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7 pages, 557 KiB

Open AccessProceeding Paper

The Application and Performance Comparison of Different Versions of YOLO Image Recognition Systems

by You-Shyang Chen and Yi-Xuan Chen

Eng. Proc. 2025, 98(1), 1; https://doi.org/10.3390/engproc2025098001 - 30 May 2025

Viewed by 436

With advancements in computational power and artificial intelligence (AI), image recognition has become more efficient and widely used. You Only Look Once (YOLO) stands out for its fast and accurate object detection, making it popular among researchers. The technology enhances daily life, from [...] Read more.

With advancements in computational power and artificial intelligence (AI), image recognition has become more efficient and widely used. You Only Look Once (YOLO) stands out for its fast and accurate object detection, making it popular among researchers. The technology enhances daily life, from smartphone facial recognition improving security to thermal imaging aiding public health during the pandemic. However, identifying the right image recognition system for varied image types remains challenging. By evaluating the performance of YOLO’s versions (e.g., YOLOv3 and YOLOv4) regarding structure, speed, accuracy, and adaptability, we identified appropriate algorithms for specific tasks, recommending optimal image recognition techniques for different applications. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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10 pages, 1229 KiB

Open AccessProceeding Paper

Heart Rate Variability-Based Non-Invasive Method for Ovulation Detection

by Yen-Hua Lee and Wei-Wen Hung

Eng. Proc. 2025, 98(1), 2; https://doi.org/10.3390/engproc2025098002 - 30 May 2025

Viewed by 77

Abstract

Monitoring women’s health during the menstrual cycle is crucial. Traditional methods for estimating ovulation dates involve measuring body temperature and analyzing blood, urine, cervical mucus, or saliva. While effective, these methods come with various advantages and limitations. Therefore, we introduce a novel approach [...] Read more.

Monitoring women’s health during the menstrual cycle is crucial. Traditional methods for estimating ovulation dates involve measuring body temperature and analyzing blood, urine, cervical mucus, or saliva. While effective, these methods come with various advantages and limitations. Therefore, we introduce a novel approach to more easily and accurately detect both the menstrual period and the ovulation date. After gathering essential physiological data from test subjects, the ovulation date is predicted. Heart rate waveform signals are used to identify physiological parameters linked to ovulation, enhancing prediction accuracy without relying on consumable items such as test strips or patches. By integrating non-invasive image signal processing technology and heart rate variability analysis algorithms, the timing of ovulation within the menstrual cycle is accurately predicted. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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6 pages, 362 KiB

Open AccessProceeding Paper

An Integrated Fuzzy Convolutional Neural Network Model for Stock Price Prediction

by Jia-Wen Wang and Jr-Shian Chen

Eng. Proc. 2025, 98(1), 3; https://doi.org/10.3390/engproc2025098003 - 30 May 2025

Viewed by 236

Abstract

Stock market forecasting has always been researched extensively in Social Sciences. In this research, Fuzzy time series with deep learning is widely adopted to create a fuzzy convolutional neural network integration model as this model enhances the fuzzification of values to enhance feature [...] Read more.

Stock market forecasting has always been researched extensively in Social Sciences. In this research, Fuzzy time series with deep learning is widely adopted to create a fuzzy convolutional neural network integration model as this model enhances the fuzzification of values to enhance feature characteristics using two-dimensional input data in convolutional neural networks (CNNs). This allows the model to retain complete feature information. The fuzzy convolutional neural network (FCNN) model autonomously learns and extracts crucial features by integrating stock market data, resulting in improved forecasting accuracy. In this study, the model was tested for forecasting the Taiwan Weighted Stock Index and metrics such as the mean squared error (MSE) and mean absolute error (MAE), and the results were compared with the real data. The results showed that the model provided accurate predictions. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 502 KiB

Open AccessProceeding Paper

Adaptive Frequency and Assignment Algorithm for Context-Based Arithmetic Compression Codes for H.264 Video Intraframe Encoding

by Huang-Chun Hsu and Jian-Jiun Ding

Eng. Proc. 2025, 98(1), 4; https://doi.org/10.3390/engproc2025098004 - 4 Jun 2025

Viewed by 189

Abstract

In modern communication technology, short videos are increasingly used on social media platforms. The advancement of video codecs is pivotal in communication. In this study, we developed a new scheme to encode the residue of intraframes. For the H.264 baseline profile, we used [...] Read more.

In modern communication technology, short videos are increasingly used on social media platforms. The advancement of video codecs is pivotal in communication. In this study, we developed a new scheme to encode the residue of intraframes. For the H.264 baseline profile, we used context-based arithmetic variable-length coding (CAVLC) to encode the residue of integer transforms in a block-wise manner. In the developed method, the DC and AC coefficients are separated. In addition, context assignment, adaptive scanning, range increment, and mutual learning are adopted in a mixture of fixed-length and variable-length schemes, and block-wise compressions of the frequency table are applied to obtain improved compression rates. Compressing the frequency prevents CAVLC from being hindered by horizontally/vertically dominated blocks. The developed method outperforms CAVLC, with average reductions of 7.81, 8.58, and 7.88% in quarter common intermediate format (QCIF), common intermediate format (CIF), and full high-definition (FHD) inputs. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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5 pages, 701 KiB

Open AccessProceeding Paper

Development of Artificial Urine Using Commonly Available Ingredients for Ultraviolet–Visible Spectroscopy

by Patryk Sokołowski and Maria Babińska

Eng. Proc. 2025, 98(1), 5; https://doi.org/10.3390/engproc2025098005 - 5 Jun 2025

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Abstract

A simple urine phantom was developed to replicate the ultraviolet–visible (UV–Vis) spectrum of healthy human urine. Made from four safe and widely available ingredients, it addresses the challenges of biological samples, including safety risks and storage issues. The spectroscopic analysis results confirmed strong [...] Read more.

A simple urine phantom was developed to replicate the ultraviolet–visible (UV–Vis) spectrum of healthy human urine. Made from four safe and widely available ingredients, it addresses the challenges of biological samples, including safety risks and storage issues. The spectroscopic analysis results confirmed strong similarity to natural urine, making the phantom appropriate for testing spectroscopic methods, calibrating optical devices, and evaluating diagnostic sensors. It can also serve as a starting point for advanced phantoms tailored to specific patient needs or diseases. This reliable alternative facilitates research in optical diagnostics or biosensor development by simplifying preliminary sensor testing. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 176 KiB

Open AccessProceeding Paper

Applying the Analytical Hierarchy Process to Exploring Demand and Technology Preferences in InsurTech: Focusing on Consumer Concerns

by Mei-Su Chen and Yung-Cheng Liao

Eng. Proc. 2025, 98(1), 6; https://doi.org/10.3390/engproc2025098006 - 9 Jun 2025

Viewed by 172

Abstract

By employing the analytic hierarchy process (AHP), we investigated consumer demand and preferences for InsurTech technologies. A survey was conducted with 350 respondents, yielding 348 completed questionnaires and achieving a response rate of 99.4%. After consistency checks, 78 invalid questionnaires were excluded, resulting [...] Read more.

By employing the analytic hierarchy process (AHP), we investigated consumer demand and preferences for InsurTech technologies. A survey was conducted with 350 respondents, yielding 348 completed questionnaires and achieving a response rate of 99.4%. After consistency checks, 78 invalid questionnaires were excluded, resulting in 270 valid responses, with an effective response rate of 77.3%. Using the Analytic Hierarchy Process (AHP), five critical dimensions were identified as top priorities for insurance companies implementing InsurTech solutions: (1) video insurance and mobile applications, (2) blockchain-based claims processing, (3) robo-advisors, (4) the Internet of Things (IoT), and (5) big data analytics. Video and mobile applications, along with blockchain, accounted for over 30% of the total importance of evaluating InsurTech technologies. Among the assessment criteria, “mobile applications” and “remote insurance” had the highest weights, highlighting their roles in the InsurTech service model. Insurance providers need to prioritize these two dimensions when designing their InsurTech service models to enhance service convenience and the customer experience. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

6 pages, 185 KiB

Open AccessProceeding Paper

Analysis of Severity of Losses and Wastes in Taiwan’s Agri-Food Supply Chain Using Best–Worst Method and Multi-Criteria Decision-Making

by Wen-Hua Yang, Yi-Chang Chen and Ya-Jhu Yang

Eng. Proc. 2025, 98(1), 8; https://doi.org/10.3390/engproc2025098008 - 9 Jun 2025

Viewed by 187

Abstract

Food loss and waste are critical challenges in Taiwan’s agri-food supply chain, deteriorating security and resource efficiency. By employing the best–worst method (BWM), a multi-criteria decision-making model was developed in this study to evaluate the severity of losses and wastes. Combining literature review [...] Read more.

Food loss and waste are critical challenges in Taiwan’s agri-food supply chain, deteriorating security and resource efficiency. By employing the best–worst method (BWM), a multi-criteria decision-making model was developed in this study to evaluate the severity of losses and wastes. Combining literature review results with expert survey analysis results, key loss points, and mitigation strategies were identified to enhance sustainability and efficiency in Taiwan’s agricultural food system. Among the seven stages of the agricultural food supply chain, supermarket waste (16.95%) was identified as the severest, followed by government policies (16.63%), restaurant waste (15.35%), processing loss (14.71%), production site loss (13.64%), household waste (11.93%), and logistics/storage/distribution loss (10.79%). In the subcategories of each supply chain stage, the eight severe issues were identified as “Inadequate planning and control of overall production and marketing policies” under government policies, “Adverse climate conditions” and “Imbalance in production and marketing” under production site loss, “Inaccurate market demand forecasting” and “Poor inventory management at supermarkets” under supermarket waste, and “Improper storage management of ingredients leading to spoilage” as well as “Inability to accurately forecast demand due to menu diversity” under restaurant waste. The least severe issues included “Poor production techniques” under production site loss. Other minor issues included “Inefficient use of ingredients due to poor cooking skills”, “Festive culture and traditional customs”, and “Suboptimal food labeling design”, all of which contributed to household waste. Based on these findings, we proposed recommendations to mitigate food loss and waste in Taiwan’s agricultural food supply chain from practical, policy, and academic perspectives. The results of this study serve as a reference for relevant organizations and stakeholders. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

7 pages, 181 KiB

Open AccessProceeding Paper

Generative Artificial Intelligence-Based Gamified Programming Teaching System: Promoting Peer Competition and Learning Motivation

by You-Jen Chen, Ze-Ping Chen, Chien-Hung Lai and Chen-Wei Peng

Eng. Proc. 2025, 98(1), 9; https://doi.org/10.3390/engproc2025098009 - 12 Jun 2025

Viewed by 155

Abstract

In traditional programming education, teachers typically design fixed questions and standard answers, manually grading the solutions submitted by students. This process not only requires significant time and effort from educators but may also fail to provide timely and personalized feedback due to limited [...] Read more.

In traditional programming education, teachers typically design fixed questions and standard answers, manually grading the solutions submitted by students. This process not only requires significant time and effort from educators but may also fail to provide timely and personalized feedback due to limited teaching resources. To alleviate these burdens and enhance teaching efficiency, this study leverages generative artificial intelligence (AI) technology to develop a system capable of automatically generating questions and grading answers. Students engage in programming exercises through a gamified approach, with the system providing instant feedback on their answers. Additionally, student performance is displayed via leaderboards, incorporating peer competition to boost learning motivation. According to a user survey, the gamified system demonstrates significant advantages: 56.67% of students found the system easy to use; 40% considered the system well-integrated; 60% indicated that they quickly mastered the system’s functionality, and over half (53.33%) believed that the leaderboard effectively enhanced their competitive awareness and motivation. These results suggest that the system not only reduces teachers’ workload but also increases student engagement and learning outcomes through gamified design. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

14 pages, 1599 KiB

Open AccessProceeding Paper

Values of Reused Unused Space Under Bridges

by Huang-Liang Lee, Yi-Han Lin and Wen-Bor Lu

Eng. Proc. 2025, 98(1), 10; https://doi.org/10.3390/engproc2025098010 - 13 Jun 2025

Viewed by 131

Abstract

In the development of the city, land planning must be precise and collective, emphasizing the multi-functional usability of space. The space under bridges can be utilized for urban development. However, the space under bridges has been researched only based on the theoretical operation [...] Read more.

In the development of the city, land planning must be precise and collective, emphasizing the multi-functional usability of space. The space under bridges can be utilized for urban development. However, the space under bridges has been researched only based on the theoretical operation of space, and the psychological values of the attributes of the space under bridges held by users have been rarely studied. Therefore, we explored the attributes of the space under bridges using the critical chain method and interviews with the stakeholders. The characteristic attributes were identified with regional implications. The attributes need to be considered in the spatial planning to enhance the space utilization under bridges. The results of this study present important information for policymakers or designers to plan the use of space. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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21 pages, 635 KiB

Open AccessProceeding Paper

Fuzzy Set Qualitative Comparative Analysis to Explore Elementary and Secondary School Teachers’ Behavior and Influencing Factors in Using Digital Learning Tools

by Nai-Chen Chen, Wu-Chuan Yang and Ming-Lung Wu

Eng. Proc. 2025, 98(1), 11; https://doi.org/10.3390/engproc2025098011 - 17 Jun 2025

Abstract

We investigated the configurational conditions influencing primary and secondary school teachers’ behavioral intentions (BIs) and usage behavior (UB) in adopting digital learning tools by using fuzzy set qualitative comparative analysis (fsQCA) and Tobit analysis. Based on the extended unified theory of acceptance and [...] Read more.

We investigated the configurational conditions influencing primary and secondary school teachers’ behavioral intentions (BIs) and usage behavior (UB) in adopting digital learning tools by using fuzzy set qualitative comparative analysis (fsQCA) and Tobit analysis. Based on the extended unified theory of acceptance and use of technology (UTAUT2) and by integrating TPK, configurations that drive or hinder teachers’ use of digital tools were identified. The results revealed that BI formation is driven by the core combination of facilitating conditions (FC) and hedonic motivation (HM); the synergy of FC, HM, and TPK; and the interplay of TPK and HM. UB was significantly promoted by the combinations of H with BI and TPK with BI. Conversely, the low levels of H and BI, or H and TPK lowered the levels of UB. By integrating fsQCA and Tobit analysis, the complex and asymmetric effects in digital tool adoption were understood, and recommendations were proposed to develop differentiated support strategies based on these configurational findings. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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18 pages, 1640 KiB

Open AccessProceeding Paper

Future Agenda on Higher Education Policy Using Artificial Intelligence Tools: A Review and Bibliometric Analysis

by Sai Manideep Appana, Ravi Sankar Pasupuleti, Jagadish Tulimelli, Yedukondalu Dokku, Wen-Kuo Chen and Venkateswarlu Nalluri

Eng. Proc. 2025, 98(1), 12; https://doi.org/10.3390/engproc2025098012 - 17 Jun 2025

Abstract

Artificial intelligence (AI) has emerged as a transformative force in higher education, reshaping pedagogical practices, administrative processes, and the overall learning experience. In this study, we analyzed 398 academic documents in the Scopus database, from 2014 to 2024, to explore the discourse surrounding [...] Read more.

Artificial intelligence (AI) has emerged as a transformative force in higher education, reshaping pedagogical practices, administrative processes, and the overall learning experience. In this study, we analyzed 398 academic documents in the Scopus database, from 2014 to 2024, to explore the discourse surrounding AI in higher education. Utilizing the Biblioshiny tool for bibliometric analysis, key insights were revealed across sources, keywords, citation patterns, authorship trends, international collaboration, annual growth rate, document age, and references. The analysis results highlighted the diversity of sources contributing to the discourse, the breadth of topics covered by keywords, and the significant impact of research using citation metrics. Collaborative efforts, particularly international collaboration, have played a prominent role in advancing AI research in academia. A rapidly evolving scholarly landscape is characterized by substantial annual growth and a relatively recent body of literature. The results of this study offer a basis for scholars, practitioners, and policymakers to further investigate specific content, methodologies, quality, impact of sources, keyword clustering, authorship dynamics, longitudinal trends, and citation patterns. The results also contribute to advancing the understanding of AI’s role in higher education and informs future research directions in the domain. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 618 KiB

Open AccessProceeding Paper

Implementing Finger Movement Measure System with Music-Gamification Elements

by Sinan Chen, Xian Wu, Atsuko Hayashi and Masahide Nakamura

Eng. Proc. 2025, 98(1), 13; https://doi.org/10.3390/engproc2025098013 - 18 Jun 2025

Abstract

Dexterity of the fingers is crucial in physical function, as it directly impacts daily activities and is closely connected to cognitive function. The production of brain-derived neurotrophic factor (BDNF) is related to the fingertips in motion. In previous research, we developed a finger [...] Read more.

Dexterity of the fingers is crucial in physical function, as it directly impacts daily activities and is closely connected to cognitive function. The production of brain-derived neurotrophic factor (BDNF) is related to the fingertips in motion. In previous research, we developed a finger motion measurement system for the elderly by integrating image recognition technology with a touch panel. However, despite the system’s ability to capture fine-grained coordinate changes at the moment when fingers touch the panel, the experiment was unengaging for participants. Therefore, we improved the system for measuring finger motion to be less exhausting and more enjoyable. We incorporated music and gamification elements at the moments of finger touch. We obtained a selection of representative rhythm tracks and implemented animated materials in gamification. The participants’ fatigue and enjoyment were measured based on “responsiveness” and “focus” using a quantitative evaluation method. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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7 pages, 1240 KiB

Open AccessProceeding Paper

Design and Application of Virtual Simulation Technology in Contextualized Live-Streaming E-Commerce Teaching

by Kun Peng, Dorothy DeWitt and Seng Yue Wong

Eng. Proc. 2025, 98(1), 14; https://doi.org/10.3390/engproc2025098014 - 18 Jun 2025

Abstract

We explored how VR technology models can be applied to live-streaming e-commerce teaching. We employed relevant real-time data analysis and feedback to design a virtual simulation experimental platform to provide students with personalized experiences in live-streaming e-commerce operations in traditional e-commerce courses. In [...] Read more.

We explored how VR technology models can be applied to live-streaming e-commerce teaching. We employed relevant real-time data analysis and feedback to design a virtual simulation experimental platform to provide students with personalized experiences in live-streaming e-commerce operations in traditional e-commerce courses. In this study, different contexts were integrated into live-streaming e-commerce teaching, and a standardized course for contextualized live-streaming e-commerce teaching was designed in a standardized process consisting of the following steps: “introduction link”, “theoretical explanation”, “virtual simulation operation”, and “summary and feedback”. Virtual simulation technology was standardized in contextualized live-streaming e-commerce teaching by simplifying the design of live-streaming e-commerce courses to enhance students’ practical skills. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 1398 KiB

Open AccessProceeding Paper

Analysis of Three-Stage Visit Behavior of Tourists Using ChatGPT: Agenda for Future Study

by Pahrudin Pahrudin, Li-Wei Liu, Anfitri Kristin Sihombing and Idrus Jamalulel

Eng. Proc. 2025, 98(1), 15; https://doi.org/10.3390/engproc2025098015 - 18 Jun 2025

Abstract

Chat generative pre-trained transformer (ChatGPT) is an artificial intelligence (AI) engine. Research on tourism using ChatGPT has gained traction from scholars all over the world. However, limited studies on ChatGPT and the tourism industry have been conducted using an analysis of three-stage visit [...] Read more.

Chat generative pre-trained transformer (ChatGPT) is an artificial intelligence (AI) engine. Research on tourism using ChatGPT has gained traction from scholars all over the world. However, limited studies on ChatGPT and the tourism industry have been conducted using an analysis of three-stage visit behavior. We analyzed the current trend in tourism research using ChatGPT with a bibliometric analysis based on the Scopus database. A total of 110 documents were used in this study for document review, and R studio Version 2022.12.0+353 was used to analyze the documents. The results present indicators for a systematic review of the documents, such as the number of publications and co-word analysis. A theoretical system was developed in this study to explore travelers’ behavior using ChatGPT in the pre-, during, and post-travel periods. The study results contribute to the development of the tourism industry to understand tourist behavior using ChatGPT. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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11 pages, 1036 KiB

Open AccessProceeding Paper

Empowering Community Developers with Digital Skills: Training in No-Code Mobile Applications in Effective Fieldwork Survey

by Phiraphath Phansiri, Pornsaran Kanthong, Suthida Songseeda, Santikorn Pinyong, Piyanart Imdee and Suriya Klangrit

Eng. Proc. 2025, 98(1), 16; https://doi.org/10.3390/engproc2025098016 - 18 Jun 2025

Abstract

This article presents the concept and principles of digital technology for community development and community developers. An approach for creating no-code mobile applications for community developers’ fieldwork surveys is also proposed to organize a digital technology skill training program focused on no-code mobile [...] Read more.

This article presents the concept and principles of digital technology for community development and community developers. An approach for creating no-code mobile applications for community developers’ fieldwork surveys is also proposed to organize a digital technology skill training program focused on no-code mobile application development for community developers. The training program consists of a two-day hands-on workshop in no-code mobile application development with 50 community developers participating in its development. A 70% increase in participants’ knowledge of utilizing digital technology for local community development was observed, with all participants (100%) successfully developing no-code mobile applications for surveying data on their communities. Additionally, the participants expressed high satisfaction with the training format and content, with an average score of 4.80. Digital technology knowledge is essential for contemporary community development efforts. Empowering community developers, especially those engaged in fieldwork, to independently acquire mobile app development skills or access continuous learning resources significantly enhances their professional capacity. This empowerment leads to more effective and efficient community development practices, particularly in community data collection. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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11 pages, 1110 KiB

Open AccessProceeding Paper

Evaluation Index for Healing Gardens in Computer-Aided Design

by Cheng-Kai Weng, Chao-Feng Lai and Wei-Chieh Yeh

Eng. Proc. 2025, 98(1), 17; https://doi.org/10.3390/engproc2025098017 - 19 Jun 2025

Abstract

We developed an evaluation index model for healing gardens designed using computer-aided design. The landscape therapy theory, innovative methodologies such as the fuzzy Delphi method, and the analytic hierarchy process (AHP) were integrated into the model. Three core design indices for healing gardens—somatosensory [...] Read more.

We developed an evaluation index model for healing gardens designed using computer-aided design. The landscape therapy theory, innovative methodologies such as the fuzzy Delphi method, and the analytic hierarchy process (AHP) were integrated into the model. Three core design indices for healing gardens—somatosensory elements, visual components, and physical activity features—were identified and analyzed using the developed index model in this study. Plant diversity was identified as the most significant factor, followed by modeling aesthetics, color variety, plant healing properties, spatial recreational features, sensory richness, unobstructed circulation, and barrier-free design. While the developed evaluation index model has limitations, it is a novel and systematic model based on innovative computing methods to assess and enhance contemporary healing garden design. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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8 pages, 386 KiB

Open AccessProceeding Paper

Effectiveness of Cooperative Learning on English Learning Using Experimental Design in Elementary School: A Case Study of the Quizlet Online Platform

by Chih-Wei Lin, Ya-Fang Hsieh, Chi-Pei Ou Yang, Shan-Shan Chen, Chin-Cheng Yang and Chuan Chang

Eng. Proc. 2025, 98(1), 8007; https://doi.org/10.3390/engproc2025098007 - 9 Jun 2025

Viewed by 231

Abstract

We examined the effects of cooperative learning on learning satisfaction and learning effectiveness of elementary school students on the Quizlet online platform using an experimental design approach. Third and fourth-grade students from an elementary school in Taichung City were recruited in this study. [...] Read more.

We examined the effects of cooperative learning on learning satisfaction and learning effectiveness of elementary school students on the Quizlet online platform using an experimental design approach. Third and fourth-grade students from an elementary school in Taichung City were recruited in this study. A total of 55 students participated in this study and were grouped into the experimental group (28) and the control group (27). The experimental group engaged in game-based cooperative learning activities, while the control group participated in individual learning sessions. After eight weeks of the intervention in which one 30 min session was conducted every week, data on learning satisfaction and learning effectiveness were collected using a questionnaire. The collected data were analyzed to obtain descriptive statistics, independent sample t-tests, Pearson correlation analysis, and regression analysis. The participants in the experimental group reported improved learning satisfaction, learning environments, learning outcomes, and peer interactions compared with the control group. The experimental group also scored higher in learning effectiveness including skills. Significant differences were observed in learning satisfaction and effectiveness across genders and grade levels. A strong positive correlation indicated that higher learning satisfaction improved learning effectiveness among elementary students. Learning satisfaction was a significant predictor of learning effectiveness, highlighting the importance of cooperative learning for better learning outcomes. The results of this study provide a reference for elementary English teachers to incorporate online platforms in their teaching practices. Full article

(This article belongs to the Proceedings of 2024 4th International Conference on Social Sciences and Intelligence Management (SSIM 2024))

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