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Purpose – To provide a resource for educators and graduate students that contains information about using formal assessment data to plan literacy instruction and intervention.

Design/methodology/approach – Several aspects of formal assessment are presented, including a definition of formal assessment, types of formal assessment scores, commonly used formal assessments, and recommendations for using formal assessments for individuals and groups. Information about formal assessment is informed both by documented sources and the experiences of the authors.

Findings – The authors provide an overview of common, commercially available assessments designed to measure literacy achievement in either individuals or groups. Reviews of formal assessments include scores, number of forms, literacy domains measured, and published reliability figures. Recommendations for formal assessment use include using assessment data to plan instruction and intervention for both individuals and groups. In addition, a case study is presented demonstrating the efficacy of using formal assessment data to plan instruction and intervention in a K-6 elementary school in the United States.

Research limitations/implications – The review of commercially available individual and group literacy assessments does not constitute an exhaustive list.

Practical implications – Information about formal assessments, assessment score types, and formal assessment uses is consolidated in one location for easy access by graduate students and other educators.

Originality/value – This chapter provides graduate students and others in the field of education an overview of formal assessments and how formal assessment data can be used to make instructional decisions for both individuals and groups.

Consumer responses of attribute liking and intensity as well as overall liking of commercial chocolate were evaluated in four types of testing situations (central location, in‐home, teaching laboratory and formal sensory laboratory). The aim was to determine if there were differences in these responses based on testing situation. This was also an attempt to evaluate and validate the use of in‐home testing for product development samples. Perceptions of certain attributes were found to differ in different testing situations but liking scores of these attributes did not. Consumers were more critical of attributes when tested in a formal sensory laboratory. All four locations tested gave similar results, meaning that, conducting sensory panels at home is as valid a method of collecting consumer opinion as traditional locations. It should be noted that the use of a formal sensory laboratory might have an impact on cost effectiveness of new product development. Results are more likely to indicate the need to continue formulation in order to perfect attribute scores, although this may not actually improve consumer‐liking scores. This continued product development only serves to increase the costs and slow the speed to market.

This study is a systematic literature review of the application of artificial intelligence (AI) in safety-critical systems. The authors aim to present the current application status according to different AI techniques and propose some research directions and insights to promote its wider application.

A total of 92 articles were selected for this review through a systematic literature review along with a thematic analysis.

The literature is divided into three themes: interpretable method, explain model behavior and reinforcement of safe learning. Among AI techniques, the most widely used are Bayesian networks (BNs) and deep neural networks. In addition, given the huge potential in this field, four future research directions were also proposed.

This study is of vital interest to industry practitioners and regulators in safety-critical domain, as it provided a clear picture of the current status and pointed out that some AI techniques have great application potential. For those that are inherently appropriate for use in safety-critical systems, regulators can conduct in-depth studies to validate and encourage their use in the industry.

This is the first review of the application of AI in safety-critical systems in the literature. It marks the first step toward advancing AI in safety-critical domain. The paper has potential values to promote the use of the term “safety-critical” and to improve the phenomenon of literature fragmentation.

Assessment and identification of children with emotional and behavioral disorders (EBD) is complex and involves multiple techniques, levels, and participants. While federal law sets the general parameters for identification in school settings, these criteria are vague and may lead to inconsistencies in selection and interpretation of assessment measures. Assessment practice across school settings is greatly influenced by clinical guidelines such as the DSM-IV, which more specifically defines emotional and behavioral disorders and highlights the issue of co-morbidity. Before a student is assessed for special education eligibility under the IDEIA category of emotional disturbance, screening techniques and pre-referral interventions are needed. Positive Behavioral Supports and Response to Intervention models provide empirically supported frameworks for establishing the need for formal psychological assessment. Collaboration among members of the multidisciplinary team, including parents, helps to ensure that identification and intervention efforts have ecological validity. Tests and techniques vary considerably, but developmental histories, interviews, observations across settings, and behavioral checklists and rating scales are recommended, along with cognitive and achievement testing. While problems exist in the reliability and validity of projective techniques, they continue to be used in school-based assessment for EBD. Multitrait, multisetting, and multimethod approaches are essential for culturally fair assessment and reduction of bias in identification and placement.

Health professionals are in an ethical dilemma. The patients should be assumed as competent. Involuntary treatment is a violation of human rights. Therefore incompetent patients should be protected. However, one cannot determine a patient's incompetency without testing him/her, which is a violation of the assumption of competency. Thus, we propose two different types of uses for competency tests. One is to measure the appropriateness of information disclosed,but with a poor test result the information should be repeated. Another is to measure the competency of the patients when making major decisions. A poor test result will be followed by the designation of a proxy so that incompetent patients can be protected.

This paper explores the evidence of a long-run co-movement between aggregate unemployment insurance spending and the labor force participation rate in the USA. The unemployment insurance (UI) program tends to expand during an economic downturn and contract during an expansion. UI may incentivize unemployment and may also facilitate better matching in the labor market. Statistical evidence of the presence of a co-movement will thus shed new light on their dynamics.

This research applies time-series econometric approach using monthly data from 1959:1 to 2020:3 to test threshold cointegration and estimate a threshold vector error-correction (TVEC) model. The estimates from the TVEC model investigating the nature of short-run dynamics.

The Enders and Siklos (2001) test find evidence of threshold cointegration between the two indicating the presence of long-run co-movement. The estimates from the TVEC model investigating the nature of short-run dynamics find evidence that the growth in aggregate UI spending and the growth in labor force participation rate adjust simultaneously to maintain the long-run co-movement above the threshold in the short run. The author also observes the same short-run dynamics for the growth in aggregate UI spending and the growth in the labor force participation rate for females.

This model is bi-variate by construction and does not address causality.

The author argues that the UI program positively impacts the female labor market outcomes, for example, better matching. This finding may explain the upward trend in the labor force participation rate for females in the USA.

The research findings may justify the transfer programs for minority and immigrants.

This is first research that analyzes the UI programs impact on the labor force participation using a macroeconometric approach. To the best of the author's knowledge, this is the first study in this genre.

To transcend the view of employment as either formal or informal, this paper evaluates the prevalence of quasi-formal employment where formal employers pay formal employees an unreported (“envelope”) wage in addition to their formal reported salary. To explain the individual-level variations in quasi-formal employment, the “marginalisation” thesis is evaluated that this practice is more prevalent among vulnerable groups and to explain the country-level variations, and a neo-institutionalist theory is evaluated that it is more prevalent where formal institutional failures lead to an asymmetry between the formal laws and regulations and the unwritten socially shared rules of informal institutions.

To evaluate the individual- and country-level variations in the prevalence of quasi-formal employment, a multi-level logistic regression is provided of data from special 2019 Eurobarometer survey 92.1 involving 11,793 interviews with employees across 28 European countries (the 27 member states of the European Union and the United Kingdom).

Of the 3.5% of employees (1 in 28) who receive under-reported salaries, the marginalisation thesis is supported that it is largely vulnerable population groups. So too is the neo-institutionalist explanation that quasi-formal employment is more common in countries where the non-alignment of formal and informal institutions is greater, with the formal institutional failings producing this identified as lower levels of economic development, less modernised state bureaucracies and lower levels of taxation and social protection.

The policy implication is that tackling quasi-formal employment requires not only enforcement authorities to improve the risk of detection of this illegal wage practice but also governments to change wider macro-level structural conditions. These are outlined.

Contemporary new evidence is provided of the prevalence of quasi-formal employment along with how this illegal wage practice can be explained and tackled.

The purpose of this paper is to document how the library at Tecnológico de Monterrey, Monterrey Campus came to use the open source Drupal with other freely available tools as the basis for an extensible platform for current and future information discovery gateways.

After informal gathering of user opinions, formal usability testing of the current OPAC and Digital Library, and an evaluation of available options, Tecnológico de Monterrey's Library decided in October 2007 to build and test a prototype version of a new portal in April 2008, which after usability testing and interviews was improved and released for its users in June 2008.

The development team found out that Drupal, despite its steep learning curve, was a solid development platform which could achieve all the functionality the library set out to achieve through its freely available modules or custom, locally‐developed modules.

This paper documents the steps required to build an information discovery tool using Drupal and other freely available tools, thus demonstrating that Drupal is a viable and extensible development platform for libraries.

Barriers exist on large scale assessment when students are not able to perform at potential for a variety of reasons. Accommodations are mostly available for students who meet criteria for diagnosed disability or criteria for the identification of students who have English as a second language. However, knowing that students have diverse needs, accommodations for a few may not be providing appropriate access for all. Options for designing broader universal design for learning (UDL) on large scale assessment, through strategies that are typically restricted to special accommodations, increase access.