Impact of Moderating Variables on the Relative Evaluation of Study Skills Programs Table 5 presents the relations between various study cha...
Impact of Moderating Variables on the Relative Evaluation of Study Skills Programs Table 5 presents the relations between various study characteristics and the categorical models. All the Qw statistics are significant, which indicates wide variation of the effect sizes within the groupings. Background variables. It has been noted already that studies classified as low in quality had greater mean effect sizes than the other studies. There were no differences in the mean effect sizes derived from the studies classified as medium (M = 0.45, n = 108) and high quality (M = 0.46, n = 162). Further, there were no differences in the means relating to the nature of the research design. The mean effect size from control groups (M = 0.42, n = 189) was close to the mean from pretest-posttest group designs (M = 0.48, n = 47) and to the mean from other designs (M = 0.59, n = 34).
Journals report marginally more effective studies than monographs, while dissertations tend to report interventions that are not effective. The last finding could be caused by a greater reliance on tertiary student participants, for whom the effects are least; it should be noted that this cannot be attributed to low-quality work being carried out by graduate students, because poor studies have already been eliminated. It was not possible to compare the socioeconomic backgrounds of the participants, as most studies either did not comment on this variable or used "mixed" groups. Where there was information on socioeconomic background, the effect sizes were based on too few studies (low M = 0.23, n = 31; middle M = 0.61, n = 21; high M = 0.02, n = 18).
When students chose to seek study and learning skills assistance the effect sizes were greater than when intact classes were used. Structural complexity of the intervention. Table 6 shows the effect sizes for the structural complexity of the interventions as classified by SOLO level, which is our major independent variable. The dependent variables are classified into three domains: performance, study skills, and affect. It can be seen that different interventions have differing effects according to the dependent variable in question; the "total" column for such comparisons is thus not very meaningful in itself. The unistructural near (M = 0.83) and relational near (M = 0.77) programs have high effect sizes across all outcomes, the latter mean being remarkably close to that reported (M = 0.71) by Haller, Child, and Walberg (1988) for the same kind of intervention (metacognitive, contextualized).
If there were no moderators, then it would be suggested that study skills programs that can be classified as unistructural or relational are most effective. Unistructural interventions have the strongest effect on performance. This is not at all unexpected, as most such interventions were simple and taught directly with narrow aims; in this they were highly successful, producing effect sizes approaching one standard deviation (0.84). There is a positive effect on attitudes as reported in one study. The majority of the performance measures were directly related to the instructional material used in the intervention. These interventions were designed to teach students to use such aids to memory as mnemonic devices, graphic organizers, mental imagery, rehearsal, and strategy verbalization in order
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