Human one‐to‐one tutoring has been shown to be a very effective form of instruction. Three contrasting hypotheses, a tutor‐centered one, a student‐centered one, and an interactive one could all potentially explain the effectiveness of tutoring. To test these hypotheses, analyses focused not only on the effectiveness of the tutors' moves, but also on the effectiveness of the students' construction on learning, as well as their interaction. The interaction hypothesis is further tested in the second study by manipulating the kind of (...) tutoring tactics tutors were permitted to use. In order to promote a more interactive style of dialogue, rather than a didactic style, tutors were suppressed from giving explanations and feedback. Instead, tutors were encouraged to prompt the students. Surprisingly, students learned just as effectively even when tutors were suppressed from giving explanations and feedback. Their learning in the interactive style of tutoring is attributed to construction from deeper and a greater amount of scaffolding episodes, as well as their greater effort to take control of their own learning by reading more. What they learned from reading was limited, however, by their reading abilities. (shrink)

Affective computing research has advanced emotion recognition systems using facial expressions, voices, gaits, and physiological signals, yet these methods are often impractical. This study integrates mouse cursor motion analysis into affective computing and investigates the idea that movements of the computer cursor can provide information about emotion of the computer user. We extracted 16–26 trajectory features during a choice-reaching task and examined the link between emotion and cursor motions. Participants were induced for positive or negative emotions by music, film clips, (...) or emotional pictures, and they indicated their emotions with questionnaires. Our 10-fold cross-validation analysis shows that statistical models formed from “known” participants could predict nearly 10%–20% of the variance of positive affect and attentiveness ratings of “unknown” participants, suggesting that cursor movement patterns such as the area under curve and direction change help infer emotions of computer users. (shrink)

Nonlinguistic signals in the voice and musical instruments play a critical role in communicating emotion. Although previous research suggests a common mechanism for emotion processing in music and speech, the precise relationship between the two domains is unclear due to the paucity of direct evidence. By applying the adaptation paradigm developed by Bestelmeyer, Rouger, DeBruine, and Belin [2010. Auditory adaptation in vocal affect perception. Cognition, 117, 217–223. doi:10.1016/j.cognition.2010.08.008], this study shows cross-domain aftereffects from vocal to musical sounds. Participants heard an (...) angry or fearful sound four times, followed by a test sound and judged whether the test sound was angry or fearful. Results show cross-domain aftereffects in one direction – vocal utterances to musical sounds, not vice-versa. This effect occurred primarily for angry vocal sounds. It is argued that there is a unidirectional relationship between vocal and musical sounds where emotion processing of vocal sounds encompasses musical sounds but not vice-versa. (shrink)

Mouse tracking, a new action‐based measure of behavior, has advanced theories of decision making with the notion that cognitive and social decision making is fundamentally dynamic. Implicit in this theory is that people's decision strategies, such as discounting delayed rewards, are stable over task design and that mouse trajectory features correspond to specific segments of decision making. By applying the hierarchical drift diffusion model and the Bayesian delay discounting model, we tested these assumptions. Specifically, we investigated the extent to which (...) the “mouse‐tracking” design of decision‐making tasks (delay discounting task, DDT and stop‐signal task, SST) deviate from the standard “keypress” design of decision making tasks. We found remarkable agreement in delay discounting rates (intertemporal impatience) obtained in the keypress and mouse‐tracking versions of DDT (ρ = 0.90) even though these tasks were given about 1 week apart. Rates of evidence accumulation converged well in the two versions (DDT, ρ =.86; SST, ρ =.55). Omission/commission error in SST showed high agreement (ρ =.42, ρ =.53). Mouse‐motion features such as maximum velocity and AUC (area under the curve) correlated well with nondecision time (ρ = −.42) and boundary separation (ρ =.44)—the amount of information needed to accumulate prior to making a response. These results indicate that the response time (RT) and motion‐based decision tasks converge well at a fundamental level, and that mouse‐tracking features such as AUC and maximum velocity do indicate the degree of decision conflict and impulsivity. (shrink)

Multidimensional space representations like those posited in Edelman's target article are not sufficient to capture all similarity phenomena. We discuss phenomena that are compatible with models of similarity that assume structured relational representations. An adequate model of similarity and perception will require multiple approaches to representation.

Judging similarities among objects, events, and experiences is one of the most basic cognitive abilities, allowing us to make predictions and generalizations. The main assumption in similarity judgment is that people selectively attend to salient features of stimuli and judge their similarities on the basis of the common and distinct features of the stimuli. However, it is unclear how people select features from stimuli and how they weigh features. Here, we present a computational method that helps address these questions. Our (...) procedure combines image-processing techniques with a machine-learning algorithm and assesses feature weights that can account for both similarity and categorization judgment data. Our analysis suggests that a small number of local features are particularly important to explain our behavioral data. (shrink)

The self-organizing consciousness (SOC) is not sufficient to account for young children's ability to acquire complex rules and word-object mappings. First, the attention-association cycles suggested by the SOC are unlikely to happen because recurrence of particular stimulus properties usually disengages the attention of an observer. Second, “primitive processors” preinstalled in the system make the SOC unnecessarily complex.