Expert systems: aspects of and limitations to the codifiability of knowledge

The creation of expert systems is one way in which knowledge is codified. In creating an expert system, in general there are three aspects to the codification process: creating a model of the knowledge to be codified; creating the language in which to express the model; and writing messages representing the knowledge in that language. These aspects have different relative importance in different contexts. Referring to four case studies, the paper argues further that codification through creating expert systems is not uniformly successful and part of the variation has to do with the nature of the knowledge, or intellectual process or activity being codified, and the difficulty in creating the model. Activities with fixed goals and linear processes lend themselves very well to this form of codification. Processes of categorization and analogy, such as fault detection and repair, are partially successful, tending more often to create systems for experts. Processes involving balancing conflicting goals have, to date, tended to be unsuccessfully codified. These process types involve knowledge or understanding at deeper and deeper levels of abstraction of the overall processes and overarching goals. The more abstract and less concrete the knowledge involved in the task, the more difficult it is to codify it.     

Dynamic and static assessment of phonological awareness in preschool: a behavior-genetic study

The genetic and environmental overlap between static and dynamic measures of preschool phonological awareness (PA) and their relation to preschool letter knowledge (LK) and kindergarten reading were examined using monozygotic and dizygotic twin children (maximum N = 1,988). The static tests were those typically used to assess a child's current level of PA such as blending and elision, and the dynamic test included instruction in phoneme identity to assess the child's ability to respond to this instruction. Both forms were influenced by genes and by shared and nonshared environment. The static and dynamic versions were influenced by the same genes, and part of the total genetic influence was shared with LK. They were subject to both overlapping and independent shared environment influences, with the component in common also affecting LK. Nonshared environment influences were mostly independent. Scores from dynamic assessment added only minimally to variance explained in kindergarten reading after LK and static assessment had been factored in. Although one of the genetic factors that influenced both forms of PA also affected kindergarten reading, it was only the one shared with LK. The authors conclude that dynamic assessment of PA in preschool offers little advantage over the more commonly used static forms, especially if LK scores are available, although they acknowledge its potential in cases of preschool educational disadvantage.     

Neurocognitive predictors of reading outcomes for children with reading disabilities

This study reports on several specific neurocognitive process predictors of reading outcomes for a sample of 278 children with reading disabilities. Three categories of response (i.e., poor, average, and good) were formed via growth curve models of six reading outcomes. Two nested discriminant function analyses were conducted to evaluate the predictive capability of the following models: (a) an intervention and phonological processing model that included intervention group, phonological awareness, and rapid naming and (b) an additive cognitive neuropsychological model that included measures of memory, visual processes, and cognitive or intellectual functioning. Over and above the substantial explanatory power of the base model, the additive model improved classification of poor and good responders. Several of the cognitive and neuropsychological variables predicted degree of reading outcomes, even after controlling for type of intervention, phonological awareness, and rapid naming.     

Do altmetrics assess societal impact in a comparable way to case studies? An empirical test of the convergent validity of altmetrics based on data from the UK research excellence framework (REF)

Altmetrics have been proposed as a way to assess the societal impact of research. Although altmetrics are already in use as impact or attention metrics in different contexts, it is still not clear whether they really capture or reflect societal impact. This study is based on altmetrics, citation counts, research output and case study data from the UK Research Excellence Framework (REF), and peers’ REF assessments of research output and societal impact. We investigated the convergent validity of altmetrics by using two REF datasets: publications submitted as research output (PRO) to the REF and publications referenced in case studies (PCS). Case studies, which are intended to demonstrate societal impact, should cite the most relevant research papers. We used the MHq’ indicator for assessing impact – an indicator which has been introduced for count data with many zeros. The results of the first part of the analysis show that news media as well as mentions on Facebook, in blogs, in Wikipedia, and in policy-related documents have higher MHq’ values for PCS than for PRO. Thus, the altmetric indicators seem to have convergent validity for these data. In the second part of the analysis, altmetrics have been correlated with REF reviewers’ average scores on PCS. The negative or close to zero correlations question the convergent validity of altmetrics in that context. We suggest that they may capture a different aspect of societal impact (which can be called unknown attention) to that seen by reviewers (who are interested in the causal link between research and action in society).     

Novel model reference adaptive control laws for improved transient dynamics and guaranteed saturation constraints

In classical model reference adaptive control (MRAC), the adaptive rates must be tuned to meet multiple competing objectives. Large adaptive rates guarantee rapid convergence of the trajectory tracking error to zero. However, large adaptive rates may also induce saturation of the actuators and excessive overshoots of the closed-loop system’s trajectory tracking error. Conversely, low adaptive rates may produce unsatisfactory trajectory tracking performances. To overcome these limitations, in the classical MRAC framework, the adaptive rates must be tuned through an iterative process. Alternative approaches require to modify the plant’s reference model or the reference command input. This paper presents the first MRAC laws for nonlinear dynamical systems affected by matched and parametric uncertainties that constrain both the closed-loop system’s trajectory tracking error and the control input at all times within user-defined bounds, and enforce a user-defined rate of convergence on the trajectory tracking error. By applying the proposed MRAC laws, the adaptive rates can be set arbitrarily large and both the plant’s reference model and the reference command input can be chosen arbitrarily. The user-defined rate of convergence of the closed-loop plant’s trajectory is enforced by introducing a user-defined auxiliary reference model, which converges to the trajectory tracking error obtained by applying the classical MRAC laws before its transient dynamics has decayed, and steering the trajectory tracking error to the auxiliary reference model at a rate of convergence that is higher than the rate of convergence of the plant’s reference model. The ability of the proposed MRAC laws to prescribe the performance of the closed-loop system’s trajectory tracking error and control input is guaranteed by barrier Lyapunov functions. Numerical simulations illustrate both the applicability of our theoretical results and their effectiveness compared to other techniques such as prescribed performance control, which allows to constrain both the rate of convergence and the maximum overshoot on the trajectory tracking error of uncertain systems.     

The forgotten promise of e-government maturity: Assessing responsiveness in the digital public sector

Assessing e-government responsiveness is one of the major gaps in the currently dominant e-government maturity models. While we have a relatively large pool of models focusing on technological and organizational integration from a supply side perspective, measures of responsiveness of e-government systems from a user perspective are still lacking. Replicating a study from New Zealand and Australia, this study explores the response time and quality of e-mail response in Danish local and central governments (N = 175). Despite that Denmark is high ranking in international benchmark studies, we find that one third of central government agencies did not respond at all, and close to 80% of the ministries provided none or incomplete answers. Local government responds faster and provides answers that are more complete and accurate than those provided by central government. Implications for e-government are discussed.     

Relationship satisfaction among Turkish and British adults

We tested three theories (adult attachment, autonomy/relatedness, and gender roles) to understand relationship satisfaction among 150 British and 170 Turkish adults, all involved in romantic relationships. Avoidance, relatedness, autonomy–relatedness, and masculinity mediated the relationship between culture and romantic relationship satisfaction. Additionally, as anticipated, Turkish participants scored lower on relationship satisfaction and autonomy whereas British participants scored lower on avoidance and relatedness. Contrary to expectation, gender role differences (differences between masculinity and femininity) in the United Kingdom were not significantly smaller than in Turkey. It is concluded that adult attachment provides a useful framework for understanding country-level differences.     

Measure of opportunity: assessing equitable conditions to learn twenty-first century thinking skills

Learning Environments Research - Many school change efforts aim to foster conditions for the development of students’ twenty-first century skills in an equitable and comprehensive way, but...     

Exploring Daily Physical Activity and Nutrition Patterns in Early Learning Settings: Snapshots of Young Children in Head Start,Primary, and After-School Settings

The purpose of this research project was to gain a greater understanding of daily routines of 4–7 year olds regarding physical activity and nutrition practices in typical early learning environments. The settings selected for this observational study included Head Start, primary, and after-school learning environments in a city in the southeast. Specifically, this exploratory study focused on the research question: What are typical daily physical activity and nutrition patterns in community-based early learning settings for young children 4–7 years of age in the United States? Two overarching themes were identified through data analysis: restriction of activity and restriction of physical movement. Results indicated that children in elementary school settings had fewer opportunities for indoor and outdoor physical activity than children in other settings and that children seek to be physically active and will do so when given the opportunity. Increasing time for both structured and unstructured physical activity and play for children ages 4–7 in early learning settings was recommended by the researchers.