Search results for: learning assessment

Authors: Yihao Kuang, Bowen Ding

Abstract:

With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graph and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improve strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference, supervised learning

Procedia PDF Downloads 64

Authors: Majno Ajbani

Abstract:

Difficulties in teaching and learning English pronunciation in Sindh province, Pakistan Abstract Sindhi language is widely spoken in Sindh province, and it is one of the difficult languages of the world. Sindhi language has fifty-two alphabets which have caused a serious issue in learning and teaching of English pronunciation for teachers and students of Colleges and Universities. This study focuses on teachers’ and students’ need for extensive training in the pronunciation that articulates the real pronunciation of actual words. The study is set to contribute in the sociolinguistic studies of English learning communities in this region. Data from 200 English teachers and students was collected by already tested structured questionnaire. The data was analysed using SPSS 20 software. The data analysis clearly demonstrates the higher range of inappropriate pronunciations towards English learning and teaching. The anthropogenic responses indicate 87 percentages teachers and students had an improper pronunciation. This indicates the substantial negative effects on academic and sociolinguistic aspects. It is suggested an improper speaking of English, based on rapid changes in geopolitical and sociocultural surroundings.

Keywords: alphabets, pronunciation, sociolinguistic, anthropogenic, imprudent, malapropos

Procedia PDF Downloads 387

Authors: Beatriz Delgado

Abstract:

Although social anxiety is one of the most prevalent disorders in adolescents and causes considerable difficulties and social distress in those with the disorder, to date very few studies have explored the impact of social anxiety on academic adjustment in student populations. The aim of this study was analyze the effect of social anxiety on school functioning in Secondary Education. Specifically, we examined the relationship between social anxiety and self-concept, academic goals, causal attributions, intellectual aptitudes, and learning strategies, personality traits, and academic performance, with the purpose of creating a causal-explanatory model of academic performance. The sample consisted of 2,022 students in the seven to ten grades of Compulsory Secondary Education in Spain (M = 13.18; SD = 1.35; 51.1% boys). We found that: (a) social anxiety has a direct positive effect on internal attributional style, and a direct negative effect on self-concept. Social anxiety also has an indirect negative effect on internal causal attributions; (b) prior performance (first academic trimester) exerts a direct positive effect on intelligence, achievement goals, academic self-concept, and final academic performance (third academic trimester), and a direct negative effect on internal causal attributions. It also has an indirect positive effect on causal attributions (internal and external), learning goals, achievement goals, and study strategies; (c) intelligence has a direct positive effect on learning goals and academic performance (third academic trimester); (d) academic self-concept has a direct positive effect on internal and external attributional style. Also, has an indirect effect on learning goals, achievement goals, and learning strategies; (e) internal attributional style has a direct positive effect on learning strategies and learning goals. Has a positive but indirect effect on achievement goals and learning strategies; (f) external attributional style has a direct negative effect on learning strategies and learning goals and a direct positive effect on internal causal attributions; (g) learning goals have direct positive effect on learning strategies and achievement goals. The structural equation model fit the data well (CFI = .91; RMSEA = .04), explaining 93.8% of the variance in academic performance. Finally, we emphasize that the new causal-explanatory model proposed in the present study represents a significant contribution in that it includes social anxiety as an explanatory variable of cognitive-motivational constructs.

Keywords: academic performance, adolescence, cognitive-motivational variables, social anxiety

Procedia PDF Downloads 329

Authors: Muna Al-Siyabi

Abstract:

When students bring mobile devices into the classrooms, they are frequently viewed as distractions from their daily educational practices rather than developing the twenty-first century skills. Such skills may involve sorting and extracting information, solving problems and evaluating results. Mobile devices, such as smartphones and tablets, have great potential for learning. Currently, schools and universities are embracing these devices with the aim of enhancing education. In Oman, mobile technologies have been introduced in the last ten years in two private schools to keep pace with the technological advancement. The researcher set out to examine the benefits and challenges of employing mobile learning in these two schools with the aim to inform the implementation of mobile technologies in more schools in Oman. The total of 16 teachers and 237 students responded to questionnaires, and 7 teachers and three student focus groups (of 13 students) were involved in interviews to explore how mobile technologies are used in these two schools. The questionnaires indicated that 87.5% of the sample teachers considered mobile learning helpful for learning and teaching. The teachers believed that mobile learning could promote learning, help teaching, offer vast resources, motivate students and save lesson time. Moreover, interviews with the teachers showed that mobile learning could offer several benefits like immediacy, saving lesson time, supporting differentiation, opportunities to learn anywhere, showing understanding, and offering vast resources. Most of the sample were also facing technical and classroom management challenges when employing mobile technologies in their lessons. In the interviews, most teachers complained of the difficulty to control their classes when they had mobile devices, which distracted their attention and understanding. They reported that their students were distracted by games and they needed to be trained to use mobile technologies for educational purposes. Most teachers recommended that certain parameters or restrictions should be established in any mobile learning project that restrict the usage of mobile technologies to educational purposes. In addition, teachers also emphasised that students needed to be trained on the advantages and limitations of mobile technologies. Teachers were also recommending that pedagogical training for using mobile technologies should be considered when implementing mobile learning in schools. These findings reveal that although of the challenges of managing their classes, teachers believe that mobile learning has great potential for learning. These results imply that mobile learning can be effectively implemented in school in Oman if certain factors and restrictions are considered.

Keywords: effective implementation, challenges, mobile learning, opportunities

Procedia PDF Downloads 214

Authors: Kika Ioannou Kazamia

Abstract:

This paper examines the action research cycle of the second phase of longitudinal research on sustainable interior design practices, between two groups of stakeholders, designers and clients. During this phase of the action research, the second step - the change stage - of Lewin’s change management model has been utilized to change values, approaches, and attitudes toward sustainable design practices among the participants. Affective domain learning theory is utilized to attach new values. Learning with the use of information technology, collaborative learning, and problem-based learning are the learning methods implemented toward the acquisition of the objectives. Learning methods, and aims, require the design of interventions with participants' involvement in activities that would lead to the acknowledgment of the benefits of sustainable practices. Interventions are steered to measure participants’ decisions for the worth and relevance of ideas, and experiences; accept or commit to a particular stance or action. The data collection methods used in this action research are observers’ reports, participants' questionnaires, and interviews. The data analyses use both quantitative and qualitative methods. The main beneficial aspect of the quantitative method was to provide the means to separate many factors that obscured the main qualitative findings. The qualitative method allowed data to be categorized, to adapt the deductive approach, and then examine for commonalities that could reflect relevant categories or themes. The results from the data indicate that during the second phase, designers and clients' participants altered their behaviours.

Keywords: design, change, sustainability, learning, practices

Procedia PDF Downloads 74

Authors: Oluyomi A. Abioye

Abstract:

The 21st century has been witnessing a lot of technological advancements and innovations, and Information and Communication Technology (ICT) happens to be one of them. Education is the cornerstone of any nation and the language in which it is delivered is the bedrock of any development. The French language is our choice in this study. French is a language of reference on the national and international scenes; however its teaching is clouded with myriads of problems. The output of students’ academic performance depends on to a large extent on the teaching and learning the process. The methodology employed goes a long way in contributing to the effectiveness of the teaching and learning the process. Therefore, with the integration of ICT, French teaching has to align with and adapt to this new digital era. An attempt is made to define the concept of ICT. Some of the challenges encountered in the teaching of French language are highlighted. Then it discusses the existing methods of French teaching and the integration of ICT in the teaching and learning of the same language. Then some prospects and challenges of ICT in the teaching and learning of French are discussed. Data collected from questionnaires administered among some students of some selected schools are analysed. Our findings revealed that only very few schools in Nigeria have the electronic and computer-mediated facilities to teach the French language. The paper concludes by encouraging 'savoir-faire' of ICT by the French teachers, an openness of students to this digital technology and adequate provision of electronic and computer-mediated gadgets by the Nigerian government to its educational institutions.

Keywords: French language in Nigeria, integration of ICT, prospects and challenges, teaching and learning

Procedia PDF Downloads 342

Authors: Chalermwut Wijit

Abstract:

This research is conducted in order to 1) study the result of applying “Active Learning” in general education subject to develop creativity 2) explore problems and obstacles in applying Active Learning in general education subject to improve the creativity in 1780 undergraduate students who registered this subject in the first semester 2013. The research is implemented by allocating the students into several groups of 10 -15 students and assigning them to design the activities for society under the four main conditions including 1) require no financial resources 2) practical 3) can be attended by every student 4) must be accomplished within 2 weeks. The researcher evaluated the creativity prior and after the study. Ultimately, the problems and obstacles from creating activity are evaluated from the open-ended questions in the questionnaires. The study result states that overall average scores on students’ ability increased significantly in terms of creativity, analytical ability and the synthesis, the complexity of working plan and team working. It can be inferred from the outcome that active learning is one of the most efficient methods in developing creativity in general education.

Keywords: creative thinking, active learning, general education, social sustainability

Procedia PDF Downloads 182

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

Abstract:

In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

Procedia PDF Downloads 61

Authors: Sandhya Rao Mehta

Abstract:

As ChatGpt and other Artificial Intelligence (AI) forms are becoming part of our regular academic world, the consequences are being gradually discussed. The extent to which an essay written by a student is itself of any value if it has been downloaded by some form of AI is perhaps central to this discourse. A larger question is whether writing should be taught as an academic skill at all. In literature classrooms, this has major consequences as writing a traditional paper is still the single most preferred form of assessment. This study suggests that it is imperative to investigate alternative forms of assessment in literature, not only because the existing forms can be written by AI, but in a larger sense, students are increasingly skeptical of the purpose of such work. The extent to which an essay actually helps the students professionally is a question that academia has not yet answered. This paper suggests that using real-world tasks like creating podcasts, video tutorials, and websites is a far better way to evaluate students' critical thinking and application of ideas, as well as to develop digital skills which are important to their future careers. Using the example of a course in literature, this study will examine the possibilities and challenges of creating digital projects as a way of confronting the complexities of student evaluation in the future. The study is based on a specific university English as a Foreign Language (EFL) context.

Keywords: assessment, literature, digital humanities, chatgpt

Procedia PDF Downloads 81

Authors: A. Nagaletchimee Annamalai

Abstract:

The study investigated on how a small group of pre-service teachers and lecturers used social media to interact and collaborate to complete their tasks. The study is a qualitative case study that explored the lecturers’ reflections and pre-service teachers’ interviews. The lecturers were given the option to choose Facebook or any other social media as their teaching and learning platforms. However, certain guidelines based on were given to lecturers to conduct their teaching and learning activities. The findings revealed that although Facebook was a popular social networking site, it was not a preferred educational platform. Lecturers preferred to use WhatsApp, Canvas, and email. The focus group interview found positive and negative experiences of the pre-service teachers. The study suggested several pedagogical implications and importantly highlighted the need for changes in curriculum to ensure lecturers leverage the potential of technology in education.

Keywords: social media, interactions, collaboration, online learning environment

Procedia PDF Downloads 180

Authors: Ying Su, Morgan C. Wang

Abstract:

Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

Procedia PDF Downloads 102

Authors: Roaa Al Sharif, Salsabil Abo Al-Azayem, Nimah Alsomali, Wjoud Alsaeed, Nawal Alshammari, Abdulaziz Alwatban, Yaseen Alrabae, Razan Orfali, Faisal Alqarni, Ahmad Alrasheedi

Abstract:

from various countries have revealed that nurses possess only a basic understanding of the GCS. Regarding this matter, limited knowledge is available about the situation in Saudi Arabia. Overall, the available research suggests that there is room for improvement in the knowledge of the GCS among nurses in Saudi Arabia. Further training and education programs may be beneficial in enhancing nurses' understanding and application of the GCS in clinical practice. Objective: To determine the level of knowledge and competence in assessing the GCS among staff nurses and to identify factors that might influence their knowledge at King Fahd Medical City in Riyadh, Saudi Arabia. Methods: A descriptive, cross-sectional survey involving 199 KFMC staff nurses was conducted. Nurses were provided with a structured questionnaire, and data were collected and analyzed using SPSS version 16, employing descriptive statistics and Chi-square tests. Results: The majority, 81.4% of nurses, had an average level of knowledge in assessing the Glasgow Coma Scale (GCS). The mean score for measuring the level of knowledge among staff nurses in GCS assessment was 8.8 ± 1.826. Overall, 13.6% of respondents demonstrated good knowledge of the GCS, scoring between 11 and 15 points, while only 5% of nurses exhibited poor knowledge of the GCS assessment. There was a significant correlation between knowledge and nurses' departments (χ2(2) = 19.184, p < 0.001). χ2(2) = 19.184," representing a Chi-square statistic with 2 degrees of freedom used to test the association between categorical variables in the data analysis. Conclusion: The findings indicate that knowledge of GCS assessment among staff nurses in a single center in Saudi Arabia is moderate. Therefore, there is a need for continuous education programs to enhance their competence in using this assessment.

Keywords: Glasgow Coma Scale, brain injury, nurses’ knowledge assessment, continuous education programs

Procedia PDF Downloads 16

Authors: Fuad M. Alkoot

Abstract:

The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

Procedia PDF Downloads 210

Authors: Emanuel Koseos

Abstract:

Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

Procedia PDF Downloads 167

Authors: Mourad Ben Bennani

Abstract:

Views of language and language learning have undergone a tremendous change over the last decades. Language is no longer seen as a set of structured rules. It is rather viewed as a tool of interaction and communication. This shift in views has resulted in change in viewing language learning, which gave birth to various approaches and methodologies of language teaching. Two of these approaches are content-based instruction and content and language integrated learning (CLIL). These are similar approaches which integrate content and foreign/second language learning through various methodologies and models as a result of different implementations around the world. This presentation deals with sociocultural view of CBI and CLIL. It also defines language and content as vital components of CBI and CLIL. Next it reviews the origins of CBI and the continuum perspectives and CLIL definitions and models featured in the literature. Finally it summarizes current aspects around research in program evaluation with a focus on the benefits and challenges of these innovative approaches for second language teaching.

Keywords: CBI, CLIL, CBI continuum, CLIL models

Procedia PDF Downloads 427

Authors: Hyeon-Kyo Lim, Hyunjung Kim, Kune-Woo Lee

Abstract:

Decommissioning process of nuclear facilities can be said to consist of a sequence of problem solving activities, partly because there may exist working environments contaminated by radiological exposure, and partly because there may also exist industrial hazards such as fire, explosions, toxic materials, and electrical and physical hazards. As for an individual hazard factor, risk assessment techniques are getting known to industrial workers with advance of safety technology, but the way how to integrate those results is not. Furthermore, there are few workers who experienced decommissioning operations a lot in the past. Therefore, not a few countries in the world have been trying to develop appropriate counter techniques in order to guarantee safety and efficiency of the process. In spite of that, there still exists neither domestic nor international standard since nuclear facilities are too diverse and unique. In the consequence, it is quite inevitable to imagine and assess the whole risk in the situation anticipated one by one. This paper aimed to find out an appropriate technique to integrate individual risk assessment results from the viewpoint of experts. Thus, on one hand the whole risk assessment activity for decommissioning operations was modeled as a sequence of individual risk assessment steps, and on the other, a hierarchical risk structure was developed. Then, risk assessment procedure that can elicit individual hazard factors one by one were introduced with reference to the standard operation procedure (SOP) and hierarchical task analysis (HTA). With an assumption of quantification and normalization of individual risks, a technique to estimate relative weight factors was tried by using the conventional Analytic Hierarchical Process (AHP) and its result was reviewed with reference to judgment of experts. Besides, taking the ambiguity of human judgment into consideration, debates based upon fuzzy inference was added with a mathematical case study.

Keywords: decommissioning, risk assessment, analytic hierarchical process (AHP), fuzzy inference

Procedia PDF Downloads 423

Authors: Thuy Phan, Stephanie Luallin

Abstract:

Inclusive education policies have demonstrated benefits for students with and without disabilities in the US. There are several laws that relate to inclusive education, such as 'No Child Left Behind', 'The Individuals with Disabilities Education Act'. However, the application of these inclusive education laws and policies vary per state and school district. Classroom teachers in an inclusive classroom often experience confusion as to how to apply these policies in order to create appropriate inclusive learning environments that meet the abilities and needs of their diverse student population. The study aims to investigate teachers’ perspective of their capacities to create an appropriate learning environment for their diverse student population including students with disabilities. Qualitative method is implemented in this study, using open-end interview questions to investigate teachers’ perspective of their capacities to create an appropriate inclusive learning environment for all students based on current inclusive education laws and district policies in the state of Colorado, USA. These findings may indicate a lack of confidence in teachers’ capacity to create appropriate inclusive learning environments based on laws and district policies; including challenges that classroom teachers may experience in creating inclusive learning environments. The purpose of this study is to examine the adequate preparation of classroom teachers in creating inclusive classrooms with the intent of determining implications for developing policies in inclusive education.

Keywords: educator’s capacity, inclusive education, inclusive learning environment, policy

Procedia PDF Downloads 168

Authors: Islam Elsayed Hussein Ali, Stefan M. Wagner

Abstract:

Smartphone and tablet computers, as well as other ultra portable devices, have already gained enough critical mass to be considered mainstream devices, being present in the daily lives of millions of higher education students. Many universities throughout the world have already adopted or are planning to adopt mobile technologies in many of their courses as a better way to connect students with the subjects they are studying. These new mobile platforms allow students to access content anywhere/anytime to immerse himself/herself into that content (alone or interacting with teachers or colleagues via web communication forms) and to interact with that content in ways that were not previously possible. This paper plans to provide a thorough overview of the possibilities and consequences of m-learning in higher education environments as a gateway to ubiquitous learning – perhaps the ultimate form of learner engagement, since it allows the student to learn, access and interact with important content in any way or at any time or place he might want so the objective of the study is to examine how the usage of mobile phones for m-learning differs between heavy and light mobile phone users at TU Braunschweig. Heavy mobile phone users are hypothesized to have access to/subscribe to one type of mobile content than light mobile phone users, to have less frequent access to, subscribe to or purchase mobile content within the last year than light mobile phone users, and to pay less money for mobile learning, its content and mobile games than light mobile phone users.

Keywords: mobile learning, technologies, applications, higher education

Procedia PDF Downloads 414

Authors: Belkis L. Cabrera

Abstract:

Contemporary technological innovations have reshaped possibility, interaction, communication, engagement, education, and training. Indeed, today, a high-quality technology enhanced learning experience can be transformative as much for the learner as for the educator-trainer. As innovative technologies continue to facilitate, support, foster, and enhance collaboration, problem-solving, creativity, adaptiveness, multidisciplinarity, and communication, the field of instructional design (ID) also continues to develop and expand. Shifting its focus from media to the systematic design of instruction, or rather from the gadgets and devices themselves to the theories, models, and impact of implementing educational technology, the evolution of ID marks a restructuring of the teaching, learning, and training paradigms. However, with all of its promise, this latter component of ID remains underdeveloped. The majority of ID models are crafted and guided by learning theories and, therefore, most models are constructed around student and educator roles rather than trainer roles. Thus, when these models or systems are employed for training purposes, they usually have to be re-fitted, tweaked, and stretched to meet the training needs. This paper is concerned with the training or professional development (PD) facet of instructional design and how ID models built on teacher-to-teacher interaction and dialogue can support the creation of professional learning communities (PLCs) or communities of practice (CoPs), which can augment learning and PD experiences for all. Just as technology is changing the face of education, so too can it change the face of PD within the educational realm. This paper not only provides a new ID model but using innovative technologies such as Padlet and Thinkbinder, this paper presents a concrete example of how a traditional body-to-body, brick, and mortar learning community can be transferred and transformed into the online context.

Keywords: communities of practice, e-learning, educational reform, instructional design, professional development, professional learning communities, technology, training

Procedia PDF Downloads 338

Authors: Youngjae Jin, Daeshik Kim

Abstract:

This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

Procedia PDF Downloads 444

Authors: H. Alqunayeer, S. Zamir

Abstract:

Blended learning, an ideal amalgamation of online learning and face to face traditional approach is a new approach that may result in outstanding outcomes in the realm of teaching and learning. The dexterity and effectiveness offered by e-learning experience cannot be guaranteed in a traditional classroom, whereas one-to-one interaction the essential element of learning that can only be found in a traditional classroom. In recent years, a spectacular expansion in the incorporation of technology in language teaching and learning is observed in many universities of Saudi Arabia. Some universities recognize the importance of blending face-to-face with online instruction in language pedagogy, Qassim University is one of the many universities adopting Blackboard Learning Management system (LMS). The university has adopted this new mode of teaching/learning in year 2015. Although the experience is immature; however great pedagogical transformations are anticipated in the university through this new approach. This paper examines the role of blended language learning with particular reference to the influence of Blackboard Learning Management System on the development of English language learning for EFL learners registered in Bachelors of English language program. This paper aims at exploring three main areas: (i) the present status of Blended learning in the educational process in Saudi Arabia especially in Qassim University by providing a survey report on the number of training courses on Blackboard LMS conducted for the male and female teachers at various colleges of Qassim University, (ii) a survey on teachers perception about the utility, application and the outcome of using blended Learning approach in teaching English language skills courses, (iii) the students’ views on the efficiency of Blended learning approach in learning English language skills courses. Besides, analysis of students’ limitations and challenges related to the experience of blended learning via Blackboard, the suggestion and recommendations offered by the language learners have also been thought-out. The study is empirical in nature. In order to gather data on the afore mentioned areas survey questionnaire method has been used: in order to study students’ perception, a 5 point Likert-scale questionnaire has been distributed to 200 students of English department registered in Bachelors in English program (level 5 through level 8). Teachers’ views have been surveyed with the help of interviewing 25 EFL teachers skilled in using Blackboard LMS in their lectures. In order to ensure the validity and reliability of questionnaire, the inter-rater approach and Cronbach’s Alpha analysis have been used respectively. Analysis of variance (ANOVA) has been used to analyze the students’ perception about the productivity of the Blended approach in learning English language skills. The analysis of feedback by Saudi teachers and students about the usefulness, ingenuity, and productivity of Blended Learning via Blackboard LMS highlights the need of encouraging and expanding the implementation of this new approach into the field of English language teaching in Saudi Arabia, in order to augment congenial learning aura. Furthermore, it is hoped that the propositions and practical suggestions offered by the study will be functional for other similar learning environments.

Keywords: blended learning, black board learning management system, English as foreign language (EFL) learners, EFL teachers

Procedia PDF Downloads 154

Authors: Maturos Chongchaikit, Sitthikorn Sumalee, Nopphawan Chimroylarp, Nongluck Manowaluilou, Thapanee Thammetha

Abstract:

The 2015 Kasetsart University Research Plan, which was funded by the National Research Institutes: TRF – NRCT, comprises four sub-research projects on the development of three OER websites and on their usage study by students in international programs. The goals were to develop the open educational resources (OER) in the form of websites that will promote three key skills of quality learning and achievement: Academic English, Educational Research, and ICT Literacy, to graduate students in international programs of Thailand. The statistics from the Office of Higher Education showed that the number of foreign students who come to study in international higher education of Thailand has increased respectively by 25 percent per year, proving that the international education system and institutes of Thailand have been already recognized regionally and globally as meeting the standards. The output of the plan: the OER websites and their materials, and the outcome: students’ learning improvement due to lecturers’ readiness for open educational media, will ultimately lead the country to higher business capabilities for international education services in ASEAN Community in the future. The OER innovation is aimed at sharing quality knowledge to the world, with the adoption of Creative Commons Licenses that makes sharing be able to do freely (5Rs openness), without charge and leading to self and life-long learning. The research has brought the problems on the low usage of existing OER in the English language to develop the OER on three specific skills and try them out with the sample of 100 students randomly selected from the international graduate programs of top 10 Thai universities, according to QS Asia University Rankings 2014. The R&D process was used for product evaluation in 2 stages: the development stage and the usage study stage. The research tools were the questionnaires for content and OER experts, the questionnaires for the sample group and the open-ended interviews for the focus group discussions. The data were analyzed using frequency, percentage, mean and SD. The findings revealed that the developed websites were fully qualified as OERs by the experts. The students’ opinions and satisfaction were at the highest levels for both the content and the technology used for presentation. The usage manual and self-assessment guide were finalized during the focus group discussions. The direct participation according to the concept of 5Rs Openness Activities through the provided tools of OER models like MERLOT and OER COMMONS, as well as the development of usage manual and self-assessment guide, were revealed as a key approach to further extend the output widely and sustainably to the network of users in various higher education institutions.

Keywords: open educational resources, international education services business, academic English, educational research, ICT literacy, international graduate program, OER

Procedia PDF Downloads 221

Authors: Abdulwakeel B. Raji

Abstract:

This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

Procedia PDF Downloads 132

Authors: Felermino D. M. A. Ali, S. C. Ng

Abstract:

E-learning is an evolutionary form of distance learning and has become better over time as new technologies emerged. Today, efforts are still being made to embrace E-learning systems with emerging technologies in order to make them better. Among these advancements, Educational Data Mining (EDM) is one that is gaining a huge and increasing popularity due to its wide application for improving the teaching-learning process in online practices. However, even though EDM promises to bring many benefits to educational industry in general and E-learning environments in particular, its principal drawback is the lack of easy to use tools. The current EDM tools usually require users to have some additional technical expertise to effectively perform EDM tasks. Thus, in response to these limitations, this study intends to design and implement an EDM application framework which aims at automating and simplify the development of EDM in E-learning environment. The application framework introduces a Service-Oriented Architecture (SOA) that hides the complexity of technical details and enables users to perform EDM in an automated fashion. The framework was designed based on abstraction, extensibility, and interoperability principles. The framework implementation was made up of three major modules. The first module provides an abstraction for data gathering, which was done by extending Moodle LMS (Learning Management System) source code. The second module provides data mining methods and techniques as services; it was done by converting Weka API into a set of Web services. The third module acts as an intermediary between the first two modules, it contains a user-friendly interface that allows dynamically locating data provider services, and running knowledge discovery tasks on data mining services. An experiment was conducted to evaluate the overhead of the proposed framework through a combination of simulation and implementation. The experiments have shown that the overhead introduced by the SOA mechanism is relatively small, therefore, it has been concluded that a service-oriented architecture can be effectively used to facilitate educational data mining in E-learning environments.

Keywords: educational data mining, e-learning, distributed data mining, moodle, service-oriented architecture, Weka

Procedia PDF Downloads 234

Authors: Sanjeeb Kumar Mohanty

Abstract:

Content Based Instruction (CBI) in English Language Teaching (ELT) basically helps English as Second Language (ESL) learners of English. At the same time, it fosters multidisciplinary style of learning by promoting collaborative learning style. It is an approach to teaching ESL that attempts to combine language with interdisciplinary learning for bettering language proficiency and facilitating content learning. Hence, the basic purpose of CBI is that language should be taught in conjunction with academic subject matter. It helps in establishing the content as well as developing language competency. This study aims at supporting the potential values of interdisciplinary approach in promoting English Language Learning (ELL) by teaching writing skills to a small group of learners and discussing the findings with the teachers from various disciplines in a workshop. The teachers who are oriented, they use the same approach in their classes collaboratively. The inputs from the learners as well as the teachers hopefully raise positive consciousness with regard to the vast benefits that Content Based Instruction can offer in advancing the language competence of the learners.

Keywords: content based instruction, interdisciplinary approach, writing skills, collaborative approach

Procedia PDF Downloads 271

Authors: Faraj Ahmed E. Alhegagi, Anagia M. Khamkam Mohamed, Bassam F. Alhajaji

Abstract:

Duplex stainless steels (DSS) are widely employed in industry for apparatus working with sea water in petroleum, refineries and in chemical plants. Fracture of DSS takes place by cleavage of the ferrite phase and the austenite phase ductile tear off. Pop-in is an important feature takes place during fracture of DSS. The procedure of Pop-ins assessment plays an important role in fracture toughness studies. In present work, Zeron100 DSS specimens were heat treated at different temperatures, cooled and pulled to failure to assess the pop-ins criterion in crack initiation prediction. The outcome results were compared to the British Standard (BS 7448) and the ASTEM standard (E1290) for Crack-Tip Opening Displacement (CTOD) fracture toughness measurement. Pop-in took place during specimens loading specially for those specimens heat treated at higher temperatures. The standard BS7448 was followed to check specimen validity for fractured toughness assessment by direct determination of KIC. In most cases, specimens were invalid for KIC measurement. The two procedures were equivalent only when single pop-ins were assessed. A considerable contrast in fracture toughness value between was observed where multiple pop-ins were assessed.

Keywords: fracture toughness, stainless steels, pop ins, crack assessment

Procedia PDF Downloads 121

Authors: Diane M. Bender

Abstract:

In architecture and design education, students learn and understand their discipline through lecture courses and within studios. A studio is where the instructor works closely with students to help them understand design by doing design work. The final jury is the culmination of the studio learning experience. It’s value and significance are rarely questioned. Students present their work before their peers, instructors, and invited reviewers, known as jurors. These jurors are recognized experts who add a breadth of feedback to students mostly in the form of a verbal critique of the work. Since the design review or jury has been a common element of studio education for centuries, jurors themselves have been instructed in this format. Therefore, they understand its value from both a student and a juror perspective. To better understand how these reviewers see the value of a studio review, a survey was distributed to reviewers at a multi-disciplinary design school within the United States. Five design disciplines were involved in this case study: architecture, graphic design, industrial design, interior design, and landscape architecture. Respondents (n=108) provided written comments about their perceived value of the studio review system. The average respondent was male (64%), between 40-49 years of age, and has attained a master’s degree. Qualitative analysis with thematic coding revealed several themes. Reviewers view the final jury as important because it provides a variety of perspectives from unbiased external practitioners and prepares students for similar presentation challenges they will experience in professional practice. They also see it as a way to validate the assessment and evaluation of students by faculty. In addition, they see a personal benefit for themselves and their firm – the ability to network with fellow jurors, professors, and students (i.e., future colleagues). Respondents also provided additional feedback about the jury system and studio education in general. Typical responses included a desire for earlier engagement with students; a better explanation from the instructor about the project parameters, rubrics/grading, and guidelines for juror involvement; a way to balance giving encouraging feedback versus overly critical comments; and providing training for jurors prior to reviews. While this study focused on the studio review, the findings are equally applicable to other disciplines. Suggestions will be provided on how to improve the preparation of guests in the learning process and how their interaction can positively influence student engagement.

Keywords: assessment, design, jury, studio

Procedia PDF Downloads 61

Authors: S. Hasan, I. Beshara

Abstract:

Infrastructure maintenance is a great challenge facing sustainable development of infrastructure assets due to the high cost of passive implementation of a sustainable maintenance plan. An assessment model of sustainable maintenance for highway infrastructure projects in Egypt is developed in this paper. It helps in improving the implementation of sustainable maintenance criteria. Thus, this paper has applied the analytical hierarchy processes (AHP) to rank and explore the weight of 26 assessment indicators using three hierarchy levels containing the main sustainable categories and subcategories with related indicators. Overall combined weight of each indicator for sustainable maintenance evaluation has been calculated to sum up to a sustainable maintenance performance index (SMI). The results show that the factor "Preventive maintenance cost" has the highest relative contribution factor among others (13.5%), while two factors of environmental performance have the least weights (0.7%). The developed model aims to provide decision makers with information about current maintenance performance and support them in the decision-making process regarding future directions of maintenance activities. It can be used as an assessment performance tool during the operation and maintenance stage. The developed indicators can be considered during designing the maintenance plan. Practices for successful implementation of the model are also presented.

Keywords: analytical hierarchy process, assessment performance Model, KPIs for sustainable maintenance, sustainable maintenance index

Procedia PDF Downloads 134

Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

Procedia PDF Downloads 16

Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

Abstract:

Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

Procedia PDF Downloads 53