Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.665743
Title: Construct representation of First Certificate in English (FCE) reading
Author: Corrigan, Michael
ISNI:       0000 0004 5350 6769
Awarding Body: University of Bedfordshire
Current Institution: University of Bedfordshire
Date of Award: 2015
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
The current study investigates the construct representation of the reading component of a B2 level general English test: First Certificate in English (FCE). Construct representation is the relationship between cognitive processes elicited by the test and item difficulty. To facilitate this research, a model of the cognitive process involved in responding to reading test items was defined, drawing together aspects of different models (Embretson & Wetzel, 1987; Khalifa & Weir, 2009; Rouet, 2012). The resulting composite contained four components: the formation of an understanding of item requirements (OP), the location of relevant text in the reading passage (SEARCH), the retrieval of meaning from the relevant text (READ) and the selection of an option for the response (RD). Following this, contextual features predicted by theory to influence the cognitive processes, and hence the difficulty of items, were determined. Over 50 such variables were identified and mapped to each of the cognitive processes in the model. Examples are word frequency in the item stem and options for OP; word frequency in the reading passage for READ; semantic match between stem/option and relevant text in the passage for SEARCH; and dispersal of relevant information in the reading passage for RD. Response data from approximately 10,000 live test candidates were modelled using the Linear Logistic Test Model (LLTM) within a Generalised Linear Mixed Model framework (De Boeck & Wilson, 2004b). The LLTM is based on the Rasch model, for which the probability of success on an item is a function of item difficulty and candidate ability. The holds for LLTM except that item difficulty is decomposed so that the contribution of each source of difficulty (the contextual features mentioned above) is estimated. The main findings of the study included the identification of 26 contextual features which either increased or decreased item difficulty. Of these features, 20 were retained in a final model which explained 75.79% of the variance accounted for by a Rasch model. Among the components specified by the composite model, OP and READ were found to have the most influence, with RD exhibiting a moderate influence and SEARCH a low influence. Implications for developers of FCE include the need to consider and balance test method effects, and for other developers the additional need to determine whether their tests test features found to be criterial to the target level (such as non-standard word order at B2 level). Researchers wishing to use Khalifa and Weir’s (2009) model of reading should modify the stage termed named inferencing and consider adding further stages which define the way in which the goal setter and monitor work and the way in which item responses are selected. Finally, for those researchers interested in adopting a similar approach to that of the current study, careful consideration should be given to the way in which attributes are selected. The aims and scope of the study are of prime importance here.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.665743  DOI: Not available
Keywords: English reading ; construct representation ; First Certificate in English ; reading ; Q110 Applied Linguistics ; language assessment ; language testing
Share: