Search results for: task based learning

Authors: Andrea Fiorista

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The learning of prepositions is a quite problematic aspect in foreign language instruction, and Italian is certainly not an exception. In their prototypical function, prepositions express schematic relations of two entities in a highly abstract, typically image-schematic way. In other terms, prepositions assume concepts such as directionality, collocation of objects in space and time and, in Cognitive Linguistics’ terms, the position of a trajector with respect to a landmark. Learners of different native languages may conceptualize them differently, implying that they are supposed to operate a recategorization (or create new categories) fitting with the target language. However, most current Italian Foreign/Second Language handbooks and didactic grammars do not facilitate learners in carrying out the task, as they tend to provide partial and idiosyncratic descriptions, with the consequent learner’s effort to memorize them, most of the time without success. In their prototypical meaning, prepositions are used to specify precise topographical positions in the physical environment which become less and less accurate as they radiate out from what might be termed a concrete prototype. According to that, the present study aims to elaborate a cognitive and conceptually well-grounded analysis of some extensive uses of the Italian preposition a, in order to propose effective pedagogical solutions in the Teaching/Learning process. Image schemas, cognitive metaphors and embodiment represent efficient cognitive tools in a task like this. Actually, while learning the merely spatial use of the preposition a (e.g. Sono a Roma = I am in Rome; vado a Roma = I am going to Rome,…) is quite straightforward, it is more complex when a appears in constructions such as verbs of motion +a + infinitive (e.g. Vado a studiare = I am going to study), inchoative periphrasis (e.g. Tra poco mi metto a leggere = In a moment I will read), causative construction (e.g. Lui mi ha mandato a lavorare = He sent me to work). The study reports data from a teaching intervention of Focus on Form, in which a basic cognitive schema is used to facilitate both teachers and students to respectively explain/understand the extensive uses of a. The educational material employed translates Cognitive Linguistics’ theoretical assumptions, such as image schemas and cognitive metaphors, into simple images or proto-scenes easily comprehensible for learners. Illustrative material, indeed, is supposed to make metalinguistic contents more accessible. Moreover, the concept of embodiment is pedagogically applied through activities including motion and learners’ bodily involvement. It is expected that replacing rote learning with a methodology that gives grammatical elements a proper meaning, makes learning process more effective both in the short and long term.

Keywords: cognitive approaches to language teaching, image schemas, embodiment, Italian as FL/SL

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Authors: Bunki Enid Pitsoane

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This study was influenced by the radical change in the tutorial system of UNISA, immigrating from face to face to E-tutoring. The study was undertaken to investigate the perceptions, experiences, and views of E-tutors in relation to active learning. The study is aimed at capturing the views and experiences of E-tutors as they are deemed to implement active learning within their E-tutoring. The problem was traced from Developmental and behaviorist’s theorists perspective and factors related to perception, experience, and views of E-tutors on active learning. The research is aligned with the views of constructivism which put more emphasis on situated learning, chaos, and digital factors. The basis of the theory is that learning is developmental, situational and context-sensitive and also digital. The theorists further purports that the tutor’s conception of teaching and learning influence their tutoring style. In order to support or reject the findings of the literature study, qualitative research in the form of interviews and document analysis were conducted. The sample of the study constituted of 10 E-tutors who are involved in tutoring modules from the College of Education. The identified E-tutors were randomly selected based on their availability. The data concerning E-tutors perception and experience was analysed and interpreted. The results of the empirical study indicated that some tutors are struggling to implement active learning because they are digital immigrants or they lack in digital knowledge which affect productivity in their teaching.

Keywords: E-Tutoring, active learning, perceptions, views

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Min Kyeong Cha, Ju Yeon Mun, Seong Baeg Kim

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Recently, ‘play of learning’ became important and is emphasized as a useful learning tool. Therefore, interest in edutainment contents is growing. Storytelling is considered first as a method that improves the transmission of information and learner's interest when planning edutainment contents. In this study, we designed edutainment contents in the form of an adventure game that applies the storytelling method. This content provides questions and items constituted dynamically and reorganized learning contents through analysis of test results. It allows learners to solve various questions through effective iterative learning. As a result, the learners can reach mastery learning.

Keywords: storytelling, edutainment, mastery learning, computer operating principle

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Authors: Roula Kitsiou, Sofia Tsioli, Eleni Gana

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The current sociopolitical realities (displacement, encampment, and resettlement) refugees experience in Greece are a quite complex issue. Their educational and social ‘integration’ is characterized by transition, insecurity, and constantly changing needs. Based on the current research data, technology and more specifically mobile phones are one of the most important resources for refugees, regardless of their levels of conventional literacy. The proposed paper discusses the challenges encountered during the design and implementation of the educational Action 16 ‘Language Education for Adult Refugees’. Action 16 is one of the 24 Actions of the Project PRESS (Provision of Refugee Education and Support Scheme), funded by the Hellenic Open University (2016-2017). Project PRESS had two main objectives: a) to address the educational and integration needs of refugees in transit, who currently reside in Greece, and b) implement research-based educational interventions in online and offline sites. In the present paper, the focus is on reflection and discussion about the challenges and the potential of integrating technology in language learning for a target-group with many specific needs, which have been recorded in field notes among other research tools (ethnographic data) used in the context of PRESS. Action 16, explores if and how technology enhanced language activities in real-time and place mediated through teachers, as well as an autonomous computer-mediated learning space (moodle platform and application) builds on and expands the linguistic, cultural and digital resources and repertoires of the students by creating collaborative face-to-face and digital learning spaces. A broader view on language as a dynamic puzzle of semiotic resources and processes based on the concept of translanguaging is adopted. Specifically, designing the blended learning environment we draw on the construct of translanguaging a) as a symbolic means to valorize students’ repertoires and practices, b) as a method to reach to specific applications of a target-language that the context brings forward (Greek useful to them), and c) as a means to expand refugees’ repertoires. This has led to the creation of a learning space where students' linguistic and cultural resources can find paths to expression. In this context, communication and learning are realized by mutually investing multiple aspects of the team members' identities as educational material designers, teachers, and students on the teaching and learning processes. Therefore, creativity, humour, code-switching, translation, transference etc. are all possible means that can be employed in order to promote multilingual communication and language learning towards raising intercultural awareness in a critical digital pedagogy context. The qualitative analysis includes critical reflection on the developed educational material, team-based reflexive discussions, teachers’ reports data, and photographs from the interventions. The endeavor to involve women and men with a refugee background into a blended learning experience was quite innovative especially for the Greek context. It reflects a pragmatist ethos of the choices made in order to respond to the here-and-now needs of the refugees, and finally it was a very challenging task that has led all actors involved into Action 16 to (re)negotiations of subjectivities and products in a creative and hopeful way.

Keywords: blended learning, integration, language education, refugees

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Authors: Dorit Alt, Nirit Raichel

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Although university teaching is claimed to have a special task to support students in adopting ways of thinking and producing new knowledge anchored in scientific inquiry practices, it is argued that students' habits of learning are still overwhelmingly skewed toward passive acquisition of knowledge from authority sources rather than from collaborative inquiry activities.This form of instruction is criticized for encouraging students to acquire inert knowledge that can be used in instructional settings at best, however cannot be transferred into real-life complex problem settings. In order to overcome this critical inadequacy between current educational goals and instructional methods, the LLAF consortium (including 16 members from 8 countries) is aimed at developing updated instructional practices that put a premium on adaptability to the emerging requirements of present society. LLAF has created a practical guide for teachers containing updated pedagogical strategies and assessment tools, based on the constructivist approach for learning that put a premium on adaptability to the emerging requirements of present society. This presentation will be limited to teachers' education only and to the contribution of the project in providing a scale designed to measure the extent to which the constructivist activities are efficiently applied in the learning environment. A mix-method approach was implemented in two phases to construct the scale: The first phase included a qualitative content analysis involving both deductive and inductive category applications of students' observations. The results foregrounded eight categories: knowledge construction, authenticity, multiple perspectives, prior knowledge, in-depth learning, teacher- student interaction, social interaction and cooperative dialogue. The students' descriptions of their classes were formulated as 36 items. The second phase employed structural equation modeling (SEM). The scale was submitted to 597 undergraduate students. The goodness of fit of the data to the structural model yielded sufficient fit results. This research elaborates the body of literature by adding a category of in-depth learning which emerged from the content analysis. Moreover, the theoretical category of social activity has been extended to include two distinctive factors: cooperative dialogue and social interaction. Implications of these findings for the LLAF project are discussed.

Keywords: constructivist learning, higher education, mix-methodology, structural equation modeling

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Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

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This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: M. Greeshma, V. Ashvini, P. Jayarekha

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Project based learning (PBL) is a student-driven educational framework and offers the student an opportunity for in-depth investigations of courses. This paper presents the need of PBL in engineering education for the student to graduate with a capacity to design and implement complex problems. The implementation strategy of PBL and its related challenges are presented. The case study that energizes the engineering curriculum with a relevance to the real-world of technology along with its benefits to the students is also included.

Keywords: PBL, engineering education, curriculum, implement complex

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: K. Z. Tang, K. Ameek, K. Kuang

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Rapid product development cycles and changing economic conditions compel businesses to find new ways to stay relevant and effective. One of the ways which many companies have adopted is to spur innovations within the various team-based units in the organization. It would be relevant and important to ensure our graduates are ready to excel in such evolving conditions within their professional eco-systems. However, it is not easy to understand the interplays of nurturing team innovation and improving students’ learning, in the context of engineering education. In this study, we seek to understand team innovation and explore ways to improve students’ performance and learning, via motivation and mentorship. Learning goals from a group of students are collected during a carefully designed two-week long summer programme to provide insights on the main themes, within the context of learning and working in a team.

Keywords: team innovation, mentorship, motivation, learning

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Authors: Zolzaya Badmaavanchig, Shoko Miyamoto

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In recent years, universal design for learning (hereinafter referred to as "UDL"), which aims to establish an inclusive education system and to make all children, regardless of their disabilities, experts in learning, has been attracting attention, and there have been some attempts to incorporate it into regular classrooms where children with developmental disabilities and those who show such tendencies are enrolled. The purpose of this study was to examine the effectiveness and challenges of implementing UDL in Japanese elementary schools based on the previous literature. As a method, we first searched for articles on UDL for learning and UDL in the classroom from 2010 to 2022. In addition, we selected practice studies that targeted children with special educational support needs and the classroom as a whole. In response to the extracted literature, this bridge examined the following five perspectives: (1) subjects and grades in which UDL was practiced, (2) methods to grasp the actual conditions of the children, (3) consideration for children with special needs during class, (4) form of class, and (5) effects of the practice. Based on the results, we would like to present issues related to future UDL efforts in Japanese elementary schools.

Keywords: universal design for learning, regular elementary school class, children with special education needs, special educational support

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Mst. Tuhin Akter, Sharun Akter Khushbu, S. M. Shaqib

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A real-time system architecture is highly effective for monitoring and detecting various damaged products or fruits that may deteriorate over time or become infected with diseases. Deep learning models have proven to be effective in building such architectures. However, building a deep learning model from scratch is a time-consuming and costly process. A more efficient solution is to utilize deep neural network (DNN) based transfer learning models in the real-time monitoring architecture. This study focuses on using a novel strawberry dataset to develop effective transfer learning models for the proposed real-time monitoring system architecture, specifically for evaluating and detecting strawberry freshness. Several state-of-the-art transfer learning models were employed, and the best performing model was found to be Xception, demonstrating higher performance across evaluation metrics such as accuracy, recall, precision, and F1-score.

Keywords: strawberry freshness evaluation, deep neural network, transfer learning, image augmentation

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Authors: Yasith Nayana, Janani Manamperuma, Lalindi Amarasinghe, Sasanka Kodithuwakku

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Educational games are popular among current e-learning systems. The approach to education through interactive media is expected to motivate students and encourage participation and engagement. ‘Kalayathra’ is an adaptive, player centered e-learning 3D game. The game identifies the player’s personality and adapt the gaming environment according to the player’s preference. Our platform measures the student’s performance and support learning through player assessment. Player experience is a good measure of the level of fun and education presented to players. To assess the level of playability we introduce an educational playability model. ‘Kalayathra’ is developed according to the GCE O/L syllabus and teaching guide in Sri Lankan education system. The game is capable of guiding players into the environment and aid them in tasks and activities depending on how much the player requires help.

Keywords: e-learning, games, adaptive, personality, gamification, player experience

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Authors: Samia Hassan, Fouzia Latif

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In many countries, education is still far from being a knowledge industry in the sense of own practices that are not yet being transformed by knowledge about the efficacy of those practices. The core question of this paper is why students get bored in class? Have we balanced between the creation and advancement of an engaging learning community and effective learning environment? And between, giving kids confidence to achieve their maximum and potential goals, we sand managing student’s behavior. We conclude that creating a positive learning environment enhances opportunities for young children to feel safe, secure, and to supported in order to do their best learning. Many factors can use in classrooms aid to the positive environment like course content, class preparation, and behavior.

Keywords: effective, environment, learning, positive

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Authors: Jonathan Ham, Christopher Koch

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There are consistently observed associations between certain odors and colors, and there is an association between the ability to imagine vivid visual objects and imagine vivid odors. However, little has been done to investigate how the associations between odors and visual information effect visual processes. This study seeks to understand the relationship between odor imaging, color associations, and visual attention by utilizing a Stroop-task based on common odor-color associations. This Stroop-task was designed using three fruits with distinct odors that are associated with the color of the fruit: lime with green, strawberry with red, and lemon with yellow. Each possible word-color combination was presented in the experimental trials. When the word matched the associated color (lime written in green) it was considered congruent; if it did not, it was considered incongruent (lime written in red or yellow). In experiment I (n = 34) participants were asked to both imagine the odor of the fruit on the screen and identify which fruit it was, and each word-color combination was presented 20 times (a total of 180 trials, with 60 congruent and 120 incongruent instances). Response time and error rate of the participant responses were recorded. There was no significant difference in either measure between the congruent and incongruent trials. In experiment II participants (n = 18) followed the identical procedure as in the previous experiment with the addition of an odorant in the room. The odorant (orange) was not the fruit or color used in the experimental trials. With a fruit-based odorant in the room, the response times (measured in milliseconds) between congruent and incongruent trials were significantly different, with incongruent trials (M = 755.919, SD = 239.854) having significantly longer response times than congruent trials (M = 690.626, SD = 198.822), t (1, 17) = 4.154, p < 0.01. This suggests that odor imagery does affect visual attention to colors, and the ability to inhibit odor-color associations; however, odor imagery is difficult and appears to be facilitated in the presence of a related odorant.

Keywords: odor-color associations, odor imagery, visual attention, inhibition

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Authors: Mariana Volpini, Volker Bartenbach, Marcos Pinotti, Robert Riener

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Restoration of gait ability is an important task in the rehabilitation of people with neurological disorders presenting a great impact in the quality of life of an individual. Based on the motor learning concept, robotic assisted treadmill training has been introduced and found to be a feasible and promising therapeutic option in neurological rehabilitation but unfortunately it is not available for most patients in developing countries due to the high cost. This paper presents the concept of a low cost rehabilitation robot to help consolidate the robotic-assisted gait training as a reality in clinical practice in most countries. This work indicates that it is possible to build a simpler rehabilitation device respecting the physiological trajectory of the ankle.

Keywords: bioengineering, gait therapy, low cost rehabilitation robot, rehabilitation robotics

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Kafi Razzaq Ahmed

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Speaking fluently in a second language requires vocabulary, grammar, and pronunciation skills. Teaching the English language entails teaching pronunciation. In professional literature, there have been a lot of attempts to integrate technology into improving the pronunciation of learners. The technique is also neglected in Kurdish contexts, Salahaddin University – Erbil included. Thus, the main aim of the research is to point out the efficiency of using video materials for both language teachers and learners within and beyond classroom learning and teaching environments to enhance student's pronunciation. To collect practical data, a research project has been designed. In subsequent research, a posttest will be administered after each lesson to 100 first-year students at Salahaddin University-Erbil English departments. All students will be taught the same material using different methods, one based on video materials and the other based on the traditional approach to teaching pronunciation. Finally, the results of both tests will be analyzed (also knowing the attitudes of both the teachers and the students about both lessons) to indicate the impact of using video in the process of teaching and learning pronunciation.

Keywords: video, pronunciation, teaching, learning

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Authors: Ying Zhou, Jian-Hua Wang

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Based upon the self-determination theory and self-regulated learning theory, this study examined the predictiveness of goal orientation and self-regulated learning strategies on academic achievement of adult students in distance learning. The results show a positive relation between goal orientation and the use of self-regulated strategies, and academic achievements. A significant and positive indirect relation of mastery goal orientation through self-regulated learning strategies was also found. In addition, results pointed to a positive indirect impact of performance-approach goal orientation on academic achievement. The effort regulation strategy fully mediated this relation. The theoretical and instructional implications are discussed. Interventions can be made to motivate students’ mastery or performance approach goal orientation and help them manage their time or efforts.

Keywords: goal orientation, self-regulated strategies, achievement, adult distance students

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Authors: B. Remya Mohan, Kamal Bijlani, R. Jayakrishnan

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Visualization in an educational context provides the learner with visual means of information. Conceptualizing certain circumstances such as consequences of smoking can be done more effectively with the help of the technology, Augmented Reality (AR). It is a new methodology for effective learning. This paper proposes an approach on how AR based on Marker Technology simulates the harmful effects of smoking and its consequences using Unity 3D game engine. The study also illustrates the impact of AR technology on students for better learning. AR technology can be used as a method to improve learning.

Keywords: augmented reality, marker technology, multi-platform, virtual buttons

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Authors: George Oliveira, Luana D. Fronza, Luiza Medeiros, Patricia D. M. Plentz

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The research presented in this article is part of a wide project that proposes a scheduling system for multi-robots in intelligent warehouses employing multi-robot path-planning (MPP) and multi-robot task allocation (MRTA) to reconcile multiple restrictions (task delivery time, task priorities, charging capacity, and robots battery capacity). We present the software component capable of interconnecting an open streaming processing architecture and robot operating system (ROS), ensuring communication and message exchange between robots and the environment in which they are inserted. Simulation results show the good performance of our proposed technique for connecting ROS and streaming platforms.

Keywords: complex distributed systems, mobile robots, smart warehouses, streaming platforms

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Authors: Jacqueline Mary Jepson

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This article provides a case study centred on the development of 13 video episodes which have been created to enhance student engagement with a post graduate online course in Project Management. The student group was unique as their online course needed to provide for asynchronistic learning and an adult learning pedagogy. In addition, students had come from a wide range professional backgrounds, with some having no Project Management experience, while others had 20 years or more. Students had to gain an understanding of an advanced body of knowledge and the course needed to achieve the academic requirements to qualify individuals to apply their learning in a range of contexts for professional practice and scholarship. To achieve this, a 13 episode case study was developed along with supportive learning materials based on the relocation of a zoo. This unique project provided a learning environment where the project could evolve over each video episode demonstrating the application of Project Management methodology which was then tied into the learning outcomes for the course and the assessment tasks. Discussion forums provided a way for students to converse and demonstrate their own understanding of content and how Project Management methodology can be applied.

Keywords: project management, adult learning, video case study, asynchronistic education

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Authors: Mauro Callejas-Cuervo, Andrea Catherine Alarcon-Aldana, Lorena Paola Castillo-Guerra

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The software industry requires highly-trained professionals, capable of developing the roles integrated in the cycle of software development. That is why a large part of the task is the responsibility of higher education institutions; often through a curriculum established to orientate the academic development of the students. It is so that nowadays there are different models that support proposals for the improvement of the curricula for the area of Software Engineering, such as ACM, IEEE, ABET, Swebok, of which the last stands out, given that it manages and organises the knowledge of Software Engineering and offers a vision of theoretical and practical aspects. Moreover, it has been applied by different universities in the pursuit of achieving coverage in delivering the different topics and increasing the professional quality of future graduates. This research presents the structure of teaching and learning guides from the objectives of training and methodological strategies immersed in the levels of learning of Bloom’s taxonomy with which it is intended to improve the delivery of the topics in the area of Requirements Engineering. Said guides were implemented and validated in a course of Requirements Engineering of the Systems and Computer Engineering programme in the Universidad Pedagógica y Tecnológica de Colombia (Pedagogical and Technological University of Colombia) using a four stage methodology: definition of the evaluation model, implementation of the guides, guide evaluation, and analysis of the results. After the collection and analysis of the data, the results show that in six out of the seven topics proposed in the Swebok guide, the percentage of students who obtained total marks within the 'High grade' level, that is between 4.0 and 4.6 (on a scale of 0.0 to 5.0), was higher than the percentage of students who obtained marks within the 'Acceptable' range of 3.0 to 3.9. In 86% of the topics and the strategies proposed, the teaching and learning guides facilitated the comprehension, analysis, and articulation of the concepts and processes of the students. In addition, they mainly indicate that the guides strengthened the argumentative and interpretative competencies, while the remaining 14% denotes the need to reinforce the strategies regarding the propositive competence, given that it presented the lowest average.

Keywords: pedagogic guide, pedagogic strategies, requirements engineering, Swebok, teaching-learning process

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Authors: Kai Yip Michael Tsang

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Science writing has played a crucial part in science assessments. This paper reports a study in an area that has received little research attention – how Language across the Curriculum (LAC, i.e. science language and literacy) learning activities in science lessons can increase the science knowledge development of English as a foreign language (EFL) students in Hong Kong. The data comes from a school-based interventional study in chemistry classrooms, with written data from questionnaires, assessments and teachers’ logs and verbal data from interviews and classroom observations. The effectiveness of the LAC teaching and learning activities in various chemistry classrooms were compared and evaluated, with discussion of some implications. Students in the treatment group with lower achieving students received LAC learning and teaching activities while students in the control group with higher achieving students received conventional learning and teaching activities. After the study, they performed better in control group in formative assessments. Moreover, they had a better attitude to learning chemistry content with a richer language support. The paper concludes that LAC teaching and learning activities yielded positive learning outcomes among chemistry learners with low English ability.

Keywords: science learning and teaching, content and language integrated learning, language across the curriculum, English as a foreign language

Procedia PDF Downloads 185

Authors: Jaya Mathew

Abstract:

Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

Procedia PDF Downloads 370

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

Abstract:

Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Muzamil Mahmood, Afshan Naseem, Muhammad Zeeshan Mirza, Yasir Ahmad, Masood Raza

Abstract:

The purpose of this research is to analyze how aviation maintenance workers’ characteristics and work demand affect their development of work-related musculoskeletal disorders (WMSDs). Guided by literature on task characteristics, work demand, and WMSDs, data is collected from 128 aviation maintenance workers of private and public airlines. Data is then analyzed through descriptive and inferential statistics. It is found that task characteristics have a significant positive effect on WMSDs and an increase in tasks performed by aviation maintenance workers leads to increase in WMSDs. Work demand did not have a significant effect on WMSDs. The task characteristics of aviation maintenance workers moderates the relationship between their work demand and WMSDs. This reveals that task characteristics of aviation maintenance workers enhance the effect of work demand on WMSDs. The task characteristics of aviation maintenance workers are challenging and unpredictable. Subsequently, WMSDs are prevalent among aviation maintenance workers. The work demand of aviation maintenance workers does not influence their development of WMSDs. Pakistan Civil Aviation Authority should minimize the intensity of tasks assigned to aviation maintenance workers by introducing work dynamisms such as task sharing, job rotation, and probably teleworking to enhance flexibility. Human Resource and Recruitment Department need to consider the ability and fitness levels of potential aviation maintenance workers during recruitment. In addition, regular physical activities and ergonomic policies should be put in place by the management of the Pakistan Civil Aviation Authority to reduce the incidences of WMSDs.

Keywords: work related musculoskeletal disorders, ergonomics, occupational health and safety, human factors

Procedia PDF Downloads 152