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排序方式: 共有869条查询结果,搜索用时 15 毫秒
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The goal of this study is to determine which features effective in‐service activities must have, and to what extent designers of in‐service activities take these features into account. The study is also directed at the relationship between these features of in‐service activities and their implementation and impact characteristics. On the basis of a Delphi‐study, a survey was carried out among teachers, principals, in‐service education and training (INSET) trainers and school counsellors. This article presents the data gathered on programme participants’ and trainers’ opinions and beliefs about effective in‐service and about implementation and impact characteristics. The study also examines the extent of the oft reported critical comments on in‐service activities. In spite of extensive criticism about the value of in‐service education, most participants are positive about the design and execution of the activities. However, INSET has to be closely watched for effectiveness, especially where it concerns applicability and functionality. This is generally judged to be insufficient. 相似文献
864.
Once again, the National Curriculum orders for English are being rewritten. The writers of the new curriculum have looked to the education systems of ‘high-performing jurisdictions’ for inspiration. The result is a curriculum draft that offers a limited view of the subject and one which apparently fails to prioritise the needs of the learner. The model of English developed in the postwar years by those working within the London Association for the Teaching of English (LATE) offers a very different view of the subject. The Aims of English Teaching is an early document articulating LATE’s vision of the subject; this article offers a reading of this document and suggests that there may be much in this history to draw on as teachers are apparently offered more freedom to design their own programmes of study. 相似文献
865.
Mara Simon 《Quest (Human Kinetics)》2020,72(2):167-184
ABSTRACTThe physical education teacher education (PETE) pipeline makes it clear to historically racially minoritized pre-service teachers the value of White norms and experiences while simultaneously “othering” their cultural knowledge. Using Critical Race Theory, Critical Whiteness Studies, and emotionality as theoretical frameworks, this visual narrative inquiry explored self-identified Black and Latinx pre-service physical education teachers’ (n = 10) stories of a racialized identity within predominantly White PETE programs as well as the emotionality of whiteness for myself as a White researcher and teacher educator. I utilized narrative-based semi-structured and conversational interviews, along with photo-elicitation, as methods of data collection. The results contrast participants’ experiences of normalized racism with my heightened emotions of shock and dismay, shedding light on my own white emotionality toward racism. The critical examination of the emotions of whiteness demonstrated the potential to lead PETE faculty toward deeper reflection as to how whiteness is upheld, but also how they might further work to de-center whiteness within their pedagogies, curricula, and programs. 相似文献
866.
Raymond Simon 《Communication quarterly》2013,61(4):20-23
This essay analyzes the divergent public response in democratic cultures to power symbols who manipulate either a self‐disparaging (ironie) public persona or a self‐aggrandizing (hypocritical) one. This divergence is explored in light of well‐known democratic assumptions about power‐holders, and it is illustrated in the contrasting presidential images of Richard M. Nixon and John F. Kennedy. It is concluded that the critic may require an extended vocabulary to evaluate the actions of power‐holders over and above those used to evaluate the actions of private individuals. 相似文献
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Kirsty Kitto Ben Hicks Simon Buckingham Shum 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(5):1095-1124
An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results produced using these methods often fail to link to theoretical concepts from the learning sciences, making them difficult for educators to trust, interpret and act upon. At the same time, many of our educational theories are difficult to formalise into testable models that link to educational data. New methodologies are required to formalise the bridge between big data and educational theory. This paper demonstrates how causal modelling can help to close this gap. It introduces the apparatus of causal modelling, and shows how it can be applied to well-known problems in LA to yield new insights. We conclude with a consideration of what causal modelling adds to the theory-versus-data debate in education, and extend an invitation to other investigators to join this exciting programme of research.
Practitioner notes
What is already known about this topic
- ‘Correlation does not equal causation’ is a familiar claim in many fields of research but increasingly we see the need for a causal understanding of our educational systems.
- Big data bring many opportunities for analysis in education, but also a risk that results will fail to replicate in new contexts.
- Causal inference is a well-developed approach for extracting causal relationships from data, but is yet to become widely used in the learning sciences.
What this paper adds
- An overview of causal modelling to support educational data scientists interested in adopting this promising approach.
- A demonstration of how constructing causal models forces us to more explicitly specify the claims of educational theories.
- An understanding of how we can link educational datasets to theoretical constructs represented as causal models so formulating empirical tests of the educational theories that they represent.
Implications for practice and/or policy
- Causal models can help us to explicitly specify educational theories in a testable format.
- It is sometimes possible to make causal inferences from educational data if we understand our system well enough to construct a sufficiently explicit theoretical model.
- Learning Analysts should work to specify more causal models and test their predictions, as this would advance our theoretical understanding of many educational systems.
869.
Marina Klimovich Simon P. Tiffin-Richards Tobias Richter 《Journal of Research in Reading》2023,46(2):123-142