Perceptions of physical and psychological aggression in close relationships: A review

This review of the literature examines the effect of contextual variables (i.e., characteristics of the perpetrator and victims, observer characteristics) on perceptions of physical and psychological aggression in close relationships. Observers view physical aggression as more serious, harmful, abusive, and more deserving of punishment than psychological aggression, male aggression as more serious than female aggression, and aggression in committed, exclusive relationships as more serious than aggression in casual ones. Victims of psychological aggression, however, perceive it as more harmful than physical aggression and consider the effects to be longer-lasting. The disparity between observer and victim perceptions of physical and psychological aggression extends to mental health professionals, who tend to judge the severity of aggressive behaviors based on frequency and duration of the actions instead of perpetrator intent. This difference of opinion may influence the reporting of and intervention in physically or psychologically aggressive situations, and how these types of aggression are treated by legal professionals, especially if those legal professionals are informed about aggressive romantic relationships by third-party observers whose opinions of the situation differ from those of the victims.     

Disguised Ideologies in Counseling and Social Justice Work

A social justice orientation for counseling is appealing to many but appears to some to violate counselor neutrality and respect for client freedom and rights. Confusion about neutrality and advocacy in the counseling field seems to reflect confused assumptions and values in the wider culture. As a result, counseling is guided more by a disguised ideology of liberal individualism than an objective theory or value‐neutral principles. The authors suggest that a hermeneutic, dialogical framework for counseling has the potential to resolve much of this confusion and to refine and broaden a social justice approach in needed ways.     

Virtual navigation performance: the relationship to field of view and prior video gaming experience

Two experiments examined whether learning a virtual environment was influenced by field of view and how it related to prior video gaming experience. In the first experiment, participants (42 men, 39 women; M age = 19.5 yr., SD = 1.8) performed worse on a spatial orientation task displayed with a narrow field of view in comparison to medium and wide field-of-view displays. Counter to initial hypotheses, wide field-of-view displays did not improve performance over medium displays, and this was replicated in a second experiment (30 men, 30 women; M age = 20.4 yr., SD = 1.9) presenting a more complex learning environment. Self-reported video gaming experience correlated with several spatial tasks: virtual environment pointing and tests of Judgment of Line Angle and Position, mental rotation, and Useful Field of View (with correlations between .31 and .45). When prior video gaming experience was included as a covariate, sex differences in spatial tasks disappeared.     

Managing Religion and the Judicialization of Religious Freedom

Religious freedom is a highly valued goal for many citizens and political leaders around the world, especially in Western‐oriented nations. Much ink has been spilled in defense of religious freedom and many have waxed eloquent about the virtues of promoting religious freedom. Most constitutions and other international documents around the world guarantee religious freedom even if those guarantees are sometimes honored in the breach. Why this focus on religious freedom is occurring and how it is being addressed are the focus of this article.     

Conceptions of learning and approaches to studying among White and ethnic minority students in distance education

Background. The attainment of White students at UK institutions of higher education tends to be higher than that of students from other ethnic groups, but the causes of this are unclear. Aims. This study compared White students and students from other ethnic groups in their conceptions of learning, their approaches to studying, and their academic attainment. Sample. A stratified sample of 1,146 White students and 1,146 students from other ethnic groups taking courses by distance learning with the UK Open University. Methods. The Mental Models section of the Inventory of Learning Styles and the Revised Approaches to Studying Inventory were administered in a postal survey. Results. The students' questionnaire scores were contaminated by response bias, which varied across different ethnic groups. When adjusted to control for response bias, the scores on the two questionnaires shared 37.2% of their variance and made a significant contribution to predicting the students' attainment. White students were more likely to exhibit a meaning‐directed learning pattern, whereas Asian and Black students were more likely to exhibit a reproduction‐directed learning pattern. However, the variation in attainment across different ethnic groups remained significant when their questionnaire scores and prior qualifications were taken into account. Conclusions. There is a strong relationship between students' conceptions of learning and their approaches to studying, and variations in conceptions of learning in different ethnic groups give rise to variations in approaches to studying. However, factors other than prior qualifications and conceptions of learning are responsible for variation in attainment across different ethnic groups.     

Estimation and visualization of confusability matrices from adaptive measurement data

We present a simple but effective method based on Luce’s choice axiom [Luce, R.D. (1959). Individual choice behavior: A theoretical analysis. New York: John Wiley & Sons] for consistent estimation of the pairwise confusabilities of items in a multiple-choice recognition task with arbitrarily chosen choice-sets. The method combines the exact (non-asymptotic) Bayesian way of assessing uncertainty with the unbiasedness emphasized in the classical frequentist approach.We apply the method to data collected using an adaptive computer game designed for prevention of reading disability. A player’s estimated confusability of phonemes (or more accurately, phoneme-grapheme connections) and larger units of language is visualized in an easily understood way with color cues and explicit indication of the accuracy of the estimates. Visualization of learning-related changes in the player’s performance is considered.The empirical validity of the choice axiom is evaluated using the game data itself. The axiom appears to hold reasonably well although a small systematic violation is observable for the smallest choice-set sizes.     

A Bayesian-optimal principle for learner-friendly adaptation in learning games

Adaptive learning games should provide opportunities for the student to learn as well as motivate playing until goals have been reached. In this paper, we give a mathematically rigorous treatment of the problem in the framework of Bayesian decision theory. To quantify the opportunities for learning, we assume that the learning tasks that yield the most information about the current skills of the student, while being desirable for measurement in their own right, would also be among those that are efficient for learning. Indeed, optimization of the expected information gain appears to naturally avoid tasks that are exceedingly demanding or exceedingly easy as their results are predictable and thus uninformative. Still, tasks that are efficient for learning may be experienced as too challenging, and the resulting failures can lower motivation. Therefore, in addition to quantifying the expected informational benefit for learning of any prospective task to be presented next, we also model the expected motivational cost of its presentation, measured simply as the estimated probability of failure in our example model. We propose a “learner-friendly” adaptation algorithm that chooses the learning tasks by optimizing the expected benefit divided by the expected cost. We apply this algorithm to a Rasch-like student model implemented within a real-world application and present initial results of a pilot experiment.