Pub Date : 2024-05-08DOI: 10.3991/ijim.v18i09.48879
Asem Mohammed Ibrahim, Ibrahim Ahmed Al-Farhan, Eman Wefky Ahmed, A. S. Abdelmagid, Majed A. Al-Zahrani, Nusaibah J. Dakamsih
In this paper, we investigate the potential of teaching energy-related topics to enhance secondary school students’ future thinking skills, including problem-solving, predicting, and envisioning. A physics enrichment program was conducted using the “Madrasati” digital platform in a semi-experimental design involving two groups of students (experimental and control). Utilizing a pre-post measurement approach, the study employed a novel instrument to assess future thinking across three distinct levels. The analysis, involving ETA squared, Cohen’s effect size, and independent sample t-tests, revealed a significant improvement in future thinking skills for the program group. These findings suggest the potential of incorporating energy-related topics and digital platforms into secondary science curricula to enhance critical thinking skills necessary for addressing future challenges. The study further underscores the potential of digital tools and innovative teaching approaches in optimizing students’ development of future thinking competencies.
在本文中，我们研究了通过教授与能源相关的话题来提高中学生未来思维能力（包括解决问题、预测和设想）的潜力。我们利用 "Madrasati "数字平台开展了一项物理强化课程，采用半实验设计，涉及两组学生（实验组和对照组）。该研究采用了一种前测后测的方法，使用一种新颖的工具来评估三个不同层次的未来思维。分析包括 ETA 平方、科恩效应大小和独立样本 t 检验，结果显示，项目组学生的未来思维能力有了显著提高。这些研究结果表明，将能源相关主题和数字平台纳入中学科学课程，有可能提高应对未来挑战所需的批判性思维能力。研究进一步强调了数字工具和创新教学方法在优化学生未来思维能力发展方面的潜力。
{"title":"Enhancing High School Students' Future Thinking Skills through Interactive Digital Platforms for Teaching Energy Issues","authors":"Asem Mohammed Ibrahim, Ibrahim Ahmed Al-Farhan, Eman Wefky Ahmed, A. S. Abdelmagid, Majed A. Al-Zahrani, Nusaibah J. Dakamsih","doi":"10.3991/ijim.v18i09.48879","DOIUrl":"https://doi.org/10.3991/ijim.v18i09.48879","url":null,"abstract":"In this paper, we investigate the potential of teaching energy-related topics to enhance secondary school students’ future thinking skills, including problem-solving, predicting, and envisioning. A physics enrichment program was conducted using the “Madrasati” digital platform in a semi-experimental design involving two groups of students (experimental and control). Utilizing a pre-post measurement approach, the study employed a novel instrument to assess future thinking across three distinct levels. The analysis, involving ETA squared, Cohen’s effect size, and independent sample t-tests, revealed a significant improvement in future thinking skills for the program group. These findings suggest the potential of incorporating energy-related topics and digital platforms into secondary science curricula to enhance critical thinking skills necessary for addressing future challenges. The study further underscores the potential of digital tools and innovative teaching approaches in optimizing students’ development of future thinking competencies.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"222 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141002036","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 : 2024-05-08DOI: 10.3991/ijim.v18i09.49029
Ahdi Hassan, Habibullah Pathan, Sedigheh Shakib Kotamjani, Sabah Mohamed Abbas Hamza, Richa Rastogi
More efficient instructional models that encourage students to engage more actively in their education are essential in today’s world. How information can be found and exchanged, as well as how explanations are delivered, have been shaped by technology. The outcomes demonstrate that mobile learning (m-learning) has enhanced collaboration among instructors and learners, provided immediate feedback, increased student participation and engagement, allowed for authentic learning and evaluation, and supported learning communities in higher education institutions. There was also a change in the teachers’ instructional methods. Students will benefit from simple learning activities, convenient communication, and coaching provided through mobile devices. This study recommends using a learning-based convolutional neural network (CNN) technique to improve students’ English-speaking fluency. In addition, communication between teachers and children in remote areas becomes easier through an interactive system, making both sides more accessible. As a result, it is advisable that educational institutions continually develop innovative teaching techniques that bridge face-to-face and formal-informal learning in the educational setting. The article discusses the background of mobile learning and how it might enhance e-learning as a whole. The m-learning approach is described in this paper as a future version of e-learning. In comparison to the next generation of educational systems, it will be extensively offered and simple to operate for any individual interested in learning. The article also discusses the benefits and potential drawbacks of mobile learning in current educational institutions.
{"title":"Analyzing the Deep Learning-Based Mobile Environment in Educational Institutions","authors":"Ahdi Hassan, Habibullah Pathan, Sedigheh Shakib Kotamjani, Sabah Mohamed Abbas Hamza, Richa Rastogi","doi":"10.3991/ijim.v18i09.49029","DOIUrl":"https://doi.org/10.3991/ijim.v18i09.49029","url":null,"abstract":"More efficient instructional models that encourage students to engage more actively in their education are essential in today’s world. How information can be found and exchanged, as well as how explanations are delivered, have been shaped by technology. The outcomes demonstrate that mobile learning (m-learning) has enhanced collaboration among instructors and learners, provided immediate feedback, increased student participation and engagement, allowed for authentic learning and evaluation, and supported learning communities in higher education institutions. There was also a change in the teachers’ instructional methods. Students will benefit from simple learning activities, convenient communication, and coaching provided through mobile devices. This study recommends using a learning-based convolutional neural network (CNN) technique to improve students’ English-speaking fluency. In addition, communication between teachers and children in remote areas becomes easier through an interactive system, making both sides more accessible. As a result, it is advisable that educational institutions continually develop innovative teaching techniques that bridge face-to-face and formal-informal learning in the educational setting. The article discusses the background of mobile learning and how it might enhance e-learning as a whole. The m-learning approach is described in this paper as a future version of e-learning. In comparison to the next generation of educational systems, it will be extensively offered and simple to operate for any individual interested in learning. The article also discusses the benefits and potential drawbacks of mobile learning in current educational institutions.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":" 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140999733","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 : 2024-05-08DOI: 10.3991/ijim.v18i09.49291
Jinjin Wang
The emergence of online education platforms, driven by interactive mobile technology, has significantly reshaped traditional educational paradigms and underscored the critical need for advanced analysis and improvement of student interactions. Effective analysis of student interaction is crucial for enhancing teaching quality and optimizing the learning experience in these digitally enriched environments. Traditional analysis frameworks often face challenges such as inaccuracies in anomaly detection and inefficiencies in data handling, particularly when handling extensive datasets typical of online platforms. This study introduces a novel approach to enhancing student interaction analysis systems by leveraging the synergy between machine learning and advanced interactive mobile technologies. Initially, the study proposes an advanced anomaly detection method tailored for identifying irregular student interactions. This method utilizes a blend of machine learning algorithms and the real-time data processing capabilities of mobile technology. Furthermore, to address the complexities of data transmission in mobile-based online education ecosystems, a state-ofthe- art congestion control algorithm has been developed. This algorithm optimizes data flow, significantly enhancing transmission stability and efficiency. The integration of interactive mobile technology with machine learning offers a robust and dynamic framework for analyzing student interactions, thereby facilitating a more engaging and effective online educational experience. This research contributes to the advancement of online education quality and efficiency by emphasizing the role of interactive mobile technology in shaping future learning environments.
{"title":"Improvement of Student Interaction Analysis in Online Education Platforms Through Interactive Mobile Technology and Machine Learning Integration","authors":"Jinjin Wang","doi":"10.3991/ijim.v18i09.49291","DOIUrl":"https://doi.org/10.3991/ijim.v18i09.49291","url":null,"abstract":"The emergence of online education platforms, driven by interactive mobile technology, has significantly reshaped traditional educational paradigms and underscored the critical need for advanced analysis and improvement of student interactions. Effective analysis of student interaction is crucial for enhancing teaching quality and optimizing the learning experience in these digitally enriched environments. Traditional analysis frameworks often face challenges such as inaccuracies in anomaly detection and inefficiencies in data handling, particularly when handling extensive datasets typical of online platforms. This study introduces a novel approach to enhancing student interaction analysis systems by leveraging the synergy between machine learning and advanced interactive mobile technologies. Initially, the study proposes an advanced anomaly detection method tailored for identifying irregular student interactions. This method utilizes a blend of machine learning algorithms and the real-time data processing capabilities of mobile technology. Furthermore, to address the complexities of data transmission in mobile-based online education ecosystems, a state-ofthe- art congestion control algorithm has been developed. This algorithm optimizes data flow, significantly enhancing transmission stability and efficiency. The integration of interactive mobile technology with machine learning offers a robust and dynamic framework for analyzing student interactions, thereby facilitating a more engaging and effective online educational experience. This research contributes to the advancement of online education quality and efficiency by emphasizing the role of interactive mobile technology in shaping future learning environments.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140998796","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 : 2024-05-08DOI: 10.3991/ijim.v18i09.49033
Cemei Li, Mohd Nazri Abdul Rahman, Xin Zhang
Several scholars have focused on this area due to the significance of mobile technology in the educational process, resulting in a substantial body of scholarly work. The primary objective of this study is to investigate the impact of mobile learning on students’ academic performance. The meta-analysis approach was utilized in this research. The available research was examined using several databases to find the relevant studies that were within the scope of the investigation. The study’s inclusion criteria and components were implemented following a literature review. This research proposes a mobile education system approach based on genetic algorithms to address the issues with the current system. The analysis findings indicate that most of them stay at around 10%. The salary only slightly increases when numerous individuals teach, but it also falls within a regular, appropriate range that can accommodate more complex tasks. According to the factor analysis findings, the influence of mobile educational devices on students’ learning performance varied depending on the course and subject. However, it remained constant regardless of the students’ education level and implementation duration. Apart from the previously mentioned research findings, this article also includes a descriptive analysis of the studies that were part of the meta-analysis.
{"title":"An Analysis of Student's Academic Achievement in Genetic Algorithms Based on Mobile Learning Applications","authors":"Cemei Li, Mohd Nazri Abdul Rahman, Xin Zhang","doi":"10.3991/ijim.v18i09.49033","DOIUrl":"https://doi.org/10.3991/ijim.v18i09.49033","url":null,"abstract":"Several scholars have focused on this area due to the significance of mobile technology in the educational process, resulting in a substantial body of scholarly work. The primary objective of this study is to investigate the impact of mobile learning on students’ academic performance. The meta-analysis approach was utilized in this research. The available research was examined using several databases to find the relevant studies that were within the scope of the investigation. The study’s inclusion criteria and components were implemented following a literature review. This research proposes a mobile education system approach based on genetic algorithms to address the issues with the current system. The analysis findings indicate that most of them stay at around 10%. The salary only slightly increases when numerous individuals teach, but it also falls within a regular, appropriate range that can accommodate more complex tasks. According to the factor analysis findings, the influence of mobile educational devices on students’ learning performance varied depending on the course and subject. However, it remained constant regardless of the students’ education level and implementation duration. Apart from the previously mentioned research findings, this article also includes a descriptive analysis of the studies that were part of the meta-analysis.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":" 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141000922","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 : 2024-04-23DOI: 10.3991/ijim.v18i08.46473
M. Karyotaki, Athanasios Drigas, C. Skianis
Chatbots are dialogue systems that utilize computational linguistics (CL), including automatic speech recognition (ASR) and natural language processing (NLP). Artificially intelligent conversational agents combine personalization, interoperability, and scalability with the aim of promoting safe information monitoring, management, and retrieval. AI chatbots offer user-friendly engagement for innovative e-learning, care assistance, and multilingual digital content creation, promoting inclusiveness and AI-enhanced communication. They are a breakthrough for future societies and economies as they can offer cost-effective, tailor-made, and instant exchange of knowledge and skills, including on-site assistance, health monitoring, and e-consultation. AI chatbots are constantly improving to the benefit of their users. Their economic and social impact is expected to rise as individuals, especially vulnerable populations, are trained to use them for lifelong learning, decision-making, and problem-solving.
{"title":"Mobile/VR/Robotics/IoT-Based Chatbots and Intelligent Personal Assistants for Social Inclusion","authors":"M. Karyotaki, Athanasios Drigas, C. Skianis","doi":"10.3991/ijim.v18i08.46473","DOIUrl":"https://doi.org/10.3991/ijim.v18i08.46473","url":null,"abstract":"Chatbots are dialogue systems that utilize computational linguistics (CL), including automatic speech recognition (ASR) and natural language processing (NLP). Artificially intelligent conversational agents combine personalization, interoperability, and scalability with the aim of promoting safe information monitoring, management, and retrieval. AI chatbots offer user-friendly engagement for innovative e-learning, care assistance, and multilingual digital content creation, promoting inclusiveness and AI-enhanced communication. They are a breakthrough for future societies and economies as they can offer cost-effective, tailor-made, and instant exchange of knowledge and skills, including on-site assistance, health monitoring, and e-consultation. AI chatbots are constantly improving to the benefit of their users. Their economic and social impact is expected to rise as individuals, especially vulnerable populations, are trained to use them for lifelong learning, decision-making, and problem-solving.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"89 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140670558","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 : 2024-04-23DOI: 10.3991/ijim.v18i08.46901
Khaled Ahmed Aqeel Alzoubi
The study focused on the impact of using augmented reality (AR) in teaching mathematics to tenth-grade students in the 2022–2023 academic year. The sample consisted of 70 students from schools in the city of Amman, who were divided into 35 students in the experimental group and 35 students in the control group. The researcher utilized the quasi-experimental method and collected data through questionnaires and testing tools. Data were statistically analyzed using the MANOVA test, outcome analysis techniques, and GLM test. The results indicate the quality of virtual reality (VR). Students’ ability to process data improved by 94% in the experimental group and 88% in the control group. The experimental group demonstrated an effective contribution of 97% in improving graphic representation ability, while the control group showed a contribution of 92%. The study relied on the descriptive-analytical method. The study concluded that AR technology and its usage have become largely dependent on preparing technical and material requirements. It also highlighted that this technology aids students in learning scientific facts, concepts, and instructions in an easy and effective manner. The results indicate the necessity of expanding scientific research and studies on the advantages and disadvantages of AR technology and its optimal utilization.
{"title":"The Effect of Virtual Reality Technology in Teaching Mathematics on Students’ Ability to Process Data and Graphic Representation","authors":"Khaled Ahmed Aqeel Alzoubi","doi":"10.3991/ijim.v18i08.46901","DOIUrl":"https://doi.org/10.3991/ijim.v18i08.46901","url":null,"abstract":"The study focused on the impact of using augmented reality (AR) in teaching mathematics to tenth-grade students in the 2022–2023 academic year. The sample consisted of 70 students from schools in the city of Amman, who were divided into 35 students in the experimental group and 35 students in the control group. The researcher utilized the quasi-experimental method and collected data through questionnaires and testing tools. Data were statistically analyzed using the MANOVA test, outcome analysis techniques, and GLM test. The results indicate the quality of virtual reality (VR). Students’ ability to process data improved by 94% in the experimental group and 88% in the control group. The experimental group demonstrated an effective contribution of 97% in improving graphic representation ability, while the control group showed a contribution of 92%. The study relied on the descriptive-analytical method. The study concluded that AR technology and its usage have become largely dependent on preparing technical and material requirements. It also highlighted that this technology aids students in learning scientific facts, concepts, and instructions in an easy and effective manner. The results indicate the necessity of expanding scientific research and studies on the advantages and disadvantages of AR technology and its optimal utilization.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"140 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140668718","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}
Board games are educational tools consisting of a board with boxes drawn on it. In this game, there are several rules that must be followed, which involve social interaction between children during playtime. This study aims to develop a board game on the theme of air to support children’s growth and development as well as enhance their knowledge related to the topic. Moreover, this R&D study employed 4D development with data analysis techniques for validation, practicality, and effectiveness. The data were collected through interviews and expert validation of the product. Moreover, this study has reached the fourth stage, which is dissemination. The population of this study consisted of 65 children aged 5–6 years at Aisyiyah Sicincin Kindergarten, Padang Pariaman Regency. Based on the results, it was found that board game media are effective in promoting children’s growth and development in terms of cognitive, linguistic, and motor skills.
{"title":"Development of Board Game Media on Air Theme for Children Aged 5-6 Years","authors":"Nenny Mahyuddin, Rani Sofiya, Andi Agusniati, Yuliani Nurani, Dony Novaliendry, Elida","doi":"10.3991/ijim.v18i08.46135","DOIUrl":"https://doi.org/10.3991/ijim.v18i08.46135","url":null,"abstract":"Board games are educational tools consisting of a board with boxes drawn on it. In this game, there are several rules that must be followed, which involve social interaction between children during playtime. This study aims to develop a board game on the theme of air to support children’s growth and development as well as enhance their knowledge related to the topic. Moreover, this R&D study employed 4D development with data analysis techniques for validation, practicality, and effectiveness. The data were collected through interviews and expert validation of the product. Moreover, this study has reached the fourth stage, which is dissemination. The population of this study consisted of 65 children aged 5–6 years at Aisyiyah Sicincin Kindergarten, Padang Pariaman Regency. Based on the results, it was found that board game media are effective in promoting children’s growth and development in terms of cognitive, linguistic, and motor skills.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"44 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140667079","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 : 2024-04-23DOI: 10.3991/ijim.v18i08.48219
Erti Hamimi, Dian Nugraheni, Syahrul Candra Ardani, Isnanik Juni Fitriyah, Ikliil Zhaafirahdiningko, Indra Fardhani, Muhammad Fajar Marsuki
The Society 5.0 era emphasizes the use of technology and innovation to address social challenges, such as the utilization of Internet of Things (IoT) technology. Creative thinking plays a vital role in generating new ideas and approaches to problem-solving. Science, technology, engineering, and mathematics (STEM)-based education can help individuals develop creative thinking skills by engaging in problem-solving and creating innovative solutions. This study aims to enhance the creative thinking abilities of junior high school students on the topic of temperature through the development of STEM-based instructional media. This is achieved by creating the fire detector system (FDS) educational kit and testing its validity and practicality in the learning process. The study model used in this study is the analysis, design, development, implementation, and evaluation (ADDIE) model. The ADDIE model consists of five stages: analysis, design, development, implementation, and evaluation. The research instruments utilized include structured questionnaires for expert validation and application testing. The participants involved in this study include several seventh-grade students and one science teacher from a junior high school. The collected data is then analyzed using qualitative and quantitative descriptive data analysis techniques. By utilizing the FDS educational kit, it is hoped that it can effectively foster creative thinking skills among junior high school students.
{"title":"Development of STEM-Based Learning Media FDS (Fire Detector System) Integrated with Blynk IoT to Improve Students' Creativity on Temperature Material","authors":"Erti Hamimi, Dian Nugraheni, Syahrul Candra Ardani, Isnanik Juni Fitriyah, Ikliil Zhaafirahdiningko, Indra Fardhani, Muhammad Fajar Marsuki","doi":"10.3991/ijim.v18i08.48219","DOIUrl":"https://doi.org/10.3991/ijim.v18i08.48219","url":null,"abstract":"The Society 5.0 era emphasizes the use of technology and innovation to address social challenges, such as the utilization of Internet of Things (IoT) technology. Creative thinking plays a vital role in generating new ideas and approaches to problem-solving. Science, technology, engineering, and mathematics (STEM)-based education can help individuals develop creative thinking skills by engaging in problem-solving and creating innovative solutions. This study aims to enhance the creative thinking abilities of junior high school students on the topic of temperature through the development of STEM-based instructional media. This is achieved by creating the fire detector system (FDS) educational kit and testing its validity and practicality in the learning process. The study model used in this study is the analysis, design, development, implementation, and evaluation (ADDIE) model. The ADDIE model consists of five stages: analysis, design, development, implementation, and evaluation. The research instruments utilized include structured questionnaires for expert validation and application testing. The participants involved in this study include several seventh-grade students and one science teacher from a junior high school. The collected data is then analyzed using qualitative and quantitative descriptive data analysis techniques. By utilizing the FDS educational kit, it is hoped that it can effectively foster creative thinking skills among junior high school students.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"12 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140667557","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 : 2024-04-23DOI: 10.3991/ijim.v18i08.48873
Jianjiang Wang
In higher education, it is imperative to maintain educational quality, which requires necessitates a thorough evaluation of teaching methods. The advent of mixed reality (MR) technology, combined with interactive mobile capabilities, introduces innovative possibilities for traditional educational assessment frameworks. This study is dedicated to investigating the application of MR and interactive mobile technologies in higher education teaching evaluations, with a focus on assessing their effectiveness and implementation outcomes. Research to date has explored MR’s educational applications. However, the integration of interactive mobile technologies alongside MR in developing specific methodologies and evaluative tools for teaching evaluations has not been fully realized. This underutilizes the combined potential of these technologies. This paper is anchored in two principal research endeavors. Initially, it delves into the construction of a meta-model facilitated by MR-aided and interactive mobile-enhanced teacher-student interactions, utilizing a hierarchical remote interaction pyramid model. This process involves developing extensible associative functions, determining index weights, and establishing evaluation levels, which collectively enhance the evaluation’s multidimensionality, interactivity, and scientific precision. Subsequently, the analytic hierarchy process (AHP) is employed to quantitatively assess the educational impact of MR and interactive mobile experiences on students. This approach provides support for customized and precise teaching evaluations. The findings reveal that integrating MR technology with interactive mobile capabilities significantly enhances the interactivity and systematic scientific approach of teaching evaluations. This fosters a more multidimensional and interactive framework for educational evaluation.
{"title":"Revolutionizing Higher Education Teaching Evaluation with Interactive Mobile and Mixed Reality: A Methodological and Applied Analysis","authors":"Jianjiang Wang","doi":"10.3991/ijim.v18i08.48873","DOIUrl":"https://doi.org/10.3991/ijim.v18i08.48873","url":null,"abstract":"In higher education, it is imperative to maintain educational quality, which requires necessitates a thorough evaluation of teaching methods. The advent of mixed reality (MR) technology, combined with interactive mobile capabilities, introduces innovative possibilities for traditional educational assessment frameworks. This study is dedicated to investigating the application of MR and interactive mobile technologies in higher education teaching evaluations, with a focus on assessing their effectiveness and implementation outcomes. Research to date has explored MR’s educational applications. However, the integration of interactive mobile technologies alongside MR in developing specific methodologies and evaluative tools for teaching evaluations has not been fully realized. This underutilizes the combined potential of these technologies. This paper is anchored in two principal research endeavors. Initially, it delves into the construction of a meta-model facilitated by MR-aided and interactive mobile-enhanced teacher-student interactions, utilizing a hierarchical remote interaction pyramid model. This process involves developing extensible associative functions, determining index weights, and establishing evaluation levels, which collectively enhance the evaluation’s multidimensionality, interactivity, and scientific precision. Subsequently, the analytic hierarchy process (AHP) is employed to quantitatively assess the educational impact of MR and interactive mobile experiences on students. This approach provides support for customized and precise teaching evaluations. The findings reveal that integrating MR technology with interactive mobile capabilities significantly enhances the interactivity and systematic scientific approach of teaching evaluations. This fosters a more multidimensional and interactive framework for educational evaluation.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"1 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140666546","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 : 2024-04-23DOI: 10.3991/ijim.v18i08.45917
Minh Pham Ngoc, Tan Ngo Duy, Hoan Huynh Duc, Kiet Tran Anh
The audio detection system enables autonomous cars to recognize their surroundings based on the noise produced by moving vehicles. This paper proposes the utilization of a machine learning model based on convolutional neural networks (CNN) integrated into an embedded system supported by a microphone. The system includes a specialized microphone and a main processor. The microphone enables the transmission of an accurate analog signal to the main processor, which then analyzes the recorded signal and provides a prediction in return. While designing an adequate hardware system is a crucial task that directly impacts the predictive capability of the system, it is equally imperative to train a CNN model with high accuracy. To achieve this goal, a dataset containing over 3000 up-to-5-second WAV files for four classes was obtained from open-source research. The dataset is then divided into training, validation, and testing sets. The training data is converted into images using the spectrogram technique before training the CNN. Finally, the generated model is tested on the testing segment, resulting in a model accuracy of 77.54%.
{"title":"Proposed CNN Model for Audio Recognition on Embedded Device","authors":"Minh Pham Ngoc, Tan Ngo Duy, Hoan Huynh Duc, Kiet Tran Anh","doi":"10.3991/ijim.v18i08.45917","DOIUrl":"https://doi.org/10.3991/ijim.v18i08.45917","url":null,"abstract":"The audio detection system enables autonomous cars to recognize their surroundings based on the noise produced by moving vehicles. This paper proposes the utilization of a machine learning model based on convolutional neural networks (CNN) integrated into an embedded system supported by a microphone. The system includes a specialized microphone and a main processor. The microphone enables the transmission of an accurate analog signal to the main processor, which then analyzes the recorded signal and provides a prediction in return. While designing an adequate hardware system is a crucial task that directly impacts the predictive capability of the system, it is equally imperative to train a CNN model with high accuracy. To achieve this goal, a dataset containing over 3000 up-to-5-second WAV files for four classes was obtained from open-source research. The dataset is then divided into training, validation, and testing sets. The training data is converted into images using the spectrogram technique before training the CNN. Finally, the generated model is tested on the testing segment, resulting in a model accuracy of 77.54%.","PeriodicalId":507995,"journal":{"name":"International Journal of Interactive Mobile Technologies (iJIM)","volume":"36 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140666214","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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