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  2. Visible learning - Wikipedia

    en.wikipedia.org/wiki/Visible_Learning

    Visible learning is a meta-study that analyzes effect sizes of measurable influences on learning outcomes in educational settings. [1] It was published by John Hattie in 2008 and draws upon results from 815 other Meta-analyses. The Times Educational Supplement described Hattie's meta-study as "teaching's holy grail". [2]

  3. John Hattie - Wikipedia

    en.wikipedia.org/wiki/John_Hattie

    John Allan Clinton Hattie ONZM (born 1950) is a New Zealand education academic. He has been a professor of education and director of the Melbourne Education Research Institute at the University of Melbourne , Australia, since March 2011.

  4. Effect size - Wikipedia

    en.wikipedia.org/wiki/Effect_size

    In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...

  5. Jigsaw (teaching technique) - Wikipedia

    en.wikipedia.org/wiki/Jigsaw_(teaching_technique)

    [1] [2] [3] A study by John Hattie found that the jigsaw method benefits students' learning. [4] The technique splits classes into mixed groups to work on small problems that the group collates into an outcome. [1] For example, an in-class assignment is divided into topics. Students are then split into groups with one member assigned to each topic.

  6. Evidence-based education - Wikipedia

    en.wikipedia.org/wiki/Evidence-based_education

    Evidence-based education (EBE) is the principle that education practices should be based on the best available scientific evidence, with randomised trials as the gold standard of evidence, rather than tradition, personal judgement, or other influences. [1]

  7. Counternull - Wikipedia

    en.wikipedia.org/wiki/Counternull

    The counternull value is the effect size that is just as well supported by the data as the null hypothesis. [2] In particular, when results are drawn from a distribution that is symmetrical about its mean, the counternull value is exactly twice the observed effect size. The null hypothesis is a hypothesis set up to be tested against an alternative.

  8. The Mandela effect: 10 examples that explain what it is and ...

    www.aol.com/lifestyle/mandela-effect-10-examples...

    Popular examples of the Mandela effect. Here are some Mandela effect examples that have confused me over the years — and many others too. Grab your friends and see which false memories you may ...

  9. Big-fish–little-pond effect - Wikipedia

    en.wikipedia.org/wiki/Big-fish–little-pond_effect

    The big-fish–little-pond effect (BFLPE) is a frame of reference model introduced by Herbert W. Marsh and John W. Parker in 1984. According to the model, individuals compare their own self-concept with their peers and equally capable individuals have higher self-concepts when in a less capable group than in a more capable group.