If One Goes Up the Other Must Come Down: Examining Gender Differences and Understanding of Models of Learning Style: A Non-Western Perspective

Models of learning style or approaches to learning have been operationalized in the Learning Process Questionnaire (LPQ). Guided by an assumed framework, the authors examine the construct validity of the LPQ in Botswana and investigate the similarities and differences in the process of learning in a non-Western context. Six structural equation modeling are used to test the association between cross-cultural variability and learning. Responses to this instrument are shown to have good internal consistency reliability, and support is provided for its construct validity in terms of its factorial structure. Results further reveal support for dimensions of deep and surface strategies, despite the differences in learning conceptualizations. The strategies utilized by students in the Western educational context are similar to those used by their African counterparts. Taken together, the interaction of gender and culture, makes us propose a relationship between culture, learning and life adaptations, thus extending the concept of learning style to account for the influence of culture. Tentatively, conceptual issues in learning process and suggestions for further research are presented.     

The evolution and problems of model management research

Models are a key resource for organizational decision making. The diversity, complexity, and reusability of this resource result in the need for model management systems. The construction of a model management system involves a modeling task dimension and a design level dimension. The modeling task dimension consists of model formulation, model representation, and model processing. The design level dimension addresses the architectural requirements of a system from a user's standpoint and a computer system's standpoint.The numerous architectures suggested in the model management systems literature address isolated areas identified by these dimensions. The research surveyed in this paper indicates that the primary focus has been on the system view of model representation. Before model management systems can be widely used in organizations, model management researchers must explore systems that address all areas of the task and design level dimensions.In this paper, we identify and justify the necessary dimensions of model management research. Next, the existing model management research is critically reviewed. Finally, neglected research areas are discussed, and investigations necessary for the development of integrated model management systems are suggested.     

The problem of population enumeration in Nigeria: further evidence from the 1978 voters' list

A history of the political and ethnic problems arising in recent Nigerian attempts to carry out a general population census is first outlined. The author then describes the procedures followed to develop a voters' registration list in preparation for the 1979 census and shows how the same problems arose. He examines the figures included in the voters' list, attempts to assess their accuracy, and considers their usefulness in estimating the population of the country. Alternative estimates of the population of Nigeria ranging from 94 to 103 million are presented, and consideration is given to how accurate these estimates might be. Their implications for Nigeria's socioeconomic development plans are also discussed.     

“Super-covariates”: Using predicted control group outcome as a covariate in randomized clinical trials

The power of randomized controlled clinical trials to demonstrate the efficacy of a drug compared with a control group depends not just on how efficacious the drug is, but also on the variation in patients' outcomes. Adjusting for prognostic covariates during trial analysis can reduce this variation. For this reason, the primary statistical analysis of a clinical trial is often based on regression models that besides terms for treatment and some further terms (e.g., stratification factors used in the randomization scheme of the trial) also includes a baseline (pre-treatment) assessment of the primary outcome. We suggest to include a “super-covariate”—that is, a patient-specific prediction of the control group outcome—as a further covariate (but not as an offset). We train a prognostic model or ensembles of such models on the individual patient (or aggregate) data of other studies in similar patients, but not the new trial under analysis. This has the potential to use historical data to increase the power of clinical trials and avoids the concern of type I error inflation with Bayesian approaches, but in contrast to them has a greater benefit for larger sample sizes. It is important for prognostic models behind “super-covariates” to generalize well across different patient populations in order to similarly reduce unexplained variability whether the trial(s) to develop the model are identical to the new trial or not. In an example in neovascular age-related macular degeneration we saw efficiency gains from the use of a “super-covariate”.     

The Wisdom of Eve: On Differentiating the Colours of Emotion that May Be Threats to Good Life

Emotion??s twin roles?C??unite and divide?? our daily life, thus motivating the good and the worst in human behaviour. The way one ??feels?? does influence the way one ??acts?? toward others. If this reasoning is correct, then behaviour can never be without motive or ??motiveless.?? Given the importance of emotions in human communication and decision making, the context of intergroup relations, with its themes of prejudice, stereotyping and discrimination against culturally dissimilar was touched on selectively. Using the Differential Emotions Scale and building upon Boyle??s (Personality 56:747?C750, 1984) work, with students, the present study reports a repeated-measure multiple discriminant function analysis for items across raters. The findings further indicate that most of the DES items are sensitive indicators. The correspondence of some of the results with prior research findings makes facial emotions less the holy grail of the social behaviour field. Likely consequences of emotions are considered, and research needs are discussed vis-a-vis uplifting individual happiness, collective identity and sense of connection to others. Perhaps its implications can be extended to the literature, thus revealing how the different lenses through which human emotions are usually viewed are connected by the incipient/concept attitude and self-identification/labelling that run through each of them.     

Diagnostic bias in organizational consultation

This article is intended to improve consultation practice by explaining the significance of models, heuristics, and diagnostic aids in organizational diagnosis. The role of diagnostic models in determining the consultant's frame of reference is explained. Evidence that organizational consultants consciously use diagnostic models is provided by citing two independent studies that revealed about 70% of the consultants reported that a diagnostic model was used. The availability, representativeness, and anchoring heuristics used by diagnosticians are summarized and examples of their use are cited. Readers are warned that bias occurs from misapplying the heuristics. However, guidance on correctly applying the heuristics is provided. The development and improvement of diagnostic expertise is explained from the perspective of learning through education as well as feedback received from clients, colleagues (as shadow consultants and as consulting team members), and self. Thus, written from the perspective of a consultant, the article provides a practical presentation on diagnostic bias, supported by theory and empirical research. It should appeal not only to a consulting constituency (i.e. practicing consultants, consultant trainers, and novice consultants), but also to the large number of potential clients (i.e. organizational decision-makers). Future research directions are discussed in terms of (1) the research that has identified relationships between consultant characteristics (e.g. Jungian constructs) and diagnostic information, and (2) the potential of expert systems in organizational diagnosis.