TY - GEN
T1 - Methodology for knowledge elicitation in visual abductive reasoning tasks
AU - Haass, Michael J.
AU - Matzen, Laura E.
AU - Stevens-Adams, Susan M.
AU - Roach, Allen R.
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - The potential for bias to affect the results of knowledge elicitation studies is well recognized. Researchers and knowledge engineers attempt to control for bias through careful selection of elicitation and analysis methods. Recently, the development of a wide range of physiological sensors, coupled with fast, portable and inexpensive computing platforms, has added an additional dimension of objective measurement that can reduce bias effects. In the case of an abductive reasoning task, bias can be introduced through design of the stimuli, cues from researchers, or omissions by the experts. We describe a knowledge elicitation methodology robust to various sources of bias, incorporating objective and cross-referenced measurements. The methodology was applied in a study of engineers who use multivariate time series data to diagnose mance of devices throughout the production lifecycle. For visual reasoning tasks, eye tracking is particularly effective at controlling for biases of omission by providing a record of the subject’s attention allocation.
AB - The potential for bias to affect the results of knowledge elicitation studies is well recognized. Researchers and knowledge engineers attempt to control for bias through careful selection of elicitation and analysis methods. Recently, the development of a wide range of physiological sensors, coupled with fast, portable and inexpensive computing platforms, has added an additional dimension of objective measurement that can reduce bias effects. In the case of an abductive reasoning task, bias can be introduced through design of the stimuli, cues from researchers, or omissions by the experts. We describe a knowledge elicitation methodology robust to various sources of bias, incorporating objective and cross-referenced measurements. The methodology was applied in a study of engineers who use multivariate time series data to diagnose mance of devices throughout the production lifecycle. For visual reasoning tasks, eye tracking is particularly effective at controlling for biases of omission by providing a record of the subject’s attention allocation.
KW - Abductive reasoning
KW - Eye tracking
KW - Knowledge elicitation
UR - https://www.scopus.com/pages/publications/84947258088
U2 - 10.1007/978-3-319-20816-9_38
DO - 10.1007/978-3-319-20816-9_38
M3 - Conference contribution
AN - SCOPUS:84947258088
SN - 9783319208152
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 401
EP - 409
BT - Foundations of Augmented Cognition - 9th International Conference, AC 2015 Held as Part of HCI International 2015, Proceedings
A2 - Fidopiastis, Cali M.
A2 - Schmorrow, Dylan D.
PB - Springer Verlag
T2 - 9th International Conference on Augmented Cognition, AC 2015 Held as Part of 17th International Conference on Human Computer Interaction, HCI International 2015
Y2 - 2 August 2015 through 7 August 2015
ER -