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61.
There is still little consensus on whether and how teaching is affected by small and large classes, especially in the case of students in the later primary years. This study investigated effects of class size on teaching of pupils aged 7 – 11 years. We used a multimethod approach, integrating qualitative information from teachers' end-of-year accounts and data from case studies with quantitative information from systematic observations. Results showed that there was more individual attention in smaller classes, a more active role for pupils, and beneficial effects on the quality of teaching. It is suggested that teachers in both large and small classes need to develop strategies for more individual attention but also recognize the benefits of other forms of learning, for example, group work.  相似文献   
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Teaching assistants (TAs) are part of a growing international trend toward paraprofessionals working in public services. There has been controversy over TAs’ deployment and appropriate role when supporting the learning of pupils with special educational needs (SEN) in mainstream schools. Such debates have been transformed by findings from a large study of school support staff in the UK (the DISS project). The findings from this study show that TA support has a negative impact on pupils’ academic progress, especially pupils with SEN. The findings render the current system of support for SEN highly questionable: TAs have inadvertently become the primary educators of pupils with SEN. This paper sets out the likely explanations for the negative effects in terms of three ‘frames’ – deployment, practice and preparedness – and then uses these frames to identify specific implications for pupils with SEN. We offer suggestions on how to make the most productive use of TA support.  相似文献   
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This study evaluated the representations of nature of science (NOS) in U.S. state science standards, and examined the changes in these representations from documents advanced in the 1980s through 2016. Drawing from the consensus perspective on NOS and prior studies focusing on the analysis of textual content, documents were inspected for 10 target NOS aspects: the empirical, tentative, inferential, creative, theory-driven, and social NOS, in addition to the myth of “The Scientific Method,” the nature of scientific theories and laws, and the social and cultural embeddedness of science. Ninety-eight state documents from 48 states were analyzed and multiple editions were collected from 34 states. Additionally, relevant materials from the Next Generation Science Standards (NGSS) were assessed for their coverage of the same NOS aspects. Collected materials were scored as whole documents, including over 11,000 pages of text in total, on each target aspect, which reflected the treatment (naïve vs. informed) of NOS in text and the manner of presentation (explicit vs. implicit). Overall, surprisingly, state standards documents have improved very little with respect to their NOS coverage over the last 30 years. NOS standards documents remain silent on a majority of key aspects of NOS, and the number of aspects showing explicit, informed representations has held constant. The NGSS performed well compared to many contemporary documents, but they failed to address all target NOS aspects in a desirable manner. Further analysis raised concerns with the degree that states fully adopt and disseminate standards in manner consistent with the NGSS despite stated intentions, which may negatively impact NOS coverage in instructional resources and classroom enactments. To improve NOS representations in standards, recognizing the role these documents play in shaping instructional materials and teaching in the science classroom, exemplars from analyzed materials were highlighted with informed and explicit representations of multiple aspects.  相似文献   
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Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student’s affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that would give extra support for learners with intellectual disabilities, little work on AIEd systems that utilise affect recognition currently addresses this group. Our system used multimodal sensor data and machine learning to first identify three affective states linked to learning (engagement, frustration, boredom) and second determine the presentation of learning content so that the learner is maintained in an optimal affective state and rate of learning is maximised. To evaluate this adaptive learning system, 67 participants aged between 6 and 18 years acting as their own control took part in a series of sessions using the system. Sessions alternated between using the system with both affect detection and learning achievement to drive the selection of learning content (intervention) and using learning achievement alone (control) to drive the selection of learning content. Lack of boredom was the state with the strongest link to achievement, with both frustration and engagement positively related to achievement. There was significantly more engagement and less boredom in intervention than control sessions, but no significant difference in achievement. These results suggest that engagement does increase when activities are tailored to the personal needs and emotional state of the learner and that the system was promoting affective states that in turn promote learning. However, longer exposure is necessary to determine the effect on learning.  相似文献   
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Prior research on the structure of academic self-concepts has demonstrated academic self-concepts to be domain-specific and hierarchically organized, but has largely failed to support the hypothesis that general academic self-concept is at the apex of the hierarchy. The present study investigates a new multidimensional nested-factor model of academic self-concepts that incorporates both domain-specific and general academic self-concepts, and the position of general academic self-concept at the apex of the self-concept hierarchy. Data were obtained from representative samples of 15-year-old students in 26 countries (total N = 106,680). Results showed that the nested-factor model provided a good fit to the data in each of the 26 countries, and that general and domain-specific academic self-concepts were meaningfully related to gender as well as to student achievement. Moreover, it emerged that the relationships between academic self-concepts and these student characteristics may differ substantially depending on whether the model applied does or does not account for the influence of general academic self-concept on domain-specific measures of academic self-concepts.  相似文献   
69.
Working with scientists has been suggested as an effective way for high-school students to learn authentic science. However, little research has involved students’ perceptions of science learning environments in a university internship. This study drew on the theoretical framework of community of practice with cogenerative dialogues to design an internship program that aims to build a constructivist internship for students. Students who learned science in the internship program developed stronger constructivist learning perceptions than those who learned science in school. Specifically, students perceived that they had more opportunities to think independently of the instructors and other students. Three effective principles for program design are: (a) high school students conduct open-inquiry projects with the support of scientists; (b) high school students and scientists conduct cogenerative dialogues regularly to address issues and share experiences; and (c) high school students present their project proposals and scientific findings at open house events. Implications of the results are discussed.  相似文献   
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