The purpose of this study was to evaluate a model for considering general and specific elements of student experience in a gateway course in undergraduate Financial Accounting in a large university on the East Coast, USA. Specifically, the study evaluated a bifactor analytic strategy including a general factor of student classroom experience, conceptualized as student engagement as rooted in flow theory, as well as factors representing specific dimensions of experience. The study further evaluated the association between these general and specific factors and both student classroom practices and educational outcomes. The sample of students (N = 407) in two cohorts of the undergraduate financial accounting course participated in the Experience Sampling Method (ESM) measuring students' classroom practices, perceptions, engagement, and perceived learning throughout the one-semester course. Course grade information was also collected. Results showed that a two-level bifactor model fit the data better than two traditional (i.e., non-bifactor) models and also avoided significant multicollinearity of the traditional models. In addition to student engagement (general factor), specific dimensions of classroom experience in the bifactor model at the within-student level included intrinsic motivation, academic intensity, salience, and classroom self-esteem. At the between-student level, specific aspects included work orientation, learning orientation, classroom self-esteem, and disengagement. Multilevel Structural Equation Modeling (MSEM) demonstrated that sitting in the front of the classroom (compared to the sitting in the back), taking notes, active listening, and working on problems during class had a positive effect on within-student variation in student engagement and attention. Engagement, in turn, predicted perceived learning. With respect to between-student effects, the tendency to sit in front seats had a significant effect on student engagement, which in turn had a significant effect on perceived learning and course grades. A significant indirect relationship of seating and active learning strategies on learning and course grade as mediated by student engagement was found. Support for the general aspect of student classroom experience was interpreted with flow theory and suggested the need for additional research. Findings also suggested that active learning strategies are associated with positive learning outcomes even in educational environments where possibilities for action are relatively constrained.
Cryptocurrencies and blockchain technology are disruptive innovations at the vanguard of a new wave of the digital revolution. The far-reaching appeal, global reach, unprecedented mobility of capital, and multitude of trading venues have created a marketplace like no other. The economic fundamentals underlying this market are yet to be fully comprehended, as evidenced by the often-contradicting guidelines recommended by accounting firms, government agencies, and standard setters. Many of the definitions and models used for classical markets cannot be applied directly to cryptocurrency. Basic concepts must be reinterpreted, and models must be modified to fit the mechanics of these markets. In this article, we focus on one such concept: that of fair value. We argue that in light of the fragmentation of cryptocurrency markets and the global dispersion of trading venues, a principal market may be difficult to identify. The primary objective of this article is to present a methodology to dynamically designate principal markets and derive fair value prices for financial reporting using this designation.
This study examines whether there is an association between discretionary accounting changes and the accuracy of management earnings forecasts. First, we discuss the rationale for management's incentive to improve the accuracy of publicly disclosed earnings forecasts. We then conduct empirical tests to determine whether there is support for the hypothesized relationship between discretionary accounting changes and management forecast accuracy. The empirical results indicate that there is a strong association between high prechange forecast errors and the adoption of discretionary accounting changes. Most accounting changes are associated with significant forecast errors (i.e., deviations between the prechange earnings and predicted earnings are high); after adopting discretionary changes, the deviations are reduced. The results of a comparative analysis using analyst forecasts as a benchmark indicate that accounting changes are adopted when management forecast errors are higher than analyst forecast errors. Accounting changes are not used if management forecast errors are less than or equal to analyst forecast errors. The OLS regression results demonstrate that there is a significant association between the size of management forecast errors and the magnitude of the change in EPS. Overall, the study shows that management has an incentive to engage in discretionary accounting changes to improve the accuracy of their publicly disclosed earnings forecasts. The empirical results are, however, subject to two interpretations. Either discretionary accounting changes are used to improve the accuracy of publicly disclosed management earnings forecasts, or managers' earnings forecasts are sometimes disclosed in anticipation of planned accounting changes.
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