Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197731
Chase D. Carthen, Araam Zaremehrjardi, Vinh D. Le, Carlos Cardillo, S. Strachan, A. Tavakkoli, F. Harris, S. Dascalu
In many smart city projects, a common choice to capture spatial information is the inclusion of LiDAR data, but this decision will often invoke severe growing pains within the existing infrastructure. In this paper, we introduce a data pipeline that orchestrates Apache NiFi (NiFi), Apache MiNiFi (MiNiFi), and several other tools as an automated solution in order to relay and archive LiDAR data captured by deployed edge devices. The LiDAR sensors utilized within this workflow are Velodyne Ultra Pucks sensors that capture at a rate of 10 frames per second and produces 6-7 GB packet capture (PCAP) files per hour. By both compressing the file after capturing it and compressing the file in real-time, we discovered that gzip produced a file of 5 GB and saved about 5 minutes in transmission time to NiFi, as well as saving considerable CPU time when compressing the file in real-time. Alternatively, we chose XZ as the compression algorithm for the ingestion of LiDAR data onto an institution compute cluster due to its high compression ratio. In order to evaluate the capabilities of our system design, the features of this data pipeline were compared against existing third-party services, namely Globus and RSync.
{"title":"Orchestrating Apache NiFi/MiNiFi within a Spatial Data Pipeline","authors":"Chase D. Carthen, Araam Zaremehrjardi, Vinh D. Le, Carlos Cardillo, S. Strachan, A. Tavakkoli, F. Harris, S. Dascalu","doi":"10.1109/SERA57763.2023.10197731","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197731","url":null,"abstract":"In many smart city projects, a common choice to capture spatial information is the inclusion of LiDAR data, but this decision will often invoke severe growing pains within the existing infrastructure. In this paper, we introduce a data pipeline that orchestrates Apache NiFi (NiFi), Apache MiNiFi (MiNiFi), and several other tools as an automated solution in order to relay and archive LiDAR data captured by deployed edge devices. The LiDAR sensors utilized within this workflow are Velodyne Ultra Pucks sensors that capture at a rate of 10 frames per second and produces 6-7 GB packet capture (PCAP) files per hour. By both compressing the file after capturing it and compressing the file in real-time, we discovered that gzip produced a file of 5 GB and saved about 5 minutes in transmission time to NiFi, as well as saving considerable CPU time when compressing the file in real-time. Alternatively, we chose XZ as the compression algorithm for the ingestion of LiDAR data onto an institution compute cluster due to its high compression ratio. In order to evaluate the capabilities of our system design, the features of this data pipeline were compared against existing third-party services, namely Globus and RSync.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117158384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197805
Yang Wang, T. Goto, Tadaaki Kirisima, K. Tsuchida
Music is an essential "element" in our lives. With the rapid development of technology, the use of compact disks and tapes for listening various forms of music of different cultures has become obsolete. Because of the generation of considerable music data, the accurate classification of music data has become a critical topic of research, and the development of deep learning technology provides a solution for music classification. Transfer learning techniques are widely used in image recognition but are rarely used for music classification. In this study, a small music dataset is used for music classification using transfer learning.
{"title":"Novel Music Genre Classification System Using Transfer Learning on a Small Dataset","authors":"Yang Wang, T. Goto, Tadaaki Kirisima, K. Tsuchida","doi":"10.1109/SERA57763.2023.10197805","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197805","url":null,"abstract":"Music is an essential \"element\" in our lives. With the rapid development of technology, the use of compact disks and tapes for listening various forms of music of different cultures has become obsolete. Because of the generation of considerable music data, the accurate classification of music data has become a critical topic of research, and the development of deep learning technology provides a solution for music classification. Transfer learning techniques are widely used in image recognition but are rarely used for music classification. In this study, a small music dataset is used for music classification using transfer learning.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116089268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197775
Young Lee, Arlen P. McDonald, Jeong Yang
The issues related to SolarWinds attacks point out a large concern with modern software development projects in that there are fundamental flaws with existing security infrastructure. The purpose of this research is to investigate to what extent can the SootDiff analysis tool, a bytecode comparison tool, be used to determine if an application has been tampered with by comparing a known good version with a version that is unknown. The compiled and decompiled bytecodes as Jimple representations were compared to analyze the unique differences in identifying code tempering. The results showed that the scope of the variable is important in whether the change was detected. Variables with a scope that was entirely contained within one method could have their names changed without triggering a warning, but global variables to objects could not. The parameter variable and the local variable behave differently. Since the parameter is in the publicly available part of the method Java treats it the same way as it does the global variable. The local variable is strictly private to the method and not made available to the outside. Such findings can support the analysis tool which is useful for identifying potential breaches to detect meaningful changes in code even if it is decompiled.
{"title":"Identifying Code Tampering Using A Bytecode Comparison Analysis Tool","authors":"Young Lee, Arlen P. McDonald, Jeong Yang","doi":"10.1109/SERA57763.2023.10197775","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197775","url":null,"abstract":"The issues related to SolarWinds attacks point out a large concern with modern software development projects in that there are fundamental flaws with existing security infrastructure. The purpose of this research is to investigate to what extent can the SootDiff analysis tool, a bytecode comparison tool, be used to determine if an application has been tampered with by comparing a known good version with a version that is unknown. The compiled and decompiled bytecodes as Jimple representations were compared to analyze the unique differences in identifying code tempering. The results showed that the scope of the variable is important in whether the change was detected. Variables with a scope that was entirely contained within one method could have their names changed without triggering a warning, but global variables to objects could not. The parameter variable and the local variable behave differently. Since the parameter is in the publicly available part of the method Java treats it the same way as it does the global variable. The local variable is strictly private to the method and not made available to the outside. Such findings can support the analysis tool which is useful for identifying potential breaches to detect meaningful changes in code even if it is decompiled.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115513094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197743
Madhukar Shrestha, Y. Kim, Jeehyun Oh, J. Rhee, Yung Ryn Choe, Fei Zuo, M. Park, Gang Qian
System provenance forensic analysis has been studied by a large body of research work. This area needs fine granularity data such as system calls along with event fields to track the dependencies of events. While prior work on security datasets has been proposed, we found a useful dataset of realistic attacks and details that can be used for provenance tracking is lacking. We created a new dataset of eleven vulnerable cases for system forensic analysis. It includes the full details of system calls including syscall parameters. Realistic attack scenarios with real software vulnerabilities and exploits are used. Also, we created two sets of benign and adversary scenarios which are manually labeled for supervised machine-learning analysis. We demonstrate the details of the dataset events and dependency analysis.
{"title":"ProvSec: Cybersecurity System Provenance Analysis Benchmark Dataset","authors":"Madhukar Shrestha, Y. Kim, Jeehyun Oh, J. Rhee, Yung Ryn Choe, Fei Zuo, M. Park, Gang Qian","doi":"10.1109/SERA57763.2023.10197743","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197743","url":null,"abstract":"System provenance forensic analysis has been studied by a large body of research work. This area needs fine granularity data such as system calls along with event fields to track the dependencies of events. While prior work on security datasets has been proposed, we found a useful dataset of realistic attacks and details that can be used for provenance tracking is lacking. We created a new dataset of eleven vulnerable cases for system forensic analysis. It includes the full details of system calls including syscall parameters. Realistic attack scenarios with real software vulnerabilities and exploits are used. Also, we created two sets of benign and adversary scenarios which are manually labeled for supervised machine-learning analysis. We demonstrate the details of the dataset events and dependency analysis.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124899576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197671
Fei Zuo, J. Rhee, M. Park, Gang Qian
Programming courses in colleges often involve a myriad of coding assignments, which brings heavy grading workloads for instructors. To alleviate this problem, automatic programming evaluation tools are becoming more of a requirement than an option. However, after considering the actual requirements in our teaching practice, we have noticed that the current solutions still suffer from shortcomings and limitations. In the process of addressing the challenges, we propose and implement a brand new code assessment application based on PowerShell, which shows both extendibility and configurability. In particular, we integrate both black-box testing and the lexical analysis into the system, thus achieving a customized solution to meet specific requirements. This paper presents the architecture and design of our automatic code assessment application. Furthermore, we conduct empirical evaluations on the proposed system following the Technology Acceptance Model, and also investigate the drawbacks of manual assessment of coding assignments in terms of reliability and fairness. Finally, the evaluations demonstrate the effectiveness of our proposed auto-grader in facilitating the code assessment targeting college-level programming courses.
{"title":"PowerGrader: Automating Code Assessment Based on PowerShell for Programming Courses","authors":"Fei Zuo, J. Rhee, M. Park, Gang Qian","doi":"10.1109/SERA57763.2023.10197671","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197671","url":null,"abstract":"Programming courses in colleges often involve a myriad of coding assignments, which brings heavy grading workloads for instructors. To alleviate this problem, automatic programming evaluation tools are becoming more of a requirement than an option. However, after considering the actual requirements in our teaching practice, we have noticed that the current solutions still suffer from shortcomings and limitations. In the process of addressing the challenges, we propose and implement a brand new code assessment application based on PowerShell, which shows both extendibility and configurability. In particular, we integrate both black-box testing and the lexical analysis into the system, thus achieving a customized solution to meet specific requirements. This paper presents the architecture and design of our automatic code assessment application. Furthermore, we conduct empirical evaluations on the proposed system following the Technology Acceptance Model, and also investigate the drawbacks of manual assessment of coding assignments in terms of reliability and fairness. Finally, the evaluations demonstrate the effectiveness of our proposed auto-grader in facilitating the code assessment targeting college-level programming courses.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130543041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197801
Sung-woo Moon, Y. Lim
Vehicular edge computing (VEC) is a promising technology to support vehicular applications that leverage machine learning (ML) technology. Due to limited resources of the vehicle, the vehicle uses Split learning (SL) to split the computation of the ML model and offload it to the VEC server (VECS). Federated learning (FL) is also used for data privacy and parallel training of the vehicles. Therefore, SplitFed learning, which combines SL and FL, enables parallel processing, which is an advantage of FL, and reduces the computational burden on the vehicle through ML model split, which is an advantage of SL. However, the SplitFed learning does not consider the mobility of device/vehicle. Therefore, we propose a SplitFed learning with mobility method to minimize the training time of the model. SplitFed learning with mobility method is a migration method of the ML model when the vehicle moves from the current serving VECS to the target VECS. Through simulations, compared with conventional SplitFed learning where the vehicle travels after 50% and 80% of training is completed, the proposed method can reduce training time by about 19-33% for LeNet and by about 22-44% for VGG16, respectively, and does not degrade accuracy of model.
{"title":"Split and Federated Learning with Mobility in Vehicular Edge Computing","authors":"Sung-woo Moon, Y. Lim","doi":"10.1109/SERA57763.2023.10197801","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197801","url":null,"abstract":"Vehicular edge computing (VEC) is a promising technology to support vehicular applications that leverage machine learning (ML) technology. Due to limited resources of the vehicle, the vehicle uses Split learning (SL) to split the computation of the ML model and offload it to the VEC server (VECS). Federated learning (FL) is also used for data privacy and parallel training of the vehicles. Therefore, SplitFed learning, which combines SL and FL, enables parallel processing, which is an advantage of FL, and reduces the computational burden on the vehicle through ML model split, which is an advantage of SL. However, the SplitFed learning does not consider the mobility of device/vehicle. Therefore, we propose a SplitFed learning with mobility method to minimize the training time of the model. SplitFed learning with mobility method is a migration method of the ML model when the vehicle moves from the current serving VECS to the target VECS. Through simulations, compared with conventional SplitFed learning where the vehicle travels after 50% and 80% of training is completed, the proposed method can reduce training time by about 19-33% for LeNet and by about 22-44% for VGG16, respectively, and does not degrade accuracy of model.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124077570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197760
Yohei Hara, H. Ono
In recent years, the world has been promoting the control of carbon dioxide emissions, the substance responsible for global warming, in order to prevent global warming as the global environment has become increasingly degraded. In addition, a system has been established to curb not only global warming but also other categories that have an impact on the global environment. In this context, industries are promoting operations and activities that take in account the environment in addition to the pursuit of profit. However, while environmental emissions have been evaluated, the impact on the environment has not yet been assessed in detail. Therefore, this study aims to clarify the emissions of environmental impacts in the chemical industry, which is the large source of emissions.
{"title":"Study on Emissions of Environmental Impact in Chemical Industry","authors":"Yohei Hara, H. Ono","doi":"10.1109/SERA57763.2023.10197760","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197760","url":null,"abstract":"In recent years, the world has been promoting the control of carbon dioxide emissions, the substance responsible for global warming, in order to prevent global warming as the global environment has become increasingly degraded. In addition, a system has been established to curb not only global warming but also other categories that have an impact on the global environment. In this context, industries are promoting operations and activities that take in account the environment in addition to the pursuit of profit. However, while environmental emissions have been evaluated, the impact on the environment has not yet been assessed in detail. Therefore, this study aims to clarify the emissions of environmental impacts in the chemical industry, which is the large source of emissions.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129134277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Internet of Things (IoT) connects a huge number of IoT devices, including sensors, actuators, computing nodes, etc. Those IoT devices communicate with each other by using different communication techniques. Generally, LTE, 5G, and WiFi are involved in IoT to support communication. However, it needs considerable communication infrastructures to support wireless communication. An obvious issue is how to create a communication network in some regions that have less communication support. Wireless Sensor Network (WSN) is a kind of wireless ad hoc network, which organizes a huge number of wireless sensors to create a self-organized wireless network. Therefore, the WSN is a potential approach to providing communication in those regions. Since WSN is highly dynamic, how to create the wireless network to provide optimal coverage rate is still open. In this article, we propose a dynamic wireless sensor deployment scenarios that provide optimal coverage rate in a certain region. Our model proposes a coverage rate based on possible disaster scenarios for communication between Base Stations and UAVs. We optimize the Particle Swarm Optimization (PSO) algorithm and find the maximum coverage rate.
{"title":"A Dynamic Wireless Sensor Network Deployment Algorithm for Emergency Communications","authors":"Kubra Gundogan, Nuri Alperen Kose, Khushi Gupta, Damilola Oladimeji, Fan Liang","doi":"10.1109/SERA57763.2023.10197686","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197686","url":null,"abstract":"The Internet of Things (IoT) connects a huge number of IoT devices, including sensors, actuators, computing nodes, etc. Those IoT devices communicate with each other by using different communication techniques. Generally, LTE, 5G, and WiFi are involved in IoT to support communication. However, it needs considerable communication infrastructures to support wireless communication. An obvious issue is how to create a communication network in some regions that have less communication support. Wireless Sensor Network (WSN) is a kind of wireless ad hoc network, which organizes a huge number of wireless sensors to create a self-organized wireless network. Therefore, the WSN is a potential approach to providing communication in those regions. Since WSN is highly dynamic, how to create the wireless network to provide optimal coverage rate is still open. In this article, we propose a dynamic wireless sensor deployment scenarios that provide optimal coverage rate in a certain region. Our model proposes a coverage rate based on possible disaster scenarios for communication between Base Stations and UAVs. We optimize the Particle Swarm Optimization (PSO) algorithm and find the maximum coverage rate.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131214898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197798
Sajidullah S. Khan, Mohammed Bin Abdulrahman Alawairdhi, M. Al-Akhras
Facial expressions are the most effective way to characterize people’s motives, emotions, and feelings. Several new methods are proposed each year; however, the accuracy of facial expression recognition still needs to be improved especially in uncontrolled conditions. In this paper, we propose a hybrid facial expression model that considers both texture and orientation features to classify expressions. Two types of descriptors namely Local binary pattern and Weber local descriptor are used to preserve the local intensity information and orientation of edges. In the next step, computing the Histograms of oriented gradients (HOG) features from the Local binary pattern and Weber local descriptor images to capture micro-expressions. Then, the AdaBoost feature selection algorithm is utilized to choose the best features from the combined HOG features. The results of the experiments demonstrate that the method proposed in this study performs better than existing methods.
{"title":"Texture and Orientation-based Feature Extraction for Robust Facial Expression Recognition","authors":"Sajidullah S. Khan, Mohammed Bin Abdulrahman Alawairdhi, M. Al-Akhras","doi":"10.1109/SERA57763.2023.10197798","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197798","url":null,"abstract":"Facial expressions are the most effective way to characterize people’s motives, emotions, and feelings. Several new methods are proposed each year; however, the accuracy of facial expression recognition still needs to be improved especially in uncontrolled conditions. In this paper, we propose a hybrid facial expression model that considers both texture and orientation features to classify expressions. Two types of descriptors namely Local binary pattern and Weber local descriptor are used to preserve the local intensity information and orientation of edges. In the next step, computing the Histograms of oriented gradients (HOG) features from the Local binary pattern and Weber local descriptor images to capture micro-expressions. Then, the AdaBoost feature selection algorithm is utilized to choose the best features from the combined HOG features. The results of the experiments demonstrate that the method proposed in this study performs better than existing methods.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133948975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-23DOI: 10.1109/SERA57763.2023.10197734
A. Mbiada, Bassey Isong, Francis Lugayizi, A. Abu-Mahfouz
This paper proposes a framework for creating educational software systems that effectively meet student engagement and pedagogical goals. While different design methodologies have been used in developing educational software, most fail to satisfy the demands of users, stakeholders, and students, making it difficult to incorporate them into daily activities and support optimal learning outcomes. The proposed framework combines important techniques in Scrum, dynamic system development methods, and instructional design models. It comprises seven key phases: initial, instructional orientation, analysis, design, production, integration and implementation, and evaluation. The framework aims to guide the creation of educational software that successfully satisfies teachers' and students' demands and can be easily incorporated into teaching and learning procedures. We present the proposed framework components and compare them with other existing related models. Implementing the framework is expected to improve teaching/ learning, reduce development costs and time.
{"title":"Towards Integrated Framework for Efficient Educational Software Development","authors":"A. Mbiada, Bassey Isong, Francis Lugayizi, A. Abu-Mahfouz","doi":"10.1109/SERA57763.2023.10197734","DOIUrl":"https://doi.org/10.1109/SERA57763.2023.10197734","url":null,"abstract":"This paper proposes a framework for creating educational software systems that effectively meet student engagement and pedagogical goals. While different design methodologies have been used in developing educational software, most fail to satisfy the demands of users, stakeholders, and students, making it difficult to incorporate them into daily activities and support optimal learning outcomes. The proposed framework combines important techniques in Scrum, dynamic system development methods, and instructional design models. It comprises seven key phases: initial, instructional orientation, analysis, design, production, integration and implementation, and evaluation. The framework aims to guide the creation of educational software that successfully satisfies teachers' and students' demands and can be easily incorporated into teaching and learning procedures. We present the proposed framework components and compare them with other existing related models. Implementing the framework is expected to improve teaching/ learning, reduce development costs and time.","PeriodicalId":211080,"journal":{"name":"2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116289555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：