A Review of Articles Using Observation Methods to Study Creativity in Education (1980–2018)

This paper reports on an integrative literature review of published articles that used either quantitative or qualitative observation methods to research creativity in learning contexts. Observation is an empirical research method used in quantitative and qualitative naturalistic studies focused on understanding behavior and interactions as they unfold in real-time, which makes it particularly salient for examining the processes associated with the generation and adoption of creative ideas. However, observation remains underutilized in the field of creativity studies, partly because data collection can be time and resource intensive, but also because there are a lack of protocols and recommended research practices for observing creative thinking and problem solving in an educational environment that covers all phases of design, collection, analysis, and reporting. Thirty-seven articles from 1980–2018 were reviewed along seven dimensions: definition of creativity, unit of observation, observer role, observation sampling method, research design, data collection, and data analysis. The paper concludes with five recommendations for using observation to advance the state of research on creativity and education.     

Comparing predictive validity in a community sample: High-dimensionality and traditional domain-and-facet structures of personality variation

Prediction of outcomes is an important way of distinguishing, among personality models, the best from the rest. Prominent previous models have tended to emphasize multiple internally consistent “facet” scales subordinate to a few broad domains. But such an organization of measurement may not be optimal for prediction. Here, we compare the predictive capacity and efficiency of assessments across two types of personality-structure model: conventional structures of facets as found in multiple platforms, and new high-dimensionality structures emphasizing those based on natural-language adjectives, in particular lexicon-based structures of 20, 23, and 28 dimensions. Predictions targeted 12 criterion variables related to health and psychopathology, in a sizeable American community sample. Results tended to favor personality-assessment platforms with (at least) a dozen or two well-selected variables having minimal intercorrelations, without sculpting of these to make them function as indicators of a few broad domains. Unsurprisingly, shorter scales, especially when derived from factor analyses of the personality lexicon, were shown to take a more efficient route to given levels of predictive capacity. Popular 20^th-century personality-assessment models set out influential but suboptimal templates, including one that first identifies domains and then facets, which compromise the efficiency of measurement models, at least from a comparative-prediction standpoint. © 2020 European Association of Personality Psychology     

佛教的善的思想的心理诠释

佛教的宗旨是众善奉行诸恶莫作,认为人的先天本性无分善恶,亲近善知识能形成善的心理,亲近恶知识会形成恶的心理。佛教相信善有善报恶有恶报,鼓励人们行善积德。佛教认为欲望是恶的根源,控制欲望,通过戒定慧、八正道等方式能达到善的心理状态。佛教关于善的先天本性的观点、善恶形成的思想以及善的自我修养方法符合心理学的有关规律。佛教的崇善理念及善的修养思想对于构建社会主义核心价值观的友善价值准则具有积极意义。     

The Multiplicative AHP,SMART and ELECTRE in a Common Context

This paper presents a comparative study of three popular methods for multicriteria decision analysis based on a particular model of human preferential judgement. Since decisions are invariably made within a given context, we model relative preferences as ratios of increments or decrements in an interval on an axis of desirability. Next we sort the ratio magnitudes into a small number of categories, represented by numerical values on a geometric scale. We explain why the analytic hierarchy process (AHP) and the French collection of ELECTRE methods, typically based on pairwise comparison methods, are concerned with categories of ratio magnitudes, whereas the simple multiattribute rating technique (SMART) essentially uses orders of magnitude of these ratios. This phenomenon provides a common basis for the analysis of the methods in question and for a cross-validation of their results. We illustrate the approach via a well-known case study, the choice of a location for a nuclear power plant. We conclude by discussing the scope of the comparative study. © 1997 John Wiley & Sons, Ltd.     

Invidious Comparisons: Imagining a Psychology of Race and Gender Beyond Differences

Within psychology there is a longstanding debate concerning whether large, fundamental differences between races and genders exist. Much of this research involves comparisons that are invidious (offensively discriminating) and supports a political ideology in which members of different groups are held to be fundamentally different, alien, and therefore destined to different spheres. In this paper, specific factors are identified that make research on group differences more likely to produce distorted and partial findings. In addition, studies are cited whose methodological strategies offer insight into the processes that create and maintain group differences. Such research may illuminate not only the differences between groups, but also the very meaning of group categories. The process of scholarly peer review should become sensitive to the features that make comparisons invidious, so as to incorporate them into the criteria used to evaluate research.     

Pairwise comparisons of trimmed means for two or more groups

The paper takes up the problem of performing all pairwise comparisons amongJ independent groups based on 20% trimmed means. Currently, a method that stands out is the percentile-t bootstrap method where the bootstrap is used to estimate the quantiles of a Studentized maximum modulus distribution when all pairs of population trimmed means are equal. However, a concern is that in simulations, the actual probability of one or more Type I errors can drop well below the nominal level when sample sizes are small. A practical issue is whether a method can be found that corrects this problem while maintaining the positive features of the percentile-t bootstrap. Three new methods are considered here, one of which achieves the desired goal. Another method, which takes advantage of theoretical results by Singh (1998), performs almost as well but is not recommended when the smallest sample size drops below 15. In some situations, however, it gives substantially shorter confidence intervals.     

Understanding Dignity in the Lives of Homeless Persons

The current investigation is a planned, systematic study of dignity as critical to understanding the experience of homelessness and improving services and programs for the homeless. Specifically, we conducted a thematic content analysis of interviews with 24 homeless men and women to identify their perception of specific environmental events that validate and invalidate dignity. In addition, we explored the impact that these events have on homeless persons. Eight types of events were identified that sustain dignity such as being cared for by staff and having resources available to meet basic needs. Eight types of events were found that undermine dignity, such as being yelled at or insulted by staff persons and having staff use rules in an excessive and arbitrary way. Two outcomes followed the sustenance of dignity including increased self-worth and motivation to exit homelessness. Three outcomes followed the undermining of dignity including anger, depression, and feelings of worthlessness. The results suggest that dignity is an important variable to consider in understanding the experience of homelessness. Policies and programs that support validating the dignity of homeless persons are encouraged.     

Signal Detection Models with Random Participant and Item Effects

The theory of signal detection is convenient for measuring mnemonic ability in recognition memory paradigms. In these paradigms, randomly selected participants are asked to study randomly selected items. In practice, researchers aggregate data across items or participants or both. The signal detection model is nonlinear; consequently, analysis with aggregated data is not consistent. In fact, mnemonic ability is underestimated, even in the large-sample limit. We present two hierarchical Bayesian models that simultaneously account for participant and item variability. We show how these models provide for accurate estimation of participants’ mnemonic ability as well as the memorability of items. The model is benchmarked with a simulation study and applied to a novel data set. This research is supported by NSF grants SES-0095919 and SES-0351523, NIH grant R01-MH071418, a University of Missouri Research Leave grant and fellowships from the Spanish Ministry of Education and the University of Leuven, Belgium.