Does adviser mentoring add value? A longitudinal study of mentoring and doctoral student outcomes

This study of the impact of doctoral adviser mentoring on student outcomes was undertaken in response to earlier research that found (a) students with greater incoming potential received more adviser mentoring, and (b) adviser mentoring did not significantly contribute to important student outcomes, including research productivity [Green, S. G., and Bauer, T. N. (1995). Personnel Psychology 48(3): 537–561]. In this longitudinal study spanning 5 1/2 years, the effect of mentorship on the research productivity, career commitment, and self-efficacy of Ph.D. students in the ‘hard’ sciences was assessed, while controlling for indicators of ability and attitudes at program entry. Positive benefits of mentoring were found for subsequent productivity and self-efficacy. Mentoring was not significantly associated with commitment to a research career.     

Making Connections: Learning and Teaching Chemistry in Context

Even though several studies have reported positive attitudinal outcomes from context-based chemistry programs, methodological obstacles have prevented researchers from comparing satisfactorily the chemistry-learning outcomes between students who experience a context-based program with those who experience a content-driven program. In this narrative inquiry we are able to address the question: how do the recalled experiences of a student and her teacher in context-based and concept-based chemistry programs compare? From the student’s unique perspective of experiencing both programs with the same teacher, we have constructed our collective account around four themes; namely, the extent to which the student makes connections between chemistry concepts and real-world contexts, developing research independence through engaging in extended experimental investigations related to contexts, learning chemistry concepts through contexts, and conceptual sequencing in a context-based program. The student reported real-world connections between chemistry concepts and contexts, found her engagement in the context-driven tasks interesting and productive, and identified connected sequences of concepts across the contexts studied. Despite difficulties for teachers who are required to shift pedagogies, the student’s lived experiences and outcomes from a context-based program provide some encouragement in working through these issues.     

Building a model to define the concept of teacher success in Hong Kong

The research studies how outstanding teachers from Hong Kong conceptualize teacher success or effectiveness. This study adds to the knowledge base concerned by raising the importance of the coexistence of personal attributes and professional qualities as well as contextual factors, in bringing out the success of a teacher. It draws the attention of teacher educators/trainers and school administrators to the necessity of viewing the concept of teacher success from a broader perspective, instead of focusing narrowly on the professional qualities of a teacher. It also provides insights for school administrators in selecting teachers or supporting their work.     

Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods

A number of psychometricians have suggested that parallel analysis (PA) tends to yield more accurate results in determining the number of factors in comparison with other statistical methods. Nevertheless, all too often PA can suggest an incorrect number of factors, particularly in statistically unfavorable conditions (e.g., small sample sizes and low factor loadings). Because of this, researchers have recommended using multiple methods to make judgments about the number of factors to extract. Implicit in this recommendation is that, when the number of factors is chosen based on PA, uncertainty nevertheless exists. We propose a Bayesian parallel analysis (B-PA) method to incorporate the uncertainty with decisions about the number of factors. B-PA yields a probability distribution for the various possible numbers of factors. We implement and compare B-PA with a frequentist approach, revised parallel analysis (R-PA), in the contexts of real and simulated data. Results show that B-PA provides relevant information regarding the uncertainty in determining the number of factors, particularly under conditions with small sample sizes, low factor loadings, and less distinguishable factors. Even if the indicated number of factors with the highest probability is incorrect, B-PA can show a sizable probability of retaining the correct number of factors. Interestingly, when the mode of the distribution of the probabilities associated with different numbers of factors was treated as the number of factors to retain, B-PA was somewhat more accurate than R-PA in a majority of the conditions.     

Loglinear analysis of cross-classified ordinal data: applications in developmental research

This article provides an introduction to loglinear analysis of cross-classification tables, including tables with nominal and ordinal variables. Loglinear models offer several advantages over the more commonly used chi-square test of independence, including the ability to analyze 3-, 4-, and higher-way interactions, the ability to determine whether the association between variables is linear or nonlinear, and the ability to interpret scale scores assigned to categories of an ordinal variable. After a review of the advantages of loglinear modeling, the chi-square test of independence is compared with the loglinear model of independence. This comparison serves to introduce the notation and terminology of loglinear modeling. The overall strategy of loglinear modeling is introduced next; then special loglinear models for ordinal data are reviewed. Each model discussed in the article is applied to data from the developmental literature.     

Time and response matching with topographically different responses

Four pigeons were exposed to several nonindependent concurrent variable-interval schedules of reinforcement. One schedule component required a keypecking response; the other component required a treadlepressing response. The birds matched the ratio of their behavior (as measured by responses and time) between the two topographically different responses to the ratio of reinforcement in those two components. When additional foods not contingent on a keypeck or treadle-press were then added, the birds matched time spent in the components to total rates of food delivered in those components; response matching was somewhat disrupted. The matching law, developed under concurrent variable-interval schedules requiring similar responses, can thus account for choice behavior involving topographically different responses.     

The development of a hypertext-based tutor for Geographical Information Systems

Experience gained in the construction of the world's first Geographical Information Systems tutor, ARCDEMO, emphasised the importance of accommodating different learning strategies. ARCDEMO, while highly successful, suffered from static graphical displays, a single pre-determined access path, and an overall design which restricted its scope in use. The Geographical Information System Tutor (GIST) was developed to address these problems using Apple's object-orientated HyperCard software. GIST incorporates a 'point-and-click' interface with graphical cues to initiate operations which include animated demonstrations, step-by-step illustrative graphics and graphical displays capable of user modification. The system was designed with two alternative access modes, serial or browsing , to allow different classes of user to work through the material in their preferred fashion. The use of GIST in undergraduate and short course teaching has shown how users respond well to the interface and find graphical explanations easy to follow.