How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Pedagosko i psiholosko testiranje i procjenjivanje spadaju među najvažnije doprinose znanosti o ponasanju nasem drustvu i pružaju temeljna i znacajna poboljsanja u odnosu na ranije postupke. Iako se ne može ustvrditi da su svi testovi dovoljno usavrseni niti da su sva testiranja razborita i korisna, postoji velika kolicina informacija koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima. Pravilna upotreba testova može dovesti do boljih odluka o pojedincima i programima nego sto bi to bio slucaj bez njihovog koristenja, a također i ukazati na put za siri i pravedniji pristup obrazovanju i zaposljavanju. Međutim, losa upotreba testova može dovesti do zamjetne stete nanesene ispitanicima i drugim sudionicima u procesu donosenja odluka na temelju testovnih podataka. Cilj Standarda je promoviranje kvalitetne i eticne upotrebe testova te uspostavljanje osnovice za ocjenu kvalitete postupaka testiranja. Svrha objavljivanja Standarda je uspostavljanje kriterija za evaluaciju testova, provedbe testiranja i posljedica upotrebe testova. Iako bi evaluacija prikladnosti testa ili njegove primjene trebala ovisiti prvenstveno o strucnim misljenjima, Standardi pružaju okvir koji osigurava obuhvacanje svih relevantnih pitanja. Bilo bi poželjno da svi autori, sponzori, nakladnici i korisnici profesionalnih testova usvoje Standarde te da poticu druge da ih također prihvate.

Standards for educational and psychological testing

Principles and Practice of Structural Equation Modeling (2nd ed.)

A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Multimedia in Learning

The purpose of this article is to provide researchers, editors, and readers with a set of guidelines for what to expect in an article using logistic regression techniques. Tables, figures, and charts that should be included to comprehensively assess the results and assumptions to be verified are discussed. This article demonstrates the preferred pattern for the application of logistic methods with an illustration of logistic regression applied to a data set in testing a research hypothesis. Recommendations are also offered for appropriate reporting formats of logistic regression results and the minimum observation-to-predictor ratio. The authors evaluated the use and interpretation of logistic regression presented in 8 articles published in The Journal of Educational Research between 1990 and 2000. They found that all 8 studies met or exceeded recommended criteria.

An Introduction to Logistic Regression Analysis and Reporting

Structural equation modeling (SEM) is a versatile statistical modeling tool. Its estimation techniques, modeling capacities, and breadth of applications are expanding rapidly. This module introduces some common terminologies. General steps of SEM are discussed along with important considerations in each step. Simple examples are provided to illustrate some of the ideas for beginners. In addition, several popular specialized SEM software programs are briefly discussed with regard to their features and availability. The intent of this module is to focus on foundational issues to inform readers of the potentials as well as the limitations of SEM. Interested readers are encouraged to consult additional references for advanced model types and more application examples.

/pdf/introduction-to-structural-equation-modeling-issues-and-3zle1hxkii.pdf

Introduction to Structural Equation Modeling: Issues and Practical Considerations

Few instruments have been designed specifically to address the needs of college counseling centers. This article reviews existing instruments and presents 4 studies that describe the development and psychometric properties of a new instrument, the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62). Study 1 describes the initial item development, factor analysis, and preliminary scale development steps. Study 2 describes the results of exploratory and confirmatory factor analyses using data from more than 22,000 clients pooled via a national practice-research network of counseling centers. Studies 3 and 4 provide preliminary evidence of subscales' convergent validity and retest reliability. Results from these 4 studies provide support for the instrument's factor structure, construct validity, and subscale reliabilities for both the total sample and subgroups. Clinical and methodological issues pertaining to the future development of the CCAPS are discussed in the context of a national practice-research network of college counseling centers.

Development of the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62)

http://www.ux1.eiu.edu/~glcanivez/Adobe%20pdf/Publications-Papers/Watkins,%20Lei,%20&%20Canivez%20(2007).pdf

Psychometric Intelligence and Achievement: A Cross-Lagged Panel Analysis.

This study examined the performance of two alternative estimation approaches in structural equation modeling for ordinal data under different levels of model misspecification, score skewness, sample size, and model size. Both approaches involve analyzing a polychoric correlation matrix as well as adjusting standard error estimates and model chi-squared, but one estimates model parameters with maximum likelihood and the other with robust weighted least-squared. Relative bias in parameter estimates and standard error estimates, Type I error rate, and empirical power of the model test, where appropriate, were evaluated through Monte Carlo simulations. These alternative approaches generally provided unbiased parameter estimates when the model was correctly specified. They also provided unbiased standard error estimates and adequate Type I error control in general unless sample size was small and the measured variables were moderately skewed. Differences between the methods in convergence problems and the evaluation criteria, especially under small sample and skewed variable conditions, were discussed.

Evaluating estimation methods for ordinal data in structural equation modeling

This study examined longitudinal predictive relationships between young children's classroom behaviors and their growth in mathematics skills during the primary grades. Using the Early Childhood Longitudinal Study--Kindergarten cohort, the authors tested a longitudinal model featuring positive (interpersonal skills and approaches to learning) and negative (internalizing and externalizing) behaviors at kindergarten entry as predictors of growth in mathematics achievement through 3rd grade. Results indicated that negative behaviors demonstrate negligible relationships with early development of mathematics skills. Interpersonal skills demonstrated a small negative relationship with mathematics growth when other positive behaviors were included as predictors in the model. In contrast, approaches to learning (goal-directed behavior, persistence, organization) demonstrated small positive relationships with growth in mathematical skills and may represent a skill domain for educators to consider in designing their instructional practices.

Kindergarten predictors of mathematical growth in the primary grades: An investigation using the Early Childhood Longitudinal Study - Kindergarten cohort

Pui Wa Lei

Papers

Introduction to Structural Equation Modeling: Issues and Practical Considerations

Development of the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62)

Psychometric Intelligence and Achievement: A Cross-Lagged Panel Analysis.

Evaluating estimation methods for ordinal data in structural equation modeling

Kindergarten predictors of mathematical growth in the primary grades: An investigation using the Early Childhood Longitudinal Study - Kindergarten cohort