2018
DOI: 10.1016/j.edurev.2018.03.003
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The use of Latin-square designs in educational and psychological research

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Cited by 48 publications
(20 citation statements)
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“…To eliminate participants’ inattention due to technical novelty, the learners can be exposed to the new technology environment for a period of time, helping them adapt to the equipment and the intervention learning mode ( Gavgani et al, 2018 ). On this basis, we can eliminate some unnecessary interference factors, or we can use the Latin square design to exclude the above interference factors to reduce the influence of endogenous factors generated by the research design ( Richardson, 2018 ). Undoubtedly, the research on this issue needs to be supplemented by more empirical studies.…”
Section: Resultsmentioning
confidence: 99%
“…To eliminate participants’ inattention due to technical novelty, the learners can be exposed to the new technology environment for a period of time, helping them adapt to the equipment and the intervention learning mode ( Gavgani et al, 2018 ). On this basis, we can eliminate some unnecessary interference factors, or we can use the Latin square design to exclude the above interference factors to reduce the influence of endogenous factors generated by the research design ( Richardson, 2018 ). Undoubtedly, the research on this issue needs to be supplemented by more empirical studies.…”
Section: Resultsmentioning
confidence: 99%
“…Therefore, the obtained graphs have similar topological characteristics, while being sufficiently different to avoid a learning effect when switching from one to another. We then built 24 configurations with the various surfaces so that each surface and graph is performed at least once as first, using something similar to the concept of the Latin square [Freeman79,Richardson18]. A Latin square is an n x n array filled with n different symbols in such a way that each symbol occurs exactly once in each row and exactly once in each column.…”
Section: Experimental Protocol and Measuresmentioning
confidence: 99%
“…As recommended by Richardson (2018), the order of conditions was included in each statistical model; however, for simplicity, is otherwise not reported. Model fits and statistical significance were evaluated by comparing Akaike's information criterion (AIC) and computing the 𝜒 2 change, respectively.…”
Section: Analysesmentioning
confidence: 99%