Digital technologies can be used to support the inclusion of diverse student groups in education in a number of ways including enhancing accessibility of educational content, increasing personalisation and providing distance learning opportunities, as was the case during the COVID-19 pandemic. However, persistent digital inequalities can undermine…

This supplemental report provides technical documentation for the full report (published separately) concerning the 63% of AISD's Class of 2013 graduates who enrolled in a postsecondary institution the year after high school, and 74% of Class of 2012 graduates persisted in college for a second year. [For the full report, see ED626498.]

It is known that the Maxbet algorithm, which is an alternative to the method of generalized canonical correlation analysis and Procrustes analysis, may converge to local maxima. Discusses an eigenvalue criterion that is sufficient, but not necessary, for global optimality of the successive Maxbet algorithm. (SLD)

Presents an algorithm for the production of a graphical diagram from a matrix formula in such a way that its components are logically and hierarchically arranged. The algorithm, which relies on the matrix equations of J. McArdle and R. McDonald (1984), calculates the individual path components of expected covariance between variables and…

Discussion of access methods and information retrieval algorithms focuses on the vertical counting approach. Determines the speedup gained from using the Hamming Distance Bit Vertical counter, evaluates the parameters that influence the speedup, and discusses the point that makes the vertical approach faster than the horizontal approach.…

Discusses XML and information retrieval and describes a query language, ELIXIR (expressive and efficient language for XML information retrieval), with a textual similarity operator that can be used for similarity joins. Explains the algorithm for answering ELIXIR queries to generate intermediate relational data. (Author/LRW)

Discussion of information retrieval focuses on the use of binary trees and how to compact it to use less memory and take less time. Explains retrieval algorithms and describes data structure and hierarchical structure. (LRW)

A formula for the determinant of a partitioned matrix, possibly with singular submatrices, is derived and applied to some psychometric and numerical problems. (Author)

Discusses the problem of enhancing the speed of Huffman decoding of compressed data. Topics addressed include the Huffman decoding tree; multibit decoding; binary string mapping problems; and algorithms for solving mapping problems. (22 references) (LRW)

Describes a new combinatorial algorithm for fitting additive trees to proximity data. This generalized triples method examines all triples of objects of interest in relation to the remaining set of objects to be clustered. The procedure is illustrated, and a simulation study shows its advantages. (SLD)

Provides a comprehensive, nontechnical overview of the three maximum likelihood algorithms available for use with missing data and discusses multiple imputation, frequently used in conjunction with the EM algorithm. (SLD)

The residual variance is often used as an approximation to the uniqueness in factor analysis. An upper bound approximation to the residual variance is presented for the case when the correlation matrix is singular. (Author/JKS)

Efron's Monte Carlo bootstrap algorithm is shown to cause degeneracies in Pearson's r for sufficiently small samples. Two ways of preventing this problem when programing the bootstrap of r are considered. (Author)

Describes a system for the automatic coding of most descriptive titles which generates Nested Phrase Indexing System (NEPHIS) input strings of sufficient quality for permuted index production. A series of examples and an 11-item reference list accompany the text. (JL)

Describes a method for choosing rejection probabilities for the tests of independence that are used in constraint-based algorithms of exploratory path analysis. The method consists of generating a Markov or semi-Markov model from the equivalence class represented by a partial ancestral graph and then testing the d-separation implications. (SLD)