This paper aims to explore the effect of teacher–student collaboration on academic innovation in universities in different stages of collaboration.
Abstract
Purpose
This paper aims to explore the effect of teacher–student collaboration on academic innovation in universities in different stages of collaboration.
Design/methodology/approach
Based on collaboration life cycle, this paper divided teacher–student collaboration into initial, growth and mature stages to explore how teacher–student collaboration affects academic innovation.
Findings
Collecting data from National Science Foundation of China, the empirical analysis found that collaboration increases the publication of local (Chinese) papers at all stages. However, teacher–student collaboration did not significantly improve the publication of international (English) papers in the initial stage. In the growth stage, teacher–student collaboration has a U-shaped effect on publishing English papers, while its relationship is positive in the mature stage.
Practical implications
The results offer suggestions for teachers and students to choose suitable partners and also provide some implications for improving academic innovation.
Originality/value
This paper constructed a model in which the effect of teacher–student collaboration on academic innovation in universities was established.
Details
Keywords
Xinhua Guan, Zhenxing Nie, Catheryn Khoo, Wentao Zhou and Yaoqi Li
This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether…
Abstract
Purpose
This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether tourists’ travel intention is affected by travel content consumption in social networks, and more importantly, whether social comparison and envy play a mediating role in this process.
Design/methodology/approach
Data was collected through intercept in four popular tourist spots in Guangzhou and Zhuhai in South China. A self-administered questionnaire was used. A total of 400 participants were recruited, and 291 valid questionnaires were obtained. Bias-corrected nonparametric percentile bootstrap mediation variable test method was used to test hypotheses.
Findings
The study yielded three results. First, travel content consumption in the social networks positively influences travel intention. Second, travel content consumption in social networks indirectly affects travel intention through social comparison and envy. Third, the control variables, such as gender, age, education and income, mainly affect envy.
Originality/value
This study constructs a theoretical framework of stimulus–cognitive appraisal–emotion–behavioral responses. To the best of the authors’ knowledge, it is the first study to reveal that the internal psychological mechanism of travel content consumption affects travel intention. It also discloses that envy of seemingly negative emotions can encourage positive behaviors in certain situations.
Details
Keywords
- Social networks
- Content consumption
- Social comparison
- Envy
- Travel intention
- Cognitive appraisal theory of emotion
- Redes sociales
- consumo de contenido
- comparación social
- envidia
- intención de viaje
- teoría de evaluación cognitiva emocional
- 社交网络
- 内容消费
- 社会比较
- 嫉妒
- 旅游意向
- 情感认知评价理论
- Redes sociales
- Consumo de contenido
- Comparación social
- Envidia
- Intención de viaje
- Teoría de evaluación cognitiva emocional
Guocheng Xiang, Jingjing Liu and Yuxuan Yang
The modernization of China’s economy is an integral part of Chinese-style modernization. According to the principle of unifying…
Abstract
Purpose
The modernization of China’s economy is an integral part of Chinese-style modernization. According to the principle of unifying theoretical, historical and practical logic, theoretically explaining the modernization of China’s economy is both a political necessity and a higher scientific requirement.
Design/methodology/approach
Following this evolutionary line – from modes of production to the general economic development mechanism and then to patterns of economic operation and development – this paper employs the principal contradiction analysis method to offer an interpretation of China’s economic modernization from the broad Marxist political economy perspective.
Findings
In economic terms, “get organized” primarily refers to the development and mutual promotion of team-based and market-based division of labor organizations, as discussed by Karl Marx. “Get organized” (specifically the development of team-based division of labor organizations) acts as the engine of China’s economic modernization and serves as the historical logical starting point. Division of labor is the theoretical logical starting point for interpreting China’s economic modernization. The two of them are congruent, achieving the unity of theoretical and historical logic at the starting point. The development and mutual promotion of these “two types of division of labor” inherently generate the general mechanism of economic development first comprehensively discussed by Marx and Friedrich Engels, which involves the division of labor development and market expansion accumulating cyclically and reinforcing each other. This mechanism drives both the high-speed and high-quality development of China’s economic modernization.
Originality/value
The broad Marxist political economy paradigm facilitates explaining China’s economic modernization theoretically, historically and practically with unified logic. “Get organized” serves as both the engine and the realization mechanism of this modernization, with the Communist Party of China (CPC) consistently being the core force of this organizational effort.
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Jiaqi Fang, Kun Ma, Yanfang Qiu, Ke Ji, Zhenxiang Chen and Bo Yang
The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant…
Abstract
Purpose
The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying solely on textual discrepancies between the title and content to distinguish between real and fake news has proven ineffective. The purpose of this paper is to develop a new approach called semantic enhancement network with content–title discrepancy (SEN–CTD), which enhances the accuracy of fake news detection.
Design/methodology/approach
The SEN–CTD framework is composed of two primary modules: the SEN and the content–title comparison network (CTCN). The SEN is designed to enrich the representation of news titles by integrating external information and position information to capture the context. Meanwhile, the CTCN focuses on assessing the consistency between the content of news articles and their corresponding titles examining both emotional tones and semantic attributes.
Findings
The SEN–CTD model performs well on the GossipCop, PolitiFact and RealNews data sets, achieving accuracies of 80.28%, 86.88% and 84.96%, respectively. These results highlight its effectiveness in accurately detecting fake news across different types of content.
Originality/value
The SEN is specifically designed to improve the representation of extremely short texts, enhancing the depth and accuracy of analyses for brief content. The CTCN is tailored to examine the consistency between news titles and their corresponding content, ensuring a thorough comparative evaluation of both emotional and semantic discrepancies.