Martin V Butz
Biographic Data
| ID | 6630800 |
|---|---|
| NAME | Martin V Butz |
| GIVEN NAMES | Martin V |
| FAMILY NAME | Butz |
| SIGNATURE | BUTZ M V |
| AFFILIATIONS | University of Tübingen |
| ORCID | 0000-0002-8120-8537 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2004 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Modal and amodal cognition
Accounting for how the human mind represents the internal and external world is a crucial feature of many theories of human cognition. Central to this question is the distinction between modal as opposed to amodal representational formats. It has often been assumed that one but not both of these two types of representations underlie processing in specific domains of cognition (e.g., perception, mental imagery, and language). However, in this pape…
Active Iterative Social Inference in Multi-Trial Signaling Games
Human behavioral choices can reveal intrinsic and extrinsic decision-influencing factors. We investigate the inference of choice priors in situations of referential ambiguity. In particular, we use the scenario of signaling games and investigate to which extent study participants profit from actively engaging in the task. Previous work has revealed that speakers are able to infer listeners’ choice priors upon observing ambiguity resolution. Howev…
A cognitive definition of computational thinking in primary education
Learning about others
Bayesian accounts of social cognition successfully model the human ability to infer goals and intentions of others on the basis of their behavior. In this paper, we extend this paradigm to the analysis of ambiguity resolution during brief communicative exchanges. In a reference game experimental setup, we observed that participants were able to infer listeners' preferences when analyzing their choice of object given referential ambiguity. Moreove…
Towards motivation-based adaptation of difficulty in e-learning programs
The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of motivational states. This data was then utilised to extract rules for an adequate motivation-based adaptati…
Anticipation for learning, cognition and education
Predictions, desires, or intentions have recently shown to strongly influence behavior, adaptation, and learning. These anticipations influence behavior mediating decision making and action execution as well as attention. Although it is not the future itself that influences the present but the anticipated future states or future properties, the difference to purely stimulus‐driven behavior and learning is highly significant. Recent analyses inves…
Anticipation for learning, cognition and education
Predictions, desires, or intentions have recently shown to strongly influence behavior, adaptation, and learning. These anticipations influence behavior mediating decision making and action execution as well as attention. Although it is not the future itself that influences the present but the anticipated future states or future properties, the difference to purely stimulus‐driven behavior and learning is highly significant. Recent analyses inves…
Anticipation for learning, cognition and education
Predictions, desires, or intentions have recently shown to strongly influence behavior, adaptation, and learning. These anticipations influence behavior mediating decision making and action execution as well as attention. Although it is not the future itself that influences the present but the anticipated future states or future properties, the difference to purely stimulus‐driven behavior and learning is highly significant. Recent analyses inves…
Towards motivation-based adaptation of difficulty in e-learning programs
The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of motivational states. This data was then utilised to extract rules for an adequate motivation-based adaptati…
A cognitive definition of computational thinking in primary education
Learning about others
Bayesian accounts of social cognition successfully model the human ability to infer goals and intentions of others on the basis of their behavior. In this paper, we extend this paradigm to the analysis of ambiguity resolution during brief communicative exchanges. In a reference game experimental setup, we observed that participants were able to infer listeners' preferences when analyzing their choice of object given referential ambiguity. Moreove…
Active Iterative Social Inference in Multi-Trial Signaling Games
Human behavioral choices can reveal intrinsic and extrinsic decision-influencing factors. We investigate the inference of choice priors in situations of referential ambiguity. In particular, we use the scenario of signaling games and investigate to which extent study participants profit from actively engaging in the task. Previous work has revealed that speakers are able to infer listeners’ choice priors upon observing ambiguity resolution. Howev…
Modal and amodal cognition
Accounting for how the human mind represents the internal and external world is a crucial feature of many theories of human cognition. Central to this question is the distinction between modal as opposed to amodal representational formats. It has often been assumed that one but not both of these two types of representations underlie processing in specific domains of cognition (e.g., perception, mental imagery, and language). However, in this pape…
Computer Science (5 works) · Psychology (5 works) · Artificial Intelligence (4 works) · Cognitive psychology (4 works) · Child and Animal Learning Development (3 works) · Cognition (3 works) · Cognitive science (2 works) · Machine learning (2 works) · Neuroscience (2 works) · Ambiguity (1 works)