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Articles 2161 - 2190 of 2925
Full-Text Articles in Computer Sciences
Exploring The Functional And Geometric Bias Of Spatial Relations Using Neural Language Models, Simon Dobnik, Mehdi Ghanimifard, John D. Kelleher
Exploring The Functional And Geometric Bias Of Spatial Relations Using Neural Language Models, Simon Dobnik, Mehdi Ghanimifard, John D. Kelleher
Conference papers
The challenge for computational models of spatial descriptions for situated dialogue systems is the integration of information from different modalities. The semantics of spatial descriptions are grounded in at least two sources of information: (i) a geometric representation of space and (ii) the functional interaction of related objects that. We train several neural language models on descriptions of scenes from a dataset of image captions and examine whether the functional or geometric bias of spatial descriptions reported in the literature is reflected in the estimated perplexity of these models. The results of these experiments have implications for the creation of …
Towards A Conceptual Framework For The Development Of Immersive Experiences To Negotiate Meaning And Identify In Irish Language Learning, Naoise Collins, Brian Vaughan, Keith Gardiner, Charlie Cullen
Towards A Conceptual Framework For The Development Of Immersive Experiences To Negotiate Meaning And Identify In Irish Language Learning, Naoise Collins, Brian Vaughan, Keith Gardiner, Charlie Cullen
Conference papers
The onset of virtual reality systems allows for new immersive content which provides users with a sense of presence in their virtual environment. This paper provides the conceptual framework for a larger study examining how designed virtual reality experiences can be utilised to transform Irish language meaning making and a user's personal Irish language identity.
An Investigation Of The Impact Of Language Runtime On The Performance And Cost Of Serverless Functions, David Jackson, Gary Clynch
An Investigation Of The Impact Of Language Runtime On The Performance And Cost Of Serverless Functions, David Jackson, Gary Clynch
Conference Papers
Serverless, otherwise known as “Function-as-a- Service” (FaaS), is a compelling evolution of cloud computing that is highly scalable and event-driven. Serverless applications are composed of multiple independent functions, each of which can be implemented in a range of programming languages. This paper seeks to understand the impact of the choice of language runtime on the performance and subsequent cost of serverless function execution. It presents the design and implementation of a new serverless performance testing framework created to analyse performance and cost metrics for both AWS Lambda and Azure Functions. For optimum performance and cost management of serverless applications, Python …
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a transformer incipient fault diagnosis model has been developed with the help of an artificial neural network (ANN), taking into account the difference in the energy required to produce the different fault gases. The key fault gases are indicative of the fault type prevailing in the transformer. However, in conventional studies, the energy difference in fault gas formation is not considered while adopting the key gas method for fault diagnosis. In this work, a weighting factor has been used to take into account this relative difference in energy requirement for various fault gas formations. The fault gas …
Real-Time Chaff Generation For A Biometric Fuzzy Vault, Manvjeet Kaur, Sanjeev Sofat
Real-Time Chaff Generation For A Biometric Fuzzy Vault, Manvjeet Kaur, Sanjeev Sofat
Turkish Journal of Electrical Engineering and Computer Sciences
Biometric technology is rapidly being adopted in wide variety of security applications. However, the system itself is not completely foolproof and is vulnerable to many attacks. Some of the attacks on the biometric system are very severe, one of which is the attack on template security. In spite of the various template security techniques presented in the literature, none of them is able to provide security, diversity, revocability, and good performance simultaneously to the biometric system. Fuzzy vault is one of the most promising bio-cryptographic techniques to prevent the template data from being misused. To make the fuzzy vault practically …
Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz
Construction Of A Turkish Proposition Bank, Koray Ak, Cansu Toprak, Volkan Esgel, Olcay Taner Yildiz
Turkish Journal of Electrical Engineering and Computer Sciences
This paper describes our approach to developing the Turkish PropBank by adopting the semantic role-labeling guidelines of the original PropBank and using the translation of the English Penn-TreeBank as a resource. We discuss the semantic annotation process of the PropBank and language-specific cases for Turkish, the tools we have developed for annotation, and quality control for multiuser annotation. In the current phase of the project, more than 9500 sentences are semantically analyzed and predicate-argument information is extracted for 1330 verbs and 1914 verb senses. Our plan is to annotate 17,000 sentences by the end of 2017.
Analysis And Design Of A Converter Based On Noncascading Structure, Sunil Kumar, Kanwar Pal Singh Rana, Vineet Kumar
Analysis And Design Of A Converter Based On Noncascading Structure, Sunil Kumar, Kanwar Pal Singh Rana, Vineet Kumar
Turkish Journal of Electrical Engineering and Computer Sciences
In the present work, a converter employing two noncascading structures, combined in a single circuit, is presented. The power stored by the storage element is transferred to two subconverters by means of two storage capacitors that complement each other. The stress on the main power switch is of interest as it reduces as the load falls, which in turn reduces the power loss. By means of the storage elements, the input power factor as well as the load transient response can be improved simultaneously. The overall efficiency is high because the amount of power processed twice decreases. There is no …
Mutatedsocioagentsim (Msas): Semisupervised Modelling Of Multiagent Simulation To Predict And Detect The Mutation In A Camouflaged Social Network, Karthika Subbaraj, Bose Sundan
Mutatedsocioagentsim (Msas): Semisupervised Modelling Of Multiagent Simulation To Predict And Detect The Mutation In A Camouflaged Social Network, Karthika Subbaraj, Bose Sundan
Turkish Journal of Electrical Engineering and Computer Sciences
A social network is a networked structure formed by a set of agents/actors. It describes their interrelationships that facilitate the exchange and flow of resources and information. A camouflaged social network is one such community that influences the underlying structure and the profile of the agents, to cause mutation. The proposed MSAM is a novel system that simulates a multiagent network whose community structure is analyzed to identify the critical agents by studying the mutations caused due to attachment and detachment of agents. The isolation of the tagged agents will demonstrate disruption of information flow, which leads to the dismantling …
Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar
Improvement Of Air Pollution Prediction In A Smart City And Its Correlation With Weather Conditions Using Metrological Big Data, Talat Zaree, Ali Reza Honarvar
Turkish Journal of Electrical Engineering and Computer Sciences
Smart cities are an important concept for urban development. This concept addresses many current critical urban problems including traffic and environmental pollution. As utilization of the Internet of things and technology in smart cities increases, large volumes of big data are generated and collected by sensors embedded at different places in the city, which present a real-time display of what is happening throughout the city at all times. Such data should be processed and analyzed as a response to ensure effectiveness and improvement in quality of provided services; correct use and analysis of such data is valuable. Big data mining …
Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi
Topological Feature Extraction Of Nonlinear Signals And Trajectories And Its Application In Eeg Signals Classification, Saleh Lashkari, Ali Sheikhani, Mohammad Reza Hashemi Golpayegani, Ali Moghimi, Hamid Reza Kobravi
Turkish Journal of Electrical Engineering and Computer Sciences
This study introduces seven topological features that characterize attractor dynamic of nonlinear and chaotic trajectories in a phase space. These features quantify volume, occupied space, nonuniformity, and curvature of trajectory. The features are evaluated as initial point invariant measures by a practical approach, which means that a feature is only sensitive to dynamic changes. The Lorenz and Rossler system trajectories are employed in this evaluation. Moreover, the proposed features are used in a real world application, i.e. epileptic seizure electroencephalogram signal classification. As the result shows, these features are efficient in this task in comparison with others studies that used …
Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman
Optimum, Projected, And Regularized Extreme Learning Machine Methods With Singular Value Decomposition And L$_{2}$-Tikhonov Regularization, Mohanad Abd Shehab, Ni̇han Kahraman
Turkish Journal of Electrical Engineering and Computer Sciences
The theory and implementation of an extreme learning machine (ELM) have proved that it is a simple, efficient, and accurate machine learning methodology. In an ELM, the hidden nodes are randomly initiated and fixed without iterative tuning. However, the optimal hidden layer neuron number ($L_{opt})$ is the key to ELM generalization performance where initializing this number by trial and error is not reasonably satisfied. Optimizing the hidden layer size using the leave-one-out cross validation method is a costly approach. In this paper, a fast and reliable statistical approach called optimum ELM (OELM) was developed to determine the minimum hidden layer …
Novel Low-Loss Microstrip Triplexer Using Coupled Lines And Step Impedance Cells For 4g And Wimax Applications, Abbas Rezaei, Leila Noori
Novel Low-Loss Microstrip Triplexer Using Coupled Lines And Step Impedance Cells For 4g And Wimax Applications, Abbas Rezaei, Leila Noori
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a new microstrip triplexer with flexible resonance frequencies is designed based on the properties of coupled lines, steps, and spiral cells. It operates at 2.67 GHz for 4G LTE and at 3.1 GHz and 3.43 GHz for IEEE 802.16 WiMAX. The close resonance frequencies make it suitable for frequency division duplex applications. In order to improve insertion loss, the LC equivalent circuit of the proposed resonator is analyzed. Moreover, careful alignment of the coupled lines and step impedance structures is performed to improve the insertion and return losses so that they are 0.72/0.63/0.81 dB and 24.5/24/24.7 dB, …
A Low-Cost And Flexible Architecture Of Digitally Controlled Dc-Dc Converter To Improve Dynamic Performance, Abdolsamad Hamidi, Arash Ahmadi, Shahram Karimi
A Low-Cost And Flexible Architecture Of Digitally Controlled Dc-Dc Converter To Improve Dynamic Performance, Abdolsamad Hamidi, Arash Ahmadi, Shahram Karimi
Turkish Journal of Electrical Engineering and Computer Sciences
One type of DC-DC converters is dual transistor forward converter. In this article, a low-cost architecture of a digital controller for dual transistor forward converter is presented. This architecture is designed by using the finite set model predictive control technique. Based on this approach, a low-cost fixed-point arithmetic architecture with minimum functional units is presented to find the optimum switching time at each sampling point. Charge balance control method is utilized to improve the dynamic performance of the transient response. The proposed architecture is implemented and realized by using a field-programmable gate array (FPGA) platform to evaluate the precision of …
Mn-Zn Ferrite Line Emi Suppressor For Power Switching Noise In The Impulse/High Current Bias Regime, Dragana Petrovic, Miroslav Lazic, Obrad Aleksic, Maria Nikolic, Vedran Ibrahimovic, Milan Pajnic
Mn-Zn Ferrite Line Emi Suppressor For Power Switching Noise In The Impulse/High Current Bias Regime, Dragana Petrovic, Miroslav Lazic, Obrad Aleksic, Maria Nikolic, Vedran Ibrahimovic, Milan Pajnic
Turkish Journal of Electrical Engineering and Computer Sciences
Ferrite cores 50 mm long were formed from large ferrite tubes obtained using fine Mn-Zn ferrite powder (M-30-IHIS) extruded and sintered at 1280 $^{\circ}$C for 2 h. Core impedance was measured in the HF range (0.1--100 MHz), varying the number of coil turns and DC bias. Characteristic parameters such as maximum of impedance Z$_m$, frequency of maximum impedance F$_m$, and suppressing range f around F$_m$ were determined for each configuration. The analyzed ferrite cores were tested as round cable suppressors in the impulse regime. Impulses were generated by MOSFET transistor switching of high currents (1--10 A). The number of turns, …
Secure Access Control In Multidomain Environments And Formal Analysis Of Model Specifications, Fatemeh Nazerian, Homayun Motameni, Hossein Nematzadeh
Secure Access Control In Multidomain Environments And Formal Analysis Of Model Specifications, Fatemeh Nazerian, Homayun Motameni, Hossein Nematzadeh
Turkish Journal of Electrical Engineering and Computer Sciences
Distributed multiple organizations interact with each other. If the domains employ role-based access control, one method for interaction between domains is role-mapping. However, it may violate constraints in the domains such as role hierarchy, separation of duty, and cardinality. Therefore, autonomy of the domains is lost. This paper proposes secure interoperation in multidomain environments. For this purpose, a cross-domain is created by foreign permission assignment. In an effort to maintain the autonomy of every domain, several rules are defined formally. Then, a decentralized scheme is used to provide permission mapping between domains. At the next stage, the proposed cross-domain is …
Prediction Of Gross Calorific Value Of Coal Based On Proximate Analysis Using Multiple Linear Regression And Artificial Neural Networks, Mustafa Açikkar, Osman Si̇vri̇kaya
Prediction Of Gross Calorific Value Of Coal Based On Proximate Analysis Using Multiple Linear Regression And Artificial Neural Networks, Mustafa Açikkar, Osman Si̇vri̇kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Gross calorific value (GCV) of coal was predicted by using as-received basis proximate analysis data. Two main objectives of the study were to develop prediction models for GCV using proximate analysis variables and to reveal the distinct predictors of GCV. Multiple linear regression (MLR) and artifcial neural network (ANN) (multilayer perceptron MLP, general regression neural network GRNN, and radial basis function neural network RBFNN) methods were applied to the developed 11 models created by different combinations of the predictor variables. By conducting 10-fold cross-validation, the prediction accuracy of the models has been tested by using $ R^2 $, $ RMSE …
Q-Axis Current Perturbation Based Active Islanding Detection For Converter Interfaced Distributed Generators, Suman Murugesan, Venkatakirthiga Murali
Q-Axis Current Perturbation Based Active Islanding Detection For Converter Interfaced Distributed Generators, Suman Murugesan, Venkatakirthiga Murali
Turkish Journal of Electrical Engineering and Computer Sciences
Thanks to the incessant developments in technology towards extracting electric power from renewable energy resources, incorporation of distributed generators has been gaining great importance in recent years. The key expedients for such power generation include reduction in power loss and improvement in the power quality and reliability. In spite of the numerous advantages, it is mandatory to ascertain the island formation and shut down the distributed generators (DGs) during an unplanned islanding. An analyzing technique subsequent to an active islanding detection technique is proposed in this work for faster and accurate detection of island formation. The proposed technique is investigated …
Estimation Of The Depth Of Anesthesia By Using A Multioutput Least-Square Support Vector Regression, Mercedeh Jahanseir, Kamal Setarehdan, Sirous Momenzadeh
Estimation Of The Depth Of Anesthesia By Using A Multioutput Least-Square Support Vector Regression, Mercedeh Jahanseir, Kamal Setarehdan, Sirous Momenzadeh
Turkish Journal of Electrical Engineering and Computer Sciences
Today, most surgeries are performed under general anesthesia where one of the most growing methods for anesthesia depth monitoring is using electroencephalogram (EEG). The bispectral index (BIS) is the most commonly used parameter for anesthesia depth monitoring using EEG, the validity of which is still to be studied before being accepted as a routine method by clinicians. This paper proposes a new technique for detecting the depth of anesthesia by means of EEG, which is based on multioutput least-squares support vector regression (MLS-SVR), which provides the probability that the patient is in the four different possible anesthesia states. In this …
Detecting Slow Wave Sleep And Rapid Eye Movement Stage Using Cortical Effective Connectivity, Aminollah Glorou, Ali Sheikhani, Ali Motie Nasrabadi, Mohammad Reza Saebipour
Detecting Slow Wave Sleep And Rapid Eye Movement Stage Using Cortical Effective Connectivity, Aminollah Glorou, Ali Sheikhani, Ali Motie Nasrabadi, Mohammad Reza Saebipour
Turkish Journal of Electrical Engineering and Computer Sciences
In recent neuroimaging research, there has been considerable interest in identifying neuromarkers of sleep. Automatic slow wave sleep (SWS) and rapid eye movement (REM) are two known phases of sleep. However, the level by which those changes contribute to brain interactions has not been well characterized. In recent years, it has been shown that brain connectivity measuring can be helpful in investigation of behavioral states of the brain. By considering the fact that brains have different states in different stages of sleep, the present work employs effective connectivity and machine-learning analysis to quantify and classify SWS and REM stages of …
Dynamic Liquid Level Detection Method Based On Resonant Frequency Difference For Oil Wells, Wei Zhou, Juan Liu, Liqun Gan
Dynamic Liquid Level Detection Method Based On Resonant Frequency Difference For Oil Wells, Wei Zhou, Juan Liu, Liqun Gan
Turkish Journal of Electrical Engineering and Computer Sciences
The dynamic liquid level of an oil well can be used to determine the oil production strategies and analyze the reservoir performance. Therefore, it is important to measure the dynamic liquid level in an oil field. This paper proposes a novel dynamic liquid level measurement method for oil wells, where the resonant frequency difference (RFD) of the resonant acoustic signal in annular is used to calculate the dynamic liquid level. To solve the noise interference problem in the resonant acoustic signal, a spectral fast Fourier transform (FFT) method based on Welch power spectrum is proposed to obtain the RFD. First, …
Influence Of Thyristor-Controlled Series Capacitor On Wheeling Cost Incorporating The Impact Of Real And Reactive Power Losses, Kranthi Kiran Irinjila, Jaya Laxmi Askani
Influence Of Thyristor-Controlled Series Capacitor On Wheeling Cost Incorporating The Impact Of Real And Reactive Power Losses, Kranthi Kiran Irinjila, Jaya Laxmi Askani
Turkish Journal of Electrical Engineering and Computer Sciences
Electric power transmission and transmission pricing are the key issues in the deregulated electric power industry. Factors like fast power demand growth, competition, service outage, and scarce natural resources make transmission systems operate close to their thermal limits. However, new transmission systems cannot be built in due to economic, environmental, and political reasons. For better utilization of existing power system capacities, the power electronic technology-based power system equipment called flexible alternating current transmission system (FACTS) devices like thyristor-controlled series compensators (TCSCs) can be effectively used for operating the transmission grid economically, rapidly, dynamically, and efficiently with increased flexibility and efficiency …
A Novel Optimization Method For Solving Constrained And Unconstrained Problems: Modified Golden Sine Algorithm, Erkan Tanyildizi
A Novel Optimization Method For Solving Constrained And Unconstrained Problems: Modified Golden Sine Algorithm, Erkan Tanyildizi
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, the metaheuristic optimization algorithms inspired by nature and different science branches have been powerful solution methods for unconstrained, constrained, and engineering problems. Various metaheuristic optimization algorithms have been proposed and they have been applied to problems in different fields. This paper proposes a novel optimization method based on a modified version of the Golden Sine Algorithm for solving unconstrained, constrained, and engineering problems. The basic idea behind the proposed modified Golden Sine Algorithm (GoldSA-II) depends on finding the optimum solution field in search space by using the decreasing pattern of the sine function and the golden ratio. The performance …
New Optimization Algorithm Inspired By Fluid Mechanics For Combined Economic And Emission Dispatch Problem, Ruyi Dong, Shengsheng Wang
New Optimization Algorithm Inspired By Fluid Mechanics For Combined Economic And Emission Dispatch Problem, Ruyi Dong, Shengsheng Wang
Turkish Journal of Electrical Engineering and Computer Sciences
With the increasing concern over environmental protection, the combined economic emission dispatch (CEED) problem has received much attention. It needs to minimize both fuel cost and emission pollution. This study aims to propose a new metaheuristic algorithm inspired by fluid mechanics to solve the CEED problem with the weighted sum method. The new algorithm simulates the inverse process of fluid flowing spontaneously from high pressure to low pressure, similar to the optimization process of the CEED problem. When applied in two real-world cases, the new algorithm achieves better performance compared with other algorithms in the literature.
Type I General Exponential Class Of Distributions, Gholamhossein G. Hamedani, Haitham M. Yousof, Mahdi Rasekhi, Morad Alizadeh, Seyed Morteza Najibi
Type I General Exponential Class Of Distributions, Gholamhossein G. Hamedani, Haitham M. Yousof, Mahdi Rasekhi, Morad Alizadeh, Seyed Morteza Najibi
Mathematics, Statistics and Computer Science Faculty Research and Publications
We introduce a new family of continuous distributions and study the mathematical properties of the new family. Some useful characterizations based on the ratio of two truncated moments and hazard function are also presented. We estimate the model parameters by the maximum likelihood method and assess its performance based on biases and mean squared errors in a simulation study framework.
The Relevance Of A Good Internal Control System In A Computerised Accounting Information System, Raymond Lutui, Tau’Aho ‘Ahokovi
The Relevance Of A Good Internal Control System In A Computerised Accounting Information System, Raymond Lutui, Tau’Aho ‘Ahokovi
Australian Information Security Management Conference
Advancements in information technology (IT) have enabled companies to use computers to carry out their activities that were previously performed manually. Accounting systems that were previously performed manually can now be performed with the help of computers. With all the advantages of computerized accounting software, business owners need to realize that problems do arise for a variety of reasons. Dependence on computers sometimes leads to bigger problems. This paper, therefore provide a detail information about the concept of internal control to its relevance in a computerised accounting information. This study also considers the trend between manual and computerised accounting system. …
An Investigation Into A Denial Of Service Attack On An Ethereum Network, Richard Greene, Michael N. Johnstone
An Investigation Into A Denial Of Service Attack On An Ethereum Network, Richard Greene, Michael N. Johnstone
Australian Information Security Management Conference
Apart from its much-publicised use in crypto-currency, blockchain technology is used in a wide range of application areas, from diamonds to wine. The most common application of this technology is in smart contracts in supply chain management, where assurance of delivery and provenance are important. One problem for an Ethereum consortium is the potential for disruption caused by a Denial-of-Service attack across the consortium nodes. Such an attack can be launched from a single source or multiple sources to amplify the effect. This paper investigates the impact of various Denial-of-Service attacks on an Ethereum Consortium deployed on the Azure Cloud …
Mobile Device Wardriving Tools’ Comparison: Nuku’Alofa As Case Study, Raymond Lutui, ‘Osai Tete’Imoana, George Maeakafa
Mobile Device Wardriving Tools’ Comparison: Nuku’Alofa As Case Study, Raymond Lutui, ‘Osai Tete’Imoana, George Maeakafa
Australian Information Security Management Conference
This paper describes the justification for a project to assess the security status of wireless networks usage in Nuku’alofa, the CBD of Tonga, By War Driving these suburbs, actual data was gathered to indicate the security status of wireless networks and provide an understanding of the users’ level of awareness and attitudes towards wireless security. This paper also takes the opportunity to compare the performance of the War driving tools that this study employed – GMoN, SWardriving, and Wi-Fi Scan. Wireless network communication remains a challenging and critical issue. This study takes an exploratory approach in which it allows the …
The Terror Network Industrial Complex: A Measurement And Analysis Of Terrorist Networks And War Stocks, James Usher, Pierpaolo Dondio
The Terror Network Industrial Complex: A Measurement And Analysis Of Terrorist Networks And War Stocks, James Usher, Pierpaolo Dondio
Conference papers
This paper presents a measurement study and analysis of the structure of multiple Islamic terrorist networks to determine if similar characteristics exist between those networks. We examine data gathered from four terrorist groups: Al-Qaeda, ISIS, Lashkar-e-Taiba (LeT) and Jemaah Islamiyah (JI) consisting of six terror networks. Our study contains 471 terrorists’ nodes and 2078 links. Each terror network is compared in terms efficiency, communication and composition of network metrics. The paper examines the effects these terrorist attacks had on US aerospace and defence stocks (herein War stocks). We found that the Islamic terror groups increase recruitment during the planned attacks, …
Ai For Ground Robots For Autonomous Coverage Of Designated Areas, Danxue Huang
Ai For Ground Robots For Autonomous Coverage Of Designated Areas, Danxue Huang
Summer Community of Scholars Posters (RCEU and HCR Combined Programs)
No abstract provided.
The Effects Of Student Activity Dashboards On Student Participation, Performance, And Persistence, Edwin Hill
The Effects Of Student Activity Dashboards On Student Participation, Performance, And Persistence, Edwin Hill
CCAC Theses and Dissertations
Researchers have turned their attention to the use of learning analytics and dashboard systems in education. Schools are using knowledge gained in this area to address the issue of persistence to increase graduation rates. While dashboard systems have been developed and are starting to be implemented, it is not yet clear how activity and performance data from dashboards influences student behavior. In addition, much of the research has been focused on instructor-facing dashboards rather than student-facing dashboards. The current study implemented a student-facing dashboard in the learning management system and measured how information on the dashboard may have influenced participation …