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In grades K-3, the primary focus of instruction is learning to read. In grades 4 and beyond, however, the focus shifts to reading to learn. Whereas teachers may use a variety of instructional approaches, research has clearly documented that learning from text is the primary instructional model found in most classrooms. This means that efforts to close the achievement gap must focus on ensuring that all students can access text-based learning materials, engage with the content in meaningful ways, and ultimately demonstrate success in the form of measurable gains in learning outcomes. Whereas the philosophy of UDL is relatively easy to understand, it has proven problematic to design, implement, evaluate, and scale. The purpose of this chapter is to describe a universal design engineering approach known as Design for More Types that can be applied to the design of text-based learning materials, this chapter will describe the conceptual and practical issues involved in the development of text-based learning materials for diverse learners. We begin by providing some foundational concepts for this multidisciplinary work. Next, we provide a series of case studies to illustrate how universal usability can be applied to various instructional designs. Finally, we describe how the Design for More Types framework can be used in both research and practice.

This literature review is on advanced computer analytics, which is a major trend in the field of Human Resource Management (HRM). The authors focus specifically on computer-assisted text analysis (CATA) because text data are a prevalent yet vastly underutilized data source in organizations. The authors gathered 341 articles that use, review, or promote CATA in the management literature. This review complements existing reviews in several ways including an emphasis on CATA in the management literature, a description of the types of software and their advantages, and a unique emphasis on findings in employment. This examination of CATA relative to employment is based on 66 studies (of the 341) that bear on measuring constructs potentially relevant to hiring decisions. The authors also briefly consider the broader machine learning literature using CATA outside management (e.g., data science) to derive relevant insights for management scholars. Finally, the authors discuss the main challenges when using CATA for employment, and provide recommendations on how to manage such challenges. In all, the authors hope to demystify and encourage the use of CATA in HRM scholarship.

Nowadays, the use of WCMS (web content management systems) is widespread. The conversion of this infrastructure into its semantic equivalent (semantic WCMS) is a critical issue, as this enables the benefits of the semantic web to be extended. The purpose of this paper is to present a FLERSA (Flexible Range Semantic Annotation) for flexible range semantic annotation.

A FLERSA is presented as a user‐centred annotation tool for Web content expressed in natural language. The tool has been built in order to illustrate how a WCMS called Joomla! can be converted into its semantic equivalent.

The development of the tool shows that it is possible to build a semantic WCMS through a combination of semantic components and other resources such as ontologies and emergence technologies, including XML, RDF, RDFa and OWL.

The paper provides a starting‐point for further research in which the principles and techniques of the FLERSA tool can be applied to any WCMS.

The tool allows both manual and automatic semantic annotations, as well as providing enhanced search capabilities. For manual annotation, a new flexible range markup technique is used, based on the RDFa standard, to support the evolution of annotated Web documents more effectively than XPointer. For automatic annotation, a hybrid approach based on machine learning techniques (Vector‐Space Model + n‐grams) is used to determine the concepts that the content of a Web document deals with (from an ontology which provides a taxonomy), based on previous annotations that are used as a training corpus.

Auditors’ skills and knowledge of data analytics and big data can influence their judgment at the audit planning stage. At this stage, the auditor will determine the level of audit risk and estimate how long the audit will take. This study aims to test whether big data and data analytics affect auditors’ judgment by adopting the cognitive fit theory.

This was an experimental study involving 109 accounting students as participants. The 2 × 2 factorial design between subjects in a laboratory setting was applied to test the hypothesis.

First, this study supports the proposed hypothesis that participants who are provided with visual analytics information will rate audit risk lower than text analytics. Second, participants who receive information on unstructured data types will assess audit risk (audit hours) higher (longer) than those receiving structured data types. In addition, those who receive information from visual analytics results have a higher level of reliance than those receiving text analytics.

This research has implications for external and internal auditors to improve their skills and knowledge of data analytics and big data to make better judgments, especially when the auditor is planning the audit.

Previous studies have examined the effect of data analytics (predictive vs anomaly) and big data (financial vs non-financial) on auditor judgment, whereas this study examined data analytics (visual vs text analytics) and big data (structured and unstructured), which were not tested in previous studies.

Nowadays, there is a high demand for online services and applications. However, there is a challenge to keep these applications secured by applying different methods rather than using the traditional approaches such as passwords and usernames. Keystroke dynamics is one of the alternative authentication methods that provide high level of security in which the used keyboard plays an important role in the recognition accuracy. To guarantee the robustness of a system in different practical situations, there is a need to examine how much the performance of the system is affected by changing the keyboard layout. This paper aims to investigate the impact of using different keyboards on the recognition accuracy for Arabic free-text typing.

To evaluate how much the performance of the system is affected by changing the keyboard layout, an experimental study is conducted by using two different keyboards which are a Mac’s keyboard and an HP’s keyboard.

By using the Mac’s keyboard, the results showed that the false rejection rate (FRR) was 0.20, whilst the false acceptance rate (FAR) was 0.44. However, these values have changed when using the HP’s keyboard where the FRR was equal to 0.08 and the FAR was equal to 0.60.

The number of participants in the experiment, as the authors were targeting much more participants.

These results showed for the first time the impact of the keyboards on the system’s performance regarding the recognition accuracy when using Arabic free-text.

The purpose of this chapter is to present key characteristics of early reading text by describing a new series of researcher-developed early reading books that were specifically designed to address multiple criteria, including word structure or decodability, familiarity, repetition, high-frequency, syntax, and text cohesion. We describe the theoretical and empirical rationale that guided the design of the books, how we developed them, and their key features. This is followed by a technical analysis that describes the (1) characteristics of the target words used to guide the writing of the books and (2) characteristics of the text, such as the percentage of words on common high-frequency word lists, word counts, type-token ratio, sentence counts, unique sight words, unique decodable words, and content (i.e., picture-supported) words. The analysis demonstrates that the target words and the text in the books are consistent with our intended goal of simultaneously addressing multiple variables.

This article examines the discourse of appointment, promotion, and tenure (APT) documents for academic librarians. Discourse analysis can illuminate the social role of language, social systems, and social practices.

This qualitative research analyzes the APT documents for librarians from a group of US universities (n = 50) whose librarians are tenured faculty (n = 35). Linguistic features were examined to identify genre (text type) and register (language variety) characteristics.

The documents showed strong relationships with other texts; vocabulary from the language of human resources (HR); grammatical characteristics such as nominalization; passive constructions; few pronouns; the “quasi-synonymy” of series of adjectives, nouns, or verbs; and expression of certainty and obligation. The documents have a sociolinguistic and social semiotic component. In using a faculty genre, librarians assert solidarity with other faculty, while the prominent discourse of librarians as practitioners detracts from faculty solidarity.

This research is limited to librarians at US land grant institutions. It has implications for other research institutions and other models of librarian status.

This research can help academic librarians fulfill their obligations by understanding how values encoded in these documents reflect positive and negative approaches.

Higher education and academic librarianship are in a state of flux. Understanding the discourse of these documents can help librarians encode appropriate goals and values. Little has been written on the discourse of librarianship. This is a contribution to the understanding of librarians as a discourse community and of significant communicative events.

This study aims to explore the influence of information presentation conditions on the flow experience of digital reading for high school students.

Firstly, a survey determines the preferred reading medium and the types of texts that high school students frequently read. Secondly, Experiment 1 focuses on the effects of the text type and reading medium on flow experience and reading comprehension. Finally, Experiment 2 addresses a narrative text presented on a smartphone, and discusses the influence of advance organizer, presentation format and page layout on flow experience and reading comprehension.

In digital reading, the narrative text has a stronger flow experience than explanatory text; the flow experience of reading narration on smartphones is more evident than on computers. The advance organizer and text combined with pictures are more conducive to a flow experience when a smartphone is used as a reading medium. From the perspective of reading comprehension, scrolling is more suitable for reading text combined with pictures and paging best suits pure text.

Through experimental methods, this study reveals the influence of information presentation conditions on the digital reading flow experience, which is a meaningful and innovative topic. The findings can provide more enlightenment and reference for the design and promotion of digital resources and digital reading by teenagers.

Browsing a database of article abstracts is one way to select and buy relevant magazine articles online. Our research contributes to the design and development of text grammars for abstracting texts in unlimited subject domains. We developed a system that parses texts based on the text grammar of a specific text type and that extracts sentences and statements which are relevant for inclusion in the abstracts. The system employs knowledge of the discourse patterns that are typical of news stories. The results are encouraging and demonstrate the importance of discourse structures in text summarisation.

This paper assesses the degree to which established practices in terminology can provide the translation industry with the lexical means to support mediation of information between languages, especially where such mediation involves modification. The effects of term variation, collocation and sublanguage phraseology present problems of term choice to the translator. Current term resources cannot help much with these problems; however, tools and techniques are discussed which, in the near future, will offer translators the means to make appropriate choices of terminology.