Search results for: skills gained through learning

Authors: kaveh Jalilzadeh, Maryam Rastgari

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Motivation for learning a foreign language is needed for learners of any foreign language to effectively learn language skills. However, there are some factors that lead to the learners’ demotivation. Therefore, teachers of foreign languages, most notably English language which turned out to be an international language for academic and business purposes, need to be well aware of the demotivation sources and know how to reduce learners’ demotivation. This study is an attempt to explore demotivation-reducing strategies employed by Turkish EFL learners in L2 writing. The researchers used a qualitative case study and employed semi-structured interviews to collect data. The informants recruited in this study were 20 English writing lecturers who were selected through purposive sampling among university lecturers/instructors at the state and non-state universities in Istanbul and Ankara. Interviews were transcribed verbatim, and MAXQDA software (version 2022) was used for performing coding and thematic analysis of the data. Findings revealed that Turkish EFL teachers use 18 strategies to reduce language learners’ demotivation. The most frequently reported strategies were: writing in a group, writing about interesting topics, writing about new topics, writing about familiar topics, writing about simple topics, and writing about relevant topics. The findings have practical implications for writing teachers and learners of the English language.

Keywords: phenomenological study, emotional vulnerability, motivation, digital Settings

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

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

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

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Authors: Narges Nemati, Mohammadreza Fallahpour, Hossein Bozorgian

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Reading is one of the receptive skills which has an important role in improving other skills like writing and speaking. Furthermore, language learners can acquire plenty of vocabularies and become more acquainted with written expression through reading. Also, negative attitudes toward reading can cause negligible reading comprehension, which could prompt poor performance in the English language. Considering the fact that reading instruction was discussed as a low priority skill in the field of EFL teacher education, this study attempted to investigate EFL teachers’ attitudes toward reading instruction. Therefore, to serve the purpose of this study, a mixed-method approach was utilized by inviting 100 Iranian EFL teachers who taught at English language institutes of Iran to fill out a validated questionnaire on teachers’ attitude toward reading. Subsequently, 10 participants were randomly selected for further observations and interview sessions to evaluate the differences between their stated attitude and their actual practices. The findings from analyzing questionnaires, observations, and interviews revealed that EFL teachers’ stated attitude toward reading instruction was positive; whereas, due to some reasons like lack of time, scarcity of interesting passages, and lack of interest in reading long passages, teachers did not show positive actual attitude toward teaching reading skill.

Keywords: English as foreign language classroom, English language, reading skill, teachers' attitude

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Authors: Mohammed Hassan Alshaikhi

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Vocabulary is essential factor of learning and mastering any languages, and it helps learners to communicate with others and to be understood. The aim of this study was to examine whether semantic mapping technique was helpful in terms of improving student's English vocabulary learning comparing to the traditional technique. The students’ age was between 11 and 13 years old. There were 60 students in total who participated in this study. 30 students were in the treatment group (target vocabulary items were taught with semantic mapping). The other 30 students were in the control group (the target vocabulary items were taught by a traditional technique). A t-test was used with the results of pre-test and post-test in order to examine the outcomes of using semantic mapping when teaching vocabulary. The results showed that the vocabulary mastery in the treatment group was increased more than the control group.

Keywords: English language, learning vocabulary, Saudi teachers, semantic mapping, teaching vocabulary strategies

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Mustafa Gultekin

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It is believed that drama can be used in language classes to create a positive atmosphere for students to use the target language in an interactive way. Thus, drama has been extensively used in many settings in language classes. Although happening has been generally used as a performance art of theatre, this new kind of performance has not been widely known in language teaching area. Therefore, it can be an innovative idea to use happening in language classes, and thus a positive environment can be created for students to use the language in an interactive way. Happening can be defined as an art performance that puts emphasis on interaction in an audience. Because of its interactive feature, happening can also be used in language classes to motivate students to use the language in an interactive environment. The present study aims to explain how a happening performance can be applied to a learning environment to teach vocabulary in English. In line with this purpose, a learning environment was designed for a vocabulary presentation lesson. At the end of the performance, students were asked to compare the traditional way of teaching and happening performance in terms of effectiveness. It was found that happening performance provided the students with a more creative and interactive environment to use the language. Therefore, happening can be used in language classrooms as an innovative tool for education.

Keywords: English, happening, language learning, vocabulary teaching

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Authors: Kuixi Du, Thomas J. Lipscomb

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The proficiency in Mathematics skills is fundamental to success in the STEM disciplines. In the US, beginning college students who are placed in remedial/developmental Mathematics courses frequently struggle to achieve academic success. Therefore, Mathematics remediation in college has become an important concern, and providing Mathematics remediation is a prevalent way to help the students who may not be fully prepared for college-level courses. Programs vary, however, and the effectiveness of a particular remedial Mathematics program must be empirically demonstrated. The purpose of this study was to apply the sharp regression discontinuity (RD) technique to determine the effectiveness of the Jack Leaps Summer (JLS) Mathematic remediation program in supporting improved Mathematics learning outcomes among newly admitted Mathematics students in the South Dakota State University. The researchers studied the newly admitted Fall 2019 cohort of Mathematics majors (n=423). The results indicated that students whose pretest score was lower than the cut-off point and who were assigned to the JLS program experienced significantly higher scores on the post-test (Math 101 final score). Based on these results, there is evidence that the JLS program is effective in meeting its primary objective.

Keywords: causal inference, mathematisc remedial program evaluation, quasi-experimental research design, regression discontinuity design, cohort studies

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Authors: Chinlun Lai, Lunjyh Jiang

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Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

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Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Nhung T. Bui

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Part of the dilemma facing educational reforms in Vietnam as in other Asian contexts is how to encourage more independence in students’ learning approaches. Since 2005, the Ministry of Education and Training of Vietnam has included the students’ ability to learn independently in its national education objectives. While learner autonomy has been viewed as a goal in the teaching and learning English as a foreign language (EFL) and there has been a considerable literature on strategies to stimulate autonomy in learners, teachers’ voices have rarely been heard. Given that teachers play a central role in helping their students to be more autonomous, especially in an inherent Confucian heritage culture like Vietnam, their attitudes towards learner autonomy should be investigated before any practical implementations could be undertaken. This paper reports significant findings of a survey questionnaire with 262 lecturers of English from 5 universities in Hanoi, Vietnam giving opinions regarding the practices and prospects of learner autonomy in their classrooms. The study reveals that lecturers perceive they should be more responsible than their students in all class-related activities; they most appreciate their students’ ability to learn cooperatively and that they consider stimulating students’ interest as the most important teaching strategy to promote learner autonomy. Lecturers, then, are strongly suggested to gradually ‘empower’ their students through the application of out-of-classroom activities; of learning activities which requires collaboration and team spirit; and of activities which could boost students’ interest in learning English.

Keywords: English as a foreign language, higher education, learner autonomy, Vietnam

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Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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Authors: Yulan Wu

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With the rapid development of social media, the issue of fake news has gained considerable prominence, drawing the attention of both the public and governments. The widespread dissemination of false information poses a tangible threat across multiple domains of society, including politics, economy, and health. However, much research has concentrated on supervised training models within specific domains, their effectiveness diminishes when applied to identify fake news across multiple domains. To solve this problem, some approaches based on domain labels have been proposed. By segmenting news to their specific area in advance, judges in the corresponding field may be more accurate on fake news. However, these approaches disregard the fact that news records can pertain to multiple domains, resulting in a significant loss of valuable information. In addition, the datasets used for training must all be domain-labeled, which creates unnecessary complexity. To solve these problems, an unsupervised domain knowledge discovery framework for fake news detection is proposed. Firstly, to effectively retain the multidomain knowledge of the text, a low-dimensional vector for each news text to capture domain embeddings is generated. Subsequently, a feature extraction module utilizing the unsupervisedly discovered domain embeddings is used to extract the comprehensive features of news. Finally, a classifier is employed to determine the authenticity of the news. To verify the proposed framework, a test is conducted on the existing widely used datasets, and the experimental results demonstrate that this method is able to improve the detection performance for fake news across multiple domains. Moreover, even in datasets that lack domain labels, this method can still effectively transfer domain knowledge, which can educe the time consumed by tagging without sacrificing the detection accuracy.

Keywords: fake news, deep learning, natural language processing, multiple domains

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Authors: Jacqueline P. Davies

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Introduction: Student nurses must develop skills in observation, communication and reflection as well as public health knowledge from their first year of training. This paper will explain a method developed for students to collect their own findings about public health in urban areas. These areas are both rich in the history of old public health that informs the content of many traditional public health walks, but are also locations where new public health concerns about chronic disease are concentrated. The learning method explained in this paper enables students to collect their own data and write original work as first year students. Examples of their findings will be given. Methodology: In small groups, health care students are instructed to walk in neighbourhoods near to the hospitals they will soon attend as apprentice nurses. On their walks, they wander slowly, engage in conversations, and enter places open to the public. As they drift, they observe with all five senses in the real three dimensional world to collect data for their reflective accounts of old and new public health. They are encouraged to stop for refreshments and taste, as well as look, hear, smell, and touch while on their walk. They reflect as a group and later develop an individual reflective account in which they write up their deep reflections about what they observed on their walk. In preparation for their walk, they are encouraged to look at studies of quality of Life and other neighbourhood statistics as well as undertaking a risk assessment for their walk. Findings: Reflecting on their walks, students apply theoretical concepts around social determinants of health and health inequalities to develop their understanding of communities in the neighbourhoods visited. They write about the treasured historical architecture made of stone, bronze and marble which have outlived those who built them; but also how the streets are used now. The students develop their observations into thematic analyses such as: what we drink as illustrated by the empty coke can tossed into a now disused drinking fountain; the shift in home-life balance illustrated by streets where families once lived over the shop which are now walked by commuters weaving around each other as they talk on their mobile phones; and security on the street, with CCTV cameras placed at regular intervals, signs warning trespasses and barbed wire; but little evidence of local people watching the street. Conclusion: In evaluations of their first year, students have reported the health walk as one of their best experiences. The innovative approach was commended by the UK governing body of nurse education and it received a quality award from the nurse education funding body. This approach to education allows students to develop skills in the real world and write original work.

Keywords: education, innovation, nursing, urban

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: dynamic system modeling, neural network, normal equation, second order gradient descent

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Authors: Amal Machtalay

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In this survey, we aim to review the rapidly growing literature on numerical methods to solve different forms of mean field problems, namely mean field games (MFG), mean field controls (MFC), potential MFGs, and master equations, as well as their corresponding recent applications. Here, we distinguish two families of numerical methods: iterative methods based on mesh generation and those called mesh-free, normally related to neural networking and learning frameworks.

Keywords: mean-field games, numerical schemes, partial differential equations, complex systems, machine learning

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Authors: Ali M. Alsagheir

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Effective teaching is concerned to be one of the research fields of teaching, and its fundamental case is to reach the most successful ways that makes teaching fruitful. Undoubtedly, these methods are common factors between all parties who are concerned with the educational process such as instructors, directors, parents, and others. This study had aimed to recognize the cognitions of physical education supervisors and teachers for conceptions of effective teaching according to the interests theory. A questionnaire was used to collect data of the study; the sample contained 230 teachers and supervisors.The results were ended in: that the average of conceptions of effective teaching expressions for the sample of the study decreases at the progress through stages of teaching development in general. The study showed the absence of statistical indicator between teachers and supervisors at the core of both teaching principals and teaching tasks although the results showed that there are statistical indicators at the core of teaching achievements between supervisors and teachers in favor of supervisors. The study ended in to recommendations which can share in increasing the effectiveness of teaching such as: putting clear and specific standards for the effectiveness of teaching in which teacher's performance is based, constructing practical courses that focus on bringing on both supervisors and teachers with skills and strategies of effectiveness teaching, taking care of children achievement as an important factor and a strong indicator on effectiveness of teaching and learning.

Keywords: concerns theory, effective teaching, physical education, supervisors, teachers

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Authors: David Sinfield, Thomas Cochrane, Marcos Steagall

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While there is much hype around the potential and development of mobile virtual reality (VR), the two key critical success factors are the ease of user experience and the development of a simple user-generated content ecosystem. Educational technology history is littered with the debris of over-hyped revolutionary new technologies that failed to gain mainstream adoption or were quickly superseded. Examples include 3D television, interactive CDROMs, Second Life, and Google Glasses. However, we argue that this is the result of curriculum design that substitutes new technologies into pre-existing pedagogical strategies that are focused upon teacher-delivered content rather than exploring new pedagogical strategies that enable student-determined learning or heutagogy. Visual Communication design based learning such as Graphic Design, Illustration, Photography and Design process is heavily based on the traditional forms of the classroom environment whereby student interaction takes place both at peer level and indeed teacher based feedback. In doing so, this makes for a healthy creative learning environment, but does raise other issue in terms of student to teacher learning ratios and reduced contact time. Such issues arise when students are away from the classroom and cannot interact with their peers and teachers and thus we see a decline in creative work from the student. Using AR and VR as a means of stimulating the students and to think beyond the limitation of the studio based classroom this paper will discuss the outcomes of a student project considering the virtual classroom and the techniques involved. The Atelier learning environment is especially suited to the Visual Communication model as it deals with the creative processing of ideas that needs to be shared in a collaborative manner. This has proven to have been a successful model over the years, in the traditional form of design education, but has more recently seen a shift in thinking as we move into a more digital model of learning and indeed away from the classical classroom structure. This study focuses on the outcomes of a student design project that employed Augmented Reality and Virtual Reality technologies in order to expand the dimensions of the classroom beyond its physical limits. Augmented Reality when integrated into the learning experience can improve the learning motivation and engagement of students. This paper will outline some of the processes used and the findings from the semester-long project that took place.

Keywords: augmented reality, blogging, design in community, enhanced learning and teaching, graphic design, new technologies, virtual reality, visual communications

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Authors: Dua Hişam, Serhat İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: Deepa Kapoor, Rajshree Singh

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This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

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Authors: Maha Wiss, Wael Khreich

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Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

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Authors: Maria Vinca Novenia

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The number of school-aged children with autism in Indonesia has been increasing each year. Autism is a developmental disorder which can be diagnosed in childhood. One of the symptoms is the lack of communication skills. Music therapy is known as an effective treatment for children with autism. Music elements and structures create a good space for children with autism to express their feelings and communicate their thoughts. School-aged children are expected to be able to communicate non-verbally very well, but children with autism experience the difficulties of communicating non-verbally. The aim of this research is to analyze the significance of music therapy treatment to improve non-verbal communication tools for children with autism. This research informs teachers and parents on how music can be used as a media to communicate with children with autism. The qualitative method is used to analyze this research, while the result is described with the microanalysis technique. The result is measured specifically from the whole experiment, hours of every week, minutes of every session, and second of every moment. The samples taken are four school-aged children with autism in the age range of six to 11 years old. This research is conducted within four months started with observation, interview, literature research, and direct experiment. The result demonstrates that music therapy could be effectively used as a non-verbal communication tool for children with autism, such as changes of body gesture, eye contact, and facial expression.

Keywords: autism, improvisation, microanalysis, music therapy, nonverbal communication, school-aged

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Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors by Latour. The learning conditions are found to be distinguished by broad complexity characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation

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Authors: Merry Pearl Rupinta, Rivika Alda

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Inclusive education provides the same opportunity for all students regardless of the difficulties they encounter. Teaching English to learners with special education needs (LSENs) is a significant factor for learners to cope with the academic demands in the regular class. However, these special education (SPED) teachers lack specialized training to teach specific skills in English. Using purposive sampling, this study explored the lived experience of nine SPED teachers handling English to learners with intellectual disabilities from the four divisions of Region 10. An interview schedule, validated by experts, was used in conducting the investigation, where a semi-structured one-on-one interview was employed. The data were analyzed using Smith's (2009) five-step data analysis. The study highlighted themes on challenges in teaching English, coping strategies, adjusted classroom management, and inclusivity. The results suggest that SPED teachers' experience teaching English is a continuous and indefinite loop that continues until the primary goal of mainstreaming LSENs into the regular class is achieved. This study recommends that policymakers and curriculum developers focus their efforts on professional development through a series of training on various strategies and approaches in teaching English that can help SPED teachers provide a more effective and efficient teaching-learning experience.

Keywords: English language teaching, inclusive education, intellectual disability, special education

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Authors: Mamani Acurio Alex, Aguilar Alonso Igor

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The lack of interest and the lack of motivation are related. The lack of both in school generates serious problems such as school dropout or a low level of learning. Augmented reality has been very useful in different areas, and in this research, it was implemented in the area of education. Information necessary for the correct development of this mobile application with augmented reality was searched using six different research repositories. It was concluded that the application must be immersive, attractive, and fun for students, and the necessary technologies for its construction were defined.

Keywords: augmented reality, Vuforia, school interest, learning

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Authors: Şefika Dilek Güven, Gülden Küçükakça

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Objective: Learning the process of interaction with patient occurs within the process of nursing education. For this reason, it is considered to provide an opportunity for questioning and rearrangement of nursing education programs by assessing attitudes of nursing students towards caring nurse-patient interaction. Method: This is a descriptive study conducted in order to assess attitudes of nursing students towards caring nurse-patient interaction. The study was conducted with 318 students who were studying at nursing department of Semra and Vefa Küçük Health High School, Nevşehir Hacı Bektaş Veli University in 2015-2016 academic year and agreed to participate in the study. “Personal Information Form” prepared by the researchers utilizing the literature and “Caring Nurse-Patient Interaction Scale (CNPIS)”, who Turkish validity and reliability were conducted by Atar and Aştı, were used in the study. The Cronbach α coefficient of CNPIS was found as 0.973 in the study. Permissions of the institution and participants were received before starting to conduct study. Significance test of the difference between two means, analysis of variance, and correlation analysis were used to assess the data. Results: Average age of nursing students participating in the study was 20.72±1.91 and 74.8% were female, and 28.0% were the fourth-year students. 52.5% of the nursing students stated that they chose nursing profession willingly, 80.2% did not have difficulty in their interactions with patients, and 84.6% did not have difficulty in their social relationships. CNPIS total mean score of nursing students was found to be 295.31±40.95. When the correlation between total CNPIS mean score of the nursing students in terms of some variables was examined; it was determined there was a significant positive correlation between ages of the nursing students and total mean score of CNPIS (r=0.184, p=0.001). CNPIS total mean score was found to be higher in female students compared to male students, in 3rd–year students compared to students studying at other years, in those choosing their profession willingly compared to those choosing their profession unwillingly, in those not having difficulty in relations with the patients compared to those having difficulty, and in those not having difficulty in social relationships compared to those having difficulty. It was determined there was a significant difference between CNPIS total mean scores in terms of the year and state of having difficulty in social relationships (p<0,005). Conclusion: Nursing students had positive attitudes towards caring nurse-patient interactions, attitudes of nursing students, who were female, studying at 3rd year, chose nursing profession willingly, did not have difficulty in patient relations, and did not have difficulty in social relationships, towards caring nurse-patient interaction were found to be more positive. In the line with these results; it can be recommended to organize activities for introducing nursing profession to the youth preparing for the university, to use methods that will increase further communication skills to nursing students during their education, to support students in terms of communication skills, and to involve activities that will strengthen their social relationships.

Keywords: nurse-patient interaction, nursing student, patient, communication

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Authors: Aiydh Aljeddani, Fran Martin

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Sustainable human development is an essential component of a sustainable economic, social and environmental development. Addressing sustainable learning only through the addition of new teaching methods, or embedding certain approaches, is not sufficient on its own to support the goals of sustainable human development. This research project seeks to explore how the process of redesigning the current principles of curriculum based on the concept of sustainable learning could contribute to preparing a citizen who could later contribute towards sustainable human development. Multiple qualitative methodologies were employed in order to achieve the aim of this study. The main research methods were teachers’ field notes, artefacts, informal interviews (unstructured interview), a passive participant observation, a mini nominal group technique (NGT), a weekly diary, and weekly meeting. The study revealed that the integration of a curriculum for sustainable development, in addition to the use of innovative teaching approaches, highly valued by students and teachers in social studies’ sessions. This was due to the fact that it created a positive atmosphere for interaction and aroused both teachers and students’ interest. The content of the new curriculum also contributed to increasing students’ sense of shared responsibility through involving them in thinking about solutions for some global issues. This was carried out through addressing these issues through the concept of sustainable development and the theory of Thinking Activity in a Social Context (TASC). Students had interacted with sustainable development sessions intellectually and they also practically applied it through designing projects and cut-outs. Ongoing meetings and workshops to develop work between both the researcher and the teachers, and by the teachers themselves, played a vital role in implementing the new curriculum. The participation of teachers in the development of the project through working papers, exchanging experiences and introducing amendments to the students' environment was also critical in the process of implementing the new curriculum. Finally, the concept of sustainable learning can contribute to the learning outcomes much better than the current curriculum and it can better develop the learning objectives in educational institutions.

Keywords: redesigning, social studies and citizenship education curriculum, sustainable learning, thinking activity in a social context

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Authors: Nicholas V. Scott, Jack McCarthy

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Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

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Authors: Paulomi Polly Burey, Mark Lynch

Abstract:

It has been shown that laboratory activities can help cement understanding of theoretical concepts, but it is difficult to deliver such an activity to an online cohort and issues such as occupational health and safety in the students’ learning environment need to be considered. Chemistry, in particular, is one of the sciences where practical experience is beneficial for learning, however typical university experiments may not be suitable for the learning environment of a distance learner. Food provides an ideal medium for demonstrating chemical concepts, and along with a few simple physical and virtual tools provided by educators, analytical chemistry can be experienced by distance learners. Food chemistry experiments were designed to be carried out in a home-based environment that 1) Had sufficient scientific rigour and skill-building to reinforce theoretical concepts; 2) Were safe for use at home by university students and 3) Had the potential to enhance student learning by linking simple hands-on laboratory activities with high-level virtual science. Two main components of the resources were developed, a home laboratory experiment component, and a virtual laboratory component. For the home laboratory component, students were provided with laboratory kits, as well as a list of supplementary inexpensive chemical items that they could purchase from hardware stores and supermarkets. The experiments used were typical proximate analyses of food, as well as experiments focused on techniques such as spectrophotometry and chromatography. Written instructions for each experiment coupled with video laboratory demonstrations were used to train students on appropriate laboratory technique. Data that students collected in their home laboratory environment was collated across the class through shared documents, so that the group could carry out statistical analysis and experience a full laboratory experience from their own home. For the virtual laboratory component, students were able to view a laboratory safety induction and advised on good characteristics of a home laboratory space prior to carrying out their experiments. Following on from this activity, students observed laboratory demonstrations of the experimental series they would carry out in their learning environment. Finally, students were embedded in a virtual laboratory environment to experience complex chemical analyses with equipment that would be too costly and sensitive to be housed in their learning environment. To investigate the impact of the intervention, students were surveyed before and after the laboratory series to evaluate engagement and satisfaction with the course. Students were also assessed on their understanding of theoretical chemical concepts before and after the laboratory series to determine the impact on their learning. At the end of the intervention, focus groups were run to determine which aspects helped and hindered learning. It was found that the physical experiments helped students to understand laboratory technique, as well as methodology interpretation, particularly if they had not been in such a laboratory environment before. The virtual learning environment aided learning as it could be utilized for longer than a typical physical laboratory class, thus allowing further time on understanding techniques.

Keywords: chemistry, food science, future pedagogy, STEM education

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Authors: Robert Jesiolowski, Monique Jesiolowski

Abstract:

Today more than ever before, we have access to new technologies which provide unforeseen opportunities for educators to pursue in online education. It starts with an idea, but that needs to be coupled with the right team of experts willing to take big risks and put in the hard work to build something different. An instructional design team was empowered to reimagine an Introduction to Sociology university course as a Game-Based Learning (GBL) experience utilizing cutting edge Virtual Reality (VR) technology. The result was a collaborative process that resulted in a type of learning based in Game theory, Method of Loci, and VR Immersion Simulations to promote deeper retention of core concepts. The team deconstructed the way that university courses operated, in order to rebuild the educational process in a whole learner-centric manner. In addition to a review of the build process, this paper will explore the results of in-course surveys completed by student participants.

Keywords: higher education, innovation, virtual reality, game-based learning, loci method

Procedia PDF Downloads 69