Search results for: learning technology

Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Paulomi Polly Burey, Mark Lynch

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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: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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Authors: Georges Bou Ghantous

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This literature review examines the transformative impact of Artificial Intelligence (AI) on higher education, highlighting both the potential benefits and challenges associated with its adoption. The review reveals that AI significantly enhances personalized learning by tailoring educational experiences to individual student needs, thereby boosting engagement and learning outcomes. Automated grading systems streamline assessment processes, allowing educators to focus on improving instructional quality and student interaction. AI's data-driven insights provide valuable analytics, helping educators identify trends in at-risk students and refine teaching strategies. Moreover, AI promotes enhanced instructional innovation through the adoption of advanced teaching methods and technologies, enriching the educational environment. Administrative efficiency is also improved as AI automates routine tasks, freeing up time for educators to engage in research and curriculum development. However, the review also addresses the challenges that accompany AI integration, such as data privacy concerns, algorithmic bias, dependency on technology, reduced human interaction, and ethical dilemmas. This balanced exploration underscores the need for careful consideration of both the advantages and potential hurdles in the implementation of AI in higher education.

Keywords: administrative efficiency, data-driven insights, data privacy, ethical dilemmas, higher education, personalized learning

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Authors: Kaycee Bills

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Action research is a method of inquiry useful in solving social problems in social work. This study seeks to address a significant problem: higher education’s use of traditional instructional methods in social work education. Ineffective techniques, such as lecturing, fail to account for students’ variable learning needs. In contrast to traditional pedagogy, universal design for learning (UDL) is a robust framework that '[improves] and [optimizes] teaching and learning for all people' (CAST, 2018), including students with disabilities. For this project, the research team interviewed the UDL and Accessibility Specialist at their institution for two reasons: (1) to learn how to implement UDL practices in their classrooms, and in turn, (2) to motivate other faculty members at their institution to consider enacting UDL principles. A thematic analysis of the interview’s transcript reveals themes relevant to practicing UDL. Implications for future practice, as well as the researcher’s reflections on the research process, are shared in the discussion section.

Keywords: disabilities, higher education, inclusive education, universal design for learning

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Authors: Komal Ghafoor, Tauqir Ahmad, Murtaza Hanif, Hira Zaheer

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Assistive technology has been developed to support visually impaired people in their social interactions. Conversation assistive technology is designed to enhance communication skills, facilitate social interaction, and improve the quality of life of visually impaired individuals. This technology includes speech recognition, text-to-speech features, and other communication devices that enable users to communicate with others in real time. The technology uses natural language processing and machine learning algorithms to analyze spoken language and provide appropriate responses. It also includes features such as voice commands and audio feedback to provide users with a more immersive experience. These technologies have been shown to increase the confidence and independence of visually impaired individuals in social situations and have the potential to improve their social skills and relationships with others. Overall, conversation-assistive technology is a promising tool for empowering visually impaired people and improving their social interactions. One of the key benefits of conversation-assistive technology is that it allows visually impaired individuals to overcome communication barriers that they may face in social situations. It can help them to communicate more effectively with friends, family, and colleagues, as well as strangers in public spaces. By providing a more seamless and natural way to communicate, this technology can help to reduce feelings of isolation and improve overall quality of life. The main objective of this research is to give blind users the capability to move around in unfamiliar environments through a user-friendly device by face, object, and activity recognition system. This model evaluates the accuracy of activity recognition. This device captures the front view of the blind, detects the objects, recognizes the activities, and answers the blind query. It is implemented using the front view of the camera. The local dataset is collected that includes different 1st-person human activities. The results obtained are the identification of the activities that the VGG-16 model was trained on, where Hugging, Shaking Hands, Talking, Walking, Waving video, etc.

Keywords: dataset, visually impaired person, natural language process, human activity recognition

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Authors: Michele Gattullo, Vito M. Manghisi, Alessandro Evangelista, Enricoandrea Laviola

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In this work, we explored the use of Augmented Reality (AR) to support students in laboratory lectures in Distance Learning (DL), designing an application that proved to be ready for use next semester. AR could help students in the understanding of complex concepts as well as increase their motivation in the learning process. However, despite many prototypes in the literature, it is still less used in schools and universities. This is mainly due to the perceived limited advantages to the investment costs, especially regarding changes needed in the teaching modalities. However, with the spread of epidemiological emergency due to SARS-CoV-2, schools and universities were forced to a very rapid redefinition of consolidated processes towards forms of Distance Learning. Despite its many advantages, it suffers from the impossibility to carry out practical activities that are of crucial importance in STEM ("Science, Technology, Engineering e Math") didactics. In this context, AR perceived advantages increased a lot since teachers are more prepared for new teaching modalities, exploiting AR that allows students to carry on practical activities on their own instead of being physically present in laboratories. In this work, we designed an AR application for the support of engineering students in the understanding of assembly drawings of complex machines. Traditionally, this skill is acquired in the first years of the bachelor's degree in industrial engineering, through laboratory activities where the teacher shows the corresponding components (e.g., bearings, screws, shafts) in a real machine and their representation in the assembly drawing. This research aims to explore the effectiveness of AR to allow students to acquire this skill on their own without physically being in the laboratory. In a preliminary phase, we interviewed students to understand the main issues in the learning of this subject. This survey revealed that students had difficulty identifying machine components in an assembly drawing, matching between the 2D representation of a component and its real shape, and understanding the functionality of a component within the machine. We developed a mobile application using Unity3D, aiming to solve the mentioned issues. We designed the application in collaboration with the course professors. Natural feature tracking was used to associate the 2D printed assembly drawing with the corresponding 3D virtual model. The application can be displayed on students’ tablets or smartphones. Users could interact with selecting a component from a part list on the device. Then, 3D representations of components appear on the printed drawing, coupled with 3D virtual labels for their location and identification. Users could also interact with watching a 3D animation to learn how components are assembled. Students evaluated the application through a questionnaire based on the System Usability Scale (SUS). The survey was provided to 15 students selected among those we participated in the preliminary interview. The mean SUS score was 83 (SD 12.9) over a maximum of 100, allowing teachers to use the AR application in their courses. Another important finding is that almost all the students revealed that this application would provide significant power for comprehension on their own.

Keywords: augmented reality, distance learning, STEM didactics, technology in education

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Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

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Authors: M. Aherrahrou

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Moroccan education is currently facing many difficulties and problems due to traditional methods of teaching. Neuro -Linguistic Programming (NLP) appears to hold much potential for education at all levels. In this paper, the major aim is to explore the effect of certain Neuro -Linguistic Programming techniques in one educational institution in Morocco. Quantitative and Qualitative methods are used. The findings prove the effectiveness of this new approach regarding Moroccan education, and it is a promising tool to improve the quality of learning.

Keywords: learning and teaching environment, Neuro- Linguistic Programming, education, quality of learning

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Authors: Dian Guan

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With the wide application of multimedia and the Internet, the development of teaching theories, and the implementation of teaching reforms, many different university English classroom teaching modes have emerged. The university English teaching mode is changing from the traditional teaching mode based on conversation and text to the multimodal English teaching mode containing discussion, pictures, audio, film, etc. Applying university English teaching models is conducive to cultivating lifelong learning skills. In addition, lifelong learning skills can also be called learners' autonomous learning skills. Learners' independent learning ability has a significant impact on English learning. However, many university students, especially art and design students, don't know how to learn individually. When they become university students, their English foundation is a relative deficiency because they always remember the language in a traditional way, which, to a certain extent, neglects the cultivation of English learners' independent ability. As a result, the autonomous learning ability of most university students is not satisfactory. The participants in this study were 60 students and one teacher in their first year at a university in western China. Two observations and interviews were conducted inside and outside the classroom to understand the impact of a multimodal teaching model of university English on students' autonomous learning ability. The results were analyzed, and it was found that the multimodal teaching model of university English significantly affected learners' autonomy. Incorporating classroom presentations and poster exhibitions into multimodal teaching can increase learners' interest in learning and enhance their learning ability outside the classroom. However, further exploration is needed to develop multimodal teaching materials and evaluate multimodal teaching outcomes. Despite the limitations of this study, the study adopts a scientific research method to analyze the impact of the multimodal teaching mode of university English on students' independent learning ability. It puts forward a different outlook for further research on this topic.

Keywords: art university, EFL education, learner autonomy, multimodal pedagogy

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Authors: Joanna K. Konstantinou

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The aim of this study is to explore the need of small and medium-sized businesses in tourism and hospitality industry to adopt technology and enhance their degree of digitalization, along with the main benefits enjoyed by technology and the main challenges that hinder its adoption. Within a hermeneutic phenomenological perspective, semi-structured interviews were conducted with three hotel owners and the focus was to identify the main reasons of adoption of technology, enablers and barriers. The findings were grouped with the goal of identifying typology of business practices in using and adopting technology.

Keywords: digitization, SMEs, tourism and hospitality, challenges, benefits

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: Elena Krelja Kurelović, Jasminka Tomljanović, Vlatka Davidović

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The development of web technologies and mobile devices makes creating, accessing, using and sharing information or communicating with each other simpler every day. However, while the amount of information constantly increasing it is becoming harder to effectively organize and find quality information despite the availability of web search engines, filtering and indexing tools. Although digital technologies have overall positive impact on students’ lives, frequent use of these technologies and digital media enriched with dynamic hypertext and hypermedia content, as well as multitasking, distractions caused by notifications, calls or messages; can decrease the attention span, make thinking, memorizing and learning more difficult, which can lead to stress and mental exhaustion. This is referred to as “information overload”, “information glut” or “information anxiety”. Objective of this study is to determine whether students show signs of information overload and to identify the possible predictors. Research was conducted using a questionnaire developed for the purpose of this study. The results show that students frequently use technology (computers, gadgets and digital media), while they show moderate level of information literacy. They have sometimes experienced symptoms of information overload. According to the statistical analysis, higher frequency of technology use and lower level of information literacy are correlated with larger information overload. The multiple regression analysis has confirmed that the combination of these two independent variables has statistically significant predictive capacity for information overload. Therefore, the information science teachers should pay attention to improving the level of students’ information literacy and educate them about the risks of excessive technology use.

Keywords: information overload, computers, mobile devices, digital media, information literacy, students

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Authors: Valerie Yocco Rossi

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Objective: The author will share why differentiation is necessary for all classrooms as well as strategies for differentiating content, process, and product. Through learning how to differentiate, teachers will be able to create activities and assessments to meet the abilities, readiness levels, and interests of all learners. Content and Purpose: This work will focus on how to create a learning experience for students that recognizes their different interests, abilities, and readiness levels by differentiating content, process, and product. Likewise, the best learning environments allow for choice. Choice boards allow students to select tasks based on interests. There can be challenging and basic tasks to meet the needs of various abilities. Equally, rubrics allow for personalized and differentiated assessments based on readiness levels and cognitive abilities. The principals of DI help to create a classroom where all students are learning to the best of their abilities. Outcomes: After reviewing the work, readers will be able to (1) identify the benefits of differentiated instruction; (2) convert traditional learning activities to differentiated ones; (3) differentiate, writing-based assessments.

Keywords: differentiation, personalized learning, design, instructional strategies

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Authors: Ahmet Oguz Akturk, Kemal Izci, Gurbuz Caliskan, Ismail Sahin

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Rapid developments in technology are to necessitate societies to closely follow technological developments and change themselves to adopt those developments. It is obvious that one of the areas that are impacted from technological developments is education. Analyzing preservice teachers’ attitudes toward technology is crucial for both educational and professional purposes since teacher candidates are essential for educating future individual living in technological age. In this study, it is aimed to analyze preservice teachers’ attitudes toward technology and some variables (e.g., gender, daily internet usage and possessed technological devices) that predicting those attitudes. In this study, relational survey model used as research method and 329 preservice teachers who are studying in a large university located at the middle part of Turkey are voluntarily participated. Results of the study showed that mostly preservice teachers displayed positive attitudes toward technology while male preservice teachers’ attitudes toward technology was more positive than female preservice teachers. In order to analyze predicting factors for preservice teachers’ attitudes toward technology, stepwise multiple regressions were utilized. The results of stepwise multiple regression showed that daily internet use was the most strong predicting factor for predicting preservice teachers’ attitudes toward technology.

Keywords: attitudes toward technology, preservice teachers, gender, stepwise multiple regression analysis

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Authors: Rishi Agarwal

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Digital twins are emerging as a strong technology used to imitate and monitor physical objects digitally in real time across sectors. It is not only dealing with the digital space, but it is also actuating responses in the physical space in response to the digital space processing like storage, modeling, learning, simulation, and prediction. This paper explores the application of digital twins for enhancing physical security in retail stores. The retail sector still relies on outdated physical security practices like manual monitoring and metal detectors, which are insufficient for modern needs. There is a lack of real-time data and system integration, leading to ineffective emergency response and preventative measures. As retail automation increases, new digital frameworks must control safety without human intervention. To address this, the paper proposes implementing an intelligent digital twin framework. This collects diverse data streams from in-store sensors, surveillance, external sources, and customer devices and then Advanced analytics and simulations enable real-time monitoring, incident prediction, automated emergency procedures, and stakeholder coordination. Overall, the digital twin improves physical security through automation, adaptability, and comprehensive data sharing. The paper also analyzes the pros and cons of implementation of this technology through an Emerging Technology Analysis Canvas that analyzes different aspects of this technology through both narrow and wide lenses to help decision makers in their decision of implementing this technology. On a broader scale, this showcases the value of digital twins in transforming legacy systems across sectors and how data sharing can create a safer world for both retail store customers and owners.

Keywords: digital twin, retail store safety, digital twin in retail, digital twin for physical safety

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Authors: Shuqi Zhang

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Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.

Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning

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Authors: Somchai Buaroong

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This research aims to investigating strong points and challenges in application of an online learning management system to an English course. Data were collected from observation, learners’ oral and written reports, and the teacher’s journals. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The findings show that the system was an additional channel to enhance English language learning through written class assignments that were digitally accessible by any group members, and through communication between the teacher and learners and among learners themselves. Thus, the learning management system could be a promising tool for foreign language teachers. Also revealed in the study were difficulties in its use. The article ends with discussions of findings of the system for foreign language classes in association to pedagogy are also included and in the level of signification.

Keywords: english course, foreign language system, online learning management system, teacher’s journals

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Authors: Armin Eilaghi, Ahmad Sedaghat, Hayder Abdurazzak, Fadi Alkhatib, Shiva Sadeghi, Martin Jaeger

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A summary of experiences, recommendations, and lessons learnt in the application of PBL in the course of “Engineering Skills” in the School of Engineering at Australian College of Kuwait in Kuwait is presented. Four projects were introduced as part of the PBL course “Engineering Skills” to 24 students in School of Engineering. These students were grouped in 6 teams to develop their skills in 10 learning outcomes. The learning outcomes targeted skills such as drawing, design, modeling, manufacturing and analysis at a preliminary level; and also some life line learning and teamwork skills as these students were exposed for the first time to the PBL (project based learning). The students were assessed for 10 learning outcomes of the course and students’ feedback was collected using an anonymous survey at the end of the course. Analyzing the students’ feedbacks, it is observed that 67% of students preferred multiple smaller projects than a single big project because it provided them with more time and attention focus to improve their “soft skills” including project management, risk assessment, and failure analysis. Moreover, it is found that 63% of students preferred to work with different team members during the course to improve their professional communication skills. Among all, 62% of students believed that working with team members from other departments helped them to increase the innovative aspect of projects and improved their overall performance. However, 70% of students counted extra time needed to regenerate momentum with the new teams as the major challenge. Project based learning provided a suitable platform for introducing students to professional engineering practice and meeting the needs of students, employers and educators. It was found that students achieved their 10 learning outcomes and gained new skills developed in this PBL unit. This was reflected in their portfolios and assessment survey.

Keywords: project-based learning, engineering skills, undergraduate engineering, problem-based learning

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Authors: Nji Clement Bang, Rosemary Shafack M., Kum Henry Asei, Yaro Loveline Y

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Scholars perceive learner-centered teaching-learning reform as roles and resources in teacher education (TE) and professional outcome with transformative learning (TL) continuum dimensions. But, teaching-learning reform is fast proliferating amidst debilitating stakeholder systemic dichotomies, resources, commitment, resistance and poor quality outcome that necessitate stronger TE and professional continuums. Scholars keep seeking greater understanding of themes in teaching-learning reform, TE and professional outcome as continuums and how policymakers, student-teachers, teacher trainers and local communities concerned with initial TE can promote continuous holistic quality performance. To sustain the debate continuum and answer the overarching question, we use mixed-methods research-design with diverse literature and 409 sample-data. Onset text, interview and questionnaire analyses reveal debilitating teaching-learning reform in TE continuums that need TL revival. Follow-up focus group discussion and teaching considering TL insights reinforce holistic teaching-learning in TE. Therefore, significant increase in diverse prior-experience articulation1; critical reflection-discourse engagement2; teaching-practice interaction3; complex-activity constrain control4 and formative outcome- reintegration5 reinforce teaching-learning in learning-to-teach role-resource pathways and outcomes. Themes reiterate complex teaching-learning in TE programs that suits TL journeys and student-teachers and students cum teachers, workers/citizens become akin, transformative-learners who evolve personal and collective roles-resources towards holistic-lifelong-learning outcomes. The article could assist debate about quality teaching-learning reform through TL dimensions as TE and professional role-resource continuums.

Keywords: transformative learning perspectives, teacher education, initial teacher education, learner-centered pedagogical reform, life-long learning

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Authors: Ahmed S. Khan, Amin Karim

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During the past several decades, the economy of each nation has been significantly affected by globalization and technology. Government regulations and private sector standards affect a majority of world trade. Countries have been working together to establish international standards in almost every field. As a result, workers in all sectors need to have an understanding of standards. Engineering and technology students must not only possess an understanding of engineering standards and applicable government codes, but also learn to apply them in designing, developing, testing and servicing products, processes and systems. Accreditation Board for Engineering & Technology (ABET) criteria for engineering and technology education require students to learn and apply standards in their class projects. This paper is a follow-up of a 2006-2009 NSF initiative awarded to IEEE to help develop tutorials and case study modules for students and encourage standards education at college campuses. It presents the findings of a faculty/institution survey conducted through various U.S.-based listservs representing the major engineering and technology disciplines. The intent of the survey was to the gauge the status of use of standards and regulations in engineering and technology coursework and to identify benchmark practices. In light of survey findings, recommendations are made to standards development organizations, industry, and academia to help enhance the use of standards in engineering and technology curricula.

Keywords: standards, regulations, ABET, IEEE, engineering, technology curricula

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Authors: M. Lopez-Pereyra, I. Cisneros Alvarado, M. Del Socorro Lobato Alba

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This paper aims to discuss a conceptual, pedagogical approach that foster inclusive education and that create an awareness of the use of assistive technology in Mexico. Interdisciplinary understanding of disabilities and the use of assistive technology as a frame for an inclusive education have challenged the reality of the researchers’ participation in decision-making. Drawing upon a pedagogical inquiry process within an interdisciplinary academic project that involved the sciences, design, biotechnology, psychology and education fields, this paper provides a discussion on the challenges of assistive technology and inclusive education in interdisciplinary research on disabilities and technology project. This study is frame on an educational action research design where the team is interested in integrating, disability, technology, and inclusion, theory, and practice. Major findings include: (1) the concept of inclusive education as a strategy for interdisciplinary research; (2) inclusion as a pedagogical approach that challenges the creation of assistive technology from diverse academic fields; and, (3) inclusion as a frame, problem-focused, for decision-making. The findings suggest that inclusive pedagogical approaches provide a unique insight into interdisciplinary teams on disability and assistive technology in education.

Keywords: assistive technology, inclusive education, inclusive pedagogy, interdisciplinary research

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Authors: Jayati Bhattacharjee

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Teaching is a very dynamic profession. Teaching Science is as much challenging as Learning the subject if not more. For instance teaching of Chemistry. From the introductory concepts of subatomic particles to atoms of elements and their symbols and further presenting the chemical equation and so forth is a challenge on both side of the equation Teaching Learning. This paper combines the Neuroscience of Learning and memory with the knowledge of Learning style (VAK) and presents an effective tool for the teacher to authenticate Learning. The model of ‘Working Memory’, the Visio-spatial sketchpad, the central executive and the phonological loop that transforms short-term memory to long term memory actually supports the psychological theory of Learning style i.e. Visual –Auditory-Kinesthetic. A closer examination of David Kolbe’s learning model suggests that learning requires abilities that are polar opposites, and that the learner must continually choose which set of learning abilities he or she will use in a specific learning situation. In grasping experience some of us perceive new information through experiencing the concrete, tangible, felt qualities of the world, relying on our senses and immersing ourselves in concrete reality. Others tend to perceive, grasp, or take hold of new information through symbolic representation or abstract conceptualization – thinking about, analyzing, or systematically planning, rather than using sensation as a guide. Similarly, in transforming or processing experience some of us tend to carefully watch others who are involved in the experience and reflect on what happens, while others choose to jump right in and start doing things. The watchers favor reflective observation, while the doers favor active experimentation. Any lesson plan based on the model of Prescriptive design: C+O=M (C: Instructional condition; O: Instructional Outcome; M: Instructional method). The desired outcome and conditions are independent variables whereas the instructional method is dependent hence can be planned and suited to maximize the learning outcome. The assessment for learning rather than of learning can encourage, build confidence and hope amongst the learners and go a long way to replace the anxiety and hopelessness that a student experiences while learning Science with a human touch in it. Application of this model has been tried in teaching chemistry to high school students as well as in workshops with teachers. The response received has proven the desirable results.

Keywords: working memory model, learning style, prescriptive design, assessment for learning

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Authors: Chandan Deep Singh

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In present days, companies are facing the rapid competition in terms of customer requirements to be satisfied, new technologies to be integrated into future products, new safety regulations to be followed, new computer-based tools to be introduced into design activities that becomes more scientific. In today’s highly competitive market, survival focuses on various factors such as quality, innovation, adherence to standards, and rapid response as the basis for competitive advantage. For competitive advantage, companies have to produce various competencies: for improving the capability of suppliers and for strengthening the process of integrating technology. For more competitiveness, organizations should operate in a strategy driven way and have a strategic architecture for developing core competencies. Traditional ways to take such experience and develop competencies tend to take a lot of time and they are expensive. A new learning environment, which is built around a gaming engine, supports the development of competences in specific subject areas. Technology competencies have a significant role in firm innovation and competitiveness; they interact with the competitive environment. Technological competencies vary according to the type of competitive environment, thus enhancing firm innovativeness. Technological competency is gained through extensive experimentation and learning in its research, development and employment in manufacturing. This is a review paper based on competency and strategic success of automobile industry. The aim here is to study strategy formulation and competency tools in the industry. This work is a review of literature related to competency and strategy in automobile industry. This study involves review of 34 papers related to competency and strategy.

Keywords: manufacturing competency, strategic success, competitiveness, strategy formulation

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Authors: Jun Wang, Ge Zhang

Abstract:

Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: Joel S. Mtebe, Aron Kondoro, Mussa M. Kissaka, Elia Kibga

Abstract:

Sub-Saharan Africa is described as the second fastest growing mobile phone penetration in the world more than in the United States or the European Union. Mobile phones have been used to provide a lot of opportunities to improve people’s lives in the region such as in banking, marketing, entertainment, and paying various bills such as water, TV, and electricity. However, the potential of using mobile phones to enhance teaching and learning has not been explored. This study presents an experience of developing and delivering SMS quizzes questions that were used to assess mastery of the subject content knowledge of science and mathematics secondary school teachers in Tanzania. The SMS quizzes were used as a follow up support mechanism to 500 teachers who participated in a project to upgrade subject content knowledge of science and mathematics subjects. Quizzes of 10-15 questions were sent to teachers each week for 8 weeks and the results were analyzed using SPSS. The results showed that chemistry and biology had better performance compared to mathematics and physics. Teachers reported some challenges that led to poor performance, invalid answers, and non-responses and they are presented. This research has several practical implications for those who are implementing or planning to use mobile phones for teaching and learning especially in rural secondary schools in sub-Saharan Africa.

Keywords: mobile learning, elearning, educational technolgies, SMS, secondary education, assessment

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Authors: Saleh Abu Hashanah, Abirami Radhakrishnan, Dessa David

Abstract:

Sustainable practices in the supply chain have been an area of focus that require consideration of environmental, economic, and social sustainability practices. This paper aims to examine the use of blockchain as a disruptive technology to promote sustainable supply chains. Content analysis was used to analyze the uses of blockchain technology in sustainable supply chains. The results showed that blockchain technology features such as traceability, transparency, smart contracts, accountability, trust, immutability, anti-fraud, and decentralization promote sustainable supply chains. It is found that these features have impacted organizational efficiency in operations, transportation, and production, minimizing costs and reducing carbon emissions. In addition, blockchain technology has been found to elicit customer trust in the products.

Keywords: blockchain technology, sustainability, supply chains, economic sustainability, environmental sustainability, social sustainability

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Authors: Prachyanun Nilsook, Panita Wannapiroon

Abstract:

The purpose of this research is to study a Digital Learning Repository System (DLRS) on vocational teachers and teaching in Thailand. The innobpcd.net is a DLRS being utilized by the Office of Vocational Education Commission and operationalized by the Bureau of Personnel Competency Development for vocational education teachers. The aim of the system is to support and enhance the process of vocational teaching and to improve staff development by providing teachers with a variety of network connections and information. The system provides centralized hosting and access to content, and the ability to share digital objects or files, to set permissions and controls for access to content that can be used vocational education teachers for their teaching and for their own development. The elements of DLRS include; Digital learning system, Media Library, Knowledge-based system and Mobile Application. The system aims to link vocational teachers to the most effective emerging technologies available for learning, so they are better resourced to support their vocational students. The initial results from this evaluation indicate that there is a range of services provided by the system being used by vocational teachers and this paper indicates which facilities have the greatest usage and impact on vocational teaching in Thailand.

Keywords: digital learning repositories, vocational education, knowledge sharing, learning objects

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

Procedia PDF Downloads 510