Decomposing trait and state variability in general and specific subjective task value beliefs

Expectancy-value researchers have theorized about the extent to which subjective task value components are more trait-like or more state-like. Using a bifactor representation of subjective task value data, the current study aimed to examine the degree of trait-state variation in general subjective task value, specific attainment value, specific intrinsic value, and specific utility value. The relations of both between and within components of the subjective task value constructs with academic self-efficacy beliefs were also examined. Results indicate that, in an undergraduate life science learning context (n = 169), the general subjective task value factor was the most trait-like of the subjective task value constructs. With respect to specific value beliefs, attainment value was composed of nearly equal amounts of trait and state variation, intrinsic value was composed of the largest amount of trait variation, and utility value exhibited the most state-like variation. Additionally, findings suggest that trait-like and state-like general subjective task value, trait-like specific intrinsic value, and state-like attainment value were positively associated with self-efficacy. Finally, we propose a model of trait- state dynamics in subjective task value.     

Assessing construct of DIBELS: Measurement invariance of DIBELS subscales,from kindergarten to the first grade

A challenge using the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) in studying reading growth is that reading skills children exhibit change by age. In order to study growth using changing subscales, it is necessary to examine measurement invariance and measurement structure underlying the different subscales. The purpose of this paper is to examine the measurement structure of the DIBELS subscales, particular measurement invariance. The results indicate that the DIBELS subscales do not seem to have metric invariance but they do share a common factor over time, suggesting that the same construct of reading skills were measured but they manifested in the different fashion over time.     

Towards a unified theory of task-specific motivation

This study aims to integrate the current proliferation of motivation theories in a Unified Model of Task-specific Motivation (UMTM). According to this model readiness for action results from an interaction between four relatively independent types of valences that can be classified as affective or cognitive, and positive or negative. Affective valences are expectations about feelings while doing an activity; cognitive valences are expectations about the value of the consequences of an activity. In current theories these types of valences are designated as intrinsic, respectively extrinsic motives. Valences, furthermore, can be positive, but also negative. Positive valences give rise to approach motivation, negative valences to avoidance motivation. Important factors that influence valences are autonomy, feasibility expectation, and relatedness, each of which can be distinguished in a personal and a contextual facet, and subjective norm. In conclusion, some theoretical and practical implications are suggested and some issues for future research are proposed.     

Structural validity and invariance of the Feedback Perceptions Questionnaire

Despite a growing interest in instructional feedback, students’ feedback perceptions received limited attention. We examined the structural validity and measurement invariance of the Feedback Perceptions Questionnaire (FPQ). The FPQ measures feedback perceptions in terms of perceived fairness, usefulness, acceptance, willingness to improve, and affect. Secondary school students (N = 1486) received a fictional scenario containing Concise General Feedback or Elaborated Specific Feedback by a fictional peer. Students rated their perceptions as if they had received the feedback themselves. Confirmatory Factor Analysis (CFA) supports the structural validity of the FPQ and its invariance for the two types of peer feedback, gender, four grade-levels and two tracks. Perceived fairness of peer feedback was a strong positive predictor of willingness to improve and affect, whereas perceived usefulness and acceptance of peer feedback showed a more complex pattern in predicting willingness to improve and affect.     

Expectancy of success,attainment value,engagement, and Achievement: A moderated mediation analysis

The aim of this study was to examine how expectancy of success, attainment value, and their interaction predicted behavioural engagement, and how behavioural engagement, in turn, predicted achievement. Data were collected from 586 English students aged 10–11 years in their final year of primary school. Expectancy of success was positively related to subsequent achievement directly and indirectly, mediated by behavioural engagement, over and above the variance accounted for by prior achievement and behavioural engagement. Indirect relations from expectancy of success to achievement were moderated by attainment value. Higher attainment value protected performance from low expectancy of success by increasing behavioural engagement. The compensatory role of high attainment value diminished at higher levels of expectancy of success.     

Assessing value beliefs among university students: Validation of the Value Beliefs Questionnaire for University Students (VBQU)

The present study with 353 students aimed to examine the validity of a questionnaire called the Value Beliefs Questionnaire for University Students (VBQU) measuring five value beliefs among university students, namely: intrinsic value, attainment value, cost, utility for daily life, and utility for career. Furthermore, this study strived to explore the situated expectancy-value theory by linking those five value beliefs to multiple individual characteristics of university students (i.e., academic self-concept, procrastination, test anxiety, academic achievement). Results of CFA provided strong support for a 5-factor structure and a hierarchical structure of four major value factors (i.e., intrinsic, attainment, cost, utility) and two utility factors. Significant intercorrelations among the five value beliefs and correlations of the five value beliefs with the other individual characteristics of university students also established validity evidence of the VBQU. In line with (S)EVT, academic self-concept and intrinsic value significantly interacted with each other in predicting academic achievement.     

Evaluation of Structural Relationships in Autoregressive Cross-Lagged Models Under Longitudinal Approximate Invariance:A Bayesian Analysis

To infer longitudinal relationships among latent factors, traditional analyses assume that the measurement model is invariant across measurement occasions. Alternative to placing cross-occasion equality constraints on parameters, approximate measurement invariance (MI) can be analyzed by specifying informative priors on parameter differences between occasions. This study evaluated the estimation of structural coefficients in multiple-indicator autoregressive cross-lagged models under various conditions of approximate MI using Bayesian structural equation modeling. Design factors included factor structures, conditions of non-invariance, sizes of structural coefficients, and sample sizes. Models were analyzed using two sets of small-variance priors on select model parameters. Results showed that autoregressive coefficient estimates were more accurate for the mixed pattern than the decreasing pattern of non-invariance. When a model included cross-loadings, an interaction was found between the cross-lagged estimates and the non-invariance conditions. Implications of findings and future research directions are discussed.     

A structural equation model analyzing the relationship of student achievement motivations and personality factors in a range of academic subject-matter areas

The question of subject-specificity of achievement motivations is important, both for educational psychology, as well as for educational policy. This study contributes to the investigation of the heterogeneity in achievement motivations in the context of the expectancy-value model. Whereas existing research deals with middle and high school students and their motivations for a range of broad domains, this article focuses on university students (n = 264) and subject domains that are more congruent. We adopt an affect-extended version of the expectancy-value model. Using structural equation methods, we are able to decompose achievement motivations in generic and subject-specific components.     

非线性二阶方程周期边值问题解的存在性

在常微分方程理论中,非线性常微分方程周期边值问题是比较重要的数学问题,由于在人们生活中普遍存在着周期现象,所以研究这类问题具有比较重大的理论价值和实际意义.现今,由于科技不断进步,尤其是非线性泛函理论的不断运用,人们开始用它来进行边值问题的研究.在Banach空间中对非线性常微分方程的多解存在性进行研究.     

Understanding the behavioral intention to play Austronesian learning games: from the perspectives of learning outcome,service quality,and hedonic value

Although ubiquitous learning is a novel and creative teaching approach, two key issues inhibit its success overall: a lack of appropriate learning strategies regarding learning objectives, and ineffective learning tools for receiving knowledge regarding the chosen subjects. To address these issues, we develops and designs a game-based educational app and an object-linked knowledge environment in order to help learners learn about Taiwan’s Austronesian culture. 70 fifth-grade students are split into experimental and control groups to determine whether there are significant learning differences. For the experimental group, we use a questionnaire survey to assess students’ learning condition and to measure their willingness to continue to use this app. The questionnaire examines mobile learning from the perspectives of service quality, hedonic value,and certain control variables. Service quality reliability is found to be the key factor driving learners’ willingness to use the system. The perception of hedonic value also has significant influence on learners’ willingness. The control variable of subjective norm is found to be beneficial in encouraging learners to use the system, thus affecting and increasing learners’ willingness. We conclude that in an outdoor object-linked knowledge environment, students learn more effectively when the activities involve the use of an educational app.     

The Model Size Effect in SEM: Inflated Goodness-of-Fit Statistics Are Due to the Size of the Covariance Matrix

The size of a model has been shown to critically affect the goodness of approximation of the model fit statistic T to the asymptotic chi-square distribution in finite samples. It is not clear, however, whether this “model size effect” is a function of the number of manifest variables, the number of free parameters, or both. It is demonstrated by means of 2 Monte Carlo computer simulation studies that neither the number of free parameters to be estimated nor the model degrees of freedom systematically affect the T statistic when the number of manifest variables is held constant. Increasing the number of manifest variables, however, is associated with a severe bias. These results imply that model fit drastically depends on the size of the covariance matrix and that future studies involving goodness-of-fit statistics should always consider the number of manifest variables, but can safely neglect the influence of particular model specifications.     

Toward Improving the Modeling of MTMM Data: A Response to Geiser,Koch, and Eid (2014)

Geiser, Koch, and Eid (2014) expressed their views on an article we published describing findings from a simulation study and an empirical study of multitrait–multimethod (MTMM) data. Geiser and colleagues raised concerns with (a) our use of the term bias, (b) our statement that the correlated trait–correlated method minus one [CT–C(M–1)] model is not in line with Campbell and Fiske’s (1959) conceptualization of MTMM data, (c) our selection of a data-generating model for our simulation study, and (d) our preference for the correlated trait–correlated method (CT–CM) model over the CT–C(M–1) model. Here, we respond to and elaborate on issues raised by Geiser et al. We maintain our position on each of these issues and point to the interpretational challenges of the CT–C(M–1) model. But, we clarify our opinion that none of the existing structural models for MTMM data are flawless; each has its strengths and each has its weaknesses. We further remind readers of the goal, findings, and implications of our recently published article.     

Humanoid robots in higher education: Evaluating the acceptance of Pepper in the context of an academic writing course using the UTAUT

This study investigates the acceptance of social robots by higher education students in the social sciences. Pepper, a humanoid social robot from SoftBank Robotics, provided a sample of its capabilities during a first semester, large-scale, university course, “Introduction to academic writing.”From this course, 462 freshmen participated in our survey. The unified theory of acceptance and use of technology (UTAUT) acts as the conceptual framework, and partial least squares structural equation modelling (PLS-SEM) as the method for data analysis. The four perceived characteristics—trustworthiness, adaptiveness, social presence and appearance—all predict the intention to use the robot for learning purposes; anxiety regarding making mistakes in handling the robot and about privacy issues are not significant predictors. An importance-performance map analysis indicated adaptiveness as the robot’s most important characteristic for predicting student behavioural intention. Overall, however, the study shows that students do not have the intention to rely on social robots for learning purposes at the current level of state-of-the-art technology: behavioural intention reaches only 36.6% of the theoretical maximum.