A Note on the Use of Mixture Models for Individual Prediction

Mixture models capture heterogeneity in data by decomposing the population into latent subgroups, each of which is governed by its own subgroup-specific set of parameters. Despite the flexibility and widespread use of these models, most applications have focused solely on making inferences for whole or subpopulations, rather than individual cases. This article presents a general framework for computing marginal and conditional predicted values for individuals using mixture model results. These predicted values can be used to characterize covariate effects, examine the fit of the model for specific individuals, or forecast future observations from previous ones. Two empirical examples are provided to demonstrate the usefulness of individual predicted values in applications of mixture models. The first example examines the relative timing of initiation of substance use using a multiple event process survival mixture model, whereas the second example evaluates changes in depressive symptoms over adolescence using a growth mixture model.     

Current conceptions of literacy – insights from work with children and older learners with sensory needs

There have been many efforts to conceptualise literacy, both in terms of its essence and component parts, but it has proved difficult to define. This paper considers work that is undertaken with children and older learners with sensory needs in order to promote the early stages of literacy. Recent government initiatives aimed at fostering literacy development have caused teachers of children with sensory needs to re-examine their practice. The paper discusses early literacy as part of children's attempts to communicate and describes children with sensory needs engaging in a range of activities that are termed 'literacy' by those working with them. By taking into account these activities, the authors endeavour to throw light on the broader questions around concepts of literacy.     

Behavior-Based Student Typology: A View from Student Transition from High School to College

Research in Higher Education - Several recent studies have successfully identified college student typologies based on individuals’ behaviors. One limitation of past studies has been their...     

International organizations,educational development,and conflict: A (world) cultural perspective

PROSPECTS - Many analyses of globalized education have directed growing attention to a problematic local-global nexus, with a particular focus on international organizations (IOs) as coercive and...     

A critical review of elaboration theory

In this article the authors examine elaboration theory (ET), a model for sequencing and organizing courses which was developed by Charles Reigeluth and associates in the late 1970s. The purpose of the article is to offer a critique of ET based on recent cognitive research and to offer suggestions for updating the model to reflect new knowledge.Commentary by Charles Reigeluth follows this article.     

Push-Penny: Are you a Random Player?

Several measures of “success” for a simple game are discussed. Comparisons between players, and between a player and a simulation, can be made in several ways.     

The empirical derivation of equations for predicting subjective textual information

Parameters pertaining to information processing by human beings have, in the past, been determined by learning and memory experiments with nonsense syllables, number sequences, etc. However, in the real world we are concerned with the processing of meaningful information, not senselles texts. Therefore, the determination of subjective information directly from meaningful material becomes extremely important in the instruction-learning process.This study derives an equation for predicting the subjective textual information contained in a text of material written in the English language. Specifically, this investigation describes, by a mathematical equation, the relationship between the subjective information content of written textual material and the relative number of errors committed by a learner when asked to predict, letter by letter, the content of given textual material. This relationship shows that the subjective information of a given text for a specific learner is directly proportional to the number of wrongly guessed signs made by that learner. This is expressed mathematically by% MathType!MTEF!2!1!+- % feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn % hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr % 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9 % vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x % fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamysaiabg2 % da9iaaiodacaGGUaGaaGymaiaabccacaWGfbaaaa!3B57! \[ I = 3.1{\rm{ }}E \] 0935 0212 VWhere: I = Information in bits E = Number of wrongly guessed signsThe application of Shannon's guessing procedure (1951) in this study permits the measurement of the subjective information of a given text for a specific learner. Unlike senseless texts, the subjective information of a meaningful text varies from learner to learner. Therefore, the derived equation permits the measurement of information in terms of a value that is dependent not only upon the inherent qualities of the subject matter, but also upon the internal state of the learner.The derived equation for the English language is then compared to an equation derived by Weltner (1967) for the German language and found to be remarkably similar.This work was, in part, supported by United States Air Force Contract F41609-71-C-0027 entitled Flying Training Research on Airborne and Ground Training Systems, and a research grant from Arizona State University.