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871.
Claire E. Baker Claire E. Cameron Sara E. Rimm-Kaufman David Grissmer 《Early education and development》2013,24(6):833-854
Research Findings: Data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998–1999, were used to examine the relation between parenting, sociodemographic characteristics, and school readiness among (N = 1,136) African American boys in kindergarten. Parenting was defined as parenting style (i.e., warmth and control), home learning stimulation, and culturally relevant parenting. Two child outcomes previously linked to school readiness were examined: kindergarten reading and approaches to learning. Hierarchical regression analyses were performed to address 2 research questions. First, does parenting predict kindergarten reading above and beyond the contribution of sociodemographic characteristics? Second, does parenting predict kindergarten approaches to learning above and beyond the contribution of sociodemographic characteristics? Practice or Policy: Children with parents who set consistent bedtimes, provided more books in their homes, and read to them more frequently had better kindergarten reading scores after socioeconomic status, environmental safety, and maternal education were controlled. Similarly, children with parents who provided more books in their home and read to their children more frequently had more positive teacher-rated approaches to learning scores in kindergarten. Implications for future research are discussed. 相似文献
872.
873.
David Gibson Vitomir Kovanovic Dirk Ifenthaler Sara Dexter Shihui Feng 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(5):1125-1146
This paper discusses a three-level model that synthesizes and unifies existing learning theories to model the roles of artificial intelligence (AI) in promoting learning processes. The model, drawn from developmental psychology, computational biology, instructional design, cognitive science, complexity and sociocultural theory, includes a causal learning mechanism that explains how learning occurs and works across micro, meso and macro levels. The model also explains how information gained through learning is aggregated, or brought together, as well as dissipated, or released and used within and across the levels. Fourteen roles for AI in education are proposed, aligned with the model's features: four roles at the individual or micro level, four roles at the meso level of teams and knowledge communities and six roles at the macro level of cultural historical activity. Implications for research and practice, evaluation criteria and a discussion of limitations are included. Armed with the proposed model, AI developers can focus their work with learning designers, researchers and practitioners to leverage the proposed roles to improve individual learning, team performance and building knowledge communities.
Practitioner notes
What is already known about this topic- Numerous learning theories exist with significant cross-over of concepts, duplication and redundancy in terms and structure that offer partial explanations of learning.
- Frameworks concerning learning have been offered from several disciplines such as psychology, biology and computer science but have rarely been integrated or unified.
- Rethinking learning theory for the age of artificial intelligence (AI) is needed to incorporate computational resources and capabilities into both theory and educational practices.
- A three-level theory (ie, micro, meso and macro) of learning that synthesizes and unifies existing theories is proposed to enhance computational modelling and further develop the roles of AI in education.
- A causal model of learning is defined, drawing from developmental psychology, computational biology, instructional design, cognitive science and sociocultural theory, which explains how learning occurs and works across the levels.
- The model explains how information gained through learning is aggregated, or brought together, as well as dissipated, or released and used within and across the levels.
- Fourteen roles for AI in education are aligned with the model's features: four roles at the individual or micro level, four roles at the meso level of teams and knowledge communities and six roles at the macro level of cultural historical activity.
- Researchers may benefit from referring to the new theory to situate their work as part of a larger context of the evolution and complexity of individual and organizational learning and learning systems.
- Mechanisms newly discovered and explained by future researchers may be better understood as contributions to a common framework unifying the scientific understanding of learning theory.
874.
875.
Sabrina J. Ashwell Patricia K. Baskin Stacy L. Christiansen Sara A. DiBari Annette Flanagin Tracy Frey Racquel Jemison Mia Ricci 《Learned Publishing》2023,36(1):94-99
- Inclusive language will make scholarly publishing more accurate and more respectful, and it has the potential to help authors reach a wider audience.
- JAMA and the JAMA Network journals, the American Chemical Society and the Coalition for Diversity and Inclusion in Scholarly Communications have free guides on inclusive language, formatting and images.
- The guides provide principles and rationale, as well as examples of preferred language, in order to equip people with knowledge to choose the most inclusive words even as terminology preferences change.