Differential stability of individual differences in state and trait test anxiety

The differential stability of state and trait test anxiety was investigated in two content areas (Psychology, n = 154; Method, n = 133). The structural model supported the hypothesis regarding differential stability of individual differences for state and trait test anxiety over a three-month interval, with trait test anxiety being more stable than state test anxiety. Contrary to the invariant stability of trait test anxiety across content, the stability of state test anxiety was significantly low in Psychology as compared to that in Method, indicating that more individuals in the Psychology group reported fluctuant state test anxiety over time. Although the stability of individual differences in state test anxiety was low, the factor structures of state test anxiety at two occasions were invariant, supporting the contention that even when the factorial structures are stable over time and the test-retest stability is high, individual state test anxiety may be unstable across time.     

A Simplified Estimation of Latent State—Trait Parameters

The latent state–trait (LST) theory is an extension of the classical test theory that allows one to decompose a test score into a true trait, a true state residual, and an error component. For practical applications, the variances of these latent variables may be estimated with standard methods of structural equation modeling (SEM). These estimates allow one to decompose the coefficient of reliability into a coefficient of consistency (indicating true effects of the person) plus a coefficient of occasion specificity (indicating true effects of the situation and the person–situation interaction). One disadvantage of this approach is that the standard SEM analysis requires large sample sizes. This article aims to overcome this disadvantage by presenting a simple method that allows one to estimate the LST parameters algebraically from the observed covariance matrix. A Monte Carlo simulation suggests that the proposed method may be superior to the standard SEM analysis in small samples.     

Evaluating the Effectiveness of Physlet-Based Materials in Supporting Conceptual Learning About Electricity

To provide a good understanding of many abstract concepts in the field of electricity above that of their students is often a major challenge for secondary school teachers. Many educational researchers promote conceptual learning as a teaching approach that can help teachers to achieve this goal. In this paper, we present Physlet-based materials for supporting conceptual learning about electricity. To conduct research into the effectiveness of these materials, we designed two different physics courses: one group of students, the experimental group, was taught using Physlet-based materials and the second group of students, the control group, was taught using expository instruction without using Physlets. After completion of the teaching, we assessed students’ thinking skills and analysed the materials with an independent t test, multiple regression analyses and one-way analysis of covariance. The test scores were significantly higher in the experimental group than in the control group (p < 0.05). The results of this study confirmed the effectiveness of conceptual learning about electricity with the help of Physlet-based materials.     

Hemispheric processing and cognitive styles in learning-disabled and normal children.

A paradigm of specialized brain hemisphere processing abilities was used to test cognitive skills and cognitive style in "learning-disabled" (LD) and "normal" children. Results indicate that (1) verbal ability is not a unitary factor, and LD children are deficient in only some aspects of verbal ability; (2) the LD group perform as well as the control group on right-hemisphere tests; (3) LD boys are more field sensitive (field dependent) than the control boys; (4) LD children may be attempting to use a nonverbal information processing mode to deal with academic tasks. The need for information on nonverbal processing skills in order to aid verbal processing is discussed.     

A Two-Stage Approach to Missing Data: Theory and Application to Auxiliary Variables

A well-known ad-hoc approach to conducting structural equation modeling with missing data is to obtain a saturated maximum likelihood (ML) estimate of the population covariance matrix and then to use this estimate in the complete data ML fitting function to obtain parameter estimates. This 2-stage (TS) approach is appealing because it minimizes a familiar function while being only marginally less efficient than the full information ML (FIML) approach. Additional advantages of the TS approach include that it allows for easy incorporation of auxiliary variables and that it is more stable in smaller samples. The main disadvantage is that the standard errors and test statistics provided by the complete data routine will not be correct. Empirical approaches to finding the right corrections for the TS approach have failed to provide unequivocal solutions. In this article, correct standard errors and test statistics for the TS approach with missing completely at random and missing at random normally distributed data are developed and studied. The new TS approach performs well in all conditions, is only marginally less efficient than the FIML approach (and is sometimes more efficient), and has good coverage. Additionally, the residual-based TS statistic outperforms the FIML test statistic in smaller samples. The TS method is thus a viable alternative to FIML, especially in small samples, and its further study is encouraged.     

Virtual reality anatomy: Is it comparable with traditional methods in the teaching of human forearm musculoskeletal anatomy?

The use of cadavers to teach anatomy is well established, but limitations with this approach have led to the introduction of alternative teaching methods. One such method is the use of three-dimensional virtual reality computer models. An interactive, three-dimensional computer model of human forearm anterior compartment musculoskeletal anatomy was produced using the open source 3D imaging program "Blender." The aim was to evaluate the use of 3D virtual reality when compared with traditional anatomy teaching methods. Three groups were identified from the University of Manchester second year Human Anatomy Research Skills Module class: a "control" group (no prior knowledge of forearm anatomy), a "traditional methods" group (taught using dissection and textbooks), and a "model" group (taught solely using e-resource). The groups were assessed on anatomy of the forearm by a ten question practical examination. ANOVA analysis showed the model group mean test score to be significantly higher than the control group (mean 7.25 vs. 1.46, P < 0.001) and not significantly different to the traditional methods group (mean 6.87, P > 0.5). Feedback from all users of the e-resource was positive. Virtual reality anatomy learning can be used to compliment traditional teaching methods effectively.     

The Collaboration of Cooperative Learning and Conceptual Change: Enhancing the Students’ Understanding of Chemical Bonding Concepts

The main purpose of this study was to investigate the effects of cooperative learning based on conceptual change approach instruction on ninth-grade students’ understanding in chemical bonding concepts compared to traditional instruction. Seventy-two ninth-grade students from two intact chemistry classes taught by the same teacher in a public high school participated in the study. The classes were randomly assigned as the experimental and control group. The control group (N?=?35) was taught by traditional instruction while the experimental group (N?=?37) was taught cooperative learning based on conceptual change approach instruction. Chemical Bonding Concept Test (CBCT) was used as pre- and post-test to define students’ understanding of chemical bonding concepts. After treatment, students’ interviews were conducted to observe more information about their responses. Moreover, students from experimental groups were interviewed to obtain information about students’ perceptions on cooperative work experiences. The results from ANCOVA showed that cooperative learning based on conceptual change approach instruction led to better acquisition of scientific conceptions related to chemical bonding concepts than traditional instruction. Interview results demonstrated that the students in the experimental group had better understanding and fewer misconceptions in chemical bonding concepts than those in the control group. Moreover, interviews about treatment indicated that this treatment helped students’ learning and increased their learning motivation and their social skills.     

A Twins study of communicative adaptability: Heritability of individual differences

Recently, a model of communication theory and research has appeared in the literature within which stable individual differences in communication behavior represent individual differences in activation thresholds of neurobiological systems. The neurobiological systems thought to underly communication traits and behavior are assumed to be primarily due to genetic inheritance. As such, the model assigns a limited role to adaptability in social situations, instead positing communication adaptability as an inherited trait. In the present study, heritability estimates for the dimensions of communicative adaptability were derived from correlations based on identical and fraternal twins’ responses to a multidimensional communicative adaptability measure. Results indicated that social composure was 88% heritable, wit was 90% heritable, social confirmation was 37% heritable, articulation ability, and appropriate disclosure were 0% heritable. Theoretical implications are discussed.     

Investigating the impact of observation errors on the statistical performance of network-based diffusion analysis

Experiments in captivity have provided evidence for social learning, but it remains challenging to demonstrate social learning in the wild. Recently, we developed network-based diffusion analysis (NBDA; 2009) as a new approach to inferring social learning from observational data. NBDA fits alternative models of asocial and social learning to the diffusion of a behavior through time, where the potential for social learning is related to a social network. Here, we investigate the performance of NBDA in relation to variation in group size, network heterogeneity, observer sampling errors, and duration of trait diffusion. We find that observation errors, when severe enough, can lead to increased Type I error rates in detecting social learning. However, elevated Type I error rates can be prevented by coding the observed times of trait acquisition into larger time units. Collectively, our results provide further guidance to applying NBDA and demonstrate that the method is more robust to sampling error than initially expected. Supplemental materials for this article may be downloaded from http://lb.psychonomic-journals.org/content/supplemental.     

CONCEPTS OF CULTURE-FAIRNESS

Fairness of a test relates to fair use. One definition of fair use states that a common qualifying score may be used with two groups if the regression line based on one group does not systematically over- or under-predict criterion performance in the other. However, it is shown that when the two groups differ appreciably in mean test score, the above procedure, which is "fair" to individual members of the group scoring lower on the test, is "unfair" to the lower group as a whole in the sense that the proportion qualified on the test will be smaller, relative to the higher-scoring group, than the proportion that will reach any specified level of criterion performance. An alternate definition would specify that the qualifying scores on a test should be set at levels that will qualify applicants in the two groups in proportion to the fraction of the two groups reaching a specified level of criterion performance.     

Detection of Differential Item Functioning for More Than Two Groups: A Monte Carlo Comparison of Methods

ABSTRACT

Differential item functioning (DIF) assessment is a crucial component in test construction, serving as the primary way in which instrument developers ensure that measures perform in the same way for multiple groups within the population. When such is not the case, scores may not accurately reflect the trait of interest for all individuals in the population. Most DIF research has focused on the two groups case. However, in practice researchers may wish to investigate DIF for more than two groups; that is, for examinee ethnicity, nation of origin, or treatment condition, among others. DIF detection methods for such cases have been proposed, but little empirical work has been done to investigate their performance. Therefore, the goal of the current study was to use a simulation methodology to compare four proposed methods for assessing DIF in the multiple groups case, including the Generalized Mantel-Haenszel test, Generalized Logistic Regression, Lord’s chi-square test, and the multiple group alignment procedure. Results showed that the Generalized Mantel-Haenszel and alignment procedures provided the optimal combination of Type I error control and power.     

Looking Beyond the Overall Scores of NAEP Assessments: Applications of Generalized Linear Mixed Modeling for Exploring Value-Added Item Difficulty Effects

The central idea of differential item functioning (DIF) is to examine differences between two groups at the item level while controlling for overall proficiency. This approach is useful for examining hypotheses at a finer-grain level than are permitted by a total test score. The methodology proposed in this paper is also aimed at estimating differences at the item rather than the overall score level, yet with the innovation where item-level differences for many groups simultaneously are the focus. This is a straightforward generalization of DIF as variance rather than one or several group differences; conceptually, this can be referred to as item difficulty variation (IDV). When instruction is of interest, and "groups" is a unit at which instruction is determined or delivered, then IDV signals value-added effects that can be influenced by either demographic or instructional variables.     

Effectiveness of lab-work learning environments in and out of school: A cluster randomized study

The issue of how to increase student motivation and achievement in science subjects is considered to be a major challenge in modern school systems. Lab-work learning environments in which students get direct (“hands-on”) experience with science content that is related to their everyday lives are posited to have positive effects on state/trait motivation and achievement, but there is a lack of sound empirical evidence to support this claim. In the present study, the effectiveness of a lab-work learning unit on the topic of “the chemistry of starch” was examined by applying a cluster randomized field study with three treatment conditions with lab-work elements and a control group. The first group was taught with lab-work elements in School only, the second group (SCOL & school) was taught in a combined condition encompassing both a SCOL (Science Center Outreach Lab) visit and classroom learning, the third group was taught entirely outside the school environment (SCOL only), and the fourth group was a wait-list control group, which was not exposed to a “starch” curriculum at the time of this study. Data from 1854 students were gathered in 67 ninth-grade classes on state motivation during the intervention and on trait motivation and achievement at pretest, posttest, and follow-up. Multilevel regression analyses revealed several differences between the lab-work conditions and the control group: Whereas the hands-on practical approach effectively enhanced state motivation with positive effects on joy, situational interest, situational competence, and reduced boredom in all three treatment conditions (School only, SCOL & school, and SCOL only), there were differences in trait effects: learning at school (School only and SCOL &school) increased achievement (posttest and follow-up), whereas the SCOL visit resulted in a small and spurious increase in trait motivation (reduced cost and increased competence beliefs only on the posttest).     

bh法观测采区煤巷底板坡度

跟着煤层顶板或底板施工的采区煤巷,底板坡度变化有时较大,要掌握、准确地计算底板坡度,必须实测出底板坡度变化各特征点的标高,采用常规方法有时完成很困难,为此提出一种新的观测方法bh法,从50 m范围以内或以外两个方面三种情况,分别阐述bh法在实际中的具体运用,从而表明bh法观测采区煤巷底板坡度是切实可行的.     

论英语考试“一条龙”可以先行

我国外语教学发展到今天,费时低效,分割重复,已成瓶颈。对外语教学实行“一条龙”的改革是突破瓶颈的根本措施。方法虽已找到,但这个革命性的变化关系到教育规划。要将它付诸实践尚须时日。而作为WTO的新成员国,我们所面临的国际交流合作与竞争却不容我们慢慢来。在我国,考试这种评估形式对教育的影响超出人们的想象。本文主张先尽快实行英语考试“一条龙”,以其巨大的反拨作用促进其他方面的改革。     

Reduction in State Anxiety Scores of Freshmen through a Course in Career Decision

A total of 112 Taiwanese junior college freshmen, assigned to an experimental group (N=59) and a control group (N=62), responded to the State-Trait Anxiety Inventory. After they had participated in a career education course the experimental group scores on state anxiety decreased. An analysis of variance of the state anxiety scores yielded two main significant effects (group and trait anxiety) and a two-way interaction was found with trait anxiety and group. There was clear support for the importance of the career education course. The results and implications for continuing research are discussed.     

Gauging Item Alignment Through Online Systems While Controlling for Rater Effects

The alignment of test items to content standards is critical to the validity of decisions made from standards‐based tests. Generally, alignment is determined based on judgments made by a panel of content experts with either ratings averaged or via a consensus reached through discussion. When the pool of items to be reviewed is large, or the content‐matter experts are broadly distributed geographically, panel methods present significant challenges. This article illustrates the use of an online methodology for gauging item alignment that does not require that raters convene in person, reduces the overall cost of the study, increases time flexibility, and offers an efficient means for reviewing large item banks. Latent trait methods are applied to the data to control for between‐rater severity, evaluate intrarater consistency, and provide item‐level diagnostic statistics. Use of this methodology is illustrated with a large pool (1,345) of interim‐formative mathematics test items. Implications for the field and limitations of this approach are discussed.     

The effects of training on the development of the ability to control variables

Based on a criterion test 27 fifth and sixth grade students were selected who could not control variables. Three groups were formed. The control group received no training; a second group received training relying upon external reinforcement, and the third group, training designed to induce internal cognitive conflict. The groups receiving training did only slightly better than the control group on the posttest. On the retention test one month later, all three groups had almost identical scores. The mean combined retention test score was found to be significantly greater than the pretest score. The improvement of the control and conflict groups supports Smedslund's⁸ finding that external reinforcement may not always be necessary for behavioral changes to occur. A further analysis of test scores led to the classification of students according to Piaget's developmental stages. During the course of the study a significant number of students improved in their stage placement. Based on retention test performance nearly half of the students having a mean age 11.8 years could be classed in late formal operations with regard to their ability to control variables. Inhelder and Piaget¹² reported that this level was not normally reached until 14 or 15 years of age. In conclusion, the results support the possibility that while development of the ability to control variables can be accelerated by training at the fifth and sixth grade level some children are surprisingly unaffected regardless of whether the training is based on external reinforcement or cognitive conflict procedures.     

Using a Multidimensional Differential Item Functioning Framework to Determine if Reading Ability Affects Student Performance in Mathematics

Many teachers and curriculum specialists claim that the reading demand of many mathematics items is so great that students do not perform well on mathematics tests, even though they have a good understanding of mathematics. The purpose of this research was to test this claim empirically. This analysis was accomplished by considering examinees that differed in reading ability within the context of a multidimensional DIF framework. Results indicated that student performance on some mathematics items was influenced by their level of reading ability so that examinees with lower proficiency classifications in reading were less likely to obtain correct answers to these items. This finding suggests that incorrect proficiency classifications may have occurred for some examinees. However, it is argued that rather than eliminating these mathematics items from the test, which would seem to decrease the construct validity of the test, attempts should be made to control the confounding effect of reading that is measured by some of the mathematics items.     

Helping Teachers Formulate Sound Test Accommodation Decisions for Students with Learning Disabilities

This paper introduces a data-based approach as an alternative way to help teachers formulate decisions about the validity of test accommodations for students with LD. Three rationales for the approach are provided: (a) an inadequate research base to guide decision-making; (b) the heterogeneity of the LD population; and (c) problems with teachers' use of subjective judgment. Well-controlled studies on test accommodations are too scarce to draw firm conclusions about effects for the group of students labeled learning disabled (LD). Moreover, in light of the heterogeneity of learning disabilities, the individual, rather than the LD label, may be the more appropriate unit for deciding which test accommodations preserve the validity of test scores for students with LD. In this paper, we provide a rationale for a data-based approach to help teachers formulate decisions about the validity of test accommodations for individual students with LD. Then we describe an objective assessment process teachers may use in determining valid test accommodations. We conclude with recommendations for practitioners.