Measuring preferences for visual-spatial learning

Measuring preferences for visual-spatial learning

This dissertation is a report on the validation of an instrument, Visual-Spatial Learning Questionnaire (VSLQ), developed to measure preferences for visual-spatial
learning in secondary school students. A reliable and valid comprehensive instrument for measuring preferences for visual-spatial learning would allow secondary school teachers to effectively cater for the individual learning needs of students with a preference for this
learning style. During Study 1 an Exploratory Factor Analysis (EFA) was conducted to remove redundant items and identify the factors underlying the 70-item instrument. The EFA was conducted on 2006 archival data collected using the VSLQ. As a result of the EFA, the instrument was reduced from 70 items to 15. Reducing the number of items removed
extraneous underlying factors that did not measure preferences for visual-spatial learning and made the questionnaire more useful for classroom teachers. Completing 70 items is a significant time imposition for both students and teachers, and takes away a lot of time from a lesson. A smaller number of items will allow the classroom teacher to quickly identify a student’s learning preference and use pedagogical strategies that have been shown to be successful with students who have a preference for visual-spatial learning. Four factors emerged in analysis, each with acceptable internal consistency: organization (disorganisation), spatial awareness, object-visualisation, and spatial-visualisation. Six items
loaded onto the factor of organisation (disorganisation), five onto spatial awareness, two onto object-visualisation, and two loaded onto spatial visualisation. The EFA also began the process of providing evidence that the VSLQ has internal reliability and construct validity
(KMO = .60, BTS = .00).

During Study 2 a Confirmatory Factor Analysis (CFA) was conducted on the 15-item version of the VSLQ. A re-examination of the eigenvalues, Scree plot and total variance from Study 1 suggested that the 4 underlying factors should be merged to form 2 factors - organisation (disorganisation) and spatial awareness. Object-visualisation, spatial awareness, and spatial-visualisation have interrelated characteristics and were grouped together under the heading of spatial awareness. The CFA further reduced the instrument to 8-items and provided evidence of its internal consistency (NC = 2.64 [X2 = 52.98/ df = 20], p < .001, RMSEA = 0.05, CFI = .91, TLI = .84, NFI = .86, IFI = .91). During Study 3, the results of the revised 8-item version of the VSLQ were compared against the results of two other instruments designed to measure visual-spatial learning and visual-spatial ability –
Silverman’s (2000) Visual-Spatial Identifier (VSI), and Newton and Bristoll’s (2009) Spatial Ability Test (SAT). To date, Silverman’s (2000) VSI is the most widely used questionnaire to identify visual-spatial learners (VSL). Correlations between the underlying factors on the
three instruments provided evidence of the convergent validity of the VSLQ.

The results of the three studies demonstrated that the revised 8-item version of the VSLQ has both reliability, in the form of internal consistency, and construct validity. The implications of a short and reliable instrument for measuring preferences for visual-spatial learning will also be discussed. Unlike Silverman’s (2000) VSI, the revised 8-item version of the VSLQ has demonstrated reliability and validity. As such, classroom teachers in secondary schools who use the instrument can trust that a student identified as having a preference for visual-spatial learning will most likely achieve success if visual-spatial teaching methods are used within the classroom. The revised 8-item version of the VSLQ is half the length of Silverman’s (2000) VSI. As such, it is quicker to use for classroom
teachers. Rather than spending significant periods of time having students complete the questionnaire and analysing the results, it allows classroom teachers to quickly identify the learning preferences of their students and cater for their individual learning needs. By identifying students’ individual learning needs, teachers can use teaching strategies that will hopefully lead to educational success.