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Interactive teaching is very popular in the field of education, especially in college preschool education teaching. In this study, the experimental performance of the evaluation system based on scientific emotion construction is analyzed by the machine learning algorithm. The experimental results show that the classification model realized by the machine learning algorithm is feasible and effective for the construction of an interactive design teaching evaluation system of preschool education in colleges and universities. The main research content of this experiment is for the teaching evaluation text, this paper intends to use NB, KNN, LR, and SVM algorithms as the meta-learning algorithm in the framework, the classification effect of the meta-classifier is ranked as SVM > LR > KNN > NB. From the above data comparison, the SVM meta-classifier in the algorithm in this paper has achieved the best classification effect. The SVM meta-classifier based on the algorithm in this paper performs well, and the classification accuracy rate reaches 92.1%. This shows that this model is very suitable for studying the. And the classification accuracy rate reaches 92.1%. This shows that this model is very suitable for studying the construction of interactive teaching evaluation systems under emotional education. • The experimental results show that the classification model realized by machine learning algorithm. • This shows that this model is very suitable for studying the construction of interactive teaching. • The main research content of this experiment is for the teaching evaluation text. • This paper intends to use NB, KNN, LR and SVM algorithms as the meta-learning algorithm. [ABSTRACT FROM AUTHOR]

At present, ubiquitous learning has been becoming an important learning style for college students. However, the current studies on ubiquitous learning mostly focus on aspects such as communication and data interaction methods, while ignoring students' academic emotions. In this paper, we propose an individual adaptive ubiquitous learning paradigm that focuses on college students' academic emotions. The paradigm collects and analyses students' academic emotions to grasp student's individual characteristics. Then, the adaptive planning and adjusting learning contents is beneficial for improving students' academic emotions and enhancing the ubiquitous learning effects, initiative and concentration. In this study, the 2-year-long comparative experiments and tracking analyses were conducted from four aspects: academic grades, average study hours in after-school spare time, academic emotions status and classroom participation. The experimental results show that the individual adaptive ubiquitous learning paradigm proposed in this paper has significant positive effects and impacts on college students' learning outcomes, initiative, engagement and academic emotions. • An individual adaptive ubiquitous learning paradigm considering the impact of academic emotions is proposed. • The paradigm focuses on academic emotions to adaptively adjust individual learning content. • Academic emotions analysis and adjustment algorithms are designed to improve learning outcomes. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the influence of various advertising channels on consumers' value perceptions of luxury brands, with a specific focus on the potential negative effects of TikTok on luxury advertising. Using an experimental design, four studies were conducted to rigorously examine these research questions. Study 1 reveals that, compared to traditional media, TikTok advertising has a more adverse impact on consumers' value perceptions of luxury brands. In Study 2, the mediating role of psychological distance is identified as the underlying mechanism explaining how media types in luxury advertising affect value perceptions. Study 3(a) highlights significant disparities in the number of online reviews and "likes" for different review types. Additionally, Study 3(b) discovers that self-deprecating online reviews can significantly increase the value perception of luxury brands on TikTok. This study contributes both theoretically and practically to the field of luxury marketing management, offering insights into the nuanced dynamics of luxury advertising across diverse media channels. Furthermore, it provides valuable suggestions for future research within the realm of luxury marketing, particularly in the context of social media. • Advertising on TikTok may diminish consumers' value perceptions of luxury brands. • Psychological distance explains TikTok's negative effects on value perception. • TikTok users prefer exploring self-deprecating reviews, when watching luxury ads. • Self-deprecating reviews enhance TikTok users' value perception of luxury brands. [ABSTRACT FROM AUTHOR]

This paper examines the use of Augmented Reality Smart Glasses (ARSGs) in order-picking tasks in warehouses and explores their impact on workers' well-being. While previous research has primarily focused on the performance advantages of ARSGs, this study provides a new perspective by investigating the human factor and perceptions of worker well-being in two empirical studies. The results corroborate previous findings that ARSGs enhance order-picking efficiency by improving workers' speed and reducing error rates. Additionally, the results reveal that using ARSGs directly increases perceptions of well-being compared to traditional support tools. However, contrary to expectations, ARSG use does not generally lead to higher job satisfaction or perceived productivity enhancements for all workers. Technology savviness is identified as a crucial individual factor that shapes these effects, with tech-savvy workers benefiting more from ARSG use. Overall, this research underscores the importance of tailoring ARSG implementation to the specific needs and characteristics of the workforce and highlights the need for further investigation into the beneficiaries of ARSG technology. • Augmented reality smart glasses (ARSGs) improve efficiency in order-picking tasks, enhancing speed and reducing error rates. • ARSG use directly increases workers' perceptions of well-being compared to traditional support tools. • This is driven by increased job satisfaction and perceived productivity, but only for workers with high technology savviness. [ABSTRACT FROM AUTHOR]

Over the last decade, Educational Data Mining (EDM) and Learning Analytics (LA) have evolved enormously as interrelated research areas and disciplines. Many researchers interested in these areas may wonder why there are two different communities, whether they are the same concept or not, and the differences between them, which is key information for designing their research and publication strategies. To address this, we conducted a systematic review of academic papers about the differences between LA and EDM following the Preferred Reporting Method for Systematic Reviews (PRISMA) guidelines. We selected 10 research works and identified 11 differences. Our conclusions are that, although both use the same data and share similar goals and interests, EDM and LA are different research communities with different origins and focuses, with their respective conferences and journals. However, there is active collaboration between the two communities and their members often tend to publish in both fields' conferences and journals. Additionally, none of the differences are apparently large enough to conclude that LA and EDM follow different paths for improving the teaching-learning process, but rather the opposite. Following a common future line, it seems that the two "sister" communities are working together with the same perspective, along with some "cousin" communities such as AIED (Artificial Intelligence in Education), L@S (Learning at Scale), Learning Science (LS), etc. in the same area that could be called Educational Data Science (EDS). We propose using the term EDS to integrate both LA and EDM with all these related communities. [Display omitted] • Educational Data Mining (EDM) and Learning Analytics (LA) are interrelated and sometimes interchanged terms. • Five original differences between EDM and LA have been identified. • Other six new differences have emerged since these initial five differences. • The term Educational Data Science (EDS) is proposed to integrate EDM and LA. [ABSTRACT FROM AUTHOR]