Search results for: online learning tools

Authors: Matthias Grünke

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In this single-case study, we evaluated the effects of a self-graphing intervention to help students improve their reading fluency. Our participant was a 10-year-old girl with a suspected learning disability in reading. We applied an ABAB reversal design to test the efficacy of our approach. The dependent measure was the number of correctly read words from a children’s book within five minutes. Our participant recorded her daily performance using a simple line diagram. Results indicate that her reading rate improved simultaneously with the intervention and dropped as soon as the treatment was suspended. The findings give reasons for optimism that our simple strategy can be a very effective tool in supporting students with learning disabilities to boost their reading fluency.

Keywords: single-case study, learning disabilities, elementary education, reading problems, reading fluency

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Authors: Pouyan Jahanbin, Mahmoud Houshmand, Omid Fatahi Valilai

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A flexible manufacturing system (FMS) is a manufacturing system having the capability of handling the variations of products features that is the result of ever-changing customer demands. The flexibility of the manufacturing systems help to utilize the resources in a more effective manner. However, the control of such systems would be complicated and challenging. FMS needs CNC machines and robots and other resources for establishing the flexibility and enhancing the efficiency of the whole system. Also it needs to integrate the resources to reach required efficiency and flexibility. In order to reach this goal, an integrator framework is proposed in which the machining data of CNC machine tools is received through a STEP-NC file. The interoperability of the system is achieved by the information system. This paper proposes an information system that its data model is designed based on object oriented approach and is implemented through a knowledge-based system. The framework is connected to a database which is filled with robot’s control commands. The framework programs the robots by rules embedded in its knowledge based system. It also controls the interactions of CNC machine tools for loading and unloading actions by robot. As a result, the proposed framework improves the integration of manufacturing resources in Flexible Manufacturing Systems.

Keywords: CNC machine tools, industrial robots, knowledge-based systems, manufacturing recourses integration, flexible manufacturing system (FMS), object-oriented data model

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Authors: Enrique Barra, Aldo Gordillo, Juan Quemada

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This paper presents the Virtual Science Hub platform. It is an open source platform that combines a social network, an e-learning authoring tool, a video conference service and a learning object repository for science teaching enrichment. These four main functionalities fit very well together. The platform was released in April 2012 and since then it has not stopped growing. Finally we present the results of the surveys conducted and the statistics gathered to validate this approach.

Keywords: e-learning, platform, authoring tool, science teaching, educational sciences

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Authors: Suriyani Ariffin, Nor Aziah Alias, Khairil Iskandar Othman, Haslinda Yusoff

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An Integrated Cumulative Grade Point Average (iCGPA) is a mechanism and strategy to ensure the curriculum of an academic programme is constructively aligned to the expected learning outcomes and student performance based on the attainment of those learning outcomes that is reported objectively in a spider web. Much effort and time has been spent to develop a viable mechanism and trains academics to utilize the platform for reporting. The question is: How well do learners conceive the idea of their achievement via iCGPA and whether quality learner attributes have been nurtured through the iCGPA mechanism? This paper presents the architecture of an integrated CGPA mechanism purported to address a holistic evaluation from the evaluation of courses learning outcomes to aligned programme learning outcomes attainment. The paper then discusses the students’ understanding of the mechanism and evaluation of their achievement from the generated spider web. A set of questionnaires were distributed to a group of students with iCGPA reporting and frequency analysis was used to compare the perspectives of students on their performance. In addition, the questionnaire also explored how they conceive the idea of an integrated, holistic reporting and how it generates their motivation to improve. The iCGPA group was found to be receptive to what they have achieved throughout their study period. They agreed that the achievement level generated from their spider web allows them to develop intervention and enhance the programme learning outcomes before they graduate.

Keywords: learning outcomes attainment, iCGPA, programme learning outcomes, spider web, iCGPA reporting skills

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Authors: Guanghua Zhang, Fubao Wang, Weijun Duan

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Convolution neural network (CNN) has attracted more and more attention on recent years. Especially in the field of computer vision and image classification. However, unsupervised learning with CNN has received less attention than supervised learning. In this work, we use a new powerful tool which is deep convolutional generative adversarial networks (DCGANs) to generate images from Sloan Digital Sky Survey. Training by various star and galaxy images, it shows that both the generator and the discriminator are good for unsupervised learning. In this paper, we also took several experiments to choose the best value for hyper-parameters and which could help to stabilize the training process and promise a good quality of the output.

Keywords: convolution neural network, discriminator, generator, unsupervised learning

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Authors: Mohammed Qutishat, Khaldoun Aldiabat, Khaled Bader, Mohammad Al Qadire

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Cyberchondria refers to the irrational increase of distress about the condition of one's health as a consequence of the World Wide Web quest for medical details. The aim of this study was to examine the relationship between emotional intelligence and cyberchondria among Omani university students. A descriptive correlational design was used to collect data from eligible 370 participants using the Emotional Intelligence Questionnaire, and the short-form version of the Cyberchondria Severity Scale (CSS-12) between January and May 2020 at XX University-Oman. The participants’ age ranged between 18 and 37 years (M = 20.28). The majority of the participants were female, 59.7% (n = 221), single 99.5% (368), in their second academic year, 29.2% (n =108). The mean score of cyberchondria experiences was 32.51, and the mean score of emotional intelligence was 34.91. Linear regression indicated a strong association between cyberchondria and emotional intelligence [F (34.639) = 5.885, P=.000], with a .086 R². In conclusion, the exchange of expertise and peer networking for health-related details utilizing the Internet can benefit students with and without having health problems. Further research and methods should be developed to help students track the online medical tools effectively for the right purposes.

Keywords: emotional intelligence, cyberchondria, smartphone addiction, social media

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Kumiko Inagaki

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In recent, years, Japanese universities have begun to face a dilemma: more than half of all high school graduates go on to attend an institution of higher learning, overwhelming Japanese universities accustomed to small student bodies. These universities have been forced to embrace qualitative changes to accommodate the increased number and diversity of students who enter their establishments, students who differ in their motivations for learning, their levels of eagerness to learn, and their perspectives on the future. One of these changes is an increase in awareness among Japanese educators of the importance of active learning, which deepens students’ understanding of course material through a range of activities, including writing, speaking, thinking, and presenting, in addition to conventional “passive learning” methods such as listening to a one-way lecture. 　The purpose of this study is to examine the effectiveness of the teaching method adapted to improve active learning. A teaching method designed to promote active learning was implemented in a social science course at one of the most popular universities in Japan. A questionnaire using a five-point response format was given to students in 2,305 courses throughout the university to evaluate the effectiveness of the method based on the following measures: ① the ratio of students who were motivated to attend the classes, ② the rate at which students learned new information, and ③ the teaching method adopted in the classes. The results of this study show that the percentage of students who attended the active learning course eagerly, and the rate of new knowledge acquired through the course, both exceeded the average for the university, the department, and the subject area of social science. In addition, there are strong correlations between teaching method and student motivation and between teaching method and knowledge acquisition rate. These results indicate that the active learning teaching method was effectively implemented and that it may improve student eagerness to attend class and motivation to learn.

Keywords: active learning, Japanese university, teaching method, university education

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Authors: Wen Huei Chou, Te Lung Pan, Tsu Wen Yeh

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New media have recently received increasing attention as a new communication form. The COVID-19 outbreak has pushed people’s lifestyles into the digital age, and the drug market has infiltrated formal e-commerce platforms. The self-media boom has fostered growth in online drug myths. To set the record straight, it is imperative to develop new media-based interventions. However, the usefulness of new media on this issue has not yet been fully examined. This study selected 13 articles on the development of new media-based interventions to prevent drug abuse from Airiti Library and Pub-Med as of October 3, 2021. The key conclusions are that (1) new media have a significantly positive influence on skills, self-efficacy, and behavior; (2) most interventions package traditional course learning into new media formats; and (3) new media can create a covert, interactive environment that cannot be replicated offline, which may merit attention in future research.

Keywords: drug abuse, interventions, new media, systematic review

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Amjaad Alsalamah, Liyakathunsia Syed

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Transportation is an essential need for many people to go to their work, school, and home. In particular, the main common method inside many cities is to drive the car. Driving a car can be an easy job to reach the destination and load all stuff in a reasonable time. However, deciding to find a parking lot for a car can take a long time using the traditional system that can issue a paper ticket for each customer. The old system cannot guarantee a parking lot for all customers. Also, payment methods are not always available, and many customers struggled to find their car among a numerous number of cars. As a result, this research focuses on providing an online smart parking system in order to save time and budget. This system provides a flexible management system for both parking owner and customers by receiving all request via the online system and it gets an accurate result for all available parking and its location.

Keywords: smart parking system, IoT, tracking system, process model, cost, time

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Authors: Erhan Eroğlu

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This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

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Authors: Paramvir Singh

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The locomotion of aquatic organisms has long fascinated biologists and engineers alike, with fish fins serving as a prime example of nature's remarkable adaptations for efficient underwater propulsion. This paper presents a comprehensive study focused on the hydrodynamic analysis of fish fin kinematics, employing an innovative approach that combines machine learning and image processing techniques. Through high-speed videography and advanced computational tools, we gain insights into the complex and dynamic motion of the fins of a Tilapia (Oreochromis Niloticus) fish. This study was initially done by experimentally capturing videos of the various motions of a Tilapia in a custom-made setup. Using deep learning and image processing on the videos, the motion of the Caudal and Pectoral fin was extracted. This motion included the fin configuration (i.e., the angle of deviation from the mean position) with respect to time. Numerical investigations for the flapping fins are then performed using a Computational Fluid Dynamics (CFD) solver. 3D models of the fins were created, mimicking the real-life geometry of the fins. Thrust Characteristics of separate fins (i.e., Caudal and Pectoral separately) and when the fins are together were studied. The relationship and the phase between caudal and pectoral fin motion were also discussed. The key objectives include mathematical modeling of the motion of a flapping fin at different naturally occurring frequencies and amplitudes. The interactions between both fins (caudal and pectoral) were also an area of keen interest. This work aims to improve on research that has been done in the past on similar topics. Also, these results can help in the better and more efficient design of the propulsion systems for biomimetic underwater vehicles that are used to study aquatic ecosystems, explore uncharted or challenging underwater regions, do ocean bed modeling, etc.

Keywords: biomimetics, fish fin kinematics, image processing, fish tracking, underwater vehicles

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Authors: Annette Cosgrove, Carina Ginty, Tony Hall, Cornelia Connolly

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The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitization of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence-based digital teaching model for use in a future pandemic. The research strategy undertaken for this study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially, feedback was collected and the research instrument was edited to reflect this feedback before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioner's views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology-enhanced learning and on teaching practice in a higher education institution. The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice. This study includes quantitative and qualitative methods to elicit data that will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments/data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers. This research is currently being conducted across the ATU multi-site campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a West of Ireland university, is the focus of the study. The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi-formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning. This paper will present initial findings, reflections and data from this ongoing research study.

Keywords: TEL, technology, digital, education

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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Authors: Manuela Nayantara Jeyaraj

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Having moved into the 21^st century, it is way past being arguable that innovative technology needs to be incorporated into conventional classroom teaching. Though the Western world has found presumable success in achieving this, it is still a concept under battle in developing countries such as Sri Lanka. Reaching the acme of implementing interactive virtual learning within classrooms is a struggling idealistic fascination within the island. In order to overcome this problem, this study is set to reveal facts that limit the implementation of virtual, interactive learning within the school classrooms and provide hacks that could prove the augmented use of the Virtual World to enhance teaching and learning experiences. As each classroom moves along with the usage of technology to fulfill its functionalities, a few intense hacks provided will build the administrative onuses on a virtual system. These hacks may divulge barriers based on social conventions, financial boundaries, digital literacy, intellectual capacity of the staff, and highlight the impediments in introducing students to an interactive virtual learning environment and thereby provide the necessary actions or changes to be made to succeed and march along in creating an intellectual society built on virtual learning and lifestyle. This digital learning environment will be composed of multimedia presentations, trivia and pop quizzes conducted on a GUI, assessments conducted via a virtual system, records maintained on a database, etc. The ultimate objective of this study could enhance every child's basic learning environment; hence, diminishing the digital divide that exists in certain communities.

Keywords: digital divide, digital learning, digitization, Sri Lanka, teaching methodologies

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Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

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Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

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Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Jaeseo Lim, Jooyong Park

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Although there is ample evidence that student involvement enhances learning, college education is still mainly centered on lectures. However, in recent years, the effectiveness of discussions and the use of collective intelligence have attracted considerable attention. This study intends to examine the empirical effects of discussions on learning outcomes in various conditions. Eighty eight college students participated in the study and were randomly assigned to three groups. Group 1 was told to review material after a lecture, as in a traditional lecture-centered class. Students were given time to review the material for themselves after watching the lecture in a video clip. Group 2 participated in a discussion in groups of three or four after watching the lecture. Group 3 participated in a discussion after studying on their own. Unlike the previous two groups, students in Group 3 did not watch the lecture. The participants in the three groups were tested after studying. The test questions consisted of memorization problems, comprehension problems, and application problems. The results showed that the groups where students participated in discussions had significantly higher test scores. Moreover, the group where students studied on their own did better than that where students watched a lecture. Thus discussions are shown to be effective for enhancing learning. In particular, discussions seem to play a role in preparing students to solve application problems. This is a preliminary study and other age groups and various academic subjects need to be examined in order to generalize these findings. We also plan to investigate what kind of support is needed to facilitate discussions.

Keywords: discussions, education, learning, lecture, test

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Authors: Kious Mecheri, Hadjadj Abdechafik, Ameur Aissa

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The wear of cutting tool degrades the quality of the product in the manufacturing processes. The online monitoring of the cutting tool wear level is very necessary to prevent the deterioration of the quality of machining. Unfortunately there is not a direct manner to measure the cutting tool wear online. Consequently we must adopt an indirect method where wear will be estimated from the measurement of one or more physical parameters appearing during the machining process such as the cutting force, the vibrations, or the acoustic emission etc. In this work, a neural network system is elaborated in order to estimate the flank wear from the cutting force measurement and the cutting conditions.

Keywords: flank wear, cutting forces, high speed milling, signal processing, neural network

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Authors: Boumaraf Malak

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The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

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Authors: Michael Stewart

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Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

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Authors: Lise P. Labéjof, Krisnayne S. Ribeiro, Nicolle P. dos Santos

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An unrecorded experiment of use of the smartphone as a tool for practical classes of histology is presented in this article. Behavior, learning of the students of three science courses at the University were analyzed and compared as well as the mode of teaching of this discipline and the appreciation of the students, using either digital photographs taken by phone or drawings for record microscopic observations, analyze and interpret histological sections of human or animal tissues.

Keywords: cell phone, digital micrographies, learning of sciences, teaching practices

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Authors: Venus Torabi

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ISIS, the terrorist organization, modified two videogames, ARMA III and Grand Theft Auto 5 (2013) as means of online recruitment and ideological propaganda. The urge to study the mechanism at work, whether it has been successful or not, derives (Digital) Humanities experts to explore how codes of terror, Islamic ideology and recruitment strategies are incorporated into the ludic mechanics of videogames. Another aspect of the significance lies in the fact that this is a latent problem that has not been fully addressed in an interdisciplinary framework prior to this study, to the best of the researcher’s knowledge. Therefore, due to the complexity of the subject, the present paper entangles with game studies, philosophical and religious poles to form the methodology of conducting the research. As a contextualized epistemology of such exploitation of videogames, the core argument is building on the notion of “Culture Industry” proposed by Theodore W. Adorno and Max Horkheimer in Dialectic of Enlightenment (2002). This article posits that the ideological underpinnings of ISIS’s cause corroborated by the action-bound mechanics of the videogames are in line with adhering to the Islamic Eschatology as a furnishing ground and an excuse in exercising terrorism. It is an account of ISIS’s modification of the videogames, a tool of technological progression to practice online radicalization. Dialectically, this practice is packed up in rhetoric for recognizing a religious myth (the advent of a savior), as a hallmark of regression. The study puts forth that ISIS’s wreaking havoc on the world, both in reality and within action videogames, is negotiating the process of self-assertion in the players of such videogames (by assuming one’s self a member of terrorists) that leads to self-annihilation. It tries to unfold how ludic Mod videogames are misused as tools of mass deception towards ethnic cleansing in reality and line with the distorted Eschatological myth. To conclude, this study posits videogames to be a new avenue of mass deception in the framework of the Culture Industry. Yet, this emerges as a two-edged sword of mass deception in ISIS’s modification of videogames. It shows that ISIS is not only trying to hijack the minds through online/ludic recruitment, it potentially deceives the Muslim communities or those prone to radicalization into believing that it's terrorist practices are preparing the world for the advent of a religious savior based on Islamic Eschatology. This is to claim that the harsh actions of the videogames are potentially breeding minds by seeds of terrorist propaganda and numbing them to violence. The real world becomes an extension of that harsh virtual environment in a ludic/actual continuum, the extension that is contributing to the mass deception mechanism of the terrorists, in a clandestine trend.

Keywords: culture industry, dialectic, ISIS, islamic eschatology, mass deception, video games

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Authors: Ramorola Mmankoko Ziphorah

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Videoconference technology represents a recent experiment of technology integration into teaching and learning in South Africa. Increasingly, videoconference technology is commonly used as a substitute for the traditional face-to-face approaches to teaching and learning in helping tutors to reshape and change their teaching practices. Interestingly, though, some studies point out that videoconference technology is commonly used for knowledge dissemination by tutors and not so much for the actual teaching of course content in Open and Distance Learning context. Though videoconference technology has become one of the dominating technologies available among Open and Distance Learning institutions, it is not clear that it has been used as effectively to bridge the learning distance in time, geography, and economy. While tutors are prepared theoretically, in most tutor preparation programs, on the use of videoconference technology, there are still no practical guidelines on how they should go about integrating this technology into their course teaching. Therefore, there is an urgent need to focus on tutor development, specifically on their capacities and skills to use videoconference technology. The assumption is that if tutors become competent in the use of the videoconference technology for course teaching, then their use in Open and Distance Learning environment will become more commonplace. This is the imperative of the 4th Industrial Revolution (4IR) on education generally. Against the current vacuum in the practice of using videoconference technology for course teaching, the current study proposes a qualitative phenomenological approach to investigate the efficacy of videoconferencing as an approach to student learning. Using interviews and observation data from ten participants in Open and Distance Learning institution, the author discusses how dialogue and structure interacted to provide the participating tutors with a rich set of opportunities to deliver course content. The findings to this study highlight various challenges experienced by tutors when using videoconference technology. The study suggests tutor development programs on their capacity and skills and on how to integrate this technology with various teaching strategies in order to enhance student learning. The author argues that it is not merely the existence of the structure, namely the videoconference technology, that provides the opportunity for effective teaching, but that is the interactions, namely, the dialogue amongst tutors and learners that make videoconference technology an attractive vehicle for challenging and changing tutors practice.

Keywords: open distance learning, transactional distance, tutor, videoconference

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Authors: S. Chee Choy, Daljeet Singh Sedhu

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This study examines the relationships between how and why students learned and academic achievement for 2646 university students from various faculties. The LALQ, a self-report measure of student approaches to learning was administered and academic achievement data were obtained from student CGPA. The results showed significant differences in the approach to learning of male and female students. How and why students learned can influence their achievement and efficacy as well. High and low achievers have different learning behaviours. High female achievers were more likely to learn for a better future and be persistent in it. Meanwhile high male achievers were more likely to seek approval from their peers and be more confident about graduating on time from their university. The implications of individual differences and limitations of the study are discussed.

Keywords: student learning, learner awareness, student achievement, LALQ

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Authors: Lynette Nickleberry Stewart

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The present presentation seeks to explore distinction across disciplines in the appropriateness of accelerated courses and suggestions for implementing accelerated courses in various disciplines. Grounded in a review of research on accelerated learning (AL), this presentation will discuss the intradisciplinary appropriateness of accelerated courses for various topics and student types, and make suggestions for implementing augmented courses. Meant to inform an emerging ‘handbook’ of accelerated course development, facilitators will lead participants in a discussion of personal challenges and triumphs in their attempts at accelerated course design.

Keywords: adult learning, abbreviated courses, accelerated learning, course design

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Authors: Iman Shabanzadeh

Abstract:

The economic growth and the special model of development in China have caused sensitivity in the public opinion of the world regarding the nature of this growth and development. In this regard, the Chinese have tried to put an end to such alarming procedures by using all the tools at their disposal and seek to present a peaceful and cooperative image of themselves. In this way, one of the most important diplomatic tools that Beijing has used to reduce the concerns caused by the Threat Theory has been the use of soft power resources and its tools in its development policies. This article begins by analyzing the concept of soft power and examining its foundations in international relations, and continues to examine the components of soft power in its Chinese version. The main purpose of the article is to figure out about the position of West Asia in China's soft power strategy and resources China use to achieve its goals in this region. In response to the main question, the paper's hypothesis is that soft power in its Chinese version had significant differences from Joseph Nye's original idea. In fact, the Chinese have imported the American version of soft power and adjusted, strengthened and, in other words, internalized it with their abilities, capacities and political philosophy. Based on this, China's software presence in West Asia can be traced in three areas. The first source of China's soft power in this region of West Asia is cultural in nature and is realized through strategies such as "use of educational tools and methods", "media methods" and "tourism industry". The second source is related to political soft power, which is applied through the policy of "balance of influence" and the policy of "mediation" and relying on the "ideological foundations of Confucianism". The third source also refers to China's economic soft power and is realized through three tools: "energy exchanges", "foreign investments" and "Belt-Road initiative". The research method of this article is descriptive-analytical.

Keywords: soft power, cooperative power, china, west asia

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Authors: Vehbi Gorgulu

Abstract:

The primary objective of the current study is to explore how brand managers can employ Internet memes as a marketing tool. Internet memes are marked for their sarcastic and entertaining content and their amateur/DIY natures. The current study focuses on #TFWGucci, a collaborative marketing project enacted by Gucci, which is marked for being one of the first structured collaborative memetic marketing campaigns in the world. By embracing a qualitative approach, the study will explore production and meaning making processes of #TFWGucci campaign via analysis of sample campaign contents. The study will provide hints and insights for digital marketers on how to employ memetic marketing strategies in successful ways.

Keywords: meme, internet meme, online marketing, memetic marketing, #TFWGucci

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Authors: Bahman Gorjian

Abstract:

This study investigated the effects of closed-captioning on vocabulary learning and listening comprehension of English-language movies. Captioning is thus an effective language-learning tool for persons learning English as a second language. Because students may learn a foreign language "passively," utilizing subtitles on television could make learning English enjoyable for them. Closed captioning is an electrical technique that converts spoken words from a television program's audio into written text that mimics subtitles in another language. The findings of this study showed the importance of using closed-captioning software when learning a foreign language. As a result, these must be considered when teaching EFL/ESL. The influence of watching movies with closed captions on vocabulary and hearing is compared in this study. This goal can be reached by employing a closed-captioned movie as a teaching tool in the classroom. This research was critical because it demonstrates the advantages of closed-captioning programs in EFL classrooms for both teachers and students. The study's findings assisted teachers in better understanding how to employ closed captioning as a teaching tool in the classroom. The effects will be seen as even more significant for language learners who use the method.

Keywords: closed-captions, listening, comprehension, vcabulary

Procedia PDF Downloads 89