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Item Types and Demand: What Is the Impact on Demand of Manipulating Item Types in Computer Science GCSE and IGCSE? Research Report

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Bibliographic Details
Title: Item Types and Demand: What Is the Impact on Demand of Manipulating Item Types in Computer Science GCSE and IGCSE? Research Report
Language: English
Authors: Green, Clare, Hughes, Sarah, Cambridge University Press & Assessment (United Kingdom)
Source: Cambridge University Press & Assessment. 2022.
Availability: Cambridge University Press & Assessment. Shaftesbury Road Cambridge CB2 8EA. Tel: 44-1223-553311; e-mail: directcs@cambridge.org; Web site: https://www.cambridgeassessment.org.uk/
Peer Reviewed: N
Page Count: 21
Publication Date: 2022
Document Type: Reports - Research
Education Level: Secondary Education
Descriptors: Test Items, Computer Science, Achievement Tests, Objective Tests, Computer Assisted Testing, Foreign Countries, Test Format, Secondary Education
Geographic Terms: United Kingdom
Abstract: The Digital High Stakes Assessment Programme in Cambridge University Press & Assessment is developing digital assessments for UK and global teachers and learners. In one development, the team are making decisions about the assessment models to use to assess computing systems knowledge and understanding. This research took place as part of the evidence gathering to inform decisions about the assessment model. One option would be to use objective questions in an online test which could be auto-marked using pattern-matching. The auto-marking would require a change in some item types. This piece of responsive research aimed to provide empirical evidence to the assessment developers quickly. The key questions for the study were: (1) If exam questions were manipulated to be objective questions, can the demand be maintained? and (2) If so, how can the demand be maintained in terms of which item types could be used? The CRAS scale of demand was chosen as the analysis tool. The CRAS framework enabled the analysis to reveal where demand might be affected should questions be rewritten for auto-marking. All items in the Computer Science (Computer Systems components) GCSE and IGCSE were investigated.
Abstractor: ERIC
Entry Date: 2022
Accession Number: ED622061
Database: ERIC
Description
Abstract:The Digital High Stakes Assessment Programme in Cambridge University Press & Assessment is developing digital assessments for UK and global teachers and learners. In one development, the team are making decisions about the assessment models to use to assess computing systems knowledge and understanding. This research took place as part of the evidence gathering to inform decisions about the assessment model. One option would be to use objective questions in an online test which could be auto-marked using pattern-matching. The auto-marking would require a change in some item types. This piece of responsive research aimed to provide empirical evidence to the assessment developers quickly. The key questions for the study were: (1) If exam questions were manipulated to be objective questions, can the demand be maintained? and (2) If so, how can the demand be maintained in terms of which item types could be used? The CRAS scale of demand was chosen as the analysis tool. The CRAS framework enabled the analysis to reveal where demand might be affected should questions be rewritten for auto-marking. All items in the Computer Science (Computer Systems components) GCSE and IGCSE were investigated.