Content Quality Research Articles

Implementation and evaluation of AR games and tools in Greek primary Schools through the process of the design and creation of a Rubric by the students

The following research paper presents a comprehensive evaluation of augmented reality (AR) games and educational tools, hence AR games, implemented in the Greek primary education system, focusing on the design and creation of a graded criteria scale (Rubric) for selecting and evaluating AR educational games–applications utilized by the students. The study aims to determine, through evaluation approaches, the basic criteria for developing an effective Rubric, by the students, on specific issues such as the main functionality and effectiveness of the games in regard to cognitive areas and skills development, steered through these AR applications. A mixed-method approach was adopted, employing qualitative and quantitative analyses, assessing AR tool utilization in classroom settings, and evaluating the applications’ educational impact. The study entails collecting data from AR tool usage in Greek primary schools and the design and construct, by the students, of a Rubric based on educational and functional effectiveness. This Rubric provides a framework for assessing various aspects of AR educational games, such as Educational Value, Content Quality, Design, Usability, and Technical Features. Key findings include AR games’ effectiveness in enhancing student engagement, understanding, and retention of information through interactive experiences. A notable facet is the integration of student input in Rubric creation, which contextualizes the evaluation process within the cognitive and developmental scope of primary education learners. Four case studies detail practical implementation and evaluation of selected AR applications: <i>Mondly</i> for English language learning, <i>Clever Book AR Geometry</i>, <i>Google Expeditions AR </i>for ocean exploration, and<i> Banun Ruang AR Geometry</i> for 3D geometry comprehension. The cases highlight the educational benefits of the specified AR games, such as visualization, active and kinesthetic learning, fostering motivation and collaboration. Constraints discussed include limitations in sample size, geographic reach, device type, and infrastructure barriers. Despite these boundaries, the study proposes a structured model for evaluating and effectively integrating AR games into educational practices, signaling a shift towards STEM-enhanced learning environments.

Measuring the Use of Smart Applications in Teaching Arabic: A Case Study of University Students

This research aims to measure the extent of smart applications' usage in teaching Arabic among university students, focusing on their impact on developing essential language skills, including reading, writing, listening, and speaking. The research problem arises in light of the increasing reliance on technology in education, raising questions about the effectiveness of these applications in improving Arabic language learning and their compatibility with university students' needs. To address these concerns, the study examines the significance of smart applications in the educational process, reviewing the most commonly used applications for learning Arabic and identifying the challenges students face while using them, whether technical difficulties or issues related to the quality and alignment of educational content with university curricula. Additionally, the research includes a field study based on surveys and personal interviews with a sample of university students, providing a comprehensive perspective on the reality of smart application usage and its effectiveness. Methodologically, the study employs a descriptive-analytical approach, utilizing research tools such as surveys to collect quantitative data and personal interviews to analyze students' qualitative experiences with these applications. The findings indicate that smart applications play a significant role in enhancing Arabic language skills, particularly in reading and writing, by offering interactive and engaging learning experiences. However, several challenges hinder their full potential, including technical issues, content misalignment with traditional curricula, and the need for academic supervision to maximize educational benefits. Based on these results, the study recommends developing more comprehensive educational content tailored to university-level requirements and enhancing the technological infrastructure to support these applications more effectively. Furthermore, it emphasizes the importance of integrating smart applications into modern educational strategies to ensure maximum benefit. Keywords: smart applications, Arabic language learning, university education, interactive learning, technological challenges.

Measuring the Use of Smart Applications in Teaching Arabic: A Case Study of University Students

This research aims to measure the extent of smart applications' usage in teaching Arabic among university students, focusing on their impact on developing essential language skills, including reading, writing, listening, and speaking. The research problem arises in light of the increasing reliance on technology in education, raising questions about the effectiveness of these applications in improving Arabic language learning and their compatibility with university students' needs. To address these concerns, the study examines the significance of smart applications in the educational process, reviewing the most commonly used applications for learning Arabic and identifying the challenges students face while using them, whether technical difficulties or issues related to the quality and alignment of educational content with university curricula. Additionally, the research includes a field study based on surveys and personal interviews with a sample of university students, providing a comprehensive perspective on the reality of smart application usage and its effectiveness. Methodologically, the study employs a descriptive-analytical approach, utilizing research tools such as surveys to collect quantitative data and personal interviews to analyze students' qualitative experiences with these applications. The findings indicate that smart applications play a significant role in enhancing Arabic language skills, particularly in reading and writing, by offering interactive and engaging learning experiences. However, several challenges hinder their full potential, including technical issues, content misalignment with traditional curricula, and the need for academic supervision to maximize educational benefits. Based on these results, the study recommends developing more comprehensive educational content tailored to university-level requirements and enhancing the technological infrastructure to support these applications more effectively. Furthermore, it emphasizes the importance of integrating smart applications into modern educational strategies to ensure maximum benefit. Keywords: smart applications, Arabic language learning, university education, interactive learning, technological challenges.

The Influence of Live Streaming and Content Quality on Purchase Interest in Credifox Products on TikTok Shop

This study aims to analyze the influence of live streaming and content quality on purchase intention for Credifox products on TikTok Shop, both partially and simultaneously. The research employs a quantitative method with a non-probability sampling technique, involving 100 respondents. Data analysis was conducted using statistical quantitative methods and multiple linear regression with the aid of SPSS 25 software. The findings indicate that, partially, live streaming significantly influences purchase intention, with a t-value of 4.571 > t-table 1.985 and a significance level of 0.000 < 0.05. Similarly, content quality also has a significant influence on purchase intention, as shown by a t-value of 3.152 > t-table 1.985 and a significance level of 0.002 < 0.05. Simultaneously, live streaming and content quality have a positive and significant influence on purchase intention for Credifox products on TikTok Shop, with an F-value of 74.834 > F-table 3.100 and a significance level of 0.000 < 0.05.

Evaluating Plastic Surgery Chatbot Performance: Insights into Medical Triage, Classification Accuracy and Escalation Trends.

The integration of AI chatbots into plastic surgery websites is now standard, providing asynchronous, real-time engagement for patients. Although promoted as scheduling and medical guidance tools, their contribution to clinical workflow improvement and patient satisfaction remains unclear. This paper the accuracy AI chatbot performance in clinical triage of plastic surgery patients, focusing on triage accuracy and quality of patient interactions. The responses of chatbots on top-ranking plastic surgery websites, identified using SEO rankings, were analyzed using standardized clinical scenarios representing emergent, urgent, and elective patient inquiries. Responses were analyzed by the chatbot's triage sensitivity and specificity, classification accuracy, escalation metrics and content quality. Patient experience was quantified using a Chatbot Usability Questionnaire and Visual Analog Scale. Subgroup analysis by chatbot platform and thematic analysis was performed to identify tonal patterns in chatbot language. Performance varied significantly across 60 clinical scenarios, particularly in urgency classification. Emergent classifications were most mislabeled as urgent, with a low sensitivity (20%), negative predictive value (0.71) and high false negative rate (80.0%). Agreement with physician-determined classifications was moderate (Cohen's kappa = 0.47) and over half of conversations required human-provider escalation. Misclassified interactions were associated with lower patient usability scores compared to correct classifications (49.1 vs. 60.8, p < 0.05). Thematic analysis revealed reliance on templated, administrative language. Chatbots are practical and useful tools for managing elective plastic surgery inquiries, are ill-equipped to handle urgent and emergent patient needs. To move beyond use as basic administrative assistants, deployment of more clinically adept chatbots is needed.

The quality and reliability of short videos about hypertension on TikTok: a cross-sectional study

Hypertension is a major global health risk, and social media platforms like TikTok play an increasing role in public health communication. This study evaluates the quality of hypertension-related videos on TikTok and examines the relationship between content quality and user engagement. A systematic keyword search identified hypertension-related videos published before February 25, 2025. After applying exclusion criteria, 139 videos were analyzed. Video quality was assessed using the Journal of the American Medical Association (JAMA) benchmark criteria, the Global Quality Scale (GQS), and the modified DISCERN (mDISCERN) instrument. Engagement metrics (likes, comments, shares, and collections) were recorded, and Spearman’s correlation and linear regression analyses explored associations between quality and engagement. These videos accumulated 7190634 likes, 3608023 collections, 247602 comments, and 3252697 shares. Most (85.6%, n = 119) were uploaded by health professionals. The most common JAMA score was 2 (74.8%), while the mean GQS score was 3, with 36.7% of videos receiving this rating. The mDISCERN score was most frequently 2 (71.2%). Video duration correlated with JAMA (β = 0.235, p < 0.05), mDISCERN (β = 0.190, p < 0.05), and GQS scores (β = 0.410, p < 0.001). Likes also correlated with JAMA (β = 0.661, p < 0.001), mDISCERN (β = 0.500, p < 0.05), and GQS scores (β = 0.815, p < 0.001). Comments negatively affected GQS scores (β = -0.574, p < 0.05). TikTok is a valuable platform for hypertension education, but content quality is moderate. Extending video duration, improving rigor, and enhancing review mechanisms may improve hypertension-related health communication.

Quality and content evaluation of thyroid eye disease treatment information on TikTok and Bilibili

Thyroid eye disease (TED) is an autoimmune condition that commonly impacts patients’ visual function, appearance, and psychological well-being. Challenges in TED management include low early detection rates and large variation in treatment response. Video platforms like TikTok and Bilibili are increasingly utilized for health information dissemination, yet the quality of TED treatment content on these platforms varies significantly. This cross-sectional study collected videos on “甲亢突眼的治疗” from TikTok and Bilibili in March 2025. After applying exclusion criteria, 152 videos (89 from TikTok, 63 from Bilibili) were analyzed. Quality, reliability, and educational value were assessed using the Global Quality Score (GQS), modified DISCERN (mDISCERN), Patient Education Materials Assessment Tool (PEMAT), and Journal of the American Medical Association (JAMA) benchmark criteria. Additionally, the study analyzed video content integrity, uploader identity, and the correlation with user interaction data. TikTok videos scored higher in quality (GQS: 3.00 ± 0.58; mDISCERN: 3.17 ± 0.73) compared to Bilibili (GQS: 2.65 ± 0.65; mDISCERN: 2.21 ± 0.88; p < 0.001). On Bilibili, 62% of videos were uploaded by Traditional Chinese Medicine (TCM) physicians, yet these scored lower in quality. Professionally uploaded content, particularly by ophthalmologists, outperformed non-professional videos (e.g., patient). However, the video interaction metrics uploaded by patients showed better performance. In terms of content, only 27% addressed staged treatment, and 11.8% mentioned risk factor control. Correlation analysis revealed strong correlations between interaction data, but interaction data have no correlation with GQS, mDISCERN, and PEMAT scores. Short video platforms exhibit a dual role in the dissemination of TED treatment information: enhancing public awareness of diseases through professional content while risking misinformation due to inadequate auditing. Recommended interventions include robust platform certification, active involvement of medical organizations in content creation, and public education on prioritizing verified sources.

Evaluation of social media videos on weight-loss surgery and GLP-1 agonists: a content quality and reliability analysis.

Social media platforms have become a leading arena for disseminating health knowledge. Information on weight loss is no exception; health, fitness and nutrition are within the 5 most searched categories in 2023. Our study investigates the quality of information on TikTok and Instagram regarding the two most popular weight loss treatments: glucagon-like-peptide-1 (GLP-1) agonist and sleeve gastrectomy. TikTok and Instagram were queried for contents about GLP-1 agonists or sleeve gastrectomy. The first 50 videos from each category were evaluated by two reviewers. The videos were divided into four categories: Instagram GLP-1, Instagram weight loss surgery (WLS), TikTok GLP-1, and TikTok WLS. The quality of the contents was assessed using the DISCERN score. 200 videos were collected for analysis. 31.5% were created by medical professionals and 68.5% were from non-medical professionals. More videos from Instagram regarding GLP-1 agonists followed by videos from TikTok regarding GLP-1 agonists were made by medical professionals compared to videos about surgery (p = 0.038). The average number of likes overall was 67,024 and saves or shares 6,305. The greatest number of likes were in the TikTok surgery group (p = 0.004) and the most saves or shares were in the Instagram surgery group (p < 0.001). DISCERN scores were low for all four categories, overall 28.0 out of 80. They were highest in the Instagram GLP-1 agonist group (p < 0.001). Despite the popularity of TikTok and Instagram, the quality of the health contents, as measured by DISCERN score, on these platforms remains poor. Most are created by non-medical professionals. Healthcare professionals should encourage patients to remain vigilant and educate them on misinformation on social media. This may also represent an opportunity for healthcare providers to generate their own social media content to ensure reliability of information as well as to direct patients to reliable social media content.

Influencing the Perception and Acceptance of AI-Generated Marketing Content as Part of SGD

Objective: The objective of this study is to examine users' attitudes towards AI-generated marketing content, focusing on the influence of transparency, content quality and authenticity, as well as the socio-demographic characteristics of respondents. Theoretical Framework: This study is grounded in the intersection of consumer behavior theories and technology acceptance models. Concepts such as perceived authenticity, trust in automation, and transparency in AI use provide a basis for understanding how individuals engage with AI-generated content in marketing as part of SGD. Method: The research employed a quantitative approach using the CAWI (Computer-Assisted Web Interviewing) method, gathering data from a sample of 1308 respondents. The survey measured preferences regarding AI-generated content, demographic data, and perceived quality and transparency. Results and Discussion: The findings confirm that consumers tend to prefer AI-generated content that has been edited or supervised by a human. Transparency regarding AI involvement significantly increases acceptance, though older individuals and women show more caution, while younger respondents are more open. Perceived quality and authenticity were identified as the most influential factors in content acceptance. Research Implications: These findings have both theoretical and practical implications for marketing strategies, emphasizing the role of transparency and human oversight in AI content use. Originality/Value: This research contributes to the understanding of consumer acceptance of AI in marketing, highlighting key demographic influences and validating the need for quality and authenticity in AI-driven content strategies.

LINE OA media development using game-based learning for vocational law skills

Due to the features of a LINE Official Account, which enable the gamification of learning and enhance student engagement, this research aimed to: (1) examine the commercial law competencies of vocational students as entrepreneurs, (2) develop and evaluate the quality of instructional media via LINE Official Account using game-based learning for vocational law skills as entrepreneurs, (3) compare the commercial law competence of vocational students before and after learning with the developed instructional media, and (4) assess students’ satisfaction with the developed instructional media. Data were collected from a sample of 40 vocational students majoring in Business Computing, selected through cluster random sampling during the first semester of the 2024 academic year. The research findings revealed that commercial law competence in entrepreneurship comprises: (1) knowledge of commercial law, (2) skills in applying commercial law, and (3) attributes for applying commercial law in entrepreneurial contexts. The instructional media were developed based on these findings, incorporating game- based learning via a LINE Official Account. The media included basic, intermediate, and advanced content presented as animated videos and games, accompanied by an AI assistant named "Brain Lump." Expert evaluations revealed that the content quality was rated at a very good level (x̄ = 5.00, S.D. = 0.00), and the quality of the presentation media was also rated at a very good level (x̄ = 4.94, S.D. = 0.08). A comparison of students’ competence before and after using the developed instructional media demonstrated a statistically significant improvement at the .05 level (t-test = 13.88). Furthermore, the satisfaction evaluation indicated that the students rated the instructional media at the highest level (x̄ = 4.54, S.D. = 0.53). Therefore, the developed instructional media are practical and applicable for enhancing vocational students’ competence in commercial law as entrepreneurs.

Exploring the use of double-speed video playback in a fast-paced society through structural equation modeling

In a fast-paced society, users habitually use double-speed function when playing videos. Exploring the influence mechanism of users’ intention to use the double-speed function has applications for optimizing video platforms’ double-speed function, enhancing the user experience, and alleviating time anxiety. On the basis of the Technology Acceptance Model, we integrated perceived entertainment, subjective norms, system quality, and content quality to construct a hypothetical model of users’ intention to use the double-speed function. We obtained 360 valid samples through an online questionnaire survey, analyzing the results using structural equation model validation and mediation effect tests. The findings showed that: The key factors influencing users’ intention to use the double-speed function were perceived usefulness and attitude. Subjective norms and perceived entertainment did not directly and significantly affect users’ intention to use the double-speed function. However, through a mediating effect, these factors can have a positive impact on users’ intention to use the double-speed function. The quality of video content on platforms did not have a significant negative effect on users’ intention to use the double-speed function. Additionally, users also played videos with high-quality content at double-speed. These unique findings are the contributions of this study.

Relationship between advertising investment and sales empirical analysis based on traditional and digital advertising

Driven by the rapid development of Internet technology, advertising communication channels and presentation forms have undergone profound transformations., However, the mechanism and effect of new advertising forms on commercial sales performance have not yet been fully demonstrated. This study explores the non-linear impact mechanism of advertising investment on sales through empirical analysis, focusing on the effect differences between traditional advertising and digital hybrid advertising and the law of diminishing marginal utility. Based on the e-commerce advertising and sales data(2019-2023) from Kaggle platform, a multiple linear regression model is constructed, and it is found that the total advertising investment is significantly positively correlated with sales and the marginal contribution of digital hybrid advertising is significantly higher than that of traditional advertising. However, the marginal decreasing effect of advertising input did not pass the significance test, possibly due to the fact that advertising input did not reach the saturation threshold in the data or the complexity of the nonlinear relationship. The study further reveals the impact of channel heterogeneity on advertising effectiveness and proposes a dynamic budget allocation strategy: prioritizing investment in digital advertising channels and reducing investment in inefficient traditional channels. Limitations include insufficient data timeliness, omitted variable bias, and endogeneity issues. Future research needs to expand the data dimensions, introduce machine learning models, and explore ad content quality and cross-channel synergies.

The quality and reliability of YouTube video content about gingival recession on different time periods

BackgroundGingival recession is a mucogingival problem that can cause esthetic concerns and sensitivity. While some patients remain unaware of it, others seek solutions through various means. The COVID-19 pandemic has increased the role of social media in accessing health information. The frequent use of YouTube has prompted researchers to evaluate its contents quality and reliability. This study aims to examine this issue by comparing two periods: before and after COVID-19.MethodsThe first 100 videos for the keyword ‘receding gums’ shared in 2019 and 2024 were analyzed. A total of 23 and 35 videos were included, respectively. Quality was evaluated using Video Quality Index (VIQI) and Global Quality Scale (GQS), reliability with DISCERN and Modified DISCERN and content through an approach developed by the authors. Videos were also assessed based on their characteristics and sources. Data were analyzed using IBM SPSS 26.0. For two-group comparisons, independent sample t-tests were applied to normally distributed data, while the Mann–Whitney U test was used for non-normally distributed data. Categorical variables were analyzed with the Chi-square test. Correlations between variables were examined using Spearman’s correlation analysis.ResultsAccording to content analysis, useful videos were found to have higher scores of quality and reliability indices in both the 2019 and 2024 groups (p < 0.001). In 2024, the amount of videos uploaded by dental professionals was significantly more ‘useful’ compared to those from other sources (p = 0.45). There was a tendency of increase in sharing videos by healthcare professionals following the COVID-19 pandemic.

Research on Multimedia Animation Elements in Information Transmission Under Internet Environment

On the background of exponential growth of internet users and information, multimedia animation elements have come to the fore due to the integration of multiple elements, including dynamic and intuitive features. This research focused on multimedia animation elements in information transmission in the internet environment. Multimedia animation has a wide range of applications, covering areas such as online advertising, online education, social media, virtual reality, and augmented reality. Through empirical research based on online courses in basic physics, the results indicate that multimedia animation elements of information transmission can enhance knowledge mastery and information understanding memory. Although facing challenges such as technological updates, content quality, and network risks, in-depth research can still provide important support and reference for information dissemination and development of the animation industry.

K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers

Television remains one of the most influential mass media platforms for disseminating information and entertainment to the public, with one notable example being the I’Murojaah program aired by Muslim TV on MNC Channels. The objectives of this study are to identify the level of viewer satisfaction with the I’Murojaah program, determine the indicators influencing viewer satisfaction, classify viewers based on their satisfaction levels, and provide recommendations to program managers to improve quality and viewer satisfaction. This study employs a qualitative approach using the K-Means Clustering algorithm. The data used in this study were obtained through a survey distributed to 100 respondents, covering several viewer satisfaction indicators such as content quality (6 questions) and program presentation (6 questions). The collected data were then grouped and analyzed. The results of the first cluster iteration distance calculation consisted of 84 viewers who were very satisfied, while the second cluster consisted of 16 viewers with relatively low satisfaction levels. The Davies Bouldin Index values were -0.674 for class 2 clustering, -2.001 for class 3 clustering, -1.961 for class 4 clustering, and clustering class 5 (-2.000). In conclusion, the best clustering performance results were for classes 2, 3, 4, and 5. The smallest Davies Bouldin Index value was for clustering class 2. Recommendations for program improvement include enhancing image and sound quality, ensuring that the equipment and technology used can produce optimal quality.

Impact Of Screen Time On Executive Function In Early Childhood

The World Health Organization (WHO) mandates no screen time for children below two years of age; and an upper limit of one hour per day for children aged 2–5 years. However, contemporary research studies present a whole new perspective - 53% of Indian children receive screen exposure before the age of 2; roughly 88% use screen media during mealtime, and 68% do so within an hour before bedtime. The digital era makes it easy to normalize this increased exposure to screens, but we ought to be concerned about its developmental consequences on early childhood development. The ensuing study probes the relationship between screen time and executive function in children aged 3 to 6 years. Deploying a mixed-methods approach including caregiver surveys, structured observation, and validated executive function tasks (e.g., Dimensional Change Card Sort, Stroop-like Day-Night Task), we learnt that higher daily screen exposure, particularly passive screen time (e.g., television), is associated with significantly poorer executive function performance. The findings support the aforementioned guidelines advocating limited screen use, and underline the importance of content quality and parental supervision.

An Analysis of the Indonesian Language Textbook 'Aku yang Unik' for Grade 5: An Evaluation Based on BSNP Feasibility Criteria

In primary education, textbooks serve as a cornerstone for the learning process, playing a pivotal role in achieving educational goals. A high-quality textbook not only aligns with the curriculum but also uses precise language, features appealing visuals, and inspires students to engage actively in learning. For this reason, it is essential to evaluate the suitability of textbooks before they are adopted in classroom instruction. The Indonesian language textbook “Bergerak Bersama” for fifth-grade students is among those implemented under the Merdeka Curriculum, making a feasibility review—particularly of Chapter I, “Aku yang Unik”—crucial to ensure its positive impact on both teaching and learning outcomes. This study examines the appropriateness of content quality, language use, presentation style, and graphic design within Chapter I of the aforementioned textbook. The central question addressed is the extent to which the book meets the standards across these four dimensions. A qualitative descriptive approach was employed, utilizing document analysis as the primary method. Data were collected through direct assessment of Chapter I, following the BSNP textbook eligibility instrument, with each aspect evaluated based on established BSNP indicators. Findings reveal that, in terms of content, the material corresponds well with the latest curriculum objectives and remains relevant, especially in introducing adjectives, affixes, synonyms, antonyms, and compound sentences. Linguistically, the textbook adheres to the Indonesian spelling guidelines (PUEBI), and the language is clear and accessible to students. Regarding presentation, the textbook is considered engaging and motivating, further supported by comprehensive practice questions at the end of each chapter. Visually, choices in typography, formatting, and illustrations meet accepted standards and enhance student comprehension. The analysis indicates that Chapter I of “Bergerak Bersama” fulfills the BSNP’s criteria for use as a teaching resource in elementary schools. The four dimensions—content, language, presentation, and visual design—are all adequately addressed, supporting an effective and enjoyable learning experience. Consequently, this textbook stands as a relevant and reliable primary learning resource aligned with the curriculum and the needs of students

Exploring Information Interaction Preferences in an LLM-Assisted Learning Environment with a Topic Modeling Framework

Large Language Models (LLMs) are driving a revolution in the way we access information, yet there remains a lack of exploration to capture people’s information interaction preferences in LLM environments. In this study, we designed a comprehensive analysis framework to evaluate students’ prompt texts during a professional academic writing task. The framework includes a dimensionality reduction and classification method, three topic modeling approaches, namely BERTopic, BoW-LDA, and TF-IDF-NMF, and a set of evaluation criteria. These criteria assess both the semantic quality of topic content and the structural quality of clustering. Using this framework, we analyzed 288 prompt texts to identify key topics that reflect students’ information interaction behaviors. The results showed that students with low academic performance tend to focus on structural clarity and task execution, including task inquiry, format specifications, and methodological search, indicating that their interaction mode is instruction-oriented. In contrast, students with high academic performance interact with LLM not only in basic task completion but also in knowledge integration and the pursuit of novel ideas. This is reflected in more complex topic levels and diverse, innovative keywords. It shows that they have stronger self-planning and self-regulation abilities. This study provides a new approach to studying the interaction between students and LLM in engineering education by using natural language processing to process prompts, contributing to the exploration of the performance of students with different performance levels in professional academic writing using LLM.

Empirical Study on Generative Artificial Intelligence Enabling Chinese Writing Teaching

The digital transformation of international Chinese language education is an important direction for enhancing the global dissemination effectiveness of the Chinese language. In teaching Chinese as a second language, writing, as a form of higher-order language output, has long faced challenges such as insufficient teacher resources, lagging feedback, and a lack of personalized support. Generative artificial intelligence (GAI) offers a new path for teaching Chinese writing. This study, with intermediate Chinese learners as the subjects, systematically explores the effectiveness of GAI-assisted Chinese writing instruction through a combination of controlled experiments and interviews based on a Chinese learning platform embedded with GAI. The study found that the GAI class was significantly superior to the traditional class in terms of the adequacy dimension of content quality and the grammatical and lexical dimensions of language quality; teachers and GAI play complementary roles in this process; most Chinese learners have a positive attitude towards this model. Based on the above findings, this study presents three suggestions: using GAI to empower Chinese writing instruction, giving full play to the complementary advantages of human and machine, and enhancing the AI literacy of teachers and students to achieve two-way empowerment of human and machine, with the aim of promoting the intelligent development of international Chinese education.

ADVANCING IMPERCEPTIBLE SECURITY: EDWT-BASED WATERMARKING WITH BLS-HMAC ENCRYPTION

Image watermarking plays a crucial role in the protection and authentication of images through the watermark process. In the digital age, the proliferation of sensitive information and the increasing prevalence of cyber threats have underscored the crucial need for robust data security measures. Copyright protection and content authentication are difficult tasks in digital image data. Several cryptographic watermarking approaches have been developed for tackling the various security issues in images. However, with the advent of advanced technologies, traditional cryptographic methods face challenges in ensuring the confidentiality, integrity, and authenticity of data. Continuous efforts are required to enhance the performance due to multiple attacks and information sharing on social media. Also, it performs poorly in digital images due to correlation and redundancy issues and does not utilize security mechanisms; thus it enhances security problems. With the aim of resolving these issues, this research paper presents a comprehensive methodology for watermarking, focusing on the secure integration of an encrypted message and a watermark image into a cover image. Cryptography has emerged in this work for safeguarding data by encoding information to prevent unauthorized access. In response to persistent challenges in balancing robustness and perceptibility, this work introduces an innovative approach that employs the elastically deformable wavelet transform (EDWT). The proposed methodology begins by encrypting the original message using the Boneh-Lynn–Shacham cryptography adopted with the Hash-based message authentication code (BLS-HMAC) scheme, ensuring a high level of security. The encryption generates additional security to the original watermark image in the unauthorized watermark extraction and manipulation. Subsequently, the encrypted message, along with a watermark image, is seamlessly embedded into the cover image through the adaptive properties of EDWT. This advanced technique offers an intricate balance between robust information security and imperceptibility, addressing key limitations observed in existing watermarking methods. The application of BLS–HMAC and EDWT collectively enhances the resilience, security, and perceptual quality of watermarked content, making it suitable for diverse applications that include secure communication and content authentication. The performance of the developed method is enhanced by 12% of DWT–DCT–LZW, 11% of DWT–SVD, 8% of DWT–DCT–SVD, 7% of CEW with zero watermarking, and 2% of NSST–HD–SVD in terms of unified average change intensity (UACI) measure.