When comparing two or more groups, it is common practice to employ a statistical method of comparing means, such as a t-test or analysis of variance, with the grouping factor as the independent variable. If a significant difference is found, it is concluded that the difference is caused by the grouping factor.
However, in this study, comparing means does not constitute a valid analysis because a number of intervening factors are suspected. A significant difference of means cannot be attributed solely to the independent variable, i.e., type of learning. For example, a difference in means could be attributed to the effects of study time. If students employ several different methods of learning, as found in the MIXED category, it is likely that they spend more time on studying than the students in the other groups, and further, that the learners in MIXED may gain higher scores than the other groups due to the benefit of the greater amount of study time, not type of learning per se. Another possible cause of a mean difference is proficiency. There is a general consensus among teachers that students at a low proficiency level are likely to develop their proficiency more rapidly that those at a high proficiency level. Even if the result of a statistical analysis shows that the score gain of a particular group is smaller than another group, it may be that one group is disadvantaged by the students’ existing high proficiency.
When comparing two or more groups, it is common practice to employ a statistical method of comparing means, such as a t-test or analysis of variance, with the grouping factor as the independent variable. If a significant difference is found, it is concluded that the difference is caused by the grouping factor.However, in this study, comparing means does not constitute a valid analysis because a number of intervening factors are suspected. A significant difference of means cannot be attributed solely to the independent variable, i.e., type of learning. For example, a difference in means could be attributed to the effects of study time. If students employ several different methods of learning, as found in the MIXED category, it is likely that they spend more time on studying than the students in the other groups, and further, that the learners in MIXED may gain higher scores than the other groups due to the benefit of the greater amount of study time, not type of learning per se. Another possible cause of a mean difference is proficiency. There is a general consensus among teachers that students at a low proficiency level are likely to develop their proficiency more rapidly that those at a high proficiency level. Even if the result of a statistical analysis shows that the score gain of a particular group is smaller than another group, it may be that one group is disadvantaged by the students’ existing high proficiency.
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