing a theoretically-sound practical model for application in the classroom.

Keywords: academic language development, content and language integrated learning, english as a medium of instruction, project-based learning

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Authors: Jiaqi Huang, Yuheng Wang

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Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

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Authors: M. A. Mabasa, O. Ramokolo, M. Z. Mnikathi, D. Mathabatha, T. Manyapelo

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The study examines the importance of translating South African folklore from Oral into Written Literature in a Multilingual Education. Therefore, the study postulates that translation can be regarded as a valuable tool when oral and written literature is transmitted from one generation to another. The study entails that translation does not take place in a haphazard fashion; for that reason, skills such as translation principles are required to translate folklore significantly and effectively. The purpose of the study is to indicate the significance of using translation relating to folklore in teaching and learning. The study also observed that Modernism in literature should be shared amongst varieties of cultures because folklore is interactive in narrating stories, folktales and myths to sharpen the reader’s knowledge and intellect because they are informative and educative in nature. As a technological tool, the study points out that translation is of paramount importance in the sense that the meanings of different data can be made available in all South African official languages using oral and written forms of folklore. The study opines that tradition and customary beliefs and practices in the institution of higher learning. The study envisages the way in which literature of folklore can be juxtaposed to ensure that translated folklore is of quality assured standards. The study alludes that well-translated folklore can serve as oral and written literature, which may contribute to the child’s learning and acquisition of knowledge and insights during cognitive development toward maturity. Methodologically, the study selects a qualitative research approach and selects content analysis as an instrument for data gathering, which will be analyzed qualitatively in consideration of the significance of translating folklore as written and spoken literature in a documented way. The study reveals that the translation of folktales promotes functional multilingualism in high-function formal contexts like a university. The study emphasizes that translated and preserved literary folklore may serve as a language repository from one generation to another because of the archival and storage of information in the form of a term bank.

Keywords: translation, editing, teaching, learning, folklores

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Authors: Ryoo Hye Jin Agnes

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This study aims to investigate the efficacy of clickers in fostering L2 class interaction. In an L2 classroom, active learner-to-learner interactions and learner-to-teacher interactions play an important role in language acquisition. In light of this, introducing learning tools that promote such interactions would benefit L2 classroom by fostering interaction. This is because the anonymity of clickers allows learners to express their needs without the social risks associated with speaking up in the class. clickers therefore efficiently help learners express their level of understanding during the process of learning itself. This allows for an evaluative feedback loop where both learners and teachers understand the level of progress of the learners, better enabling classrooms to adapt to the learners’ needs. Eventually this tool promotes participation from learners. This, in turn, is believed to be effective in fostering classroom interaction, allowing learning to take place in a more comfortable yet vibrant way. This study is finalized by presenting the result of an experiment conducted to verify the effectiveness of this approach when teaching pragmatic aspect of Korean expressions with similar semantic functions. The learning achievement of learners in the experimental group was found higher than the learners’ in a control group. A survey was distributed to the learners, questioning them regarding the efficacy of clickers, and how it contributed to their learning in areas such as motivation, self-assessment, increasing participation, as well as giving feedback to teachers. Analyzing the data collected from the questionnaire given to the learners, the study presented data suggesting that this approach increased the scope of interactivity in the classroom, thus not only increasing participation but enhancing the type of classroom participation among learners. This participation in turn led to a marked improvement in their communicative abilities.

Keywords: second language acquisition, interaction, clickers, learner response system, output from learners, learner’s cognitive process

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Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

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Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

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Authors: Shweta Singh, Sudaman Katti

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The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.

Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity

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Authors: Shiao-Wei Chu

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In order to enhance the ability of their graduates to compete in an increasingly globalized economy, the majority of universities in Taiwan require students to pass Freshman English in order to earn a bachelor's degree. However, many college students show low motivation in English class for several important reasons, including exam-oriented lessons, unengaging classroom activities, a lack of opportunities to use English in authentic contexts, and low levels of confidence in using English. Students’ lack of motivation in English classes is evidenced when students doze off, work on assignments from other classes, or use their phones to chat with others, play video games or watch online shows. Cooperative learning aims to address these problems by encouraging language learners to use the target language to share individual experiences, cooperatively complete tasks, and to build a supportive classroom learning community whereby students take responsibility for one another’s learning. This study includes approximately 50 student participants in a low-proficiency Freshman English class. Each week, participants will work together in groups of between 3 and 4 students to complete various in-class interactive tasks. The instructor will employ a reward system that incentivizes students to be responsible for their own as well as their group mates’ learning. The rewards will be based on points that team members earn through formal assessment scores as well as assessment of their participation in weekly in-class discussions. The instructor will record each team’s week-by-week improvement. Once a team meets or exceeds its own earlier performance, the team’s members will each receive a reward from the instructor. This cooperative learning approach aims to stimulate EFL freshmen’s learning motivation by creating a supportive, low-pressure learning environment that is meant to build learners’ self-confidence. Students will practice all four language skills; however, the present study focuses primarily on the learners’ reading comprehension. Data sources include in-class discussion notes, instructor field notes, one-on-one interviews, students’ midterm and final written reflections, and reading scores. Triangulation is used to determine themes and concerns, and an instructor-colleague analyzes the qualitative data to build interrater reliability. Findings are presented through the researcher’s detailed description. The instructor-researcher has developed this approach in the classroom over several terms, and its apparent success at motivating students inspires this research. The aims of this study are twofold: first, to examine the possible benefits of this cooperative approach in terms of students’ learning outcomes; and second, to help other educators to adapt a more cooperative approach to their classrooms.

Keywords: freshman English, cooperative language learning, EFL learners, learning motivation, zone of proximal development

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Authors: Judith Hanke

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Due to the increase of students with reading difficulties, digital reading support with diagnostics was developed to foster the individual student's reading comprehension. The digital reading support focused on the reading comprehension of elementary school students. The digital reading packages consist of literary texts with aligned reading exercises. The number of students with German as a second language is growing in Germany. Students with multilingualism, language 1, and language 2 learn German together in school. The research's focus is on determining whether and to what extent multilingualism, language 1, and language 2 affect reading comprehension. For the methodology, an ABA design was selected for the intervention study to examine the reading support. The study was expedited from April 2023 until July 2023 and collected quantitative data of individuals, groups, and classes. It comprised a survey group (N = 58) and a control group (N = 53). The quantitative data was collected from 3 classes of 3 teachers and 47 students for all three test times. To show differences between the groups, a standardized reading comprehension test was used for the three test times, pretest, posttest, and follow-up. The standardized test consists of three subtests regarding word comprehension, sentence comprehension, and text comprehension. The main findings include that students who spoke German as their first language had the best test scores. Interestingly, students with a different language had better testing scores than students with German as the first language and (an) other language/s. Also, the students with another language outperformed the native language speakers in one of the subtests of the post-testing. The variables of spoken language at home and German as a second language were also examined and correlated with the test results. One significant correlation was found between spoken language at home and the text comprehension test of the pretesting. Additionally, the variable German as a second language had multiple significant correlations in the pretest, posttest and follow-up. The study's significance is to understand the influence of several languages, language 1, and language 2, on reading comprehension.

Keywords: multilingualism, language 1, language 2, reading comprehension, second language

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Authors: Binay Pattanayak

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More than 9 out of every 10 children in Jharkhand struggle to understand the texts and teachers in public schools. The medium of learning in the schools is Hindi, which is very different in structure and vocabulary than those in children’s home languages. Hence around 3 out of 10 children enrolled in early grades drop out in these schools. The state realized the cause of children’s high dropout in 2013-14 when the M-TALL, the language research shared the findings of a state-wide socio-linguistic study. The study findings suggested that there was a great need for initiating a mother-tongue based multilingual education (MTB-MLE) programme for the state in early grades starting from pre-school level. Accordingly, M-TALL in partnership with department of education designed two learning packages: Bhasha Puliya pre-school education programme for 3-6-year-old children for their school readiness with bilingual picture dictionaries in 9 tribal and regional languages. This was followed by a plan for MTB-MLE programme for early primary grades. For this textbooks in five tribal and two regional languages were developed under the guidance of the author. These books were printed and circulated in the 1000 schools of the state for each child. Teachers and community members were trained for facilitating culturally sensitive mother-tongue based learning activities in and around the schools. The mother-tongue based approach of learning has worked very effectively in enabling them to acquire the basic literacy and numeracy skills in own mother-tongues. Using this basic early grade reading skills, these children are able to learn Hindi and English systematically. Community resource groups were constituted in each school for promoting storytelling, singing, painting, dancing, acting, riddles, humor, sanitation, health, nutrition, protection, etc. and were trained. School academic calendar was designed in each school to enable the community resource persons to visit the school as per the learning plan to assist children and teacher in facilitating rich cultural activities in mother-tongue. This enables children to take part in plethora of learning activities and acquire desired knowledge, skills and interest in mother-tongues. Also in this process, it is attempted to promote 21st Century learning skills by enabling children to apply their new knowledge and skills to look at their local issues and address those in a collective manner through team work, innovations and leadership.

Keywords: community resource groups, learning, MTB-MLE, multilingual, socio-linguistic survey

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Evmorfia Koukia, Polyxeni Mangoulia

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Workshops tend to be a vivid and productive way as an in vivo teaching method. Due to the pandemic, COVID-19 university courses were conducted through the internet. Method It was tried for the first time to integrate online art therapy workshops in a core course named “Special Themes of Mental Health Nursing” in a MSc Program in Mental Health. The duration of the course is 3-hours per week for 11 weeks in a single semester. The course has a main instructor, a professor of psychiatric nursing experienced in arts therapies workshops and visiting art therapists. All art therapists were given a certain topic to cover. Students were encouraged to keep a logbook that was evaluated at the end of the semester and was submitted as a part of the examination process of the course. An interview of 10 minutes was conducted with each student at the end of the course from an independent investigator (an assistant professor) Participants The students (sample) of the program were: nurses, psychologists, and social workers Results: All students who participated in the courses found that the learning process was vivid, encouraging participation and self-motivation, and there were no main differences from in vivo learning. The students identified their personal needs, and they felt a personal connection with the learning experience. The result of the personalized learning was that students discovered their strengths and weaknesses and developed skills like critical thinking. All students admitted that the workshops were the optimal way for them to comprehend the courses’ content, their capability to become therapists, as well as their obstacles and weaknesses while working with patients in mental health. Conclusion: There were no important differences between the views of students in online and in vivo teaching method of the workshops. The result has shown that workshops in mental health can contribute equally in the learning experience.

Keywords: mental health, workshops, students, nursing

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Authors: Yidan Shao

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With the advancement of the economy, technology promotes online teaching, and learning has become one of the common features in the educational field. Meanwhile, the dramatic expansion of the online environment provides opportunities for more learners, including second language learners. A greater command of vocabulary improves students’ learning capacity, and word acquisition and development play a critical role in learning. Furthermore, the Word Wall is an effective tool to improve students’ knowledge of words, which works for a wide range of age groups. Therefore, this study is going to use the Word Wall as an intervention to examine whether it can bring some memorization changes in an online English language class for a second language learner based on the word morphology method. The participant will take ten courses in the experiment as it plans. The findings show that the Word Wall activity plays a slight role in improving word memorizing, but it does affect instant memorization. If longer periods and more comprehensive designs of research can be applied, it is expected to have more value.

Keywords: second language acquisition, word morphology, word memorization, the Word Wall

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Authors: Lan Cheng, Harry Qin, Yang Wang

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Background: COVID-19 has induced the largest digital learning experiment in history. There is also emerging research evidence that students have paid a high cost of learning loss from virtual learning. University-wide survey results demonstrate that digital learning remains difficult for students who struggle with learning challenges, isolation, or a lack of resources. Large-scale efforts are therefore increasingly utilized for digital education. To better prepare students in higher education for this grand scientific and technological transformation, STEM education has been prioritized and promoted as a strategic imperative in the ongoing curriculum reform essential for unfinished learning needs and whole-person development. Building upon five key elements identified in the STEM education literature: Problem-based Learning, Community and Belonging, Technology Skills, Personalization of Learning, Connection to the External Community, this case study explores the potential of pedagogical innovation that integrates computational and experimental methodologies to support, enrich, and navigate STEM education. Objectives: The goal of this case study is to create a high-fidelity prototype design for STEM education with knowledge transfer technology that contains a Cooperative Multi-Agent System (CMAS), which has the objectives of (1) conduct assessment to reveal a virtual learning mechanism and establish strategies to facilitate scientific learning engagement, accessibility, and connection within and beyond university setting, (2) explore and validate an interactional co-creation approach embedded in project-based learning activities under the STEM learning context, which is being transformed by both digital technology and student behavior change,(3) formulate and implement the STEM-oriented campaign to guide learning network mapping, mitigate the loss of learning, enhance the learning experience, scale-up inclusive participation. Methods: This study applied a case study strategy and a methodology informed by Social Network Analysis Theory within a cross-disciplinary communication paradigm (students, peers, educators). Knowledge transfer technology is introduced to address learning challenges and to increase the efficiency of Reinforcement Learning (RL) algorithms. A co-creation learning framework was identified and investigated in a context-specific way with a learning analytic tool designed in this study. Findings: The result shows that (1) CMAS-empowered learning support reduced students’ confusion, difficulties, and gaps during problem-solving scenarios while increasing learner capacity empowerment, (2) The co-creation learning phenomenon have examined through the lens of the campaign and reveals that an interactive virtual learning environment fosters students to navigate scientific challenge independently and collaboratively, (3) The deliverables brought from the STEM educational campaign provide a methodological framework both within the context of the curriculum design and external community engagement application. Conclusion: This study brings a holistic and coherent pedagogy to cultivates students’ interest in STEM and develop them a knowledge base to integrate and apply knowledge across different STEM disciplines. Through the co-designing and cross-disciplinary educational content and campaign promotion, findings suggest factors to empower evidence-based learning practice while also piloting and tracking the impact of the scholastic value of co-creation under the dynamic learning environment. The data nested under the knowledge transfer technology situates learners’ scientific journey and could pave the way for theoretical advancement and broader scientific enervators within larger datasets, projects, and communities.

Keywords: co-creation, cross-disciplinary, knowledge transfer, STEM education, social network analysis

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Authors: Justin P. Pool, Haruyo Yoshida

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This research focuses on the effects of creating an English as a foreign language curriculum that combines online learning and classroom teaching in a complementary manner. Through pre- and post-test results, teacher observation, and learner reflection, it will be shown that learners can benefit from online programs focusing on receptive skills if combined with a communicative classroom environment that encourages learners to develop their productive skills. Much research has lamented the fact that many modern mobile assisted language learning apps do not take advantage of the affordances of modern technology by focusing only on receptive skills rather than inviting learners to interact with one another and develop communities of practice. This research takes into account the realities of the state of such apps and focuses on how to best create a curriculum that complements apps which focus on receptive skills. The research involved 15 adult learners working for a business in Japan simultaneously engaging in 1) a commercial online English language learning application that focused on reading, listening, grammar, and vocabulary and 2) a 15-week class focused on communicative language teaching, presentation skills, and mitigation of error aversion tendencies. Participants of the study experienced large gains on a standardized test, increased motivation and willingness to communicate, and asserted that they felt more confident regarding English communication. Moreover, learners continued to study independently at higher rates after the study than they had before the onset of the program. This paper will include the details of the program, reveal the improvement in test scores, share learner reflections, and critically view current evaluation models for mobile assisted language learning applications.

Keywords: adult learners, communicative language teaching, mobile assisted language learning, motivation

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Authors: Maslin Masrom, Nik Hasnaa Nik Mahmood, Wan Normeza Wan Zakaria, Azizul Azizan, Norshaliza Kamaruddin

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Traditionally, in science education, the teacher provides facts and the students learn them. It is outmoded for today’s students to equip them with real-life situations, mainly because knowledge and life skills are acquired passively from the instructors. Inquiry-Based Science Education (IBSE) is an approach that allows students to experiment, ask questions, and develop responses based on reasoning. It has provided students and teachers with opportunities to actively engage in collaborative learning via inquiry. This approach inspires the students to become active thinkers, research for solutions, and gain life-long experience and self-confidence. Therefore, the research aims to investigate how the primary-school teacher supports students or pupils through an inquiry-based science education approach for computer science, specifically coding skills. The results are presented and described.

Keywords: inquiry-based science education, student-centered learning, computer science, primary school

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Authors: Lin Xie, Yang Wang

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An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning 2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: communication, education, language learning, goal achievement, academic success

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Authors: Frazer McDonald Ng'oma

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Online Learning in Malawi has only immersed in recent years due to the need to increase access to higher education, the need to accommodate upgrading students who wish to study on a part time basis while still continuing their work, and the COVID-19 pandemic, which forced the closure of schools resulting in academic institutions seeking alternative modes of teaching and Learning to ensure continued teaching and Learning. Realizing that this mode of Learning is becoming a norm, institutions of higher Learning have started pioneering online post-graduate programs from which they can draw lessons before fully implementing it in undergraduate programs. Online learning pedagogy has not been fully grasped and institutions are still experimenting with this mode of Learning until online Learning guiding policies are created and its standards improved. This single case descriptive qualitative research study sought to investigate online postgraduate students’ perceptions and experiences with Student to student interactive pedagogy in their programs. The results of the study are to inform institutions and educators how to structure their programs to ensure that their students get the full satisfaction. 25 Masters students in 3 recently introduced online programs at Kamuzu University of Health Sciences (KUHES), were engaged; 19 were interviewed and 6 responded to questionnaires. The findings from the students were presented and categorized in themes and subthemes that emerged from the qualitative data that was collected and analysed following Colaizzi’s framework for data analysis that resulted in themes formulation. Findings revealed that Student to student interactions occurred in the online programme during live sessions, on class Whatsapp group, in discussion boards as well as on emails. Majority of the students (n=18) felt the level of students’ interaction initiated by the institution was too much, referring to mandatory interactions activities like commenting in discussion boards and attending to live sessons. Some participants (n=7) were satisfied with the level of interaction and also pointed out that they would be fine with more program-initiated student–to–student interactions. These participants attributed having been out of school for some time as a reason for needing peer interactions citing that it is already difficult to get back to a traditional on-campus school after some time, let alone an online class where there is no physical interaction with other students. In general, majority of the participants (n=18) did not value Student to student interaction in online Learning. The students suggested that having intensive student-to-student interaction in postgraduate online studies does not need to be a high priority for the institution and they further recommended that if a lecturer decides to incorporate student-to-student activities into a class, they should be optional.

Keywords: online learning, interactions, student interactions, post graduate students

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Authors: Ulil Afidah, Muhamad Fathan Mubin, Firdha Aulia

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Code riverbanks Yogyakarta is a settlement area with middle to lower social classes. Socio-economic situation is affecting the behavior of society. This research aimed to find and explain the implementation and the assessment of character education which were done in elementary schools in Code riverside, Yogyakarta region of Indonesia. This research is a qualitative research which the subjects were the kids of Code riverbanks, Yogyakarta. The data were collected through interviews and document studies and analyzed qualitatively using the technique of interactive analysis model of Miles and Huberman. The results show that: (1) The learning process of character education was done by integrating all aspects such as democratic and interactive learning session also introducing role model to the students. 2) The assessment of character education was done by teacher based on teaching and learning process and an activity in outside the classroom that was the criterion on three aspects: Cognitive, affective and psychomotor.

Keywords: character, Code riverbanks, education, Yogyakarta

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Authors: Sagheer Ahmad

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Teaching is a sacred profession whereby students are developed in their mental abilities to cope with the challenges of the remote world. Thinkers have developed plenty of interesting ways to make the learning process quick and absorbing for the students. However, third world countries are still lacking these remote facilities in the institutions, and therefore, teaching is totally dependent upon the skills of the teachers. Skillful teachers use self-devised and stimulating ideas to grab the attention of their students. Most of the time their ideas are based on local grounds with which the students are already familiar. This self-explanatory characteristic is the base of several local ideologies to disseminate scientific knowledge to new generations. Biology is such a subject which largely bases upon hypotheses, and teaching it in an interesting way is needful to create a friendly relationship between teacher and student, and to make a fantastic learning environment. Taxonomic classification if presented as it is, may not be attractive for the secondary school students who just start learning about biology at elementary levels. Presenting this hierarchy by exemplifying Kingdom, Phylum, Class, Order, family, genus and Species as comparatives of our division into continents, countries, cities, towns, villages, homes and finally individuals could be an attention-grabbing approach to make this concept get into bones of students. Similarly, many other interesting approaches have also been adopted to teach students in a fascinating way so that learning science subjects may not be boring for them. Discussing these appealing ways of teaching students can be a valuable stimulus to refine teaching methodologies about science, thereby promoting the concept of friendly learning.

Keywords: biology, innovative approaches, taxonomic classification, teaching

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Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: Iqra Raza

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This paper attempts to conceptualize the (de)humanization of the Muslim subject in Karen J. Greenberg and Janet Hamlin’s transmedia Sketching Guantanamo through a close study of the aesthetics and semiotics of the text. The Muslim experience, the paper shall argue, is mediated through a (de)humanization confined and incarcerated within the chains of artistic representation. Hamlin’s reliance on the distortions offered by stereotypes is reminiscent of the late Victorian epistemology on criminality, as evidenced most starkly in the sketch of Khalid Sheikh Mohammad. The position of the white artist thus becomes suspect in the enterprise of neo-Victorian ethnography. The visual stories of movement from within Guantanamo become potent; the paper shall argue, especially in juxtaposition with the images of stillness that came out from the detention centers, which portrayed the enactment of violence on individual bodies with a deliberate erasure of faces. So, while art becomes a way for reclaiming subjectivity or humanizing these identifiable bodies, the medium predicates itself on their objectification. The paper shall explore various questions about what it means for the (criminal?) subjects to be rendered into art rather than being photographed. Does art entail a necessary departure from the assumed objectivity of the photographic images? What makes art the preferred medium for (de)humanization of the violated Muslim bodies? What happens when art is produced without a recognition of the ‘precariousness’ of the life being portrayed? Rendering the detainees into art becomes a slippery task complicated by Hamlin’s privileged position outside the glass walls of the court. The paper shall adjourn analysis at the many dichotomies that exist in the text viz. between the White men and the brown, the Muslims and the Christians, Occident and the Orient problematized by Hamlin’s politics, that of a ‘neutral outsider’ which quickly turns on its head and becomes complicity in her deliberate erasure of the violence that shaped and still shapes Guantanamo.

Keywords: Abu Ghraib, Derrida, Guantanamo, graphic journalism, Muslimness, orient, spectrality

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Authors: Sudhir Kumar Singh, Debashish Chakravarty

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Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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Authors: Ahmed Shuhaiber

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The explosion of the World Wide Web and the electronic trend of university teaching have transformed the learning style to become more learner-centred, Which has popularized the digital delivery of mediated lectures as an alternative or an adjunct to traditional lectures. Despite its potential and popularity, virtual lectures have not been adopted yet in Jordanian universities. This research aimed to fill this gap by studying the factors that influence student’s willingness to accept virtual lectures in one Jordanian University. A quantitative approach was followed by obtaining 216 survey responses and statistically applying the UTAUT model with some modifications. Results revealed that performance expectancy, effort expectancy, social influences and self-efficacy could significantly influence student’s attitudes towards virtual lectures. Additionally, facilitating conditions and attitudes towards virtual lectures were found with significant influence on student’s intention to take virtual lectures. Research implications and future work were specified afterwards.

Keywords: E-learning, student willingness, UTAUT, virtual Lectures, web-based learning systems

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Authors: Ilona Buchem, Carolin Gellner

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The call for the support of senior learners in the development of digital literacy has become prevalent in recent years, especially in view of the aging societies paired with advances in digitalization in all spheres of life, including e-health. The goal has been to create opportunities for learning that incorporate the use of context in a reflective and dialogical way. Contextual learning has focused on developing skills through the application of authentic problems. While major research efforts in supporting senior learners in developing digital literacy have been invested so far in e-learning, focusing on knowledge acquisition and cognitive tasks, little research exists in reflective mentoring and coaching with the help of pedagogical agents and addressing the contextual dimensions of learning. This paper describes an approach to creating opportunities for senior learners to improve their digital literacy in the authentic context of the electronic health record (EHR) with the support of an intelligent virtual learning coach. The paper focuses on the design of the virtual coach as part of an e-learning system, which was developed in the EPA-Coach project founded by the German Ministry of Education and Research. The paper starts with the theoretical underpinnings of contextual learning and the related design considerations for a virtual learning coach based on previous studies. Since previous research in the area was mostly designed to cater to the needs of younger audiences, the results had to be adapted to the specific needs of senior learners. Next, the paper outlines the stages in the design of the virtual coach, which included the adaptation of the design requirements, the iterative development of the prototypes, the results of the two evaluation studies and how these results were used to improve the design of the virtual coach. The paper then presents the four prototypes of a senior-friendly virtual learning coach, which were designed to represent different preferences related to the visual appearance, the communication and social interaction styles, and the pedagogical roles. The first evaluation of the virtual coach design was an exploratory, qualitative study, which was carried out in October 2020 with eight seniors aged 64 to 78 and included a range of questions about the preferences of senior learners related to the visual design, gender, age, communication and role. Based on the results of the first evaluation, the design was adapted to the preferences of the senior learners and the new versions of prototypes were created to represent two male and two female options of the virtual coach. The second evaluation followed a quantitative approach with an online questionnaire and was conducted in May 2021 with 41 seniors aged 66 to 93 years. Following three research questions, the survey asked about (1) the intention to use, (2) the perceived characteristics, and (3) the preferred communication/interaction style of the virtual coach, i. e. task-oriented, relationship-oriented, or a mix. This paper follows with the discussion of the results of the design process and ends with conclusions and next steps in the development of the virtual coach including recommendations for further research.

Keywords: virtual learning coach, virtual mentor, pedagogical agent, senior learners, digital literacy, electronic health records

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Authors: Tooba Sabir, Asima Jaffar, Namra Sabir, Mohammad Amjad Sabir

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Ecocriticism is the study of relationship between human and environment which has been represented in literature since the very beginning in pastoral tradition. However, the analysis of such representation is new as compared to the other critical evaluations like Psychoanalysis, Marxism, Post-colonialism, Modernism and many others. Ecocritics seek to find information like anthropocentrism, ecocentrism, ecofeminism, eco-Marxism, representation of environment and environmental concept and several other topics. In the current study the representation of environmental concepts, were ecocritically analyzed in Paulo Coelho’s The Alchemist, one of the most read novels throughout the world, having been translated into many languages. Analysis of the text revealed, the representations of environmental ideas like landscapes and tourism, biodiversity, land-sea displacement, environmental disasters and warfare, desert winds and sand dunes. 'This desert was once a sea' throws light on different theories of land-sea displacement, one being the plate-tectonic theory which proposes Earth’s lithosphere to be divided into different large and small plates, continuously moving toward, away from or parallel to each other, resulting in land-sea displacement. Another theory is the continental drift theory which holds onto the belief that one large landmass—Pangea, broke down into smaller pieces of land that moved relative to each other and formed continents of the present time. The cause of desertification may, however, be natural i.e. climate change or artificial i.e. by human activities. Imagery of the environmental concepts, at some instances in the novel, is detailed and at other instances, is not as striking, but still is capable of arousing readers’ imagination. The study suggests that ecocritical justifications of environmental concepts in the text will increase the interactions between literature and environment which should be encouraged in order to induce environmental awareness among the readers.

Keywords: biodiversity, ecocritical analysis, ecocriticism, environmental disasters, landscapes

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Authors: Felix Golla

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In an era where technology increasingly intersects with education, the potential of chatbots and ChatGPT agents in enhancing student learning experiences in higher education is both significant and timely. This study explores the integration of these AI-driven tools in educational settings, emphasizing their design and functionality to meet the specific needs of students. Recognizing the gap in literature concerning student-centered AI applications in education, this research offers valuable insights into the role and efficacy of chatbots and ChatGPT agents as educational tools. Employing qualitative research methodologies, the study involved conducting semi-structured interviews with university students. These interviews were designed to gather in-depth insights into the students' experiences and expectations regarding the use of AI in learning environments. The High-Performance Cycle Model, renowned for its focus on goal setting and motivation, served as the theoretical framework guiding the analysis. This model helped in systematically categorizing and interpreting the data, revealing the nuanced perceptions and preferences of students regarding AI tools in education. The major findings of the study indicate a strong preference among students for chatbots and ChatGPT agents that offer personalized interaction, adaptive learning support, and regular, constructive feedback. These features were deemed essential for enhancing student engagement, motivation, and overall learning outcomes. Furthermore, the study revealed that students perceive these AI tools not just as passive sources of information but as active facilitators in the learning process, capable of adapting to individual learning styles and needs. In conclusion, this study underscores the transformative potential of chatbots and ChatGPT agents in higher education. It highlights the need for these AI tools to be designed with a student-centered approach, ensuring their alignment with educational objectives and student preferences. The findings contribute to the evolving discourse on AI in education, suggesting a paradigm shift towards more interactive, responsive, and personalized learning experiences. This research not only informs educators and technologists about the desirable features of educational chatbots but also opens avenues for future studies to explore the long-term impact of AI integration in academic curricula.

Keywords: chatbot design in education, high-performance cycle model application, qualitative research in AI, student-centered learning technologies

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Authors: Adisorn Banhan, Toansakul Santiboon, Prasong Saihong

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Using the Socio-Scientific Issues-Based Learning Method is to compare of the blended instruction of STEM education with a sample consisted of 84 students in 2 classes at the 11th grade level in Sarakham Pittayakhom School. The 2-instructional models were managed of five instructional lesson plans in the context of electronic wave issue. These research procedures were designed of each instructional method through two groups, the 40-experimental student group was designed for the instructional STEM education (STEMe) and 40-controlling student group was administered with the Socio-Scientific Issues-Based Learning (SSIBL) methods. Associations between students’ learning achievements of each instructional method and their science attitudes of their predictions to their exploring activities toward physics with the STEMe and SSIBL methods were compared. The Measuring Reasonable Ethics Test (MRET) was assessed students’ reasonable ethics with the STEMe and SSIBL instructional design methods on two each group. Using the pretest and posttest technique to monitor and evaluate students’ performances of their reasonable ethics on electromagnetic wave issue in the STEMe and SSIBL instructional classes were examined. Students were observed and gained experience with the phenomena being studied with the Socio-Scientific Issues-Based Learning method Model. To support with the STEM that it was not just teaching about Science, Technology, Engineering, and Mathematics; it is a culture that needs to be cultivated to help create a problem solving, creative, critical thinking workforce for tomorrow in physics. Students’ attitudes were assessed with the Test Of Physics-Related Attitude (TOPRA) modified from the original Test Of Science-Related Attitude (TOSRA). Comparisons between students’ learning achievements of their different instructional methods on the STEMe and SSIBL were analyzed. Associations between students’ performances the STEMe and SSIBL instructional design methods of their reasonable ethics and their science attitudes toward physics were associated. These findings have found that the efficiency of the SSIBL and the STEMe innovations were based on criteria of the IOC value higher than evidence as 80/80 standard level. Statistically significant of students’ learning achievements to their later outcomes on the controlling and experimental groups with the SSIBL and STEMe were differentiated between students’ learning achievements at the .05 level. To compare between students’ reasonable ethics with the SSIBL and STEMe of students’ responses to their instructional activities in the STEMe is higher than the SSIBL instructional methods. Associations between students’ later learning achievements with the SSIBL and STEMe, the predictive efficiency values of the R2 indicate that 67% and 75% for the SSIBL, and indicate that 74% and 81% for the STEMe of the variances were attributable to their developing reasonable ethics and science attitudes toward physics, consequently.

Keywords: socio-scientific issues-based learning method, STEM education, science attitudes, measurement, reasonable ethics, physics classes

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Authors: Shazia Salam

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This paper focuses on studying the literary reactions of selected Muslim women writers to the event of Partition of India in the north western region. It aims to explore how Muslim women experienced the Partition and how that experience was articulated through their writing. There is a serious dearth of research on the experience of Muslim women who had to witness the momentous event of the subcontinent. Since scholars have often questioned the silence around the historiography related to the experiences of Muslim women, this paper aims to explore if literature could provide insights that may be less readily available in other modes of narration. Using literature as an archival source, it aims to delve into the arenas of history that have been cloistered and closed. Muslim women have been silent about their experiences of Partition which at the cost of essentializing could be attributed to patriarchal constraints, and taboos, on speaking of intimate matters. These silences have consigned the question of their experience to a realm of anonymity. The lack of ethnographic research has in a way been compensated in the realm of literature, mainly poetry and fiction. Besides reportage, literature remains an important source of social history about Partition and how Muslim women lived through it. Where traditional history fails to record moments of rupture and dislocation, literature serves the crucial purpose. The central premise in this paper is that there is a need to revise the history of partition owing to the gaps in historiography. It looks into if literature can serve as a ground for developing new approaches to history since the question of the representation always confronts us--between what a text represents and how it represents it since imagination of the writer plays a great role in the construction of any text. With this approach as an entry point, this paper aims to unpack the questions of representation, the coalescing of history /literature and the gendered nature of partition history. It concludes that the gaps in the narratives of Partition and the memory of Partition can be addressed by way of suing literary as a source to fill in the cracks and fissures.

Keywords: gender, history, literature, partition

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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