Inferencing

Density and distribution of Unfamiliar Lexical Items (ULIs) appear to influence learners’ Reading Comprehension Achievement (RCA). This study concerns the impact of these two variables on Iranian EFL learners’ RCA. For this, two groups of students timetabled for the experiments designed to assess learners’ RCA. To determine the participants’ levels of proficiency a Quick Proficiency Test was first given to the total population of 87 students and 60 selected as participants. They were then divided into four subgroups of 15, each of which took the pertaining text as the treatment. To do so, three short passages were administered, two for the density and one for distribution. Then, data were gathered from the questionnaires and answers analyzed by SPSS. The results revealed the participants in low density/distribution subgroups outperforming their counterparts in high density/distribution subgroups on tests devised to measure the learners’ inferencing of ULIs boldfaced in the texts. The selected method was a quasi-experimental, post-test only design and the procedures comprised short passages, multiple-choice tests, and statistics. To conclude, ULIs found detrimental to the learners’ successful RCA in the foregoing experimentation, where it can serve as a resource to the EFL development programs.

The present study aims at scrutinizing the inference complexity level (henceforth ICL) of test items of the Iranian State University TEFL Ph.D. entrance exam (ISUTPEE) from 2010 to 2017 through the lens of Kintsch's construction-integration theory (C-I) (Kintsch, 1988, 1998). Though there is ample research on inferencing in the field of reading comprehension, the existing literature reveals a serious gap in relation to inferencing complexity of test items in high-stakes exams that exert profound effects on the academic achievements of the individuals. Inferencing is examined in this study to explore the ICL of the test items of the Special Knowledge Test (SKT) according to three levels of memory representations of Kintsch's model: the surface model, the textbase, and the situation model. To this end, the test items for eight consecutive years of the ISUTPEE were examined in relation to the three distinct kinds of mental representations. To ensure the reliability of coding by the researchers, two other specialist coders assessed the ICL of 33% of the items. The intraclass correlation among the three sets of codes was 0.91. The results of the study showed that a large number of questions, accounting for more than 80% of the items, merely activate the surface and the textbase model of information representations in memory. Furthermore, the ICL for each of the four parts of SKT was examined. This analytical study carries a stark warning regarding a deficiency of systematic attention to ICL in the development of test items.