Dimensionality in Compensatory MIRT When Complex Structure Exists: Evaluation of DETECT and NOHARM

This study investigated the effect of complex structure on dimensionality assessment in compensatory multidimensional item response models using DETECT- and NOHARM-based methods. The performance was evaluated via the accuracy of identifying the correct number of dimensions and the ability to accurately recover item groupings using a simple matching similarity (SM) coefficient. The DETECT-based methods yielded higher proportion correct than the NOHARM-based methods in two- and three-dimensional conditions, especially when correlations were ≤.60, data exhibited ≤30% complexity, and sample size was 1,000. As the complexity increased and the sample size decreased, the performance of the methods typically diminished. The NOHARM-based methods were either equally successful or better in recovering item groupings than the DETECT-based methods and were mostly affected by complexity levels. The DETECT-based methods were affected largely by the test length, such that with the increase of the number of items, SM coefficients would decrease substantially.     

Prospective teachers' initial conceptions about pupils' understanding of science and mathematics

Earlier reports have shown that prospective teachers' conceptions about teaching science to a high degree are resistant and do not change substantially during the teacher‐training programme. In our investigation we elucidate the prospective teachers' initial conceptions about pupils' understanding of science and mathematics. We applied ‘The Lesson Preparation Method' and used a phenomenographic approach in order to reveal the range of conceptions that the prospective teachers hold. A third of the prospective teachers did not consider pupils' conceptions when planning lessons. The rest of the 32 participants expressed awareness; some of the prospective teachers even referred to subject‐specific teaching experience. Also regarding the prospective teachers' conceptions about pupils' knowledge and beliefs, as well as about pupils' difficulties, there was a significant diversity. By raising these issues about pedagogical content knowledge the prospective teachers' conceptions can be extended and developed during the education.     

Factors related to doctoral dissertation topic selection

Although the completed doctoral dissertation represents the culmination of a doctoral program, is often published in journal articles, and serves as the foundation of the early research career of the author, the dissertation has received relatively little attention as a subject of research in its own right. To learn more about how students select their dissertation topics, all doctoral graduates of a major midwestern research university over the one year period from spring quarter, 1986, through winter quarter, 1987, were surveyed. Results indicate that a number of factors influence the selection of a dissertation topic, but not surprisingly the most important is the student's own preference. The factors affecting the choice of topics include the preference of the adviser, trends in the field, the likelihood that the research will be published, and the projected benefit of the research on the student's job prospects. The importance of the factors vary by field and in some cases by gender. When students select their topic and the extent to which the adviser and dissertation committees are responsive to the student also vary by field.     

Educational diagrams

According to C.S. Peirce, diagrammatic constructions may be represented by words in a sentence, an algebraic formula, or a graphic display. They are the basis of all valid reasoning and provide a significant means for discovering unexpected truths. Using Peirce's work as a point of departure, the sources and uses of diagrams in education are discussed. With some educators, like Froebel, these diagrams are presented in a highly conspicuous manner. With others, they may be much less noticeable. But they are always there in any reasoned discourse, in one form or another. To the extent that these diagrams are followed, educational theory and practice may be considered to be controlled by diagrammatic constructions.     

“Teachers’ Hegemony Sucks”: examining Beavis and Butt-head for signs of life

The analysis of cultural artefacts, such as cartoons and films, provides the potential to gain insights into both the professional identities of teachers and the behaviour and self-concepts of students. This paper suggests that the ostensibly banal animated cartoon characters Beavis and Butt-head offer some utility in this respect. The paper explores aspects of the stereotypes and behaviour represented in the Beavis and Butt-head series and briefly discusses some possible interpretations of these images.     

Small, medium and large hypertext

This paper critically reviews the different types of abstractions and implementations in the hypertext area and proposes that three types of hypertext exist, namely, small-, medium- and large-volume hypertext. For a single person dealing with a single text the prominent issue is the model of the text that the user browses; this is small-volume hypertext. When a few people are involved in creating a few texts, records are maintained as to who created what and when; this is medium-volume hypertext. In large-volume hypertext the document collection is massive and special institutions are responsible for filtering and indexing material against which arbitrarily many other people issue searches. All these aspects of hypertext have in common an abstraction of text as a graph rather than a line and an ultimate goal of facilitating communication among people.     

Power in Bayesian Mediation Analysis for Small Sample Research

Bayesian methods have the potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This article compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N ≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N ≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results.