Inferencing Complexity of Iranian TEFL Ph.D. Entrance Exam under the Lens of Construction-Integration Model of Inference Processing

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.