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Changes for page 3. Evaluation Methods

Last modified by William OGrady on 2024/04/08 22:22
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edited by Rixt Hellinga
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edited by Jean-Paul Smit
on 2024/03/21 16:57
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11 11  2. **Relatedness. **Does the design positively affect the PwD's //affective //state? Do PwDs //like// the system?
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13 -3. **Competence. **Is the design //dependable//; is the design accessible enough for the PwD to rely on it? Does it feel natural?
13 +3. **Competence. **Is the design //dependable//; is the design accessible enough for the PwD to rely on it? Does it feel natural? Can the participant accurately retrieve information through the robot?
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15 +4. Recall.
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17 +5. Memory self-efficacy.
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16 16  For a sample size as small as 20 participants, it is most adequate to apply a within-subjects design (they require fewer participants) [1]. That means there is an approach where every PwD is experiencing all of the conditions examined. A within-subjects design might be prone to confounds such as pre-existing notions in the environment. That is why the attitude towards robots and the pre-study sense of affect and autonomy should be examined and evaluated as such. Another confounder variable to look into is the study location and environment.
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18 18  [[image:Socio-Cognitive Engineering - Frame 1.jpg]]
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23 23  == References ==
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25 25  [1] Bethel, C.L., Henkel, Z., Baugus, K. (2020). Conducting Studies in Human-Robot Interaction. In: Jost, C., //et al.// Human-Robot Interaction. Springer Series on Bio- and Neurosystems, vol 12. Springer, Cham. https:~/~/doi.org/10.1007/978-3-030-42307-0_4