Abstract
Today's ever-increasing amount of data places new demands on cognitive ergonomics and requires new design ideas to ensure successful human-data interaction. Our aim was to identify the cognitive factors that must be considered when designing systems to improve decision-making based on large amounts of data. We constructed a task that simulates the typical cognitive demands people encounter in data analysis situations. We demonstrate some essential cognitive limitations using a behavioural experiment with 20 participants. The studied task presented the participants with critical and noncritical attributes that contained information on two groups of people. They had to select the response option (group) with the higher level of critical attributes. The results showed that accuracy of judgement decreased as the amount of information increased, and that judgement was affected by irrelevant information. Our results thus demonstrate critical cognitive limitations when people utilise data and suggest a cognitive bias in data-based decision-making. Therefore, when designing for cognition, we should consider the human cognitive limitations that are manifested in a data analysis context. Furthermore, we need general cognitive ergonomic guidelines for design that support the utilisation of data and improve data-based decision-making.
| Original language | English |
|---|---|
| Journal | Behaviour & Information Technology |
| Volume | 38 |
| Issue number | 10 |
| Pages (from-to) | 1038-1047 |
| Number of pages | 10 |
| ISSN | 0144-929X |
| DOIs | |
| Publication status | Published - 3 Oct 2019 |
| MoE publication type | A1 Journal article-refereed |
Fields of Science
- 113 Computer and information sciences
- Human-data interaction
- cognition
- decision-making
- cognitive ergonomics
- INFORMATION
- DECISIONS
- MEMORY
- ORDER
Cite this
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Cognitive ergonomics for data analysis. Experimental study of cognitive limitations in a data-based judgement task. / Kalakoski, Virpi; Henelius, Andreas; Oikarinen, Emilia; Ukkonen, Antti; Puolamäki, Kai.
In: Behaviour & Information Technology, Vol. 38, No. 10, 03.10.2019, p. 1038-1047.Research output: Contribution to journal › Article › Scientific › peer-review
TY - JOUR
T1 - Cognitive ergonomics for data analysis. Experimental study of cognitive limitations in a data-based judgement task
AU - Kalakoski, Virpi
AU - Henelius, Andreas
AU - Oikarinen, Emilia
AU - Ukkonen, Antti
AU - Puolamäki, Kai
PY - 2019/10/3
Y1 - 2019/10/3
N2 - Today's ever-increasing amount of data places new demands on cognitive ergonomics and requires new design ideas to ensure successful human-data interaction. Our aim was to identify the cognitive factors that must be considered when designing systems to improve decision-making based on large amounts of data. We constructed a task that simulates the typical cognitive demands people encounter in data analysis situations. We demonstrate some essential cognitive limitations using a behavioural experiment with 20 participants. The studied task presented the participants with critical and noncritical attributes that contained information on two groups of people. They had to select the response option (group) with the higher level of critical attributes. The results showed that accuracy of judgement decreased as the amount of information increased, and that judgement was affected by irrelevant information. Our results thus demonstrate critical cognitive limitations when people utilise data and suggest a cognitive bias in data-based decision-making. Therefore, when designing for cognition, we should consider the human cognitive limitations that are manifested in a data analysis context. Furthermore, we need general cognitive ergonomic guidelines for design that support the utilisation of data and improve data-based decision-making.
AB - Today's ever-increasing amount of data places new demands on cognitive ergonomics and requires new design ideas to ensure successful human-data interaction. Our aim was to identify the cognitive factors that must be considered when designing systems to improve decision-making based on large amounts of data. We constructed a task that simulates the typical cognitive demands people encounter in data analysis situations. We demonstrate some essential cognitive limitations using a behavioural experiment with 20 participants. The studied task presented the participants with critical and noncritical attributes that contained information on two groups of people. They had to select the response option (group) with the higher level of critical attributes. The results showed that accuracy of judgement decreased as the amount of information increased, and that judgement was affected by irrelevant information. Our results thus demonstrate critical cognitive limitations when people utilise data and suggest a cognitive bias in data-based decision-making. Therefore, when designing for cognition, we should consider the human cognitive limitations that are manifested in a data analysis context. Furthermore, we need general cognitive ergonomic guidelines for design that support the utilisation of data and improve data-based decision-making.
KW - 113 Computer and information sciences
KW - Human-data interaction
KW - cognition
KW - decision-making
KW - cognitive ergonomics
KW - INFORMATION
KW - DECISIONS
KW - MEMORY
KW - ORDER
U2 - 10.1080/0144929X.2019.1657181
DO - 10.1080/0144929X.2019.1657181
M3 - Article
VL - 38
SP - 1038
EP - 1047
JO - Behaviour & Information Technology
JF - Behaviour & Information Technology
SN - 0144-929X
IS - 10
ER -