抗战期间的国民参政会述评     

郑建敏 《石家庄学院学报》1999,(3)

国民参政会从1938年成立到1948年结束,共召开四届十三次会议,其中在抗日战争中召开了十一次会议。国民参政会的召开是在中国共产党和其它民主党派的积极争取下实现的。参政会是抗日民族统一战线建立后成立的一个由各党派参加的政治机关,在成立之初对于抗日战争的胜利进行起了积极的推动作用,但到后期却变成了国民党一手包办的、宣传内战破坏团结的御用工具。  相似文献   

Evaluations of educational reform programmes in developing countries: whose life is it anyway?     

A. Riddell   《International Journal of Educational Development》1999,19(6):15

This article exposes some of the inconsistencies in the use of much research, monitoring and evaluation which is used as a major input into donor-supported educational reform programmes. It argues that notwithstanding the increased emphasis on participation and local ownership, the different valuing and validity of different types of knowledge colour the extent to which any evaluation or research design is going to meet different stakeholders' interests. After critiquing two case studies of educational evaluation, it concludes with some basic principles of evaluation design that should better accommodate the variety of evaluation needs from the local level up to the central ministry.  相似文献   

A systematic literature review of K-12 environmental Citizen Science (CS) initiatives: Unveiling the CS pedagogical and participatory aspects contributing to students’ environmental citizenship     

《Educational Research Review》2023

Environmental Citizen Science (CS) initiatives have been largely embraced in K-12 education, as they are often hypothesized to improve students' knowledge, skills, attitudes, and behaviours to act as “environmental citizens” according to the notion of Environmental Citizenship (EC). However, the potential of environmental CS initiatives to promote Education for Environmental Citizenship (EEC) has not been systematically explored. At the same time, environmental CS initiatives for educational purposes are highly heterogenous and learning is enacted in diverse ways, according to the participatory and the pedagogical components underpinning each initiative. To address the complexity of the field, this review study adopts the PRISMA methodology to synthesize thirty-four empirical studies (n = 34) retrieved from a systematic review of the literature covering the last two decades (2000–2020). The reviewed environmental CS initiatives were subjected to a content analysis to identify their impact on students' EC (e.g., EC competences, actions, outcomes), as well as to unveil the CS initiatives' constitutional components in terms of (a) Participation (e.g., types of students' contributions, level of data collection, frequency of students' participation, modes of student engagement, forms of students’ involvement), and (b) Pedagogy (e.g., learning goals, educational contexts, learning mechanisms, EEC pedagogy). Our analysis shed light to the three territories (Participation, Pedagogy, Environmental Citizenship) underpinning the reviewed CS initiatives as well as to their interrelations. We reflect on these findings, and we provide directions for future research to guide the development of more successful environmental CS initiatives in K-12 education, serving as a vehicle for EC.  相似文献   

Fair and Explainable Depression Detection in Social Media     

《Information processing & management》2023,60(1):103168

Detection at an early stage is vital for the diagnosis of the majority of critical illnesses and is the same for identifying people suffering from depression. Nowadays, a number of researches have been done successfully to identify depressed persons based on their social media postings. However, an unexpected bias has been observed in these studies, which can be due to various factors like unequal data distribution. In this paper, the imbalance found in terms of participation in the various age groups and demographics is normalized using the one-shot decision approach. Further, we present an ensemble model combining SVM and KNN with the intrinsic explainability in conjunction with noisy label correction approaches, offering an innovative solution to the problem of distinguishing between depression symptoms and suicidal ideas. We achieved a final classification accuracy of 98.05%, with the proposed ensemble model ensuring that the data classification is not biased in any manner.  相似文献