It's a requiem of sorts, scored for a massive orchestra with four conductors, male speaking chorus (here, the New London Chamber Choir here) also playing handbells, boys' choir (Trinity Boys), solo soprano (Claudia Barainsky) and trombone (Helen Vollam).
Likewise, two experts had novice-level card sort scores (<0).
Expert and novice sort scores were significantly different (t = −4.7, 33 df, p < 0.001).
While 80% of expert sort scores were positive, 80% of novice sort scores were negative, indicating that most novices employed novice-like sort rules and most experts employed expert-like sort rules.
While no novices' sort scores approached the highest scores of experts, three novices achieved the average expert score (about +2).
Overall, card sort scores derived from judgments of card sort rules were highly predictive of social expertise level (e.g., evolutionary biologist or student).
Table 3 Correlation patterns among measures Card sort score Teleology score Key concept diversity score Misconception diversity score Card sort score 1 0.399* 0.448** −0.545** n 35 35 35 Teleology score 1 0.328 −0.423* n 35 35 Key concept diversity score 1 −0.547** n 35 Misconception diversity score 1 n 35 *p < 0.05 **p < 0.01.
Teleology scores were significantly positively correlated with card sort scores (r = 0.4, P < 0.05) and negatively correlated with naïve idea diversity measures (r = −0.42, p < 0.05); teleology scores were only marginally related to KC diversity scores (r = 0.33, p > 0.05).
Specifically, composite card sort scores, representative of problem categorization patterns, were significantly associated with all problem solving measures: (1) positively associated with KC diversity scores (r = 0.45, P < 0.01); (2) negatively associated with naïve idea scores (r = −0.54, P < 0.01); and (3) positively associated with teleology test scores (r = 0.40, P < 0.05).
While not every movie can be Mr. Lovejoy, robots can now help producers find great films by sorting and scoring scripts based on actors, plot, and endings.
