The relationship between perceived religious discrimination and self‐esteem for Muslim Australians

Muslim Australians represent one of the fastest growing migrant groups in Australia. They are also the group who, after Indigenous Australians, experience the most discrimination. Previous research on the minority stress model confirms a link between such discrimination and mental health. However, in relation to self‐esteem and discrimination, the results are mixed, potentially reflecting whether people reject or identify with prejudiced views of them and also the type of discrimination being measured. To explore this issue further in an Australian context, we asked 49 Australian Muslims to complete Rosenberg's Self‐esteem Scale and the Perceived Religious Discrimination Scale. In support of both the minority stress model and the rejection‐identification model, we found that perceived interpersonal and systemic discrimination accounts for a small but significant variation in self‐esteem. Interpersonal discrimination was negatively related to self‐esteem, and systemic discrimination positively related. The effects of interpersonal discrimination on self‐esteem can guide therapists to interventions that help clients resist internalising discrimination experiences. The effects of institutional discrimination support therapists becoming part of the resistance to and challenging of discrimination and inequality.     

Debiasing of Pessimistic Judgments Associated with Anxiety: A Test of the Availability Heuristic

This investigation directly tested the Consider-An-Alternative debiasing procedure and the reduction of pessimistic threat-related judgments associated with anxiety. Two separate generation interventions were included to test the availability heuristic as a possible explanation of the debiasing effect. Participants were randomly assigned to one of three interventions and probability estimates of future threat-related events were completed in a repeated measures experimental design. Level of trait anxiety was measured to assign participants to “normal” and highly anxious groups. The data were analyzed in a 3 × 2 × 2 mixed factorial repeated measures ANOVA. The results found that only the short debiasing intervention showed a significant reduction of pessimistic judgments in comparison to the control group. The results were interpreted as supporting the availability heuristic as an explanation of the debiasing effect. Further analysis also suggested that the content of recall may be as important to the debiasing effect as ease of recall.     

Age-related impairments of new memories reflect failures of learning,not retention

Learning impairments and the instability of memory are defining characteristics of cognitive aging. However, it is unclear if deficits in the expression of new memories reflect an accelerated decay of the target memory or a consequence of inefficient learning. Here, aged mice (19–21-mo old) exhibited acquisition deficits (relative to 3–5-mo old mice) on three learning tasks, although these deficits were overcome with additional training. When tested after a 30-d retention interval, the performance of aged animals was impaired if initial learning had been incomplete. However, if trained to equivalent levels of competence, aged animals exhibited no retention deficits relative to their young counterparts. These results suggest that age-related “memory” impairments can be overcome through a more effective learning regimen.Aging is associated with broad deficits in the acquisition of new knowledge (Matzel et al. 2008; see, for review, Gallagher and Rapp 1997; Rosenzweig and Barnes 2003), as well as impairments in the retrieval of both old and newly acquired information. While it is clear that old memories (i.e., ones obtained prior to age-related cognitive declines) do in fact become less stable with age (Gallagher 1997), it is less clear whether newly attained memories are inherently less stable in aged animals, or whether age-related memory deficits reflect a secondary consequence of inefficient learning.The majority of published data regarding cognitive aging describes impairments of animals'' learning abilities (Gage and Dunnett 1984; Markowska et al. 1994; Meliska et al. 1997; Nalbantoglu et al. 1997; Vogel et al. 2002; Matzel et al. 2008), although a smaller percentage of these studies also report animals'' performances after long retention intervals. Of those studies that report retention deficits, in most of those studies the initial learning upon which the long-term memory was based was impaired relative to young animals (e.g., Barnes and McNaughton 1985; Kinney et al. 2001a,b; Gould and Feiro 2005). Interestingly, in those few studies in which initial learning was equated across young and old animals, including studies of spatial water maze performance and appetitive instrumental responding, no retention deficits were observed, even after retention intervals as long as 21 d (Soffie and Lejeune 1991; Martinez-Serrano et al. 1996; Port et al. 1996).Although suggestive, the above experiments were not systematically designed to assess the stability of memory in aged animals as a function of the level of initial learning. In the present study, young (3–5 mo) and old (19–21 mo) male Balb/C mice were trained in three learning tasks (a spatial water maze, an egocentric Lashley III maze, and a three-choice odor discrimination). When trained to pre-asymptotic levels, aged animals exhibited both learning and retention deficits (assessed 30 d after initial training). However, when aged animals were trained to levels of competence comparable to their young counterparts, both young and old animals exhibited statistically indistinguishable levels of retention.Sixty Balb/C mice arrived in our laboratory at 2.5 mo (n = 30) or 18.5 mo (n = 30) of age. Each age category was divided into two groups of 15, one of which would receive subasymptotic training on each of the three learning tasks, and one of which would receive extended training on those tasks. Two aged mice became ill during the course of testing and were excluded from all analyses. Young mice ranged from 19.8 to 29.1 g, and aged mice from 26.2 to 37.3 g. Maintenance, food deprivation, and training conditions were as previously described (Matzel et al. 2006, 2003). Behavioral testing of young and aged mice was concluded at ∼5 and 21 mo of age, respectively.All animals were tested in three independent learning tasks. Briefly, the spatial water maze encourages mice to integrate spatial information to efficiently escape from a pool of water. In odor discrimination, animals must use a target odor (from a group of three odors) to guide their search for food. In the Lashley III maze, animals learn an egocentric sequence of turns to obtain a food reinforcer. Training on each task required 2–10 d (depending on the task and the level of training), and animals received four days of rest between tasks. A retention test was administered 30 d after the last training trial of each task.A Lashley III maze was constructed from black Plexiglas. A 3-cm-diameter white disk was located in the center of the goal box, and a 45 mg Bio-Serv food pellet (dustless rodent grain) was placed at the center of the disk and served as the reinforcer. Food-deprived animals received a day of acclimation to the maze, followed by either one or two days of training (four trials/day). On the day prior to the acclimation, animals received three Bio-Serv pellets in their home cage (thus mitigating any neophobia to the food on subsequent exposures). On the acclimation day, each mouse was confined in each of the first three alleys of the maze for 4 min, and in the final alley (containing the goal box) for 6 min. On this acclimation day, three Bio-Serv pellets were placed in the goal box. On the subsequent training day(s), each animal was placed in the start box and allowed to freely navigate the maze, during which time the number of errors to reach the goal box were recorded. (An error was constituted by a turn in the wrong direction or a retracing of a previously completed path.) Upon consuming the food pellet, the animal was returned to its home cage for a 25-min intertrial interval (ITI). All animals completed four trials during the first training day. Half of those animals then received an additional four training trials on the following day. Twenty-nine days after the last training trial, all animals received three Bio-Serv pellets in their home cages, and on the subsequent day were again tested in the maze.For the water maze, a round pool (140 cm diameter, 56 cm deep) was filled to within 20 cm of the top with water that was clouded with a water soluble black paint. A hidden 14-cm-diameter black platform was located in a fixed position 1 cm below the surface of the water. The pool was enclosed by a ceiling high black curtain on which five different light patterns (which served as spatial cues) were fixed at various positions. These light cues provided the only illumination of the maze, which was 60 Lux at the water''s surface.On the day prior to training, each animal was confined for 360 sec to the platform by a clear Plexiglas cylinder that fits around the platform. For either one or two training days (six trials Day 1, five trials Day 2), the animals were started from one of three positions, such that no consecutive trials started from the same position. After locating the platform or swimming for 90 sec, the animals were left or placed on the platform for 10 sec, after which they were placed in a holding box (for 12 min) before the start of the next trial. After the sixth or 11th training trial, animals were returned to their home cages for 3 h, and were then administered a 30-sec “probe” test in which the escape platform was removed from the maze and the time spent searching in the target quadrant was recorded. One hour later each animal received an additional training trial (intended to re-establish the search strategy employed by the animal prior to the probe test). Animals were then returned to their home cages, where a 30-d retention interval began.In odor discrimination, mice navigate through a field using unique odors to guide them. The animals learn to choose the food cup that contains the target smell when given three choices. The food cup locations are rearranged on each trial, but the accessible food is always marked by the same target odor (in this case mint). The chamber consisted of a black Plexiglas 60-cm-square field with 30-cm-high walls, which was located in a dimly lit room with high ventilation. A food cup was located in three corners. The target cup had accessible food (30 mg of chocolate puffed rice), while the remaining cups contained food that could not be accessed. A cotton tipped swab (2-cm long) was loaded with 25 μL of lemon-, mint- (the target odor), or almond-flavored extract and extended vertically from the back corner of each cup.Each animal had one day of acclimation and one day of training (consisting of four training trials). (In this task, both young and old animals reached asymptotic levels of performance [near errorless] within four training trials.) On Day 1 (adaptation), each mouse was placed in the box for 20 min with no food cups present. On the subsequent training day, a food cup was placed in three corners of the field, but only the cup associated with the mint odor contained accessible food. Each animal received four trials in which they were placed in the corner of the training chamber that did not contain a food cup. A trial continued until the animal obtained the food from the target location, at which time the animal was returned to its home cage to begin a 20 min ITI. At the end of each trial the food cups were rearranged, but mint always remained as the target odor. For each trial, the number of errors (contact with or sniffing within 2 cm of an incorrect food cup) was recorded. After the fourth training trial, the animal was returned to its home cage for a 30-d retention interval. On the 29th retention day, all animals received three pieces of chocolate flavored rice in their home cages, and on the subsequent day were again tested as in original training.     

iSTART 2: Improvements for efficiency and effectiveness

iSTART (interactive strategy training for active reading and thinking) is a Web-based reading strategy trainer that develops students’ ability to self-explain difficult text as a means to improving reading comprehension. Its curriculum consists of modules presented interactively by pedagogical agents: an introduction to the basics of using reading strategies in the context of self-explanation, a demonstration of self-explanation, and a practice module in which the trainee generates self-explanations with feedback on the quality of reading strategies contained in the self-explanations. We discuss the objectives that guided the development of the second version of iSTART toward the goals of increased efficiency for the experimenters and effectiveness in the training. The more pedagogically challenging high school audience is accommodated by (1) a new introduction that increases interactivity, (2) a new demonstration with more and better focused scaffolding, and (3) a new practice module that provides improved feedback and includes a less intense but more extended regimen. Version 2 also benefits experimenters, who can set up and evaluate experiments with less time and effort, because pre- and posttesting has been fully computerized and the process of preparing a text for the practice module has been reduced from more than 1 person-week to about an hour’s time.     

Second-order conditioning in human predictive judgements when there is little time to think

Associative accounts uniquely predict that second-order conditioning might be observed in human predictive judgements. Such an effect was found for cue X in two experiments in which participants were required to predict the outcomes of a series of training trials that included P + and PX-, but only when training was paced by requiring participants to make a prediction within 3 s on each trial. In Experiment 1 training on P + ended before training was given on PX - . In Experiment 2 trials with P+, PX-, T + and other cues were intermixed. In the unpaced group inhibitory learning was revealed by a summation test, TX versus TM, where M was a control stimulus. These results suggest either that pacing interferes with learning successive associations more than with learning simultaneous associations or that lack of time to think interferes with inferential processes required for this type of inhibitory learning.     

Attributing “Third World Poverty” in Australia and Malawi: A Case of Donor Bias?1

Causal attributions for poverty in the developing world were examined from the perspectives of “actors” living in a “developing country” (Malawi) and “observers” living in a “developed country” (Australia). Ninety‐eight Malawian and 100 Australian weekend shoppers responded to the Causes of Third World Poverty Questionnaire (CTWPQ) and the Just World Scale (JWS), with Australian participants also providing information about their frequency of donating to foreign‐aid charities. Consistent with the actor–observer bias, Australians were more likely than were Malawians to attribute poverty to dispositional characteristics of the poor, rather than to situational factors. Among the Australians, situational attributions were in turn associated with frequency of donation behavior. The finding of a donor bias in this sample has important implications for the social marketing of foreign aid to Western donor publics.     

Prompt comprehension in UNIX command production

We hypothesize that a cognitive analysis based on the construction-integration theory of comprehension (Kintsch, 1988) can predict what is difficult about generating complex composite commands in the UNIX operating system. We provide empirical support for assumptions of the Doane, Kintsch, and Polson (1989, 1990) construction-integration model for generating complex commands in UNIX. We asked users whose UNIX experience varied to produce complex UNIX commands, and then provided help prompts whenever the commands that they produced were erroneous. The help prompts were designed to assist subjects with respect to both the knowledge and the memory processes that our UNIX modeling efforts have suggested are lacking in less expert users. It appears that experts respond to different prompts than do novices. Expert performance is helped by the presentation of abstract information, whereas novice and intermediate performance is modified by presentation of concrete information. Second, while presentation of specific prompts helps less expert subjects, they do not provide sufficient information to obtain correct performance. Our analyses suggest that information about the ordering of commands is required to help the less expert with both knowledge and memory load problems in a manner consistent with skill acquisition theories.     

The impact of task complexity on information use in multi-attribute decision making

This study presents a process analysis of multi-attribute decision making. The decision problems concerned the selection of the most suitable candidate for a job opening. The problems varied in terms of complexity, i.e. the number of candidates and the number of attributes used to describe these alternatives. Results show that with an increasing number of alternatives, subjects (N = 48) used fewer attributes for the evaluation of alternatives, and made, on average, less references to the alternatives. The type of judgment most often used was absolute dimensional (comparison of an attribute to an absolute standard) and was used more often at the beginning than toward the end of the decision process. Overall, judgments were predominantly positive. The percentage of positive judgments decreased with increasing complexity, and toward the end of the decision process. Significantly more judgments, particularly positive ones, concerned the finally chosen alternative as compared to the rest of the alternatives. Finally, analysis of subjects' usage of decision rules revealed that increasing the number of alternatives resulted in an increasing use of elimination strategies. Implications of these findings for the design of decision aids will be discussed.