891 resultados para Formative necessities


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Cadogan and Lee (this issue) discuss the problems inherent in modeling formative latent variables as endogenous. In response to the commentaries by Rigdon (this issue) and Finn and Wang (this issue), the present article extends the discussion on formative measures. First, the article shows that regardless of whether statistical identification is achieved, researchers are unable to illuminate the nature of a formative latent variable. Second, the study clarifies issues regarding formative indicator weighting, highlighting that the weightings of formative components should be specified as part of the construct definition. Finally, the study shows that higher-order reflective constructs are invalid, highlights the damage their use can inflict on theory development and knowledge accumulation, and provides recommendations on a number of alternative models which should be used in their place (including the formative model). © 2012 Elsevier Inc.

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Researchers often develop and test conceptual models containing formative variables. In many cases, these formative variables are specified as being endogenous. This article provides a clarification of formative variable theory, distinguishing between the formative latent variable and the formative composite variable. When an endogenous latent variable relies on formative indicators for measurement, empirical studies can say nothing about the relationship between exogenous variables and the endogenous formative latent variable: conclusions can only be drawn regarding the exogenous variables' relationships with a composite variable. The authors also show the dangers associated with developing theory about antecedents to endogenous formative variables at the (aggregate) formative latent variable level. Modeling relationships with endogenous formative variables at the (disaggregate) indicator level informs richer theory development, and encourages more precise empirical testing. When antecedents' relationships with endogenous formative variables are modeled at the formative latent variable level rather than the formative indicator level, theory construction can verge on the superficial, and empirical findings can be ambiguous in substantive meaning.

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This paper presents a causal explanation of formative variables that unpacks and clarifies the generally accepted idea that formative indicators are ‘causes’ of the focal formative variable. In doing this, we explore the recent paper by Diamantopoulos and Temme (AMS Review, 3(3), 160-171, 2013) and show that the latter misunderstand the stance of Lee, Cadogan, and Chamberlain (AMS Review, 3(1), 3-17, 2013; see also Cadogan, Lee, and Chamberlain, AMS Review, 3(1), 38-49, 2013). By drawing on the multiple ways that one can interpret the idea of causality within the MIMIC model, we then demonstrate how the continued defense of the MIMIC model as a tool to validate formative indicators and to identify formative variables in structural models is misguided. We also present unambiguous recommendations on how formative variables can be modelled in lieu of the formative MIMIC model.

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Feedback is a key concern for higher education practitioners, yet there is little evidence concerning the aspects of assessment feedback information that higher education students prioritise when their lecturers’ time and resources are stretched. One recent study found that in such circumstances, students actually perceive feedback information itself as a luxury rather than a necessity. We first re-examined that finding by asking undergraduates to ‘purchase’ characteristics to create the ideal lecturer, using budgets of differing sizes to distinguish necessities from luxuries. Contrary to the earlier research, students in fact considered good feedback information the single biggest necessity for lecturers to demonstrate. In a second study we used the same method to examine the characteristics of feedback information that students value most. Here, the most important perceived necessity was guidance on improvement of skills. In both studies, students’ priorities were influenced by their individual approaches to learning. These findings permit a more pragmatic approach to building student satisfaction in spite of growing expectations and demands.

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In this rejoinder, we provide a response to the three commentaries written by Diamantopoulos, Howell, and Rigdon (all this issue) on our paper The MIMIC Model and Formative Variables: Problems and Solutions (also this issue). We contrast the approach taken in the latter paper (where we focus on clarifying the assumptions required to reject the formative MIMIC model) by spending time discussing what assumptions would be necessary to accept the use of the formative MIMIC model as a viable approach. Importantly, we clarify the implications of entity realism and show how it is entirely logical that some theoretical constructs can be considered to have real existence independent of their indicators, and some cannot. We show how the formative model only logically holds when considering these ‘unreal’ entities. In doing so, we provide important counter-arguments for much of the criticisms made in Diamantopoulos’ commentary, and the distinction also helps clarify a number of issues in the commentaries of Howell and Rigdon (both of which in general agree with our original paper). We draw together these various threads to provide a set of conceptual tools researchers can use when thinking about the entities in their theoretical models.

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The use of the multiple indicators, multiple causes model to operationalize formative variables (the formative MIMIC model) is advocated in the methodological literature. Yet, contrary to popular belief, the formative MIMIC model does not provide a valid method of integrating formative variables into empirical studies and we recommend discarding it from formative models. Our arguments rest on the following observations. First, much formative variable literature appears to conceptualize a causal structure between the formative variable and its indicators which can be tested or estimated. We demonstrate that this assumption is illogical, that a formative variable is simply a researcher-defined composite of sub-dimensions, and that such tests and estimates are unnecessary. Second, despite this, researchers often use the formative MIMIC model as a means to include formative variables in their models and to estimate the magnitude of linkages between formative variables and their indicators. However, the formative MIMIC model cannot provide this information since it is simply a model in which a common factor is predicted by some exogenous variables—the model does not integrate within it a formative variable. Empirical results from such studies need reassessing, since their interpretation may lead to inaccurate theoretical insights and the development of untested recommendations to managers. Finally, the use of the formative MIMIC model can foster fuzzy conceptualizations of variables, particularly since it can erroneously encourage the view that a single focal variable is measured with formative and reflective indicators. We explain these interlinked arguments in more detail and provide a set of recommendations for researchers to consider when dealing with formative variables.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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The objective of this paper is to conceptualize Supply Chain Resilience (SCRes) and identify which supply chain capabilities can support the containment of disruptions and how these capabilities affect SCRes. Through a systematic and structured review of literature, this paper provides insights into the conceptualization and research methodological background of the SCM field. A total of one hundred and thirty four carefully selected refereed journal articles were systematically analyzed leading to the introduction of a novel definition for SCRes, which the authors view as the as “the ability to proactively plan and design the Supply Chain network for anticipating unexpected disruptive (negative) events, respond adaptively to disruptions while maintaining control over structure and function and transcending to a post-event robust state of operations, if possible, more favorable than the one prior to the event, thus gaining competitive advantage”. Finally, a critical examination of existing conceptual frameworks for understanding the relationships between the SCRes concept and its identified formative elements, is taking place.

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This article recognizes the importance of Picasso’s brief five year stay in A Coruña, being the place where he began his artistic studies. Through the narration of the events experienced by the artist in Galicia, the objective of this text is to compare his work at that time with his later paintings. In both stages one can appreciate similarities in composition and the use of colour.

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This essay deals with the teaching of literary translation in a university context from a methodological perspective. The study is firstly framed within the PACTE principles regarding the acquisition of translation competences; then, we proceed to analyze and discuss three relevant aspects to the practice and the teaching of literary translation: i) the approach to style; ii) the explicit differentiation between dialogue and narration; and iii) some issues related to the literary translation market. In order to achieve the proposed objectives, the essay is widely illustrated with translation examples taken from the classroom.

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Abstract. The performance objectives used for the formative assessment of com- plex skills are generally set through text-based analytic rubrics[1]. Moreover, video modeling examples are a widely applied method of observational learning, providing students with context-rich modeling examples of complex skills that act as an analogy for problem solving [1]. The purpose of this theoretical paper is to synthesize the components of video modeling and rubrics to support the formative assessment of complex skills. Based on theory, we argue that application of the developed Video Enhanced Rubrics (VER) fosters learners’ development of mental models, quality of provided feedback by various actors and finally, the learners mastery of complex skills.

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To learn complex skills, like collaboration, learners need to acquire a concrete and consistent mental model of what it means to master this skill. If learners know their current mastery level and know their targeted mastery level, they can better determine their subsequent learning activities. Rubrics support learners in judging their skill performance as they provide textual descriptions of skills’ mastery levels with performance indicators for all constituent subskills. However, text-based rubrics have a limited capacity to support the formation of mental models with contextualized, time-related and observable behavioral aspects of a complex skill. This paper outlines the design of a study that intends to investigate the effect of rubrics with video modelling examples compared to text-based rubrics on skills acquisition and feedback provisioning. The hypothesis is that video-enhanced rubrics, compared to text based rubrics, will improve mental model formation of a complex skill and improve the feedback quality a learner receives (from e.g. teachers, peers) while practicing a skill, hence positively effecting final mastery of a skill.

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Paper presentation at the TEA2016 conference, Tallinn, Estonia.

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Full paper presented at EC-TEL 2016