The Effect of Task Type and Word Type on Vocabulary Learning: A Comparison Based on Involvement Load Hypothesis and Technique Feature Analysis - Maryam Ehsani; Hossein Karami; Omid Mallahi (Iranian Journal of Applied Language Studies, 2023)
This study aimed to investigate the effect of task type (i.e., sentence fill-in/sentence writing) and word type (i.e., real/ pseudo) on initial learning and retention of 10 word meanings, taking the predictions of Involvement Load Hypothesis (ILH) and Technique Feature Analysis (TFA) into account. Participants were 59 intermediate-level EFL learners from eight intact classes. Each intact class was randomly assigned to one of the four learning conditions: 1) sentence fill-in with real words, 2) sentence writing with real words, 3) sentence fill-in with pseudowords, and 4) sentence writing with pseudowords. Initial learning was measured by administering a meaning recall test immediately after the tasks and medium-term retention was measured by administering the same test with rearranged items one week after the tasks phase. The results of a mixed between-within subjects ANOVA did not show any significant interaction effect between test time and learning condition. Furthermore, the main effect for learning condition was not statistically significant but there was a significant main effect for test time, suggesting that participants’ scores dropped significantly from the immediate posttest to the delayed posttest. The findings of two independent-samples t-tests failed to show any significant difference between the immediate and delayed posttest scores of the participants who received either sentence fill-in or sentence writing tasks. However, some tentative findings demonstrated that those participants who were assigned to the sentence writing task achieved higher scores on the posttests. This finding indicates that TFA has probably more predictive power than ILH and it also provides some evidence in favor of the heavier weight of the evaluation component of the ILH when compared to its search component.