Search results for: learning goal orientation

Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

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Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Carlos Oliveira, Ulrick Pimentel

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Digital games have conquered a growing space in the lives of children, adolescents and adults. In this perspective, the use of this resource has shown to be an important strategy that facilitates the learning process. This research is a literature review on the use of serious games in teaching, which shows the characteristics of these games, the benefits and possible harms that this resource can produce, in addition to the possible methods of evaluating the effectiveness of this resource in teaching. The results point out that Serious Games have significant potential as a tool for instruction. However, their effectiveness in terms of learning outcomes is still poorly studied, mainly due to the complexity involved in evaluating intangible measures.

Keywords: serious games, learning, application, literature review

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Authors: Ayat Adnan Atwah, Muhammad A. Khan

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Self-cleaning surfaces are getting significant attention in industrial fields. Especially for textile fabrics, it is observed that self-cleaning textile fabric surfaces are created by manipulating the surface features with the help of coatings and nanoparticles, which are considered costly and far more complicated. However, controlling the fabrication parameters of textile fabrics at the microscopic level by exploring the potential for self-cleaning has not been addressed. This study aimed to establish the context of self-cleaning textile fabrics by controlling the fabrication parameters of the textile fabric at the microscopic level. Therefore, 3D-printed textile fabrics were fabricated using the low-cost fused filament fabrication (FFF) technique. The printing parameters, such as orientation angle (O), layer height (LH), and extruder width (EW), were used to control the microscopic features of the printed fabrics. The combination of three printing parameters was created to provide the best self-cleaning textile fabric surface: (LH) (0.15, 0.13, 0.10 mm) and (EW) (0.5, 0.4, 0.3 mm) along with two different (O) of (45º and 90º). Three different thermoplastic flexible filament materials were used: (TPU 98A), (TPE felaflex), and (TPC flex45). The printing parameters were optimised to get the optimum self-cleaning ability of the printed specimens. Furthermore, the impact of these characteristics on mechanical strength at the fabric-woven structure level was investigated. The study revealed that the printing parameters significantly affect the self-cleaning properties after adjusting the selected combination of layer height, extruder width, and printing orientation. A linear regression model was effectively developed to demonstrate the association between 3D printing parameters (layer height, extruder width, and orientation). According to the experimental results, (TPE felaflex) has a better self-cleaning ability than the other two materials.

Keywords: 3D printing, self-cleaning fabric, microscopic features, printing parameters, fabrication

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Authors: Ahmed Mohamed Elnady Mohamed Elsafty

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This paper explains a developed applied objective model to measure the culture qualitatively and quantitatively, whether in individuals or in teams, in order to be able to use culture correctly or modify it efficiently. This model provides precise measurements and consistent interpretations by being comprehensive, updateable, and protected from being misled by imitations. Methodically, the provided model divides the culture into seven dimensions (total 43 cultural factors): First dimension is outcome-orientation which consists of five factors and should be highest in leaders. Second dimension is details-orientation which consists of eight factors and should be in highest intelligence members. Third dimension is team-orientation which consists of five factors and should be highest in instructors or coaches. Fourth dimension is change-orientation which consists of five factors and should be highest in soldiers. Fifth dimension is people-orientation which consists of eight factors and should be highest in media members. Sixth dimension is masculinity which consists of seven factors and should be highest in hard workers. Last dimension is stability which consists of seven factors and should be highest in soft workers. In this paper, the details of all cultural factors are explained. Practically, information collection about each cultural factor in the targeted person or team is essential in order to calculate the degrees of all cultural factors using the suggested equation of multiplying 'the score of factor presence' by 'the score of factor strength'. In this paper, the details of how to build each score are explained. Based on the highest degrees - to identify which cultural dimension is the prominent - choosing the tested individual or team in the supposedly right position at the right time will provide a chance to use minimal efforts to make everyone aligned to the organization’s objectives. In other words, making everyone self-motivated by setting him/her at the right source of motivation is the most effective and efficient method to achieve high levels of competency, commitment, and sustainability. Modifying a team culture can be achieved by excluding or including new members with relatively high or low degrees in specific cultural factors. For conclusion, culture is considered as the software of the human beings and it is one of the major compression factors on the managerial discretion. It represents the behaviors, attitudes, and motivations of the human resources which are vital to enhance quality and safety, expanding the market share, and defending against attacks from external environments. Thus, it is tremendously essential and useful to use such a comprehensive model to measure, use, and modify culture.

Keywords: culture dimensions, culture factors, culture measurement, cultural analysis, cultural modification, self-motivation, alignment to objectives, competency, sustainability

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Authors: Omid Noroozi

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Digital dialogue games have opened up opportunities for learning skills by engaging students in complex problem solving that mimic real world situations, without importing unwanted constraints and risks of the real world. Digital dialogue games can be motivating and engaging to students for fun, creative thinking, and learning. This study explored how undergraduate students engage with argumentative discourse activities which have been designed to intensify debate. A pre-test, post-test design was used with students who were assigned to groups of four and asked to debate a controversial topic with the aim of exploring various 'pros and cons' on the 'Genetically Modified Organisms (GMOs)'. Findings reveal that the Digital dialogue game can facilitate argumentation-based learning. The digital Dialogue game was also evaluated positively in terms of students’ satisfaction and learning experiences.

Keywords: argumentation, dialogue, digital game, learning, motivation

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Authors: Jolanta Jonak

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Traditional classrooms are challenging for many students, but especially for students that learn differently due to cognitive makeup, learning preferences, or disability. These students often require different teaching approaches and learning opportunities to benefit from learning. Teachers frequently divert to using one teaching approach, the one that matches their own learning style. For instance, teachers that are auditory learners, likely default to providing auditory learning opportunities. However, if a student is a visual learner, he/she may not fully benefit from that teaching style. Based on research, students and their parents’ feedback, large numbers of students are not provided the type of education and types of supports they need in order to be successful in an academic environment. This eventually leads to not learning at an appropriate rate and ultimately leading to skill deficiencies and deficits. Providing varied learning approaches promote high academic and social-emotional growth of all students and it will prevent inaccurate Special Education referrals. Varied learning opportunities can be delivered for all students by providing Differentiated Instruction (DI). This type of instruction allows each student to learn in the most optimal way regardless of learning preferences and cognitive learning profiles. Using Differentiated Instruction will lead to a high level of student engagement and learning. In addition, experiencing success in the classroom, will contribute to increased social emotional wellbeing. Being cognizant of how teaching approaches impact student's learning, school staff can avoid inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability. This presentation will illustrate learning differences due to various factors, how to recognize them, and how to address them through Differentiated Instruction.

Keywords: special education, disability, differences, differentiated instruction, social emotional wellbeing

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Authors: Elena F. Ruiz, Marina Vicario, Chadwick Carreto, Rubén Peredo

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One of the main obstacles in Mexico’s engineering programs is math comprehension, especially in the Derivative concept. Due to this, we present a study case that relates Mobile Computing and Classroom Learning in the “Escuela Superior de Cómputo”, based on the Educational model of the Instituto Politécnico Nacional (competence based work and problem solutions) in which we propose apps and activities to teach the concept of the Derivative. M- Learning is emphasized as one of its lines, as the objective is the use of mobile devices running an app that uses its components such as sensors, screen, camera and processing power in classroom work. In this paper, we employed Augmented Reality (ARRoC), based on the good results this technology has had in the field of learning. This proposal was developed using a qualitative research methodology supported by quantitative research. The methodological instruments used on this proposal are: observation, questionnaires, interviews and evaluations. We obtained positive results with a 40% increase using M-Learning, from the 20% increase using traditional means.

Keywords: augmented reality, classroom learning, educational research, mobile computing

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Authors: Isabelle Lorge, Napoleon Katsos

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BACKGROUND: Children growing up in a multilingual environment face challenges related to the need to monitor the speaker’s linguistic abilities, more frequent communication failures, and having to acquire a large number of words in a limited amount of time compared to monolinguals. As a result, bilingual learners may develop different word learning strategies, rely more on some strategies than others, and engage cognitive resources such as theory of mind and attention skills in different ways. HYPOTHESIS: The goal of our study is to investigate whether multilingual exposure leads to improvements in the ability to use pragmatic inference for word learning, i.e., to use speaker cues to derive their referring intentions, often by overcoming lower level salience effects. The speaker cues we identified as relevant are (a) use of a modifier with or without stress (‘the WET dax’ prompting the choice of the referent which has a dry counterpart), (b) referent extension (‘this is a kitten with a fep’ prompting the choice of the unique rather than shared object), (c) referent novelty (choosing novel action rather than novel object which has been manipulated already), (d) teacher versus random sampling (assuming the choice of specific examples for a novel word to be relevant to the extension of that new category), and finally (e) emotional affect (‘look at the figoo’ uttered in a sad or happy voice) . METHOD: To this end, we implemented on a touchscreen computer a task corresponding to each of the cues above, where the child had to pick the referent of a novel word. These word learning tasks (a), (b), (c), (d) and (e) were adapted from previous word learning studies. 113 children have been tested (54 reception and 59 year 1, ranging from 4 to 6 years old) in a London primary school. Bilingual or monolingual status and other relevant information (age of onset, proficiency, literacy for bilinguals) is ascertained through language questionnaires from parents (34 out of 113 received to date). While we do not yet have the data that will allow us to test for effect of bilingualism, we can already see that performances are far from approaching ceiling in any of the tasks. In some cases the children’s performances radically differ from adults’ in a qualitative way, which means that there is scope for quantitative and qualitative effects to arise between language groups. The findings should contribute to explain the puzzling speed and efficiency that bilinguals demonstrate in acquiring competence in two languages.

Keywords: bilingualism, pragmatics, word learning, attention

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Authors: Thapanee Musiget

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Ethnic minority children’s language learning is believed that it can be developed through school system. However, many cases prove that these kids are left to challenge with multicultural context at school and sometimes decreased the ability to acquire new learning. Consequently, it is significant for ethnicity parents to consider that prompting their children at home before their actual school age can eliminate negative outcome of children's language acquisition. This paper discusses the approach of instructional use of parents and children language learning in the context of minority language group in Thailand. By conducting this investigation, secondary source of data was gathered with the purpose to point out some primary methods for parents and children in ethnicity. The process of language learning is based on the sociocultural theory of Vygotsky, which highlights expressive communication among individuals as the best motivating force in human development and learning. The article also highlights the role of parents as they lead the instruction approach. In the discussion part, the role of ethnic minority parents as a language instructor is offered as mediator.

Keywords: ethnic minority, language learning, multicultural context, sociocultural theory

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Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Isabel Medina, Mario Duran

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Although Problem-based learning provides students with multiple opportunities for rigorous instructional experiences in which students are challenged to address problems in the community; there are still gaps in connecting community leaders to the PBL process. At a south Texas high school, community participation serves as an integral component of the PBL process. Problem-based learning (PBL) has recently gained momentum due to the increase in global communities that value collaboration and critical thinking. As an instructional approach, PBL engages high school students in meaningful learning experiences. Furthermore, PBL focuses on providing students with a connection to real-world situations that require effective peer collaboration. For PBL leaders, providing students with a meaningful process is as important as the final PBL outcome. To achieve this goal, STEM high school strategically created a space for community involvement to be woven within the PBL fabric. This study examines the impact community members had on PBL students attending a STEM high school in South Texas. At STEM High School, community members represent a support system that works through the PBL process to ensure students receive real-life mentoring from business and industry leaders situated in the community. A phenomenological study using a semi-structured approach was used to collect data about students’ perception of community involvement within the PBL process for one South Texas high school. In our proposed presentation, we will discuss how community involvement in the PBL process academically impacted the educational experience of high school students at STEM high school. We address the instructional concerns PBL critics have with the lack of direct instruction, by providing a representation of how STEM high school utilizes community members to assist in impacting the academic experience of students.

Keywords: phenomenological, STEM education, student engagement, community involvement

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Authors: Pia Wetzl

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The learning process of students can be optimized by combining online teaching with face-to-face sessions. So-called blended learning offers extensive flexibility as well as contact opportunities with fellow students and teachers. Furthermore, learning can be individualized and self-regulated. The aim of this article is to investigate which factors are necessary for blended learning to be successful. Semi-structured interviews were conducted with students (N = 60) and lecturers (N = 21) from different disciplines at two German universities. The questions focused on the perception of online, face-to-face and blended learning courses. In addition, questions focused on possible optimization potential and obstacles to practical implementation. The results show that on-site presence is very important for blended learning to be successful. If students do not get to know each other on-site, there is a risk of loneliness during the self-learning phases. This has a negative impact on motivation. From the perspective of the lecturers, the willingness of the students to participate in the sessions on-site is low. Especially when there is no obligation to attend, group work is difficult to implement because the number of students attending is too low. Lecturers would like to see more opportunities from the university and its administration to enforce attendance. In their view, this is the only way to ensure the success of blended learning. In addition, they see the conception of blended learning courses as requiring a great deal of time, which they are not always willing to invest. More incentives are necessary to keep the lecturers motivated to develop engaging teaching material. The study identifies factors that can help teachers conceptualize blended learning. It also provides specific implementation advice and identifies potential impacts. This catalogue has great value for the future-oriented development of courses at universities. Future studies could test its practical use.

Keywords: blended learning, higher education, teachers, student learning, qualitative research

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Authors: Christine K. Fulmer

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Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: social work education, problem-based learning, pedagogy, experiential learning, constructivist theoretical approach

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Authors: Chih Ming Kung

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This study is an empirical study examining the enrollment rate and dropout rate of students from the perspectives of students’ learning, parents’ involvement and the learning process. Methods: Using the data collected from the entry website of Internet of Things (IoT), parents’ participation and the installation pattern of exit poll website, an investigation was conducted. Results: This study discovered that in the aspect of the degree of involvement, the attractiveness of courses, self-performance and departmental loyalty exerts significant influences on the four aspects: psychological benefits, physical benefits, social benefits and educational benefits of learning benefits. Parents’ participation also exerts a significant influence on the learning benefits. A suitable tool on the cloud was designed to collect the dynamic big data of students’ learning process. Conclusion: This research’s results can be valuable references for the government when making and promoting related policies, with more macro view and consideration. It is also expected to be contributory to schools for the practical study of promotion for enrollment.

Keywords: students’ learning factor, parents’ involvement, involvement, technology

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Authors: A. Yacob, N. Hj. Ali, M. H. Yusoff, M. Y. MohdSaman, W. M. A. F. W. Hamzah

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Personalized learning becomes increasingly popular which not is restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability. The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT, it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores. Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.

Keywords: assessment, item response theory, cognitive load theory, learning, motivation, performance

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Authors: Rahimah Abdulrahman, A. Eardle, Wilfred Alan, Abdel Hamid Soliman

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With the rapid development in technology, and advances in learning technologies, m-learning has begun to occupy a great part of our lives. The pace of the life getting together with the need for learning started mobile learning (m-learning) concept. In 2008, Saudi Arabia requested a national plan for the adoption of information technology (IT) across the country. Part of the recommendations of this plan concerns the implementation of mobile learning (m-learning) as well as their prospective applications to higher education within the Kingdom of Saudi Arabia. The overall aim of the research is to explore the main issues that impact the deployment of m-learning in nursing institutes in Saudi Arabia, at the Armed Force Hospitals (AFH), Alhada. This is in order to be able to develop a generic model to enable and assist the educational policy makers and implementers of m-learning, to comprehend and treat those issues effectively. Specifically, the research will explore the concept of m-learning; identify and analyse the main organisational; technological and cultural issue, that relate to the adoption of m-learning; develop a model of m-learning; investigate the perception of the students of the Nursing Institutes to the use of m-learning technologies for their nursing diploma programmes based on their experiences; conduct a validation of the m-learning model with the use of the nursing Institute of the AFH, Alhada in Saudi Arabia, and evaluate the research project as a learning experience and as a contribution to the body of knowledge. Activity Theory (AT) will be adopted for the study due to the fact that it provides a conceptual framework that engenders an understanding of the structure, development and the context of computer-supported activities. The study will be adopt a set of data collection methods which engage nursing students in a quantitative survey, while nurse teachers are engaged through in depth qualitative studies to get first-hand information about the organisational, technological and cultural issues that impact on the deployment of m-learning. The original contribution will be a model for developing m-learning material for classroom-based learning in the nursing institute that can have a general application.

Keywords: activity theory (at), mobile learning (m-learning), nursing institute, Saudi Arabia (sa)

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Authors: Salvador Antelmo Casanova Valencia

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This study documents the use of the Minecraft Education Edition application to explore immersive game-based learning environments. We analyze the contributions of fourth-year university students who are pursuing a degree in Administrative Computing at the Universidad Michoacana de San Nicolas de Hidalgo. In this study, descriptive data and statistical inference are detailed using a quasi-experimental design using the Wilcoxon test. The instruments will provide data validation. Game-based learning in immersive environments necessarily implies greater student participation and commitment, resulting in the study, motivation, and significant improvements, promoting cooperation and autonomous learning.

Keywords: game-based learning, gamification, higher education, Minecraft

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Authors: Subramaniam Chandran, A. Geetha

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This paper addresses three issues: how to prepare the instructional design for imparting English language skill from inter-disciplinary self-learning material; how the disadvantaged students are benefited from such kind of language skill imparted through m-learning; and how do m-learners perform better than the other learners. This paper examines these issues through an experimental study conducted among the distance learners enrolled in a preparatory program for bachelor’s degree. This program is designed for the disadvantaged learners especially for the school drop-outs to qualify to pursue graduate program through distant education. It also explains how mobile learning helps them to enhance their capacity in learning despite their rural background and other disadvantages. In India, nearly half of the students enrolled in schools do not complete their study. The pursuance of higher education is very low when compared with developed countries. This study finds a significant increase in their learning capacity and mobile learning seems to be a viable alternative where the conventional system could not reach the disadvantaged learners. Improving the English language skill is one of the reasons for such kind of performance. Exercises framed from the relevant self-learning material for enhancing English language skill not only improves language skill but also widens the subject-knowledge. This paper explains these issues out of the study conducted among the disadvantaged learners.

Keywords: English language skill, disadvantaged learners, distance education, m-learning

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Authors: Panagiotis Kosmas, Panayiotis Zaphiris

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Embodied Cognition (EC) as a learning paradigm is based on the idea of an inseparable link between body, mind, and environment. In recent years, the advent of theoretical learning approaches around EC theory has resulted in a number of empirical studies exploring the implementation of the theory in education. This systematic literature overview identifies the mainstream of EC research and emphasizes on the implementation of the theory across learning environments. Based on a corpus of 43 manuscripts, published between 2013 and 2017, it sets out to describe the range of topics covered under the umbrella of EC and provides a holistic view of the field. The aim of the present review is to investigate the main issues in EC research related to the various learning contexts. Particularly, the study addresses the research methods and technologies that are utilized, and it also explores the integration of body into the learning context. An important finding from the overview is the potential of the theory in different educational environments and disciplines. However, there is a lack of an explicit pedagogical framework from an educational perspective for a successful implementation in various learning contexts.

Keywords: embodied cognition, embodied learning, education, technology, schools

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Hongmei Chi

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The Blockchain has become a necessity for many different societal industries and ordinary lives including cryptocurrency technology, supply chain, health care, public safety, education, etc. Therefore, training our future blockchain developers to know blockchain programming vulnerability and I.T. students' cyber security is in high demand. In this work, we propose a framework including learning modules and hands-on labs to guide future I.T. professionals towards developing secure blockchain programming habits and mitigating source code vulnerabilities at the early stages of the software development lifecycle following the concept of Secure Software Development Life Cycle (SSDLC). In this research, our goal is to make blockchain programmers and I.T. students aware of the vulnerabilities of blockchains. In summary, we develop a framework that will (1) improve students' skills and awareness of blockchain source code vulnerabilities, detection tools, and mitigation techniques (2) integrate concepts of blockchain vulnerabilities for IT students, (3) improve future IT workers’ ability to master the concepts of blockchain attacks.

Keywords: software vulnerability detection, hands-on lab, static analysis tools, vulnerabilities, blockchain, active learning

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Authors: Derek Brandon G. Yu, Clyde Vincent O. Pilapil, Christine F. Peña

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College students of Cebu province have been indoors since March 2020, and a challenge encountered is the sudden shift from face to face to online learning and with the lack of empirical data on online learning on Higher Education Institutions (HEIs) in the Philippines. Sentiments on face to face and online learning will be collected from University of San Carlos (USC), School of Arts and Sciences (SAS) students regarding Mathematics in the Modern World (MMW), a General Education (GE) course. Natural Language Processing with machine learning algorithms will be used to classify the sentiments of the students. Results of the research study are the themes identified through topic modelling and the overall sentiments of the students in USC SAS

Keywords: natural language processing, online learning, sentiment analysis, topic modelling

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Authors: Aïda C. Terblanché-Greeff

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Afro-polychronism is a unique amalgamated cultural value of social self-construal and time orientation. As such, the construct Afro-polychronism is conceptually analysed by focusing on the aspects of Ubuntu as collectivism and African time as polychronism. It is argued that these cultural values have a reciprocal and thus inseparable relationship. As it is general practice to measure cultural values empirically, the author conducted empirically engaged philosophy and aimed to develop a scale to measure Afro-polychronism based on its two dimensions of Ubuntu as social self-construal and African time as time orientation. From the scale’s psychometric properties, it was determined that the scale was, in fact, not reliable and valid. It was found that the correlation between the Ubuntu dimension and the African time is moderate (albeit statistically significant). In conclusion, the author abduced why this cultural value cannot be empirically measured based on its theoretical definition and indicated which different path would be more promising.

Keywords: African time, Afro-polychronism, empirically engaged African philosophy, Ubuntu

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Authors: PB Venkataraman

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Most of the real-life problems are ill-structured. They do not have a single solution but many competing solutions. The solution paths are non-linear and ambiguous, and the problem definition itself is many times a challenge. Students of professional education learn to solve such problems through internships. The current pandemic situation has constrained on-site internship opportunities; thus the students have no option but to pursue this learning online. This research assessed the learning gain of four undergraduate students in engineering as they undertook an online internship in an organisation over a period of eight weeks. A clinical interview at the end of the internship provided the primary data to assess the team’s problem-solving skills using a tested rubric. In addition to this, change in their learning attitudes were assessed through a pre-post study using a repurposed CLASS instrument for Electrical Engineering. Analysis of CLASS data indicated a shift in the sophistication of their learning attitude. A learning engagement survey adopting a 6-point Likert scale showed active participation and motivation in learning. We hope this new research will stimulate educators to exploit online internships even beyond the time of pandemic as more and more business operations are transforming into virtual.

Keywords: ill-structured problems, learning attitudes, internship, assessment, student engagement

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Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

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Authors: Heny Hartono, Cecilia Titiek Murniati

Abstract:

The pandemic has given teachers and students no other choice but having full online learning. In such an emergency situation as the time of the covid-19 pandemic, the application of LMS (Learner Management System) in higher education is the most reasonable solution for students and teachers. In fact, the online learning requires all elements of a higher education systems, including the human resources, infrastructure, and supporting systems such as the application, server, and stable internet connection. The readiness of the higher education institution in preparing the online system may secure those who are involved in the online learning process. It may also result in students’ self-efficacy in online learning. This research aimed to investigate how students perceive their self-efficacy in online English learning, especially in speaking classes which is considered as a productive language skill. This research collects qualitative data with narrative inquiry involving 25 students of speaking classes as the respondents. The results of this study show that students perceive their self-efficacy in speaking online classes as not very high.

Keywords: self-efficacy, online learning, speaking class, college students, e-learning

Procedia PDF Downloads 92

Authors: Jianhua Wang, Ying Zhou, Xi Zhang

Abstract:

To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

Procedia PDF Downloads 190

Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni

Abstract:

Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.

Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization

Procedia PDF Downloads 232