Development and validation of the Decision-Specific Reinvestment Scale

Abstract

Items from the Reinvestment Scale were modified to create a decision-specific version of the scale. Principal components analysis of responses from 165 participants revealed one-, two-, three-, and four-factor solutions for the Decision-Specific Reinvestment Scale. Confirmatory factor analysis of responses from a second sample of 111 participants revealed that a 13-item two-factor solution showed the best fit. The first factor comprised six items referring to conscious monitoring of the process involved in making a decision, and was termed decision reinvestment. The second factor, decision rumination, comprised seven items related to focus on negative evaluations of previous poor decisions. In an initial assessment of predictive validity, Decision-Specific Reinvestment Scale scores of 59 skilled team sport players were found to be highly correlated with coaches' ratings of players' tendency to choke under pressure (r = 0.74), with high Decision-Specific Reinvestment Scale scores indicating greater susceptibility to poor decision-making under pressure. It was concluded that the Decision-Specific Reinvestment Scale highlights a performer's predisposition to engage in behaviours detrimental to performance under pressure, namely decision reinvestment and decision rumination.     

Child, Program, and Family Ecological Variables in Early Intervention

This study is based on a conceptual framework which emphasized the importance of viewing early intervention outcomes in relation to both program and nonprogram variables. Three broad classes of independent variables were included in the framework child, program, and family ecology. The unique and combined contributions of these three sets of variables to the prediction of three indices of intervention outcome was assessed through regression techniques. As much as 68% of the variance in children's post-intervention developmental age (DA2) was explained by the combined influence of all three classes of variables. All three classes of variables again contributed uniquely to the prediction of parental satisfaction with the intervention, explaining 45% of the variance. The three classes of variables explained 36% of the variance in children's rate of development during the intervention (RDI), although the contribution of the program class was very minimal. In addition to ascertaining the contributions of sets of variables, the importance of individual variables within sets was also examined. Results from both types of analysis underscored the important role of nonprogram variables in the determination of both child and parental outcomes. The implications of these findings for the design and evaluation of early intervention are discussed.     

Anticipating the experience of higher education through computer simulation

In industry the advantages of realistic job preview have been much discussed, but lit-tle is currently done in British schools to prepare students for higher education. This article describes the development stages of a principled adventure game to simulate the experience of higher education. Playing this game is intended to provide realistic role preview for prospective students.The simulation has been developed out of an earlier board game derived, to some extent, from research findings. More recent research on student learning has provided the principles on which the new simulation game is being based. The game not only allows students to try out different study strategies, it also provides advice tailored to the specific strategies used by the individual stu-dent in interacting with the computer. This simulation can be seen as a simple expert system providing a form of intelligent tutoring.The architecture of the computer simulation is described, together with the strategies used to ensure that the game, and the advice provided, are both controlled by principles derived from the research on student learning. Illustrations are used to indicate how a student would experience the interactions with the computer, and how the rules produce tailored advice.     

Approaches to learning,evaluations of teaching,and preferences for contrasting academic environments

Previous research has demonstrated that the academic environments provided by departments in higher education have direct effects on students' approaches to studying. But other studies have indicated that these effects are mediated by the students' own perceptions of those environments. Here two studies are reported which explore the relationships between approaches to learning, or study orientations, and perceptions of the academic environment. Those perceptions are measured in two distinct ways, one which minimises the effects of differential perceptions, and one which highlights them. Factor analyses of the responses of three groups of students taking engineering and psychology are used to clarify the nature of the relationships between study orientations and perceptions of the academic environment. It is found, as in earlier studies, that there are relationships which associate deep approaches with perceptions of relevance, and surface approaches with a heavy workload. But here it is also shown that students with contrasting study orientations are likely to define effective teaching in ways which reflect those orientations. Implications both for the design of feedback questionnaires and for the improvement of teaching and learning in higher education are discussed.     

A Cross–Cultural Environmental Education Model

Abstract

This study assessed the level of scientific and natural resource knowledge that fourth-, eighth-, and eleventh-grade students in Maine possess concerning acidic deposition. A representative sample of public school students (N = 175) was interviewed on twelve concept principles considered critical to a full understanding of the acidic deposition problem. These included geological, meteorological, ecological, political, and economic concepts. Student knowledge was rated for each concept principle on a scale of complete, high partial, low partial, or no understanding. Common misconceptions were also noted. Generalized correct concept statements of current student knowledge are reported, as well as generalized missing concepts. Our conclusions have implications for teaching about acidic deposition and the design of environmental education curriculum materials based upon student knowledge. This information can help teachers better instruct students about current environmental problems and thus help learners gain an appreciation for the complex and multidisciplinary nature of science and the environment.     

Literary precocity: An exceptional case among exceptional cases

This article presents the case of Geoffrey, a prolific 5‐year‐old writer. It examines his writing and how his intrapersonal factors and propitious environment contribute to his prodigious output. Childhood precocity is presented as an age‐based comparable rather than as an adult‐based predictor, consistent with Jackson's (2000) domain‐specific developmental theory of giftedness. Geoffrey demonstrated highly precocious writing, both in production and in sophistication, and he demonstrated these abilities across a range and variety of content topics. The convergence of contributing influences evident in Geoffrey's life supports a growing literature on the coalescence factor within precocity. This implies that parents and educators have to carefully consider their influences. Suggestions are made concerning how developmental models of giftedness may need to expand to accommodate precocious writers.     

Patterns of response to an approaches to studying inventory across contrasting groups and contexts

The development of the Approaches and Study Skills Inventory for Students (ASSIST) is reported, which incorporates a revised version of the Approaches to Studying Inventory. This questionnaire was completed by three separate samples; 1284 mainly first-year students from six British universities, 466 first-year students from a Scottish technological university; and 219 students from a ‘historically disadvantaged” South African university. Analyses of these data were designed to explore the patterns of response found in sub-groups which varied in terms of their levels of attainment and contexts. Maximum likelihood analysis of the largest sample confirmed the expected three factors of deep, surface apathetic, and strategic approaches to studying, and almost identical patterns were also found in the other two samples, and in students having contrasting levels of attainment. There were, however, some interesting minor differences in the South African sample. K-means relocation cluster analysis was then carried out on the largest sample and produced clusters with generally coherent patterns of response. However, one persistent low attainment cluster showed unexpected, dissonant patterns of response, combining moderately high scores on the sub-scales of both deep and surface apathetic approaches, associated with low scores on the strategic approach.