The Phenomenology of Homesickness in Boys

Homesickness is the distress or impairment caused by an actual or anticipated separation from home. It is characterized by acute longing and preoccupying thoughts of home and attachment objects. This study extended previous research on the phenomenology of childhood homesickness by assessing a sample of 316 boys, ages 8–16, who were spending 2 weeks at a single-sex residential summer camp. Some 18% of the children reported moderate or high levels of homesickness; 7% reported concomitant severe depressive and anxious symptoms. Homesickness intensity was negatively correlated with separation experience and age. It was most commonly associated with depressive symptoms and internalizing behavior problems. For severely homesick boys, intensity increased over time, decreasing just prior to their return home. Preseparation assessment suggested that severely homesick boys had elevated levels of homesickness and negative emotions months before arriving at camp. One-year follow-up data suggested that the intensity of severe homesickness decreased with age and experience. However, severely homesick boys were less likely than other boys to return to camp. The results demonstrate how brief separations can affect children's well-being and attitudes about separations. Severe homesickness is distinct from separation anxiety disorder, but has elements of this and other psychopathologies. Theories of negative emotion, attachment, and coping complement emerging theories of homesickness.     

Knowledge level learning and the power law: A soar model of skill acquisition in scheduling

Zusammenfassung. Das hier vorgestellte Modell lernt graduell, Planungsaufgaben aus der Klasse der Maschinenbelegungsprobleme (job-shop-scheduling problems) zu lösen. Mit Hilfe des Chunking-Mechanismus von Soar wird episodisches Wissen über die Belegungsreihenfolge von Aufträgen auf Maschinen memoriert. Bei der Entwicklung des Modells wurden zahlreiche qualitative (z. B. Transfereffekte) und quantitative Befunde (z. B. Bearbeitungszeiten) aus einer früheren empirischen Untersuchung berücksichtigt. In einer Validierungsstudie wurden dieselben Aufgaben von 14 Probanden und dem Modell bearbeitet. Die Passung von Simulationsdaten und empirischen Ergebnissen fiel insgesamt gut aus. Allerdings löst das Modell die Aufgaben schneller und zeigt auch einen etwas besseren Lernverlauf als die Probanden. Das Modell liefert eine Erklärung für das Rauschen, das typischerweise bei Bearbeitungszeiten zu beobachten ist: es handelt sich um erworbenes Wissen, das mehr oder weniger gut und auch unterschiedlich häufig auf neue Situationen übertragen wird. Der Lernverlauf der Probanden entspricht nur für aggregierte Daten einer Potenzfunktion (power law). Der vorgestellte Mechanismus zeigt, wie ein symbolisches Modell der Informationsverarbeitung graduelle Verhaltensänderungen generiert und wie der offensichtliche Erwerb allgemeiner Prozeduren ohne explizites Lernen von deklarativen Regeln erfolgen kann. Es wird nahegelegt, daß es sich hier um die Modellierung einer Form impliziten Lernens handelt. Summary. The model presented here gradually learns how to perform a job-shop scheduling task. It uses Soar's chunking mechanism to acquire episodic memories about the order to schedule jobs. The model was based on many qualitative (e.g., transfer effects) and quantitative (e.g., solution time) regularities found in previously collected data. The model was tested with new data where scheduling tasks were given to the model and to 14 subjects. The model generally fit these data with the restrictions that the model performs the task (in simulated time) faster than the subjects, and its performance improves somewhat more quickly than the subjects' performance. The model provides an explanation of the noise typically found in problem solving times - it is the result of learning actual pieces of knowledge that transfer more or less to new situations but rarely by an average amount. Only when the data are averaged (i.e., over subjects) does the smooth power law appear. This mechanism demonstrates how symbolic models can exhibit a gradual change in behavior and how the apparent acquisition of general procedures can be performed without resorting to explicit declarative rule generation. We suggest that this may represent a type of implicit learning.     

The puzzle of language evolution

Linguistics must again concentrate on the evolutionary nature of language, so that language models are more realistic with respect to human natural languages and have a greater explanatory force. Multi-agent systems are proposed as a possible route to develop such evolutionary models and an example is given of a concrete experiment in the origins and evolution of word-meaning based on a multi-agent approach.     

Familiarity and pronounceability of nouns and names

Ratings of familiarity and pronounceability were obtained from a random sample of 199 surnames (selected from over 80,000 entries in the Purdue University phone book) and 199 nouns (from the Ku?era-Francis, 1967, word database). The distributions of ratings for nouns versus names are substantially different: Nouns were rated as more familiar and easier to pronounce than surnames. Frequency and familiarity were more closely related in the proper name pool than the word pool, although both correlations were modest. Ratings of familiarity and pronounceability were highly related for both groups. A production experiment showed that rated pronounceability was highly related to the time taken to produce a name. These data confirm the common belief that there are differences in the statistical and distributional properties of words as compared to proper names. The value of using frequency and the ratings of familiarity and pronounceability for predicting variations in actual pronunciations of words and names are discussed.     

Effects of Directed Thinking on Intentions to Engage in Beneficial Activities: Actions Versus Reasons1

An important application of psychological principles involves increasing intentions to engage in activities that, although admittedly beneficial, are often not initially appealing (e.g., studying, quitting smoking, dieting). The present study tests the utility of directed thinking as a tool for eliciting intentions to engage in such activities. Undergraduate students were directed to think either about the reasons why people should find studying enjoyable or about the actions that people might take to make studying enjoyable. Regardless of whether they thought as individuals or in cooperating dyads, students who thought about actions later reported greater intentions to spend time studying than did students who thought about reasons. The results have both theoretical and practical significance.     

THE EFFECT OF TOKEN REWARDS ON “INTRINSIC” MOTIVATION FOR DOING MATH

This study used a multielement baseline design to analyze the effects of token rewards delivered contingent upon completion of math problems by 2 middle-school boys. Time spent on math and number of work pages completed increased (with high accuracy) during reward conditions and were maintained during fading and withdrawal. At follow-up, time spent and work pages completed remained well above baseline for 1 boy and fell below for the other, while accuracy remained high and ratings of liking math were the highest possible for both boys. Overall, the results are inconsistent with warnings about use of token rewards to motivate children.     

Infants’ responses to objects representing levels of word knowledge and categorical information

The effects of differing levels of word knowledge on infants’ sequential touching behaviors were investigated in two studies. In both, parent report was used to assess three levels of word knowledge: known, frontier, and unknown. In the first study, 14-month-old infants sequentially touched objects consistent with parents’ reports of their word knowledge. In the second study, 20-month-old infants sequentially touched objects by both conceptual category and reported level of word knowledge. It appears that even infants, like adults, can make distinctions among objects on the basis of their knowledge about the objects’ labels.