Pub Date : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111331
Hilary K Y Ng, P. Lam
While the benefits of the flipped classroom approach on learning outcomes have been widely documented, there remain limited understandings of how positively students evaluate the flipped classroom approach. To address this, this research examined how students feel toward their flipped learning experience and whether this effect varies by academic discipline. We recruited 468 university students from seven faculties, ranging from the Faculty of Arts to the Faculty of Medicine, to fill in a short survey to evaluate their feelings toward their flipped learning experiences in terms of confidence, likeness, and satisfaction. Results showed that academic disciplines significantly shaped students’ feelings. Overall, students whose disciplines emphasize the application of the knowledge were more confident in, desired to, and satisfied with learning in the flipped classroom, than those whose disciplines emphasize theoretical explorations. Future implications of the flipped classroom as an instructional strategy are discussed.
{"title":"Emotional Responses toward the Flipped Classroom Approach across Academic Disciplines","authors":"Hilary K Y Ng, P. Lam","doi":"10.1109/ICIET56899.2023.10111331","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111331","url":null,"abstract":"While the benefits of the flipped classroom approach on learning outcomes have been widely documented, there remain limited understandings of how positively students evaluate the flipped classroom approach. To address this, this research examined how students feel toward their flipped learning experience and whether this effect varies by academic discipline. We recruited 468 university students from seven faculties, ranging from the Faculty of Arts to the Faculty of Medicine, to fill in a short survey to evaluate their feelings toward their flipped learning experiences in terms of confidence, likeness, and satisfaction. Results showed that academic disciplines significantly shaped students’ feelings. Overall, students whose disciplines emphasize the application of the knowledge were more confident in, desired to, and satisfied with learning in the flipped classroom, than those whose disciplines emphasize theoretical explorations. Future implications of the flipped classroom as an instructional strategy are discussed.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114252660","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111125
Piya Pangsapa, Paulina Pui Yun Wong, Gary Wai Chung Wong, U. Techanamurthy, Wan Syukriah Wan Mohamad, Daniel Shen Jiandong
This study aimed to evaluate the effectiveness of metaverse technology in education by analyzing the design and setup of virtual environments and comparing flipped and non-flipped classroom methods. The main analysis was conducted through statistical analysis of a survey and text feedback from participants. The results showed that the use of pedagogy in the metaverse was a significant predictor of student intent to use, while technological factors were not. This outcome is contrary to previous studies that have emphasized the importance of technological capabilities in virtual reality education. Feedback and observations also suggested that learning was more engaging when utilizing social interactions with NPCs and offline activities through the flipped classroom method, however, no statistical results were captured for these observations. Additionally, the study found that the use of authoring tools in the metaverse helped in creating and sharing scenes for learning, making it a useful tool for teachers to align their curriculum. Overall, the findings support the potential of metaverse technology to improve student engagement and performance.
{"title":"Enhancing Humanities Learning with Metaverse Technology: A Study on Student Engagement and Performance","authors":"Piya Pangsapa, Paulina Pui Yun Wong, Gary Wai Chung Wong, U. Techanamurthy, Wan Syukriah Wan Mohamad, Daniel Shen Jiandong","doi":"10.1109/ICIET56899.2023.10111125","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111125","url":null,"abstract":"This study aimed to evaluate the effectiveness of metaverse technology in education by analyzing the design and setup of virtual environments and comparing flipped and non-flipped classroom methods. The main analysis was conducted through statistical analysis of a survey and text feedback from participants. The results showed that the use of pedagogy in the metaverse was a significant predictor of student intent to use, while technological factors were not. This outcome is contrary to previous studies that have emphasized the importance of technological capabilities in virtual reality education. Feedback and observations also suggested that learning was more engaging when utilizing social interactions with NPCs and offline activities through the flipped classroom method, however, no statistical results were captured for these observations. Additionally, the study found that the use of authoring tools in the metaverse helped in creating and sharing scenes for learning, making it a useful tool for teachers to align their curriculum. Overall, the findings support the potential of metaverse technology to improve student engagement and performance.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126378891","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111226
Ryutaro Matsumoto, S. Yamaguchi
This paper formulates the problem of building a firewall to prevent the spreading of a malicious botnet using a given number of white-hat bots and proposes a solution. The baseline Surrounding tactic builds a firewall by placing white-hat bots next to each other to enclose the malicious botnet. In contrast, the proposed method builds a firewall by placing white-hat bots at bottlenecks in the network. The experimental results show that this method builds an effective firewall using fewer white- hat bots than the Surrounding tactic, and the effect depends on the network density.
{"title":"On Building Firewall with White-Hat Bots to Prevent the Infection Spread of Malicious Botnets","authors":"Ryutaro Matsumoto, S. Yamaguchi","doi":"10.1109/ICIET56899.2023.10111226","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111226","url":null,"abstract":"This paper formulates the problem of building a firewall to prevent the spreading of a malicious botnet using a given number of white-hat bots and proposes a solution. The baseline Surrounding tactic builds a firewall by placing white-hat bots next to each other to enclose the malicious botnet. In contrast, the proposed method builds a firewall by placing white-hat bots at bottlenecks in the network. The experimental results show that this method builds an effective firewall using fewer white- hat bots than the Surrounding tactic, and the effect depends on the network density.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124271045","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111185
Yiqing Mao, Jiamin Tang, Wan Wang, Li Cheng
Many scholars believe that creativity is an essential skill for students in the 21st century. In recent years, an increasing number of researchers have begun to explore the factors that influence students’ creativity and hope to enhance students’ creativity levels. Previous studies have explored the impact of offline classroom environments on students’ creativity, finding that classrooms with a more creative atmosphere can effectively stimulate students’ creative motivation, cultivate their creativity and creative personality. This study focuses on exploring the relationship between creative classroom atmosphere in online programming courses and students’ creativity, and aims to provide suggestions for cultivating students’ creativity in online courses. This study used video analysis to analyze the recorded videos of online courses and conducted interviews with six teachers who have experience in online Scratch teaching. The main conclusions drawn from the study are as follows: 1) a more creative classroom atmosphere can effectively promote student creativity, and 2) the impact of a creative classroom environment on student creative behavior is not always immediate, and may have a delayed effect.
{"title":"The Impact of Online Creative Classroom Environment on Students’ Creativity: A Case Study Based on Online Scratch Visual Programming","authors":"Yiqing Mao, Jiamin Tang, Wan Wang, Li Cheng","doi":"10.1109/ICIET56899.2023.10111185","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111185","url":null,"abstract":"Many scholars believe that creativity is an essential skill for students in the 21st century. In recent years, an increasing number of researchers have begun to explore the factors that influence students’ creativity and hope to enhance students’ creativity levels. Previous studies have explored the impact of offline classroom environments on students’ creativity, finding that classrooms with a more creative atmosphere can effectively stimulate students’ creative motivation, cultivate their creativity and creative personality. This study focuses on exploring the relationship between creative classroom atmosphere in online programming courses and students’ creativity, and aims to provide suggestions for cultivating students’ creativity in online courses. This study used video analysis to analyze the recorded videos of online courses and conducted interviews with six teachers who have experience in online Scratch teaching. The main conclusions drawn from the study are as follows: 1) a more creative classroom atmosphere can effectively promote student creativity, and 2) the impact of a creative classroom environment on student creative behavior is not always immediate, and may have a delayed effect.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115274284","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111490
Trisnawawi Azmi Ali, W. Wongkia, P. Laosinchai
Blockchain is one of the most significant and innovative technological developments in recent years. Blockchain use cases are no longer limited to the financial sector but have expanded into various industries such as healthcare and education. It is imperative to educate individuals early to prepare them for the widespread adoption of blockchain technology. To this end, we created a hybrid board game to educate players about the blockchain mechanism. The game mechanics incorporate three topics: block properties, mining nodes, and the proof-of-work process. Each player competes to get as many coins as possible from mining and transacting while protecting their mining nodes from other players. This study aims to determine how well the players understood each topic after playing the game. We experimented with 22 students in grades 11 and 12, ranging in age from 17 to 18. We administered a multiple-choice test, followed by an interview, to determine their level of knowledge. After participating in the activity, the average score for the block properties topic was 51 percent, for the mining nodes was 51 percent, and for the proof-of-work process was 40 percent.
{"title":"A Hybrid Board Game for Learning Blockchain Mechanisms","authors":"Trisnawawi Azmi Ali, W. Wongkia, P. Laosinchai","doi":"10.1109/ICIET56899.2023.10111490","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111490","url":null,"abstract":"Blockchain is one of the most significant and innovative technological developments in recent years. Blockchain use cases are no longer limited to the financial sector but have expanded into various industries such as healthcare and education. It is imperative to educate individuals early to prepare them for the widespread adoption of blockchain technology. To this end, we created a hybrid board game to educate players about the blockchain mechanism. The game mechanics incorporate three topics: block properties, mining nodes, and the proof-of-work process. Each player competes to get as many coins as possible from mining and transacting while protecting their mining nodes from other players. This study aims to determine how well the players understood each topic after playing the game. We experimented with 22 students in grades 11 and 12, ranging in age from 17 to 18. We administered a multiple-choice test, followed by an interview, to determine their level of knowledge. After participating in the activity, the average score for the block properties topic was 51 percent, for the mining nodes was 51 percent, and for the proof-of-work process was 40 percent.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115666683","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111446
Thanaphan Bhatia, Bundit Manaskasemsak, A. Rungsawang
Social media provides a rapid, simple, and accessible platform for people to communicate and share news through the Internet. However, the information published on this platform is not always trustworthy. As a result, malicious actors often use social media to disseminate fake news or mislead news readers, such as with personal or political attacks that could spark protests or riots. In this paper, we propose a learning technique for detecting fake news sources (i.e., fake users) on the Twitter platform. Three main types of features—tweet content, published time, and social graph—have been defined and extracted from Twitter to create a deep neural network (DNN) as a predictive model. We conducted experiments on PolitiFact, a standard FakeNewsNet dataset. The results show that the proposed approach outperforms traditional baselines with 98.7% accuracy.
{"title":"Detecting Fake News Sources on Twitter Using Deep Neural Network","authors":"Thanaphan Bhatia, Bundit Manaskasemsak, A. Rungsawang","doi":"10.1109/ICIET56899.2023.10111446","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111446","url":null,"abstract":"Social media provides a rapid, simple, and accessible platform for people to communicate and share news through the Internet. However, the information published on this platform is not always trustworthy. As a result, malicious actors often use social media to disseminate fake news or mislead news readers, such as with personal or political attacks that could spark protests or riots. In this paper, we propose a learning technique for detecting fake news sources (i.e., fake users) on the Twitter platform. Three main types of features—tweet content, published time, and social graph—have been defined and extracted from Twitter to create a deep neural network (DNN) as a predictive model. We conducted experiments on PolitiFact, a standard FakeNewsNet dataset. The results show that the proposed approach outperforms traditional baselines with 98.7% accuracy.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122809640","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111210
Jermine G. Valen-Dacanay, T. Palaoag
The extensive usage of simulation software to meet the demand for online learning has become the subject of learning analytics as the core of performance assessment in different program courses. This study shall determine and discover the learning analytics of students in the computer-based System Drafting and Design course using LabVIEW simulation software. Different machine learning techniques are applied and tested to evaluate the performance level of students in the computer-based System Drafting and Design course. The dataset for analysis is the students' performance and topic impressions. Machine learning algorithms are applied to determine the correlation of the datasets to determine the learning analytics. The resulting correlation coefficient presents a promising result that supports defining the learning outcomes the student acquired. Techniques that consistently respond to outcomes suggest that the student experience and teachers' assessment correlate with learning. This technique proved that using LabVIEW as a simulation software can promote the minimum required skills in an electronics design course and not only the theoretical foundation. Thus, the result can be a basis for future instruction quality improvement plans of laboratory-oriented courses.
{"title":"Exploring The Learning Analytics Of Skill-Based Course Using Machine Learning Classification Models","authors":"Jermine G. Valen-Dacanay, T. Palaoag","doi":"10.1109/ICIET56899.2023.10111210","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111210","url":null,"abstract":"The extensive usage of simulation software to meet the demand for online learning has become the subject of learning analytics as the core of performance assessment in different program courses. This study shall determine and discover the learning analytics of students in the computer-based System Drafting and Design course using LabVIEW simulation software. Different machine learning techniques are applied and tested to evaluate the performance level of students in the computer-based System Drafting and Design course. The dataset for analysis is the students' performance and topic impressions. Machine learning algorithms are applied to determine the correlation of the datasets to determine the learning analytics. The resulting correlation coefficient presents a promising result that supports defining the learning outcomes the student acquired. Techniques that consistently respond to outcomes suggest that the student experience and teachers' assessment correlate with learning. This technique proved that using LabVIEW as a simulation software can promote the minimum required skills in an electronics design course and not only the theoretical foundation. Thus, the result can be a basis for future instruction quality improvement plans of laboratory-oriented courses.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124972014","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111487
Aryobarzan Atashpendar, S. Rothkugel
Tests have been shown to improve the long-term retention of students, referred to as the "testing effect". Different question formats, such as multiple choice and recall, have varying properties. While recall questions induce a longer retention than multiple choice ones, they are harder for students since answers must be actively retrieved from memory. Moreover, regular testing inherently increases the teacher's workload, particularly since feedback on each test is paramount for an effective bearing on the student's understanding and learning. This work introduces BEACON Q, a digital quiz application combining different question formats and progressively adapting their difficulty to each student’s level. The level is derived from past answers as well as ratings provided by the students which constitute their perceived understanding of each topic. BEACON Q delivers immediate feedback through detailed explanations, without requiring manual assessment by the teacher. Tests are scheduled for periods of time, thus giving the students the flexibility to choose an appropriate time to take the test. An initial evaluation of BEACON Q has been performed in the context of three different computer science classes at our university. Preliminary results are presented in this paper.
{"title":"Improving Long-Term Retention through Personalized Recall Testing and Immediate Feedback","authors":"Aryobarzan Atashpendar, S. Rothkugel","doi":"10.1109/ICIET56899.2023.10111487","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111487","url":null,"abstract":"Tests have been shown to improve the long-term retention of students, referred to as the \"testing effect\". Different question formats, such as multiple choice and recall, have varying properties. While recall questions induce a longer retention than multiple choice ones, they are harder for students since answers must be actively retrieved from memory. Moreover, regular testing inherently increases the teacher's workload, particularly since feedback on each test is paramount for an effective bearing on the student's understanding and learning. This work introduces BEACON Q, a digital quiz application combining different question formats and progressively adapting their difficulty to each student’s level. The level is derived from past answers as well as ratings provided by the students which constitute their perceived understanding of each topic. BEACON Q delivers immediate feedback through detailed explanations, without requiring manual assessment by the teacher. Tests are scheduled for periods of time, thus giving the students the flexibility to choose an appropriate time to take the test. An initial evaluation of BEACON Q has been performed in the context of three different computer science classes at our university. Preliminary results are presented in this paper.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128958979","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111094
W. Dou
Compared with the traditional teaching mode, online distance teaching mode breaks the barriers of time and space so that more people have access to education, which makes Massive Open Online Courses (MOOCs) popular all over the world, especially in China. However, MOOCs bring more challenges to teaching in the meantime. Students’ participation in online learning becomes one of the most prominent problems, which is hard to deal with compared with traditional face-to-face teaching mode. So with the integration of the advantages of MOOCs and traditional teaching mode, Small Private Online Course(SPOC) teaching mode is more and more favored by educators. Guided by the 5C Framework Theory, this paper aims to advance effective online-teaching strategies in order to motivate students’ active participation in online learning process under SPOC mode. Based on the analyses of qualitative and quantitative data, the results show that teachers can improve students’ participation in online courses by “the Optimized Combination” from three dimensions: interactive teaching platforms, teaching content carriers and teaching task difficulty, which provide a new perspective for improving the effectiveness of online teaching.
{"title":"Online Teaching Strategies to Motivate Students’ Active Participation Based on Personalized SPOC Teaching Mode","authors":"W. Dou","doi":"10.1109/ICIET56899.2023.10111094","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111094","url":null,"abstract":"Compared with the traditional teaching mode, online distance teaching mode breaks the barriers of time and space so that more people have access to education, which makes Massive Open Online Courses (MOOCs) popular all over the world, especially in China. However, MOOCs bring more challenges to teaching in the meantime. Students’ participation in online learning becomes one of the most prominent problems, which is hard to deal with compared with traditional face-to-face teaching mode. So with the integration of the advantages of MOOCs and traditional teaching mode, Small Private Online Course(SPOC) teaching mode is more and more favored by educators. Guided by the 5C Framework Theory, this paper aims to advance effective online-teaching strategies in order to motivate students’ active participation in online learning process under SPOC mode. Based on the analyses of qualitative and quantitative data, the results show that teachers can improve students’ participation in online courses by “the Optimized Combination” from three dimensions: interactive teaching platforms, teaching content carriers and teaching task difficulty, which provide a new perspective for improving the effectiveness of online teaching.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128718030","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 : 2023-03-18DOI: 10.1109/ICIET56899.2023.10111478
Franco Martin F. Lagarde, Kenshin John B. Reales, Vince Audrey B. Sychangco, Joel C. De Goma
Anxiety is a natural response of a person’s body to stress, but if a person experiences excessive anxiety on a regular basis, it could develop into a mental condition. In this study, two algorithms were utilized and compared in order to analyze anxiety symptoms from speech from a male gender. The audio database that was utilized for this study was the CREMA-D database and selected 1,152 male audio files with emotions that are related to anxiety, which were, Anger, Fear, Sad, and Disgusted. Audio pre-processing techniques were done to the audio files in order to improve the audio quality, as well as feature extraction techniques in order to obtain better accuracy from the models. The algorithms used in this study for recognizing anxiety symptoms were the SVM model and the Convolutional Neural Network. The SVM and CNN models performed well on the dataset, with accuracy scores of 62 percent and 78.1 percent, respectively, but it can be concluded that the CNN model outperformed the SVM model. For CNN, we were able to transform the audio datasets into pictures of heat maps of each audio file. It was then separated into two folders in an 80:20 ratio. While for the SVM, the researchers used the audio files themselves. The researchers used Python and BandLab as tools for the research.
{"title":"Comparing Convolutional Neural Network and Support Vector Machine for Analyzing Anxiety Symptoms from Speech of Different Ethnicities","authors":"Franco Martin F. Lagarde, Kenshin John B. Reales, Vince Audrey B. Sychangco, Joel C. De Goma","doi":"10.1109/ICIET56899.2023.10111478","DOIUrl":"https://doi.org/10.1109/ICIET56899.2023.10111478","url":null,"abstract":"Anxiety is a natural response of a person’s body to stress, but if a person experiences excessive anxiety on a regular basis, it could develop into a mental condition. In this study, two algorithms were utilized and compared in order to analyze anxiety symptoms from speech from a male gender. The audio database that was utilized for this study was the CREMA-D database and selected 1,152 male audio files with emotions that are related to anxiety, which were, Anger, Fear, Sad, and Disgusted. Audio pre-processing techniques were done to the audio files in order to improve the audio quality, as well as feature extraction techniques in order to obtain better accuracy from the models. The algorithms used in this study for recognizing anxiety symptoms were the SVM model and the Convolutional Neural Network. The SVM and CNN models performed well on the dataset, with accuracy scores of 62 percent and 78.1 percent, respectively, but it can be concluded that the CNN model outperformed the SVM model. For CNN, we were able to transform the audio datasets into pictures of heat maps of each audio file. It was then separated into two folders in an 80:20 ratio. While for the SVM, the researchers used the audio files themselves. The researchers used Python and BandLab as tools for the research.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"483 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116191796","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}
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