Attitudes related to work of adolescents in the United Kingdom and Japan

This study was designed to provide data for notions that differences in achievement motivation in different nations may contribute to differences in national rates of economic growth. The nations investigated were the United Kingdom and Japan as representatives of low and high rates of economic growth in the decades after the end of World War II. Data were collected from college students for motivations and attitudes related to work. British students had higher achievement motivation, while Japanese students had higher competitiveness motivation and strong money beliefs. Differences in career preference between the nations were also presented. The relationship between motivations and attitudes to work with career preference were examined for each nation.     

Discerning Mouse Trajectory Features With the Drift Diffusion Model

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.     

Learning nonlinearly separable categories by inference and classification

Previous research suggests that learning categories by classifying new instances highlights information that is useful for discriminating between categories. In contrast, learning categories by making predictive inferences focuses learners on an abstract summary of each category (e.g., the prototype). To test this characterization of classification and inference learning further, the authors evaluated the two learning procedures with nonlinearly separable categories. In contrast to previous research involving cohesive, linearly separable categories, the authors found that it is more difficult to learn nonlinearly separable categories by making inferences about features than it is to learn them by classifying instances. This finding reflects that the prototype of a nonlinearly separable category does not provide a good summary of the category members. The results from this study suggest that having a cohesive category structure is more important for inference than it is for classification.     

Labeling bias and categorical induction: generative aspects of category information

When a person is characterized categorically with a label (e.g., Linda is a feminist), people tend to think that the attributes associated with that person are central and long lasting (S. Gelman & G. D. Heyman, 1999). This bias, which is related to category-based induction and stereotyping, has been thought to arise because a category label (e.g., feminist) activates the dominant properties associated with the representation of the category. This explanation implies that categorical information influences inferential processes mainly by conjuring up main attributes or instances represented in the category. However, the present experiments reveal that this attribute-based explanation of induction does not provide a complete picture of inferential processes. The results from 3 experiments suggest that category information can affect inferences of attributes that are not directly related to the category, suggesting that categories not only activate likely attributes but also help integrate unlikely or even unrelated attributes.     

Category labels versus feature labels: Category labels polarize inferential predictions

What makes category labels different from feature labels in predictive inference? This study suggests that category labels tend to make inductive reasoning polarized and homogeneous. In two experiments, participants were shown two schematic pictures of insects side by side and predicted the value of a hidden feature of one insect on the basis of the other insect. Arbitrary verbal labels were shown above the two pictures, and the meanings of the labels were manipulated in the instructions. In one condition, the labels represented the category membership of the insects, and in the other conditions, the same labels represented attributes of the insects. When the labels represented category membership, participants’ responses became substantially polarized and homogeneous, indicating that the mere reference to category membership can modify reasoning processes.     

The development of a Money Attitude Scale

On the basis of the clinical and theoretical literature, 62 items in the domains of security, retention, and power-prestige were generated. Factor analysis yielded five factors: power-prestige, retention-time, distrust, quality, and anxiety. A 29-item Money Attitude Scale (MAS) was developed on the basis of four of these factors. Reliability measures, as well as personality and psychopathological correlations, were determined and discussed.     

Task performance and metacognitive experiences in problem-solving

The effects of task performance on metacognitive experiences and relations between task performance and metacognitive experiences in problem-solving were examined with 69 Japanese undergraduate students. The task was a puzzle called the cross breaker, consisting of seven pieces, and several figures were constructed by using those seven pieces. Eight types of metacognitive experiences, before and after performing the task, were rated. Participants were classified into Success and Failure groups based on their task performance. Use of all but two metacognitive experiences differed between the groups. There were medium to high positive and negative correlations for metacognitive experiences with performance after the puzzle task, whereas metacognitive experiences before the task generally had no significant correlations with performance. Despite small N, participants' metacognitive experiences seemed to reflect their actual performance, suggesting that people obtain information from their performance and use it to revise their metacognitive experiences. Furthermore, metacognitive experiences may help people solve similar problems in the future.     

Achievement motives,cognitive and social competence,and achievement goals in the classroom

This study investigated the interrelations of approach and avoidance achievement motives (Motive to Achieve Success and Motive to Avoid Failure), two types of competence (Cognitive and Social competence), achievement goals (Mastery, Performance-approach, Performance-avoidance, and Work Avoidance goals), of 131 eighth and ninth grade students from a Japanese junior high school. Multiple regression analysis indicated positive relations between Mastery goals and the Motive to Achieve Success and Cognitive Competence. Performance-approach goals and both the Motive to Achieve Success and the Motive to Avoid Failure, and Performance-avoidance Goals and both the Motive to Achieve Success and the Motive to Avoid Failure. Negative relations were found between Work Avoidance goals and the Motive to Achieve Success and Cognitive Competence. Several interactions between achievement motives and competence on achievement goals were also found. The different antecedents of four achievement goals were discussed.     

Reading Emotion From Mouse Cursor Motions: Affective Computing Approach

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 (training data) 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.     

Learning from human tutoring

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.