Vatsavayi Sravya received her MS Dual Degree in Computer Science and Engineering (CSE). Her research work was supervised by Dr. Kavita Vemuri. Here’s a summary of Vatsavayi Sravya’s thesis Analysing differential solution approaches as applied by fine art and engineering students – A fluid intelligence study as explained by her:
Analytic reasoning differences, as gauged from intelligence metrics, in students engaged in streams requiring a predominantly divergent (arts) or convergent thinking (science and engineering) is a topic of interest. In this thesis an attempt is made to examine the differential application of solution analysis in standard non-verbal intelligence tests by fine arts and engineering students, two cohorts with distinct academic coursework, skill training and attributed differences in their thinking. As understood from previous research, intelligence being a multi-dimensional entity, can be broadly categorized into two divisions (Cattel,1963) – a) Fluid Intelligence (Gf) b) Crystallized Intelligence (Gc). The former refers to the ability of humans to solve novel problems and is measured using tests requiring induction, deduction and reasoning. The latter defines the skill of humans in applying existing knowledge and experience, mostly evaluated by verbal comprehension and working memory tests. There are debates about fluid intelligence being an innate ability or genetic factor but measures of Gf have been observed to be affected by various factors such as socio-economic differences, gender, skill training etc. Keeping in context the larger debate on the role of each factor and the correlations, the aim of my study is to find whether skill training creates a difference in performance in a Gf test. Ravens Progressive Matrices (RPM) – a standard measure of fluid intelligence was used to examine not just the score-wise performance but the analytical processes applied and problem solving techniques. The premise for considering fine arts students for a fluid intelligence test with shapes, patterns and constant, is their artistic talent to create identified visual patterns, manipulate geometrical shapes and sharper contrast elimination. Other reasoning applied for the selection of this participant cohort for comparison is that they differ in their thinking style based on Hudson’s theory (1966), that this variation in thinking style is reflected in choice of profession/education. That is, this theory proposed that convergent thinkers display a rule-based thinking and engage in science, mathematics while divergent thinkers are defined as engaging in freethinking and excel in arts and/or humanities. Various arguments have been made on the accuracy of this distinction, fine arts such as music also have a certain set of rules (mathematical) while fields such as engineering encourage divergent thinking in design and applications. Hence, in my work I extend the research on this theory by exploring the approach towards analytical problem solving and make inferences on the thinking styles as per the above-proposed theory, with two distinct cohorts – computer science and fine art students. To examine further the role of academic skill training, the engineering students were grouped into art-trained and non art-trained setsA difference in performance just based on numerical data such as scores would be insufficient. In- sights of the approach to solution can be extracted from the differences in visual strategies applied with eye-tracking technique as valid method. This technique has been established in literature as efficient for analyzing attention patterns, which is said to reveal the underlying cognitive processes applied. Hence in this study, visual search strategy (scan-path) was inspected to extract the approaches towards a problem solution for each item of the RPM test. Additional measurements included analysis of fixation duration and area of interest in the matrix elements and options spaces. The selection of RPM for the current study is based on established concepts : RPM being a pattern- based test, studies have indicated that visual information processing or visual strategies might be crucial to understand and solve these questions. To further identify the underlying differential visual strategies applied, the Navon stimuli and Embedded Figures Task (EFT) were also administered. Navon stimuli allows for insights to the variations in visual information processing technique, principally global vs. local processing and the Embedded Figures Test is utilized to analyze field independence and its association to thinking style. The results show that engineering students performed better than art students in terms of score (T-test: p <0.0001) while no significant difference was seen among art-trained and non art-trained engineering students (p >0.05). Analysis of eye-tracking data showed considerable differences in the various perfor- mance metrics such as time and fixations. Scan-paths generated from fixation mapping were compared within-subject and for each question. First, three major scan-path directions that indicated pattern iden- tification variations were observed – Horizontal, Vertical and Defocused [elements of matrix scanned in no particular direction]. On an average, artists preferred defocused scan-path. Engineers followed horizontal scan-path, which could suggest a rule-identified behavior in agreement with Carpenter et al, (1990). From the combined analysis of the scan-path and fixations with Area of Interest (AOIs) analysis, there seems to be a support for Bethell-Fox theory(Bethell-Fox, Lohman & Snow, 1984) as art students seemed to follow an elimination procedure while engineering students displayed constructive matching technique. No particular pattern or significant differences were found for the Navon and EFT tests. From the quantitative and detailed qualitative analysis, we argue that intelligence (RPM) performance is enhanced by constant training in mathematical/logical reasoning tests and RPM style tests as per the scores from the engineering participants and might not solely reflect an innate ability. This infer- ence is further supported by the similar scores of the art-trained and non art-trained engineering student scores. Higher scores by engineering students could also be due to rule-based thinking inculcated by their academic curriculum as STEM students are more practiced in MCQ based tests and schooled in mathematical cognition, which is considered to enhance performance by consistent application of rules. The explanation is further supported by test on cognitive style wherein similar performance is seen in the EFT, which is designed to test for the ability to dismember or extract information or patterns from the surrounding ‘noise’ and in contrast to studies which have analysed for field dependent-independent cognitive styles increative skilled people. The scan-path evidence from the RPM and similar results across EFT supplements our reasoning that skill training might be the primary cause for differences in RPM performance among artists and engineers. Hence, an artist trained on a series of analytical tests might achieve a significant increment in scores. The critical finding is the efficacy of RPM as a non-verbal fluid intelligence test, as analytical skills seem to have a significant effect on performance. The objective of our study was not to compare intelligence levels by a unitary index as usually done when administering a RPM type test, rather it was an attempt to understand from the information extraction technique the visual search strategies while making the differential pattern identification, and matching strategies to the cognitive thinking style.