Alan M. Taylor

Hierarchical Dependence in Meta-Analysis

Meta-analysis is a frequent tool among education and behavioral researchers to combine results from multiple experiments to arrive at a clear understanding of some effect of interest. One of the traditional assumptions in a meta-analysis is the independence of the effect sizes from the studies under consideration. This article presents a meta-analytic review of 13 experiments with 18 study reports all involving the effect of native-language (L1) vocabulary aids on second-language (L2) reading comprehension. Some experiments produced multiple study reports, creating a dependence structure among the resulting effect size estimates. The covariance among these effect size estimates is estimated and incorporated into a proposed meta-analysis model that accounts for the dependence at a hierarchical level. The overall effect size estimate (g =.63) indicates that L1 vocabulary aids can be an effective L2 reading comprehension aid in the short term. An interpretation of the hierarchical components is discussed.

L1 glossing and strategy training for improving L2 reading comprehension: a meta-analysis

Extensive research on the effects of interventions to improve L2 reading has been conducted yet the results are often not conclusive. The present research synthesis intends to provide a more accurate measurement of studies that have attempted to improve L2 reading comprehension. It includes 62 studies conducted on either explicit reading strategy training (ERST) or native language (L1) glosses. Besides updating past meta-analyses conducted on ERST and L1 glossing, it concludes that reading comprehension can be more effective (g = .64) whether through glossing or ERST. Moderating variables were identified and analysed, including type of intervention, learning context, test task and learning level.

Meta-Analysis and Computer-Mediated Communication.

Because of the use of human participants and differing contextual variables, research in second language acquisition often produces conflicting results, leaving practitioners confused and unsure of the effectiveness of specific treatments. This article provides insight into a recent seminal meta-analysis on the effectiveness of computer-mediated communication, providing further statistical evidence of the importance of its results. The significance of the study is examined by looking at the p values included in the references, to demonstrate how results can easily be misconstrued by practitioners and researchers. Lin’s conclusion regarding the research setting of the study reports is also evaluated. In doing so, other possible explanations of what may be influencing the results can be proposed.