What is educational theory and how to make it?

An analysis is provided detailing the conditions for the appropriate theoretical study of the object of educational science: pedagogy.     

Do medical decision analyses' largest gains grow from the smallest trees?

Some decision analysts recommend reserving their models for careful, complete study of complex problems. Others believe simple problem analyses provide the greatest gains. To clarify these issues, I tested: (1) whether simple published analyses compared to complex ones, produced results as non-intuitive; and (2) whether non-intuitiveness represented analytic gain (or equivalently, intuitive loss). Very limited data also examined (3) the gain from adding model intricacy for a given problem vs. selecting more complex problems for analysis. To assess two non-intuitiveness measures, 75 subjects (33 physicians and 42) non-physicians stated their intuitive preferences in 40 (22 published and 18 unpublished) medical dilemmas. For both physicians and non-physicians, simpler models (those with lees than 30 terminal branches in the decision tree) had about one third the non-intuitiveness of more complex ones. Three tests also supported the premise that analyses outperform intuition, therefore that on average the formers' non-intuitiveness reflects less analytic gain. In addition, for different models of the same problem, tree complexity did not correlate with gain. Thus, simpler trees may not generally gain less because they inadequately describe problems. Instead, simpler analyses may represent simpler problems, with more similar intuitive and formal solutions. If so, these findings may help us avoid some costly but unnecessary simple analyses.     

The place of human values in the language of science: Kuhn,Saussure, and structuralism

The current paradigm in medicine generally distinguishes between genetic and environmental causes of disease. Although the word paradigm has become a commonplace, the theories of Thomas Kuhn have not received much attention in the journals of medicine. Kuhn's structuralist method differs radically from the daily activities of the scientific method itself. Using linguistic theory, this essay offers a structuralist reading of Thomas Kuhn's The Structure of Scientific Revolutions. Our purpose is to highlight the similarities between these structuralist models of science and language. In part, we focus on the logic that enables Kuhn to assert the priority of perception over interpretation in the history of science. To illustrate some of these issues, we refer to the distinction between environmental and genetic causes of disease. While the activity of scientific research results in the revision of concepts in science, the production of significant differences that shape our knowledge is in part a social and linguistic process.     

Reducing residential electrical energy use: payments, information, and feedback

Monetary payments, energy information, and daily feedback on consumption were employed to reduce electricity use in four units of a university student housing complex. A combined multiple-baseline and withdrawal design permitted both within- and between-unit comparisons. Payments produced immediate and substantial reductions in consumption in all units, even when the magnitude of the payments was reduced considerably. Feedback also produced reductions, but information about ways to conserve and about the cost of using various appliances did not. It was also found that, in general, payments combined with either information or feedback produced no greater effect than payments alone.     

Clock control of human performance on avoidance and fixed-interval schedules

The avoidance and fixed-interval performances of human subjects were studied in two experiments. Addition of time-correlated stimuli (added clock) improved behavioral efficiency, since response rates decreased without decreases in reinforcement rates. Response-dependent display of the clock maintained a second, observing response and reductions in clock duration weakened such observing behavior. Generally, the reinforcing properties of the clock were more apparent with the avoidance than with the fixed-interval schedule, a finding attributed to temporal cues already provided by delivery of the fixed-interval reinforcers. Reduced rates of the main response when the clock was dependent on an observing response were more than offset by rates of the observing response in the majority of subjects. Thus, the results do not support an interpretation of the reinforcing properties of added clocks simply in terms of work reduction.     

Spread of Risk Information Through Microblogs: Twitter Users with More Mutual Connections Relay News That is More Dreadful1

In elucidating the spread of risk information through microblogging, it is important to understand the behaviors of numerous average users, in addition to the activities of authorities. We followed the transmission pathways of 10 actual widely spread tweets concerning several risk information topics, including natural disasters, nuclear disasters, and infectious diseases, and we identified the types of risk that affected retweeting by classifying each tweet based on Slovic's risk-perception model. Furthermore, we examined the types of users who did and did not retweet the information. Users with few connections in the form of followers (i.e., people who are following a user) or followees (people a user is following), or with a low ratio of mutual followers within their connections, had a tendency to retweet a large amount of risk information, regardless of the type of risk involved. On the other hand, users with a high ratio of mutual followers exhibited a greater tendency to retweet risk information when it was perceived as dreadful, though they did not retweet risk information much on the whole. These results suggest that there are two mechanisms by which risk information is spread within the Twitter network: information exchange and social sharing of personal reactions.     

A note on computing Louis’ observed information matrix identity for IRT and cognitive diagnostic models

Using Louis’ formula, it is possible to obtain the observed information matrix and the corresponding large-sample standard error estimates after the expectation–maximization (EM) algorithm has converged. However, Louis’ formula is commonly de-emphasized due to its relatively complex integration representation, particularly when studying latent variable models. This paper provides a holistic overview that demonstrates how Louis’ formula can be applied efficiently to item response theory (IRT) models and other popular latent variable models, such as cognitive diagnostic models (CDMs). After presenting the algebraic components required for Louis’ formula, two real data analyses, with accompanying numerical illustrations, are presented. Next, a Monte Carlo simulation is presented to compare the computational efficiency of Louis’ formula with previously existing methods. Results from these presentations suggest that Louis’ formula should be adopted as a standard method when computing the observed information matrix for IRT models and CDMs fitted with the EM algorithm due to its computational efficiency and flexibility.     

Toward a More Credible Understanding of Post-Traumatic Growth

Traditional research on post-traumatic growth has utilized methodologically flawed cross-sectional designs that involve retrospective assessments of post-traumatic growth. This has resulted in a majority of research in this field suffering from a lack of credibility and reliability. In this special issue, we present nine articles that seek to make innovative conceptual and methodological contributions with the goal of promoting better research practices on post-traumatic growth. In the introduction to this special issue, we provide an overview of these contributions, and discuss the implications of these articles both to improving future scholarship and to encouraging personality scientists to examine this important phenomenon in the years and decades to come.     

The effects of exposure to political and domestic violence on preschool children and their mothers

The purpose of this study was to examine the effects of exposure to political violence on preschool children and their mothers. We explored whether these dyads are different from dyads with no known history of exposure to violence and from mother–child dyads with known exposure to domestic violence. Specifically, we explored differences in mothers' psychological status (depression and anxiety), dyadic emotional availability (EA), children's social information processing, and children's social behaviour, in a sample of 216 dyads divided into three groups (exposure to political violence, no exposure to violence, and exposure to domestic violence). We found evidence to support our hypotheses that children exposed to domestic violence exhibit the highest levels of social maladjustment with smaller but still significant differences between children exposed to political violence and children in the comparison group. As expected, the lowest EA scores were found in the exposure to domestic violence group, followed by dyads in the exposure to political violence group. Dyads belonging to the comparison group (no exposure) exhibited the highest levels of EA. These findings contribute to our understanding of the meaning of exposure to political violence, as well as sharpen the difference between exposure to political and domestic violence.