比较视阈的中美医学伦理学教学——以武汉大学与芝加哥大学为例

中美两国都很重视医者人文素质的培养, 都重视医学伦理学教学。在与芝加哥大学的交流活动中, 武汉大学积极总结经验, 锐意改革, 取得了若干成果。其值得推广的经验包括:注重医学伦理教育的持续性, 构建长效教育机制;注重医学基础课程的道德教化功能, 形成隐性的医德渗透机制;注重临床医生的参与, 确立理论与实践的融通机制;审视中国传统文化特色与医疗现状, 培育域外教学方法的本土化机制;重视医学伦理学学科建设, 建立生命伦理学与医学伦理学的整合机制。     

Kindergarten self-control mediates the gender reading achievement gap: A population-based cohort study

Could superior self-control explain the gender difference in reading achievement favoring girls? To test this idea, we drew on a unique population-based sample (N = 11,336) where self-control was measured in kindergarten using a multimethod battery of assessments. Girls showed substantially higher levels of self-control in kindergarten (β = 0.47) and outperformed boys on standardized tests of reading achievement in third/fourth grade (β = 0.20). Further, kindergarten self-control prospectively predicted reading achievement throughout elementary school (β = 0.37). Connecting these findings, our mediation analyses revealed that the female self-control advantage in kindergarten could account for subsequent gender differences in reading achievement. Our results suggest that early gender differences in self-control may represent a key pathway through which gender disparities in reading skills, vocabulary knowledge, and reading comprehension occur.     

Why Higher Working Memory Capacity May Help You Learn: Sampling,Search, and Degrees of Approximation

Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the number of samples, or “particles,” available to perform inference. To test this idea, we focus on two recent experiments that report positive associations between WMC and two distinct aspects of categorization performance: the ability to learn novel categories, and the ability to switch between different categorization strategies (“knowledge restructuring”). In favor of the idea of modeling WMC as a number of particles, we show that a single model can reproduce both experimental results by varying the number of particles—increasing the number of particles leads to both faster category learning and improved strategy‐switching. Furthermore, when we fit the model to individual participants, we found a positive association between WMC and best‐fit number of particles for strategy switching. However, no association between WMC and best‐fit number of particles was found for category learning. These results are discussed in the context of the general challenge of disentangling the contributions of different potential sources of behavioral variability.     

Degree of Language Experience Modulates Visual Attention to Visible Speech and Iconic Gestures During Clear and Degraded Speech Comprehension

Visual information conveyed by iconic hand gestures and visible speech can enhance speech comprehension under adverse listening conditions for both native and non‐native listeners. However, how a listener allocates visual attention to these articulators during speech comprehension is unknown. We used eye‐tracking to investigate whether and how native and highly proficient non‐native listeners of Dutch allocated overt eye gaze to visible speech and gestures during clear and degraded speech comprehension. Participants watched video clips of an actress uttering a clear or degraded (6‐band noise‐vocoded) action verb while performing a gesture or not, and were asked to indicate the word they heard in a cued‐recall task. Gestural enhancement was the largest (i.e., a relative reduction in reaction time cost) when speech was degraded for all listeners, but it was stronger for native listeners. Both native and non‐native listeners mostly gazed at the face during comprehension, but non‐native listeners gazed more often at gestures than native listeners. However, only native but not non‐native listeners' gaze allocation to gestures predicted gestural benefit during degraded speech comprehension. We conclude that non‐native listeners might gaze at gesture more as it might be more challenging for non‐native listeners to resolve the degraded auditory cues and couple those cues to phonological information that is conveyed by visible speech. This diminished phonological knowledge might hinder the use of semantic information that is conveyed by gestures for non‐native compared to native listeners. Our results demonstrate that the degree of language experience impacts overt visual attention to visual articulators, resulting in different visual benefits for native versus non‐native listeners.     

Keeping the Result in Sight and Mind: General Cognitive Principles and Language‐Specific Influences in the Perception and Memory of Resultative Events

We study how people attend to and memorize endings of events that differ in the degree to which objects in them are affected by an action: Resultative events show objects that undergo a visually salient change in state during the course of the event (peeling a potato), and non‐resultative events involve objects that undergo no, or only partial state change (stirring in a pan). We investigate general cognitive principles, and potential language‐specific influences, in verbal and nonverbal event encoding and memory, across two experiments with Dutch and Estonian participants. Estonian marks a viewer's perspective on an event's result obligatorily via grammatical case on direct object nouns: Objects undergoing a partial/full change in state in an event are marked with partitive/accusative case, respectively. Therefore, we hypothesized increased saliency of object states and event results in Estonian speakers, as compared to speakers of Dutch. Findings show (a) a general cognitive principle of attending carefully to endings of resultative events, implying cognitive saliency of object states in event processing; (b) a language‐specific boost on attention and memory of event results under verbal task demands in Estonian speakers. Results are discussed in relation to theories of event cognition, linguistic relativity, and thinking for speaking.     

On Fodor's First Law of the Nonexistence of Cognitive Science

In his enormously influential The Modularity of Mind, Jerry Fodor (1983) proposed that the mind was divided into input modules and central processes. Much subsequent research focused on the modules and whether processes like speech perception or spatial vision are truly modular. Much less attention has been given to Fodor's writing on the central processes, what would today be called higher‐level cognition. In “Fodor's First Law of the Nonexistence of Cognitive Science,” he argued that central processes are “bad candidates for scientific study” and would resist attempts at empirical analysis. This essay evaluates his argument for this remarkable claim, concluding that although central processes may well be “messier” than input modules, this does not mean that they cannot be studied and understood. The article briefly reviews the scientific progress made in understanding central processes in the 35 years since the book was published, showing that Fodor's prediction is clearly falsified by massive advances in topics like decision making and analogy. The essay concludes that Fodor's Law was not based on a clear argument for why the complexities of central systems could not be studied but was likely based on intuitions and preferences that were common in psychology at the time.     

Cognitive Task Analysis for Implicit Knowledge About Visual Representations With Similarity Learning Methods

Visual representations are prevalent in STEM instruction. To benefit from visuals, students need representational competencies that enable them to see meaningful information. Most research has focused on explicit conceptual representational competencies, but implicit perceptual competencies might also allow students to efficiently see meaningful information in visuals. Most common methods to assess students’ representational competencies rely on verbal explanations or assume explicit attention. However, because perceptual competencies are implicit and not necessarily verbally accessible, these methods are ill‐equipped to assess them. We address these shortcomings with a method that draws on similarity learning, a machine learning technique that detects visual features that account for participants’ responses to triplet comparisons of visuals. In Experiment 1, 614 chemistry students judged the similarity of Lewis structures and in Experiment 2, 489 students judged the similarity of ball‐and‐stick models. Our results showed that our method can detect visual features that drive students’ perception and suggested that students’ conceptual knowledge about molecules informed perceptual competencies through top‐down processes. Furthermore, Experiment 2 tested whether we can improve the efficiency of the method with active sampling. Results showed that random sampling yielded higher accuracy than active sampling for small sample sizes. Together, the experiments provide the first method to assess students’ perceptual competencies implicitly, without requiring verbalization or assuming explicit visual attention. These findings have implications for the design of instructional interventions that help students acquire perceptual representational competencies.     

Make‐or‐Break: Chasing Risky Goals or Settling for Safe Rewards?

Humans regularly pursue activities characterized by dramatic success or failure outcomes where, critically, the chances of success depend on the time invested working toward it. How should people allocate time between such make‐or‐break challenges and safe alternatives, where rewards are more predictable (e.g., linear) functions of performance? We present a formal framework for studying time allocation between these two types of activities, and we explore optimal behavior in both one‐shot and dynamic versions of the problem. In the one‐shot version, we illustrate striking discontinuities in the optimal time allocation policy as we gradually change the parameters of the decision‐making problem. In the dynamic version, we formulate the optimal strategy—defined by a giving‐up threshold—which adaptively dictates when people should stop pursuing the make‐or‐break goal. We then show that this strategy is computationally inaccessible for humans, and we explore boundedly rational alternatives. We compare the performance of the optimal model against (a) a myopic giving‐up threshold that is easier to compute, and even simpler heuristic strategies that either (b) only decide whether or not to start pursuing the goal and never give up or (c) consider giving up at a fixed number of control points. Comparing strategies across environments, we investigate the cost and behavioral implications of sidestepping the computational burden of full rationality.     

Self‐Priming in Production: Evidence for a Hybrid Model of Syntactic Priming

Syntactic priming in language production is the increased likelihood of using a recently encountered syntactic structure. In this paper, we examine two theories of why speakers can be primed: error‐driven learning accounts (Bock, Dell, Chang, & Onishi, 2007; Chang, Dell, & Bock, 2006) and activation‐based accounts (Pickering & Branigan, 1999; Reitter, Keller, & Moore, 2011). Both theories predict that speakers should be primed by the syntactic choices of others, but only activation‐based accounts predict that speakers should be able to prime themselves. Here we test whether speakers can be primed by their own productions in three behavioral experiments and find evidence of structural persistence following both comprehension and speakers’ own productions. We also find that comprehension‐based priming effects are larger for rarer syntactic structures than for more common ones, which is most consistent with error‐driven accounts. Because neither error‐driven accounts nor activation‐based accounts fully explain the data, we propose a hybrid model.