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      Feedback literacy: a critical review of an emerging concept

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      Higher Education
      Springer Science and Business Media LLC

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          A typology of reviews: an analysis of 14 review types and associated methodologies.

          The expansion of evidence-based practice across sectors has lead to an increasing variety of review types. However, the diversity of terminology used means that the full potential of these review types may be lost amongst a confusion of indistinct and misapplied terms. The objective of this study is to provide descriptive insight into the most common types of reviews, with illustrative examples from health and health information domains. Following scoping searches, an examination was made of the vocabulary associated with the literature of review and synthesis (literary warrant). A simple analytical framework -- Search, AppraisaL, Synthesis and Analysis (SALSA) -- was used to examine the main review types. Fourteen review types and associated methodologies were analysed against the SALSA framework, illustrating the inputs and processes of each review type. A description of the key characteristics is given, together with perceived strengths and weaknesses. A limited number of review types are currently utilized within the health information domain. Few review types possess prescribed and explicit methodologies and many fall short of being mutually exclusive. Notwithstanding such limitations, this typology provides a valuable reference point for those commissioning, conducting, supporting or interpreting reviews, both within health information and the wider health care domain.
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            The Power of Feedback

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              Feedback and Self-Regulated Learning: A Theoretical Synthesis

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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Higher Education
                High Educ
                Springer Science and Business Media LLC
                0018-1560
                1573-174X
                June 2023
                July 19 2022
                June 2023
                : 85
                : 6
                : 1381-1400
                Article
                10.1007/s10734-022-00895-9
                22727e5d-8d86-4aa3-b05a-0cd8ff2c369a
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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