The measurement of calibration in real contexts

Accurate judgment of performance, or calibration, is an important element of self-regulated learning (SRL) and itself has been an area of growing study. The current study contributes to work on calibration by presenting practical and predictive results of varying calibration measures from authentic educational data: elementary-aged students' interactions with a year-long digital mathematics curriculum. Comparison of predictive validity of measures show only small differences in explained variance in models predicting posttest performance while controlling for pretest. A combined model including Sensitivity and Specificity outperforms other single measures, confirming results in Schraw, Kuch, & Gutierrez (2013); however, results show that student patterns of calibration within these data differ from those assumed in simulation studies and these differences have implications for the calculability of popular calibration measures.     

新疆油田VSP测井数据库系统研发与反思

由于VSP资料采集、处理、解释分别由不同单位的不同人员来完成,相互之间缺乏统一和规范化的工作目标和工作要求,导致终端解释用户无法准确标定地址层位,做详细的地质构造解释。因此,我们开发了一套集VSP外业采集、资料处理、标定对比的VSP数据库系统,建立了VSP外业采集的地震辅助数据、处理流程标准和成果格式标准,使物探行业能更好地适应国际、国内勘探市场的要求,也为VSP数据的规范化管理创造了一种手段和条件。该系统将有关VSP数据和研究的所有信息有效地关联起来,使其在地震解释标定计算中得以充分利用,从而有效地解决了以往VSP数据没有集中管理和计算工具落后产生的一些难题。     

滴定分析用标准溶液的实践分析

标准溶液是已知其准确浓度的溶液,在滴定分析中用来滴加到被测物质中与被滴定的组分按照化学反应式的计量关系达到理论终点,根据消耗的标准溶液的浓度和体积来计算待测组分的含量,因此标准溶液的准确配制及标定直接影响到分析结果的准确。在实际的生产检测中标准溶液被广泛应用,许多产品的检测都是通过标准溶液来完成的。文章结合生产实际对标准溶液进行分析讨论。     

GPS时间系统的校准原理分析

本文利用相对论原理,针对GPS时间系统的误差进行了广义与狭义相对论两方面的分析,同时分析了萨格纳克效应对 GPS时间系统造成的误差,并提出了校准补偿的方法。     

Predicting performance on academic and non-academic tasks: A comparison of adolescents with and without learning disabilities

Previous research suggests that adolescents with learning disabilities (LD) are less accurate in predicting academic performance than normally achieving (NA) adolescents and display a tendency to overestimate their level of performance (e.g., Klassen, 2007). However, no studies have been conducted investigating whether this overestimation is specific to academic contexts or a phenomenon that extends across domains. Ninety-four adolescents (46 LD, 48 NA) predicted their performance on a spelling task and on a ball-throwing task. Results revealed group differences in performance calibration across domains with adolescents with LD showing an overestimation of ability on the spelling and ball-throwing tasks, and NA adolescents demonstrating more precise self-appraisals. Additionally, the accuracy of non-academic performance predictions remained stable with increasing difficulty in the NA group whereas the adolescents with LD demonstrated a decrease in accurate performance prediction as the difficulty level increased.     

Unwrapping and stereo rectification for omnidirectional images

Omnidirectional imaging sensors have been used in more and more applications when a very large field of view is required. In this paper, we investigate the unwrapping, epipolar geometry and stereo rectification issues for omnidirectional vision when the particular mirror model and the camera parameters are unknown in priori. First, the omnidirectional camera is calibrated under the Taylor model, and the parameters related to this model are obtained. In order to make the classical computer vision algorithms of conventional perspective cameras applicable, the ring omnidirectional image is unwrapped into two kinds of panoramas： cylinder and cuboid. Then the epipolar geometry of arbitrary camera configuration is analyzed and the essential matrix is deduced with its properties being indicated for ring images. After that, a simple stereo rectification method based on the essential matrix and the conformal mapping is proposed. Simulations and real data experimental results illustrate that our methods are effective for the omnidirectional camera under the constraint of a single view point.     

Metacognitive calibration—an extended conceptualization and potential applications

In this theoretical paper, I present a short critical review of research on calibration. Based on this conceptual analysis I argue for two extensions of this construct: In addition to traditional applications, the methodology should be transferred to also measure calibration between students’ metacognitive control processes (traditionally, only students’ metacognitive judgments were considered) and important external criteria (traditionally, judgments were only compared to students’ own performance). As an illustrative example, one application context will be highlighted where these proposed extensions would alleviate potential problems with the traditional conceptualization: While students’ idiosyncratic task definitions constitute unwanted error variance in the traditional account it would be possible to investigate them as a primary research question within this extended notion. More specifically, it would be possible to investigate how well students’ learning processes match objective task demands. I will put forward theoretical and empirical arguments in favor of these suggestions.     

Reading Across Mediums: Effects of Reading Digital and Print Texts on Comprehension and Calibration

This study explored differences that might exist in comprehension when students read digital and print texts. Ninety undergraduates read both digital and print versions of newspaper articles and book excerpts on topics of childhood ailments. Prior to reading texts in counterbalanced order, topic knowledge was assessed and students were asked to state medium preferences. After reading, students were asked to judge under which medium they comprehended best. Results demonstrated a clear preference for digital texts, and students typically predicted better comprehension when reading digitally. However, performance was not consistent with students' preferences and outcome predictions. While there were no differences across mediums when students identified the main idea of the text, students recalled key points linked to the main idea and other relevant information better when engaged with print. No differences in reading outcomes or calibration were found for newspaper or book excerpts.     

CALIMERA: A new early time series classification method

Early time series classification is a variant of the time series classification task, in which a label must be assigned to the incoming time series as quickly as possible without necessarily screening through the whole sequence. It needs to be realized on the algorithmic level by fusing a decision-making method that detects the right moment to stop and a classifier that assigns a class label. The contribution addressed in this paper is twofold. Firstly, we present a new method for finding the best moment to perform an action (terminate/continue). Secondly, we propose a new learning scheme using classifier calibration to estimate classification accuracy. The new approach, called CALIMERA, is formalized as a cost minimization problem. Using two benchmark methodologies for early time series classification, we have shown that the proposed model achieves better results than the current state-of-the-art. Two most serious competitors of CALIMERA are ECONOMY and TEASER. The empirical comparison showed that the new method achieved a higher accuracy than TEASER for 35 out of 45 datasets and it outperformed ECONOMY in 20 out of 34 datasets.     

Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing

The increasing interest in fuzzy-set Qualitative Comparative Analysis (fsQCA) in Information Systems and marketing raises the need for a tutorial paper that discusses the basic concepts and principles of the method, provide answers to typical questions that editors, reviewers, and authors would have when dealing with a new tool of analysis, and practically guide researchers on how to employ fsQCA. This article helps the reader to gain richer information from their data and understand the importance of avoiding shallow information‐from‐data reporting. To this end, it proposes a different research paradigm that includes asymmetric, configurational‐focused case‐outcome theory construction and somewhat precise outcome testing. This article offers a detailed step-by-step guide on how to employ fsQCA by using as an example an already published study. We analyze the same dataset and present all the details in each step of the analysis to guide the reader onto how to employ fsQCA. The article discusses differences between fsQCA and variance-based approaches and compares fsQCA with those from structured equation modelling. Finally, the article offers a summary of thresholds and guidelines for practice, along with a discussion on how existing papers that employ variance-based methods are extendable and complemented through fsQCA.