38978 research outputs found
Sort by
(Tracked) From Thought to Senses: Assessing the Relationship Between the Generation Effect and Multisensory Facilitation
No full textThe current study investigated whether the generation effect, a memory advantage for self-generated verbal information, is enhanced in multisensory conditions. Such a finding would be consistent with the multisensory facilitation effect, a phenomenon wherein multiple sensory inputs may reduce the cognitive load required to process and respond to co-occurring stimuli from multiple senses. Although extensive research has explored the generation effect, the multisensory aspect of this task has been overlooked. In the current study, we aimed to determine if the generation effect is modulated by the multisensory facilitation effect. Multisensory facilitation involves the brain’s ability to efficiently process information from diverse sensory sources simultaneously, enhancing cognitive performance. We employed a 2 (Task Type: generate, read) X 3 (Sensory Modality: auditory, visual, multisensory) factorial design, utilizing word pair lists and a cued recall test. A generation effect emerged for the auditory and audiovisual condition, but not for the visual condition. The hypothesis that the magnitude of the generation effect would be greater for the multisensory encoding condition was not supported. Overall, the hypothesis that generation effect will be enhanced for multisensory learning was not supported. The current study addresses a gap in existing literature by examining the multisensory component of generation tasks and extends the current understanding of multisensory learning by incorporating verbal stimuli as the visual component
Care Robots in moral dilemmas
No full textThe study focuses on the acceptance of artificial moral agents in care settings. More specifically, we examine how moral decisions made by robots are evaluated. Participants will read four care dilemma scenarios, each presenting a robot with two options. For each scenario, participants will rate: (1) the moral appropriateness of the robot's decision, (2) how much blame the robot deserves for its decision and (3) how much they trust the robot.
Furthermore, we will investigate several variables that might affect how the robot's decisions are judged. These variables include characteristics of the robot and characteristics of the participants. Among the former are the following: 'gender' of the robot (based on its physical appearance) as well as ascribed warmth, morality/sociability, competence and gender. Participants will be randomly assigned to one of two conditions: 'female' vs. 'male' robot. They will be shown a brief AI-generated video of either the 'female' or 'male' robot. Both robots are identical with regard to key features (e.g., size, color scheme, similarity to humans, mobility etc.) and perform the same action in the video. Only a few modifications were made to the body shape (e.g., waist-to-hip ratio, chest area) to make the robot appear more 'feminine' or 'masculine.' Ascribed characteristics (warmth, competence etc.) are assessed using standardized questionnaires. Person variables include attitudes towards robots and technology, personality traits (Need for cognition, Dark Factor of personality), political orientation, religiosity, age, and gender
