How Learning Works : Seven Research-Based Principles for Smart Teaching

1.4k indexed citations
published 2010
Journal
CERN Document Server (European Organization for Nuclear Research)

In The Last Decade

doi.org/w51479781 →

Countries where authors are citing How Learning Works : Seven Research-Based Principles for Smart Teaching

Specialization
Citations

This map shows the geographic impact of How Learning Works : Seven Research-Based Principles for Smart Teaching. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by How Learning Works : Seven Research-Based Principles for Smart Teaching with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites How Learning Works : Seven Research-Based Principles for Smart Teaching more than expected).

Fields of papers citing How Learning Works : Seven Research-Based Principles for Smart Teaching

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of How Learning Works : Seven Research-Based Principles for Smart Teaching. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the How Learning Works : Seven Research-Based Principles for Smart Teaching.

About How Learning Works : Seven Research-Based Principles for Smart Teaching

This paper, published in 2010, received 1.4k indexed citations . Written by Susan A. Ambrose. It is primarily cited by scholars working on Education (813 citations), Developmental and Educational Psychology (295 citations) and Media Technology (208 citations). Published in CERN Document Server (European Organization for Nuclear Research).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w51479781.

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