Facilitation by Variation: Right-to-Left Learning of English Yes/No Questions

This study advances the hypothesis that optional structural variation in language facilitates syntactic learning (facilitation‐by‐variation). Support for this is provided by a right‐to‐left‐elaboration acquisition model for English yes/no questions (YNQs). Previous studies have focused on the acquisition of ‘‘inverted’’ YNQs, a cornerstone of nativist theories of language development. Data from five American children (1;3 to 5;1) and their parents show that children hear a range of adult questions (Coming?You coming?Are you coming?), not all inverted. These variants are ordered from structurally least complex noncanonical forms to complex canonical inverted forms. I use state‐of‐the‐art econometric techniques to estimate breakpoints in YNQ time series and show that noncanonical questions emerge early in children’s speech and facilitate acquisition of canonical ones. This incremental structure‐building process relies on an adjunction strategy that augments noncanonical questions with initial auxiliaries and subjects. Development proceeds incrementally from right to left to derive auxiliary‐initial structures.     

群体水平领域分数及其估计方法

对人才的需求已经引起各国政府和国际组织对教育的高度重视,纷纷在国家和地区层面进行大规模的教育评估。在大尺度教育评估中,如何向政府、管理者和公众报告学生表现是不可避免的重要问题。报告学生表现有多种方式,领域分数作为管理者和公众最容易理解和接受的分数报告工具之一,在近些年受到研究者和实践者的关注,因此也成为了大型教育评价项目的必然选择。文中将介绍群体领域分数的起源和定义,并重点介绍群体领域分数的估计方法和相关研究,最后对未来开展进一步研究进行展望。     

疼痛条件下时间目标对时距估计的影响

本研究采用冷压任务引发疼痛,以健康大学生为被试,试图探讨在疼痛条件下时间目标对时距估计的影响。结果发现：疼痛条件下的时距估计值小于非疼痛条件下时距估计值,疼痛条件下具体时间目标的时距估计值显著大于无目标时距估计值。临床上给患者提供具体的时间目标或许有助于他们应对疼痛。     

数量对时间知觉的影响-来自抽象数量和实际数量的证据

本研究采用抽象数量和实际数量叠加的方式呈现刺激,进一步探讨数量对时间知觉的影响。两个实验都运用时间的系列比较任务,以抽象数量和实际数量这两种数量的一致和不一致为条件,将阿拉伯数字和其字体大小叠加及阿拉伯数字和其呈现个数叠加的方式系列呈现在屏幕中央,要求被试比较判断刺激呈现的时间长短。结果显示被试均依靠实际数量的大小判断时间长短,而似乎忽略了抽象数量的存在。这一结果表明实际数量对时间知觉的影响要比抽象数量大,支持并扩展了数量理论。     

计划缺失设计——通过有意缺失让研究更高效

缺失值是社会科学研究中非常普遍的现象。全息极大似然估计和多重插补是目前处理缺失值最有效的方法。计划缺失设计利用特殊的实验设计有意产生缺失值, 再用现代的缺失值处理方法来完成统计分析, 获得无偏的统计结果。计划缺失设计可用于横断面调查减少(或增加)问卷长度和纵向调查减少测量次数, 也可用于提高测量有效性。常用的计划缺失设计有三式设计和两种方法测量。     

时距长度和速度变化对进度条时距知觉的影响

进度条在人机交互界面中具有广泛应用。本研究运用单任务的预期式范式和口头估计法,探究速度变化对不同时距长度进度条的时距知觉的影响,为进度条的智能化设计提供参考。研究表明：（1）时距长度影响个体的时距估计,时距长度与时距估计比率分数成反比关系;（2）进度条的不同速度变化趋势影响进度条时距知觉,在持续时间相同的匀速、减速、加速和先加后减四种进度条类型中,加速进度条的时距知觉最短,而匀速进度条时距估计最长。     

使用似然比D2统计量的题目属性定义方法

题目属性的定义是实施认知诊断评价的关键步骤, 通过有丰富经验的领域专家对题目的属性进行定义是当前的主要方法, 然而该方法受到许多主观经验因素的影响。寻找客观的题目属性定义或验证方法可以为主观定义过程提供策略支持或对结果进行改进, 因此已经引起研究者们的关注。本研究构建了一种简单高效的题目属性定义方法, 研究使用似然比D2统计量从作答数据中估计题目属性的方法, 实现属性掌握模式、题目参数和题目属性向量的联合估计。模拟研究结果表明, 使用似然比D2统计量可以有效地识别题目的属性向量, 该方法一方面可以实现新编制题目属性向量的在线估计, 另一方面可以验证已经定义的题目属性向量的准确性。     

儿童数字线表征的发展——心理长度的影响

探讨儿童在数字线估计任务中心理长度的发展及其对数量表征模式的影响.选取7~9岁儿童共109名进行数字线估计任务测试,设置了10cm和20cm两种长度条件,要求儿童完成根据位置判断数字任务(position to number,PN任务).结果表明儿童在数字线PN任务中存在心理长度,且7岁儿童心理长度的范围超过10,随着儿童年龄的增长,他们的心理长度范围不断缩小;心理长度范围影响儿童的表征模式,随着心理长度范围的缩小,儿童的数字线表征出现从指数模式到线性模式的变化趋势;与表征模式的发展趋势一致,儿童估计的精确性随年龄增长逐渐提高.     

Reducing Measurement Error in Student Achievement Estimation

The achievement level is a variable measured with error, that can be estimated by means of the Rasch model. Teacher grades also measure the achievement level but they are expressed on a different scale. This paper proposes a method for combining these two scores to obtain a synthetic measure of the achievement level based on the theory developed for regression with covariate measurement error. In particular, the focus is on ordinal scaled grades, using the SIMEX method for measurement error correction. The result is a measure comparable across subjects with smaller measurement error variance. An empirical application illustrates the method.     

A fast numerical algorithm for the estimation of diffusion model parameters

In this paper, we describe a new algorithmic approach for parameter estimation in Ratcliff's [(1978). A theory of memory retrieval. Psychological Review, 85 (2), 59-108] diffusion model. This problem, especially if inter-trial variabilities of parameters are included in the model, is computationally very expensive; the parameter estimation procedure often takes a long time even with today's high-speed computers. The algorithm described here makes the calculation of the cumulative distribution functions for predicted process durations computationally much less expensive. This improvement is achieved by solving the Kolmogorov backward equation numerically instead of employing the previously used closed form solution. Additionally, the algorithm can determine the optimum fit for one of the model parameters (the starting point z) directly, thereby reducing the dimension of the parameter search space by one. The resulting method is shown to be notably faster than the standard (closed-form solution) method for parameter estimation.