When we compared the participants' performance while working with a human-aware robot to their performance working with a robot using standard motion planning, significant differences were found for all quantitative team fluency metrics.
We then described a human subject experiment aimed at studying human response to this motion-planning technique and quantifying its potential benefits through quantitative team fluency metrics and subjective evaluation of satisfaction, safety, and comfort.
Quantitative measures of writing fluency, grammatical complexity, and lexical complexity are statistically compared among five pre-task planning conditions.
This was done to explicate the two writers' reading-into-writing processes in relation to graphic time-based analysis of the overall text production patterns, quantitative measures of writing fluency and pauses, and reading-into-writing sub-processes (i.e. task representation, transforming ideas from sources and revisions).
The significant differences in favor of human-aware motion planning observed in all quantitative metrics of team fluency indicate that this type of motion planning leads to more effective human robot teamwork (Hypothesis 1).
The dependent measures we considered when evaluating human response to human-aware motion planning and the possible derived benefits were split into two main groups: quantitative metrics of team fluency and subjective evaluation by the participants.
These future biologists and physicians need to develop fluency in the quantitative tools and language used in interdisciplinary science (Gross, 2000; Association of American Medical Colleges [AACU] and Howard Hughes Medical Institute, 2009; NRC, 2009; Labov et al., 2010).
Although only a small percentage of students who initially enroll in our life science and mathematics courses will become researchers or physicians, it is essential that these students develop fluency in the quantitative tools used in science (Gross, 2000; Association of American Medical Colleges and Howard Hughes Medical Institute, 2009; National Research Council, 2009; Labov et al., 2010).
This is in line with recent research demonstrating that the qualitative measure of ideational originality draws strongly upon intelligence, whereas ideational fluency, as a purely quantitative indicator, rather depends upon executive functioning (Benedek et al., 2012; Gilhooly et al., 2007; Nusbaum & Silvia, 2011b).
The second study examined 11 to 16 year olds in five domains: quantitative, causal, social reasoning, drawing, and ideational fluency.
