Scale Considerations in Using Vague Quantifiers

The responses to many survey questions are often made in terms of vague quantifiers such as very often or occasionally. However, we know little about the scale characteristics of such quantifiying terms. This paper reviews the literature on the use of frequency expressions as questionnaire anchor points. Data are presented which suggest that the popularly used five-point response category set of always, often, occasionally, seldom, and never is not intervally scaled. Utilizing data obtained through ratio estimation, an approximately equal interval measurement scale is developed for a five-point response category set.     

Using Retrospective Pre-Ratings to Counteract Response-Shift Confounding

A potential confounding effect present in research designs which employ self-report instruments is response-shift, i.e., a change in the internalized standard by which a subject rates himself. Howard et al. (6) suggest that when self-report measures must be used to measure behavioral changes there should be a modification of Campbell and Stanley’s design (2) so as to include a “retrospective pre-rating.” In the current research, the response-shift phenomenon is demonstrated in the context of a typical classroom setting. Retrospective pre-ratings are shown to yield significantly more accurate estimates of preinstruction knowledge than simple pre-ratings. However, there was no statistically significant difference between correlation co-efficients relating “behavioral change” and “self-reported change” when self-reported change was defined in terms of retrospective pre-ratings rather than in terms of simple pre-ratings.     

Communicating the variability of a software-product family to customers

Variability is a central concept in software product family development. Variability empowers constructive reuse and facilitates the derivation of different, customer specific products from the product family. If many customer specific requirements can be realised by exploiting the product family variability, the reuse achieved is obviously high. If not, the reuse is low. It is thus important that the variability of the product family is adequately considered when eliciting requirements from the customer. In this paper we sketch the challenges for requirements engineering for product family applications. More precisely we elaborate on the need to communicate the variability of the product family to the customer. We differentiate between variability aspects which are essential for the customer and aspects which are more related to the technical realisation and need thus not be communicated to the customer. Motivated by the successful usage of use cases in single product development we propose use cases as communication medium for the product family variability. We discuss and illustrate which customer relevant variability aspects can be represented with use cases, and for which aspects use cases are not suitable. Moreover we propose extensions to use case diagrams to support an intuitive representation of customer relevant variability aspects.     

Computer-Assisted Instruction Augmented with Planned Teacher/Student Contacts

This paper discussed a study of the differences in student learning achievement and retention in a college-level statistics course taught in a variety of teaching/learning environments. Statistical test results revealed that students experiencing a CAI environment performed no differently on achievement or retention tests than students experiencing a traditional lecture/discussion environment. However, students experiencing an “enriched” CAI environment (CAI plus planned teacher/student contacts) performed significantly better on achievement tests than students experiencing any of several other environments, including: lecture/discussion, lecture/discussion supplemented with planned teacher/student contacts, PI texts, PI texts supplemented with planned teacher/student contacts, and CAI.     

Metacognitive knowledge in children at early elementary school

In metacognition research, many studies focused on metacognitive knowledge of preschoolers or children at the end of elementary school or secondary school, but investigations of children starting elementary school are quite limited. The present study, thus, took a closer look at children’s knowledge about mental processes and strategies in early elementary school aiming to extend findings on the respective age period. Therefore, at first, a new test that can be administered in group settings and that assesses a broad concept of children’s metacognitive knowledge in early elementary school was evaluated. Furthermore, analyses on the structure of metacognitive knowledge were carried out in cross-sectional as well as longitudinal analyses. In a longitudinal design, the new test instrument was administered to 870 children at the end of first grade and again one year later (N?=?720). Item Response models were used to evaluate the construct validity of the test. Test characteristics were checked based on different fit statistics, test fairness, and discriminant validity. In summary, the test exhibited good psychometric properties. Analyses on the dimensionality of the assessed metacognitive knowledge revealed that different strategies seemed to form rather distinct dimensions of metacognitive knowledge. However, these dimensions showed a rather homogeneous development from first to second grade. Impacts of the findings on theoretical considerations and on the theoretical understanding of metacognitive knowledge and further analyses with metacognitive competence data are discussed.     

Dealing With Item Nonresponse in Large‐Scale Cognitive Assessments: The Impact of Missing Data Methods on Estimated Explanatory Relationships

Competence data from low‐stakes educational large‐scale assessment studies allow for evaluating relationships between competencies and other variables. The impact of item‐level nonresponse has not been investigated with regard to statistics that determine the size of these relationships (e.g., correlations, regression coefficients). Classical approaches such as ignoring missing values or treating them as incorrect are currently applied in many large‐scale studies, while recent model‐based approaches that can account for nonignorable nonresponse have been developed. Estimates of item and person parameters have been demonstrated to be biased for classical approaches when missing data are missing not at random (MNAR). In our study, we focus on parameter estimates of the structural model (i.e., the true regression coefficient when regressing competence on an explanatory variable), simulating data according to various missing data mechanisms. We found that model‐based approaches and ignoring missing values performed well in retrieving regression coefficients even when we induced missing data that were MNAR. Treating missing values as incorrect responses can lead to substantial bias. We demonstrate the validity of our approach empirically and discuss the relevance of our results.     

Child sexual abuse prevention: Evaluation of a teacher training model

Teachers are potentially helpful resource persons for large numbers of sexually abused children who may have difficulty disclosing abuse, particularly to family members. In the present study, the effectiveness of a 6-hour teacher training workshop on child sexual abuse prevention was evaluated. Responses of 26 female elementary teachers who participated in the workshop were compared to responses of 19 control teachers on several pre-, post-, and follow-up measures. Relative to controls, trained teachers demonstrated significant increases from pre- to post-testing in knowledge about child sexual abuse and pro-prevention opinions. On a post-only vignettes measure, trained teachers were better able than control teachers to identify behavioral indicators of abuse and suggest appropriate interventions for hypothetical sexually abused children. Over a 6-week follow-up period, trained teachers read more about child abuse than control teachers but did not differ on other behavioral dimensions such as reporting suspected abuse cases. Further research will examine the effects of additional teacher training over an extended follow-up period.     

Longitudinal Multistage Testing

This article introduces longitudinal multistage testing (lMST), a special form of multistage testing (MST), as a method for adaptive testing in longitudinal large‐scale studies. In lMST designs, test forms of different difficulty levels are used, whereas the values on a pretest determine the routing to these test forms. Since lMST allows for testing in paper and pencil mode, lMST may represent an alternative to conventional testing (CT) in assessments for which other adaptive testing designs are not applicable. In this article the performance of lMST is compared to CT in terms of test targeting as well as bias and efficiency of ability and change estimates. Using a simulation study, the effect of the stability of ability across waves, the difficulty level of the different test forms, and the number of link items between the test forms were investigated.     

Communicating the variability of a software-product family to customers

Variability is a central concept in software product family development. Variability empowers constructive reuse and facilitates the derivation of different, customer specific products from the product family. If many customer specific requirements can be realised by exploiting the product family variability, the reuse achieved is obviously high. If not, the reuse is low. It is thus important that the variability of the product family is adequately considered when eliciting requirements from the customer. In this paper we sketch the challenges for requirements engineering for product family applications. More precisely we elaborate on the need to communicate the variability of the product family to the customer. We differentiate between variability aspects which are essential for the customer and aspects which are more related to the technical realisation and need thus not be communicated to the customer. Motivated by the successful usage of use cases in single product development we propose use cases as communication medium for the product family variability. We discuss and illustrate which customer relevant variability aspects can be represented with use cases, and for which aspects use cases are not suitable. Moreover we propose extensions to use case diagrams to support an intuitive representation of customer relevant variability aspects.Received: 14 October 2002, Accepted: 8 January 2003, This work was partially funded by the CAFÉ project From Concept to Application in System Family Engineering; Eureka ! 2023 Programme, ITEA Project ip00004 (BMBF, Förderkennzeichen 01 IS 002 C) and the state Nord-Rhein-Westfalia. This paper is a significant extension of the paper Modellierung der Variabilität einer Produktfamilie, [15].