Cognitive Style Analysis Test Research Articles

The effect of Cognitive Style Analysis (CSA) test on achievement: A meta-analytic review

Riding's (1991) Cognitive Style Analysis test has been a popular UK test of the verbal–imagery and wholistic–analytic cognitive style dimensions. Researchers have claimed numerous academic advantages for these style dimensions, but the direction of the effects is inconsistent. A meta-analysis was therefore conducted that used the CSA along with an academic outcome measure. While 25 studies met the inclusion criteria, only 15 provided sufficient information for statistical analysis. The studies included five experimental and 10 observational studies and involved participants in primary, secondary and tertiary institutions. The results show no clear academic achievement advantage for either the verbal–imagery cognitive style dimension or the wholistic–analytic cognitive style dimension, regardless of the learning task or environment. While the final sample of included studies was relatively small the results of this meta-analysis suggest that the relationship between the CSA's cognitive style dimensions and academic achievement, if any, is likely to be negligible.

The impact of users’ verbal/imagery cognitive styles on their Web search behavior

Purpose – The purpose of this paper is to investigate the effects of verbal-imagery cognitive styles of information searching behavior of users in using the Web. Design/methodology/approach – In all, 44 participants were recruited for this study. The participants’ cognitive styles were measured by using Riding's Cognitive Style Analysis test. Three search tasks were designed based on Kim's search task definitions. Moreover, an individual lab session was arranged and then participants’ memos were analyzed using content analysis. Findings – In all, 48 strategies in four categories of behaviors in searching the Web were identified. There were associations between users’ cognitive styles and their information searching behavior. The participants’ selection of the search initiation behaviors varied, so that imagers suffered from more varied initial behavior than verbalizers. The verbalizers tended to search in a narrow area, then broadening the area and following structured navigation and reading behavior to process information, while imagers tended to search in a general area, then narrowing down the search and adopting mixed navigational styles and mixed behaviors to process information. This study revealed that there was a difference in search performance of verbalizers and imagers descriptively, as verbalizers spent more time compared to imagers and imagers visited more nodes than verbalizers for the tasks completion. In addition, the task was an important variable influencing the search performance. Based on the key findings (search initiation behaviors, formulating search queries, navigational behaviors, information processing behaviors), a conceptual pattern of Web searching and cognitive styles is presented. Research limitations/implications – The study provides a new understanding of Web users’ information search behavior based on cognitive styles which contributes to the theoretical basis of Web search research. It also raises various questions within the context of user studies Originality/value – The paper adopted a mixed approach in the area of information searching on the Web. A valuable contribution lies in the methods developed.

Instructional methods and cognitive and learning styles in web-based learning: report of two randomised trials

Adapting web-based (WB) instruction to learners' individual differences may enhance learning. Objectives This study aimed to investigate aptitude-treatment interactions between learning and cognitive styles and WB instructional methods. We carried out a factorial, randomised, controlled, crossover, post-test-only trial involving 89 internal medicine residents, family practice residents and medical students at 2 US medical schools. Parallel versions of a WB course in complementary medicine used either active or reflective questions and different end-of-module review activities ('create and study a summary table' or 'study an instructor-created table'). Participants were matched or mismatched to question type based on active or reflective learning style. Participants used each review activity for 1 course module (crossover design). Outcome measurements included the Index of Learning Styles, the Cognitive Styles Analysis test, knowledge post-test, course rating and preference. Post-test scores were similar for matched (mean +/- standard error of the mean 77.4 +/- 1.7) and mismatched (76.9 +/- 1.7) learners (95% confidence interval [CI] for difference - 4.3 to 5.2l, P = 0.84), as were course ratings (P = 0.16). Post-test scores did not differ between active-type questions (77.1 +/- 2.1) and reflective-type questions (77.2 +/- 1.4; P = 0.97). Post-test scores correlated with course ratings (r = 0.45). There was no difference in post-test subscores for modules completed using the 'construct table' format (78.1 +/- 1.4) or the 'table provided' format (76.1 +/- 1.4; CI - 1.1 to 5.0, P = 0.21), and wholist and analytic styles had no interaction (P = 0.75) or main effect (P = 0.18). There was no association between activity preference and wholist or analytic scores (P = 0.37). Cognitive and learning styles had no apparent influence on learning outcomes. There were no differences in outcome between these instructional methods.

Factors Influencing Successful Achievement in Contrasting Design and Technology Activities in Higher Education

The aim of the study was to investigate the relationship between such factors as learning style, gender, prior experience, and successful achievement in contrasting modules taken by a cohort of thirty design and technology trainee teachers during their degree programme at a University in the North East of England. Achievement data were collected from three design and three electronic modules at levels 1, 2 and 3. Data concerning appropriate, previous experience before starting the course was obtained through a short questionnaire. The learning style of each member of the sample was ascertained using the Cognitive Style Analysis test. The findings from the study indicated that the learning style groupings were not as expected. A positive relationship between achievement and past experience in both electronics and design activity was found, although improvement for those with no prior experience in comparison to those with previous experience was only evident in electronics. A concern arising out of the data was the differences in terms of achievement between male and female students and also the difference in achievement when learning style and gender were scrutinised. The implications of the findings in relation to the success of the trainees as impending teachers of design and technology were discussed. The problems associated with the small cell size caused by splitting the sample by the three variables was acknowledged and a suggestion was made that further study would be required to ascertain whether the gender and learning style differences witnessed in this study would be replicated in a larger sample.

Test–retest reliability of Riding’s cognitive styles analysis test

The test–retest reliability of Riding’s cognitive styles analysis (CSA) was investigated over mean intervals of (i) 14 days and (ii) 23 months. The test–retest reliability, measured using the Pearson product-moment correlation, for cohorts of largely third year information systems and engineering students was found to average r=0.34 for the wholist-analytic dimension while the verbaliser–imager dimension varied between −0.19 and 0.36. These values are considerably below the generally accepted value of r=0.8 as a minimum figure for reliability as estimated by test–retest correlation. Consequently it can be concluded that the CSA does not estimate these dimensions with sufficient precision for at least these sample populations.

The reliability of Riding’s Cognitive Style Analysis test

The reliability of Riding’s popular Cognitive Styles Analysis test (CSA) was examined by comparing performance on the original CSA test and a new parallel version. Fifty participants completed both test versions twice, with the second sitting approximately a week later. Reliability was measured using parallel forms, test–re-test, and split-half analysis. Correlations of the verbal–imagery (VI) and wholist–analytic (WA) ratios from both test versions (original and parallel) were low (Range r=0.07 to r=0.36, Mean r=0.24). When the CSA and parallel form data were combined however, split-half analysis of the WA style ratio was stable (Mean r=0. 69) but the VI style ratio remained unreliable (Mean r=0.36).

On the assessment of cognitive style: four red herrings

This paper is a reply to Riding's (2002) four main comments on Peterson, Deary, and Austin's (2002) paper ‘The Reliability of Riding's Cognitive Style Analysis Test.’ Riding's comments centre around Peterson et al.'s sample size, sample composition, test interval, and the alleged use of a different test from the original. We argue that the first three of these comments are incorrect and the fourth is disingenuous and that they merely distract from, rather than criticise, our simple, novel, positive finding that the reliability of the wholistic–analytic dimension of the Cognitive Styles Analysis (CSA) test can be improved.