Search results for: embedded learning support

Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Ellen A. Kalinga

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Moodle is an open source learning management system that enables creation of a powerful and flexible learning environment. Many organizations, especially learning institutions have customized Moodle open source LMS for their own use. In general open source LMSs are of great interest due to many advantages they offer in terms of cost, usage and freedom to customize to fit a particular context. Tanzania Secondary School e-Learning (TanSSe-L) system is the learning management system for Tanzania secondary schools. TanSSe-L system was developed using a number of methods, one of them being customization of Moodle Open Source LMS. This paper presents few areas on the way Moodle OS LMS was customized to produce a functional TanSSe-L system fitted to the requirements and specifications of Tanzania secondary schools’ context.

Keywords: LMS, Moodle, e-learning, Tanzania, secondary school

Procedia PDF Downloads 375

Authors: J. Becker, R. Arnold

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The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structures. Combined with qualitative measures the decision support system will contribute to a more efficient design of distribution logistics.

Keywords: decision support system, distribution logistics, potential analyses, supply chain management

Procedia PDF Downloads 392

Authors: Sara Moridpour

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To meet emerging industry needs, engineering students must learn different software packages and enhance their computational skills. Traditionally, face-to-face is selected as the preferred approach to teaching software packages. Face-to-face tutorials and workshops provide an interactive environment for learning software packages where the students can communicate with the teacher and interact with other students, evaluate their skills, and receive feedback. However, COVID-19 significantly limited face-to-face learning and teaching activities at universities. Worldwide lockdowns and the shift to online and remote learning and teaching provided the opportunity to introduce different strategies to enhance the interaction among students and teachers in online and virtual environments and improve the learning and teaching of software packages in online and blended teaching methods. This paper introduces a blended strategy to teach engineering software packages to undergraduate students. This article evaluates the effectiveness of the proposed blended learning and teaching strategy in students’ learning by comparing the impact of face-to-face, online and the proposed blended environments on students’ software skills. The paper evaluates the students’ software skills and their software learning through an authentic assignment. According to the results, the proposed blended teaching strategy successfully improves the software learning experience among undergraduate engineering students.

Keywords: teaching software packages, undergraduate students, blended learning and teaching, authentic assessment

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Suriani Oxley

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All teachers aim to conduct a successful and an effective teaching. Teacher will use a variety of teaching techniques and methods to ensure that students achieve the learning objectives but often the teaching and learning processes are interrupted by a number of things such as noisy students, students not paying attention, the students play and so on. Such disturbances must be addressed to ensure that students can concentrate on their learning activities. This qualitative study observed and captured a video of numerous tricks that teachers in Labuan have implemented in helping the students to pay attentions in the classroom. The tricks are such as Name Calling, Non-Verbal Clues, Body Language, Ask Question, Offer Assistance, Echo Clapping, Call and Response & Cues and Clues. All of these tricks are simple but yet interesting language learning strategies that helped students to focus on their learning activities.

Keywords: paying attention, observation, tricks, learning strategies, classroom

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Authors: Nguyen Duc An

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To the movement towards learning community, creating friendly, positive and appropriate learning environments which best suit the local features is the most salient and decisive factor of the development and success of that learning society. With the aim at building such an English language learning community for the inhabitants in Moc Chau - the national tourist zone, Tay Bac University has successfully designed and deployed the program ‘English in Tourism’ in the project ‘English for Community’. With the strong attachment to the local reality and close knit to the certain communicative situations, this program which was carefully designed and compiled with interesting and practical activities, has greatly helped the locals confidently introduce and popularize the natural beauty, unique culture and specific characteristics of Moc Chau to the foreign tourists; in addition, reinforce awareness of the native culture of the local people as well as improve the professional development in tourism and service.

Keywords: English for community, learning society, learning community, English in tourism

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Authors: May Ling González-Ruiz, Ana Cristina Solís-Solís

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Everyday more people can thrive towards the dream of pursuing a university diploma. This can be more attainable for some than for others who may face different types of limitations. Even though not all limitations come from within the individual but most of the times they come from without it may include the environment, the support of the person’s family, the school – its infrastructure, administrative procedures, and attitudes. This is a qualitative type of research that is developed through a case study. It is based on the experiences of two students who are visually impaired and who have attended a public university in Costa Rica. We enquire about the experiences of these two students in the English as a Foreign Language courses at the university scenario. An in-depth analysis of their lived experiences is presented. Their values, attitudes, and expectations serve as the guiding elements for this research. Findings are presented in light of the Social Justice Approach to inclusive education. Some of the most salient aspects found have to do with the attitudes the students used to face challenges; others point at those elements that may have hindered the learning experience of the persons observed and to those that encouraged them to continue their journey and successfully achieve a diploma.

Keywords: inclusion, case study, visually impaired student, learning experience, social justice approach

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Authors: Ertekin Kotbas

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Teaching English as a Foreign Language (EFL) is on the front burner of many countries in the world, in particular for English Language Teaching departments that train EFL teachers. Under the head of motivational theories in foreign language education, there are numerous researches in literature. However; researches comprising English Language Self-Efficacy and Teachers’ Learning Goal Orientation which has a positive impact on learning teachings skills are scarce. Examination of these English Language self-efficacy beliefs and Learning Goal Orientations of Pre-Service EFL Teachers may broaden the horizons, in consideration the importance of self-efficacy and goal orientation on learning and teaching activities. At this juncture, the present study aims to investigate the relationship between English Language Self-Efficacy and Teachers’ Learning Goal Orientation from Turkish context.

Keywords: English language, learning goal orientation, self-efficacy, pre-service teachers

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Authors: Aroona Hashmi

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The prime motive for this endeavor was to explore the tenth grade English class students’ preferred learning styles studying in government secondary school so that English subject teachers could tailor their pedagogical strategies in relation to their students learning needs. The further aim of this study was to identify any significance difference among the students on a gender basis, area basis and different categories of school basis. The population of this study consisting of all the secondary level schools working in the government sector and positioned in the province of Punjab. The multi-stage cluster sampling method was employed while selecting the study sample from the population. The scale used for the identification of students’ learning styles in this study was developed by Grasha-Riechmann. The data collected through learning style scale was analyzed by employing descriptive statistics technique. The results from data analysis depict that learning styles of the majority of students found to be Collaborative and Competitive. Overall, no considerable difference was surfaced between male-female, urban-rural, general-other categories of 10th grade English class students learning styles.

Keywords: learning style, learning style scale, grade, government sector

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Authors: Sayed-Mahdi Hashemi-Dehkordi, Ian Baker

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This paper investigates the benefits of implementing distance learning in training courses for the oil and gas industries to reduce lean. Due to the remote locations of many oil and gas operations, scheduling and organizing in-person training classes for employees in these sectors is challenging. Furthermore, considering that employees often work in periodic shifts such as day, night, and resting periods, arranging in-class training courses requires significant time and transportation. To explore the effectiveness of distance learning compared to in-class learning, a set of questionnaires was administered to employees of a far on-shore refinery unit in Iran, where both in-class and distance classes were conducted. The survey results revealed that over 72% of the participants agreed that distance learning saved them a significant amount of time by rating it 4 to 5 points out of 5 on a Likert scale. Additionally, nearly 67% of the participants acknowledged that distance learning considerably reduced transportation requirements, while approximately 64% agreed that it helped in resolving scheduling issues. Introducing and encouraging the use of distance learning in the training environments of oil and gas industries can lead to notable time and transportation savings for employees, ultimately reducing lean in a positive manner.

Keywords: distance learning, in-class learning, lean, oil and gas, scheduling, time, training programs, transportation

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Authors: Scott Hollier, Ruchi Permvattana

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The purpose of this abstract is to share the findings of a recently completed disability-related Internet of Things (IoT) project undertaken at Curtin University in Australia. The project focused on identifying how IoT could support people with disabilities with their educational outcomes. To achieve this, the research consisted of an analysis of current literature and interviews conducted with students with vision, hearing, mobility and print disabilities. While the research acknowledged the ability to collect data with IoT is now a fairly common occurrence, its benefits and applicability still need to be grounded back into real-world applications. Furthermore, it is important to consider if there are sections of our society that may benefit from these developments and if those benefits are being fully realised in a rush by large companies to achieve IoT dominance for their particular product or digital ecosystem. In this context, it is important to consider a group which, to our knowledge, has had little specific mainstream focus in the IoT area –people with disabilities. For people with disabilities, the ability for every device to interact with us and with each other has the potential to yield significant benefits. In terms of engagement, the arrival of smart appliances is already offering benefits such as the ability for a person in a wheelchair to give verbal commands to an IoT-enabled washing machine if the buttons are out of reach, or for a blind person to receive a notification on a smartphone when dinner has finished cooking in an IoT-enabled microwave. With clear benefits of IoT being identified for people with disabilities, it is important to also identify what implications there are for education. With higher education being a critical pathway for many people with disabilities in finding employment, the question as to whether such technologies can support the educational outcomes of people with disabilities was what ultimately led to this research project. This research will discuss several significant findings that have emerged from the research in relation to how consumer-based IoT can be used in the classroom to support the learning needs of students with disabilities, how industrial-based IoT sensors and actuators can be used to monitor and improve the real-time learning outcomes for the delivery of lectures and student engagement, and a proposed method for students to gain more control over their learning environment. The findings shared in this presentation are likely to have significant implications for the use of IoT in the classroom through the implementation of affordable and accessible IoT solutions and will provide guidance as to how policies can be developed as the implications of both benefits and risks continue to be considered by educators.

Keywords: disability, higher education, internet of things, students

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Authors: Omer Agail

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The purpose of this study was to assess the social skills of students with and without learning disabilities in primary education in Saudi Arabia. A Social Skills Rating Scale for Teachers Form (SSRS-TF) was used to evaluate students' social skills as perceived by teachers. A randomly-selected sample was chosen from students with and without learning disabilities. Descriptive statistics were used to describe the demographic characteristics of participants. Analysis indicated that there were statistically significant differences in SSRS-TF by academic status, i.e. students with learning disabilities exhibit less social skills compared to students without learning disabilities. In addition, analysis indicated that there were no statistically significant differences in SSRS-TF by gender. A conclusion and recommendations are presented.

Keywords: primary education, students with learning disabilities, social skills, social competence

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Authors: Shohreh Ghasemi

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Introduction: Managing oral and maxillofacial trauma is a multifaceted challenge, as it can have life-threatening consequences and significant functional and aesthetic impact. Navigation techniques have been introduced to improve surgical precision to meet this challenge. A machine learning algorithm was also developed to support clinical decision-making regarding treating oral and maxillofacial trauma. Given these advances, this systematic meta-analysis aims to assess the efficacy of navigational techniques in treating oral and maxillofacial trauma and explore the impact of machine learning on their management. Methods: A detailed and comprehensive analysis of studies published between January 2010 and September 2021 was conducted through a systematic meta-analysis. This included performing a thorough search of Web of Science, Embase, and PubMed databases to identify studies evaluating the efficacy of navigational techniques and the impact of machine learning in managing oral and maxillofacial trauma. Studies that did not meet established entry criteria were excluded. In addition, the overall quality of studies included was evaluated using Cochrane risk of bias tool and the Newcastle-Ottawa scale. Results: Total of 12 studies, including 869 patients with oral and maxillofacial trauma, met the inclusion criteria. An analysis of studies revealed that navigation techniques effectively improve surgical accuracy and minimize the risk of complications. Additionally, machine learning algorithms have proven effective in predicting treatment outcomes and identifying patients at high risk for complications. Conclusion: The introduction of navigational technology has great potential to improve surgical precision in oral and maxillofacial trauma treatment. Furthermore, developing machine learning algorithms offers opportunities to improve clinical decision-making and patient outcomes. Still, further studies are necessary to corroborate these results and establish the optimal use of these technologies in managing oral and maxillofacial trauma

Keywords: trauma, machine learning, navigation, maxillofacial, management

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Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Amanda Watson

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The goal of this project is to create the conditions wherein every teacher, especially subjectarea experts, sees themselves as a teacher of language and vocabulary. Assessment and observational data suggest that students are not getting the support they need in vocabulary and reading comprehension, and secondary teachers do not currently have the confidence or expertise to provide this support. This study seeks to examine the impact of 10-20 minutes of daily, targeted instruction around orthography and vocabulary on student competence with the navigation of complex vocabulary and comprehension of subject-specific concepts and texts. The first phase of the pilot included 6 participating classroom teachers of grades 9 and 10 English (95 students in total) who administered an initial reading comprehension assessment. The results of this assessment indicated that the vast majority of students were reading below grade level. Teachers were then provided with a slide deck of complete lessons on orthography, vocabulary (etymology, roots and affixes) and reading comprehension strategies. For five weeks, teachers delivered lessons with their students, implementing the recommended evidence-based teaching strategies. Students and teachers completed surveys to provide feedback on the value and impact of the method. The results confirmed that this was new learning for the students and that the teaching strategies improved engagement. The lessons succeeded in providing equitable access to challenge by simultaneously offering theoretical learning to proficient readers, and exposure and practice to weaker readers. A second reading comprehension was administered after 5 weeks of daily instruction. Average scores increased by 41%, and almost every student experienced progress. The first phase was not long enough to measure the impact of the method on vocabulary acquisition or reading comprehension of subject-specific texts, however. The project will use the results of the first phase to design the second phase, and new teaching and learning strategies will be added. The goals of the second phases are to increase motivation, and to grow the daily practice beyond English class and into science and / or math. This team will continue to document a continuation of the daily lessons, Commented [E1]: Please do not use rhetorical questions in the abstract. measure the impact of the strategies, and address questions about the correlation between daily practice and improvements in the skills students need for vocabulary acquisition and disciplinary reading comprehension.

Keywords: adolescent, comprehension, orthography, reading, vocabulary, etymology, word study, disciplinary, teaching strategies

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Authors: Gavin J. Baxter, Mark H. Stansfield

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This paper reviews the internal use of blogs and their potential effectiveness as organisational learning tools. Prior to and since the emergence of the concept of ‘Enterprise 2.0’ there still remains a lack of empirical evidence associated with how organisations are applying social media tools and whether they are effective towards supporting organisational learning. Surprisingly, blogs, one of the more traditional social media tools, still remains under-researched in the context of ‘Enterprise 2.0’ and organisational learning. The aim of this paper is to identify the theoretical linkage between blogs and organisational learning in addition to reviewing prior research on organisational blogging with a view towards exploring why this area remains under-researched and identifying what needs to be done to try and move the area forward. Through a review of the literature, one of the principal findings of this paper is that organisational blogs, dependent on their use, do have a mutual compatibility with the interpretivist aspect of organisational learning. This paper further advocates that further empirical work in this subject area is required to substantiate this theoretical assumption.

Keywords: Enterprise 2.0, blogs, organisational learning, social media tools

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Authors: Hatib Shabbir

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Student support services play an important role in providing technical and motivational support to distance learner. ICT based systems have improved the efficiency and effectiveness of support services. In distance education, students being at distant require quick responses from their institution. In the manual system, it is practically hard to give prompt response to each and every student, so as a result student has to suffer a lot. The best way to minimize inefficiencies is to use automated systems. This project involves the development of centralized automated software that would not only replace the manual degree issuance system of 1.3 million students studying at AIOU but also provide online tracking to all the students applying for Degrees. DTS is also the first step towards the paperless culture which is adopted by the major organizations of the world. DTS would not only save university cost but also save students cost and time too by conveying all the information/objection through email and SMS. Moreover, DTS also monitors the performance of each and every individual working in the exam department AIOU and generates daily, monthly and yearly reports of every individual which helps a lot in continuous performance monitoring of the employees.

Keywords: aiou dts, dts aiou, dts, degree tracking aiou

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Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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Authors: Soressa Tolcha Jarra

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Looking into firm-level internationalization strategies and their effects on firms' productivity is needed in order to understand the role of firms’ participation in trading activities on the one hand and the effects of firms’ internalization strategies on firm-level productivity on the other. Thus, this study aims to investigate firms' imports of intermediates and export strategies and their impact on firm productivity using an establishment-level panel dataset from Ethiopian manufacturing firms over the period 2011–2020. Methodologically, the joint firm’s decision to import intermediates and estimate exports is undertaken by system GMM using Wooldridge's approach. The translog-production function is used to estimate firm-level productivity by considering a general Markov process. The size of the firm is used in a mediating role. The result indicates evidence of the self-selection of more productive firms into exporting and importing intermediates, which is indicative of sizable export and import market entry costs. Furthermore, there is evidence in favor of learning by exporting (LBE) and learning by importing (LBI) hypotheses for smaller and medium Ethiopian manufacturing firms. However, for large firms, there is only evidence in support of the learning by exporting (LBE) hypothesis.

Keywords: Ethiopia, export, firm productivity, intermediate imports

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Naoki Okamura

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From a perspective of moral education, this study has examined the experiences of a group of college students who volunteered in disaster areas after the magnitude 9.0 Earthquake, which struck the Northeastern region of Japan in March, 2011. The research, utilizing the method of grounded theory, has uncovered that most of the students have gone through positive changes in their development of moral and social characters, such as attaining deeper sense of empathy and caring personalities. The study expresses, in identifying the nature of those transformations, that the importance of volunteer work should strongly be recognized by the colleges and universities in Japan, in fulfilling their public responsibility of creating and building learning communities that are responsible and caring.

Keywords: moral development, moral education, service learning, volunteer learning

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Authors: Naritphol Boonyakiat

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This research attempts to investigate the effects of corporate social responsibility and knowledge management factors on students’ learning process of the Silpakorn University. The goal of this study is to fill the literature gap by gaining an understanding of corporate social responsibility and the knowledge management factors that fundamentally relate to students’ learning process within the university context. Thus, this study will focus on the outcomes that derive from a set of quantitative data that were obtained using Silpakorn university’s database of 200 students. The results represent the perceptions of students regarding the impact of corporate social responsibility and knowledge management factors on their learning process within the university. The findings indicate that corporate social responsibility and knowledge management have significant effects on students’ learning process. This study may assist us in gaining a better understanding of the integrated aspects of university and learning environments to discover how to allocate optimally university’s resources and management approaches to gain benefits from corporate social responsibility and knowledge management practices toward students’ learning process within the university bodies. Therefore, there is a sufficient reason to believe that the findings can contribute to research in the area of CSR, KM and students’ learning process as an essential aspect of university’s stakeholder.

Keywords: corporate social responsibility, knowledge management, learning process, university’s students

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Authors: Bi̇rsen Tutunis, Zuhal Aydin

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Guided digital learning has attracted many researchers as it leads to autonomous learning.The developments in Guided digital learning have led to changes in teaching and learning in English Language Teaching classes (Jeong-Bae, 2014). This study reports on tasks designed under the principles of learner autonomy in an online learning platform ‘’Webquest’’ with the purpose of teaching English to Turkish tertiary level students at a foundation university in Istanbul. Guided digital learning blog project contents were organized according to work-cycles phases (planning and negotiation phase, decision-making phase, project phase and evaluation phase) which are compatible with the principles of autonomous learning (Legenhausen,2003). The aim of the study was to implement the class blog project to find out its impact on students’ behaviours and beliefs towards autonomous learning. The mixed method research approach was taken. 24 tertiary level students participated in the study on voluntary basis. Data analysis was performed with Statistical Package for the Social Sciences. According to the results, students' attitudes towards digital learning did not differ before and after the training application. The learning styles of the students and their knowledge on digital learning scores differed. It has been observed that the students' learning styles and their digital learning scores increased after the training application. Autonomous beliefs, autonomous behaviors, group cohesion and group norms differed before and after the training application. Students' motivation level, strategies for learning English, perceptions of responsibility and out-of-class activity scores differed before and after the training application. It was seen that work-cycles in online classes create student centered learning that fosters autonomy. This paper will display the work cycles in detail and the researchers will give examples of in and beyond class activities and blog projects.

Keywords: guided digital learning, work cycles, english language teaching, autonomous learning

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Authors: Elsayed M. A. Elbashbeshy, T. G. Emam, M. S. El-Azab, K. M. Abdelgaber

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The effect of thermal radiation on flow, heat and mass transfer of an incompressible viscous nanofluid over a stretching horizontal cylinder embedded in a porous medium with suction/injection is discussed numerically. The governing boundary layer equations are reduced to a system of ordinary differential equations. Mathematica has been used to solve such system after obtaining the missed initial conditions. Comparison of obtained numerical results is made with previously published results in some special cases, and found to be in a good agreement.

Keywords: laminar flow, boundary layer, stretching horizontal cylinder, thermal radiation, suction/injection, nanofluid

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Authors: Somtop Keawchuer

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This research aims to study (1) the relationship between competency-based learning and learning efficiency of new media communication students at Suan Sunandha University (2) the demographic factor effect on learning efficiency of students at Suan Sunandha University. This research method will use quantitative research; data was collected by questionnaires distributed to students from new media communication in management science faculty of Suan Sunandha Rajabhat University for 1340 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including T-test, ANOVA and Pearson correlation for hypothesis testing. The results showed that the competency-based learning in term of ability to communicate, ability to think and solve the problem, life skills and ability to use technology has a significant relationship with learning efficiency in term of the cognitive domain, psychomotor domain and affective domain at the 0.05 level and which is in harmony with the research hypotheses.

Keywords: competency-based learning, learning efficiency, new media communication students, Suan Sunandha Rajabhat University

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Authors: Bahloul Amel

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This study is an attempt to raise the awareness of the stakeholders and the authorities on the sensitivity of Algerian secondary school teachers of English as a Foreign Language about the students’ loss of English language skills learned during formal schooling with effort and at expense and the supposed measures to arrest that loss. Data was collected from secondary school teachers of EFL and analyzed quantitatively using a questionnaire containing open-ended and close-ended questions. The results advocate a consensus about the need for actions to be adopted to make assessment techniques outcome-oriented. Most of the participants were in favor of including curricular activities involving contextualized learning, problem-solving learning critical self-awareness, self and peer-assisted learning, use of computers and internet so as to make learners autonomous.

Keywords: lifelong learning, EFL, contextualized learning, Algeria

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Chuanphit Chumkhong

Abstract:

This research aimed 1) to study the effects of the management of Active Learning among 3rd year students enrolled in teacher’s profession courses and 2) to assess the satisfaction of the students with courses using the Active Learning approach. The population for the study consisted of 442 3rd year undergraduate students enrolled in two teacher education courses in 2015: Curriculum Development and Learning Process Management. They were 442 from 11 education programs. Respondents for evaluation of satisfaction with Active Learning management comprised 432 students. The instruments used in research included a detailed course description and rating scale questionnaire on Active Learning. The data were analyzed using arithmetic mean and standard deviation. The results of the study reveal the following: 1. Overall, students gain a better understanding of the Active Learning due to their actual practice on the activity of course. Students have the opportunity to exchange learning knowledge and skills. The AL teaching activities make students interested in the contents and they seek to search for knowledge on their own. 2. Overall, 3rd year students are satisfied with the Active Learning management at a ‘high’ level with a mean score (μ) of 4.12 and standard deviation (σ) of. 51. By individual items, students are satisfied with the 10 elements in the two courses at a ‘high’ level with the mean score (μ) between 3.79 to 4.41 and a standard deviation (σ) between to 68. 79.

Keywords: active learning teaching model, teacher’s professional courses, professional courses, curriculum and instruction teacher's

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Authors: Ana Luiza Blanco, Juliana Cordeiro Carvalho, Tábatta Renata Pereira Brito, Ariene Angelini dos Santos Orlandi, Ligiana Pires Corona, Daniella Pires Nunes

Abstract:

Depressive symptoms are recurrent in older adults and affect the quality of life and well-being of individuals. One of the strategies to reduce depression is social support, but studies are still needed to determine which types of social support are most effective in moderating this effect in certain populations. The objective was to identify the relationship between social support and depressive symptoms in participants of a University of the Third Age. This is a cross-sectional study. Participants were 82 individuals (≥ 50 years) who responded to the Geriatric Depression Scale - GDS and the Medical Outcomes Study - MOS. Data collection was carried out from November 2020 to May 2021. The Chi-Square and Mann Whitney tests were used, at a significance level of 5% for data analysis. Among the participants, 83.4% were female, 57.3% were age between 60 to 69 years, 83.1% studied 12 year or more and 48.1% receive from 4 to 10 minimum wages. The prevalence of depressive symptoms was 12.2%. The type of support with the highest median score was affective (100 points) and the lowest, or emotional (87.5 points). The results showed that participants without depressive symptoms had higher median scores for informational support when compared to those with depressive symptoms (p=0.029). The other types of social support were not statistically significant. The findings suggested that informational support is related to depressive symptoms in older adults. Promote informational support and educational actions in Universities of the Third Age may be an important strategy for preventing depressive symptoms and improve the quality of life of this population.

Keywords: aged, depressive symptoms, social support, university of the third age

Procedia PDF Downloads 105