Improving reading: a handbook for improving reading in key stages 3 and 4 (National Strategies: secondary)

"This handbook explores what it means to be a reader and some core challenges and skills that need to be addressed in the teaching of reading. The handbook outlines a route to improvement that can be followed to ensure that all pupils make expected levels of progress so that they can become skilled and independent readers. Detailed guidance is provided for each stage of the improvement process: gathering and analysing information; writing the improvement plan; evaluating planning, approaches to teaching and learning and the assessment of reading. Subject leaders can decide which stages of the process their department is confident with and which areas need to be developed further. Each section provides relevant resources and tools to guide and support this work." - National Strategies website

The impact of technology: value-added classroom practice: final report

This report extends Becta’s enquiries into the ways in which digital technologies are supporting learning. It looks in detail at the learning practices mediated by ICT in nine secondary schools in which ICT for learning is well embedded. The project proposes a broader perspective on the notion of ‘impact’ that is rather different from a number of previous studies investigating impact. Previous studies have been limited in that they have either focused on a single innovation or have reported on institutional level factors. However, in both cases this pays insufficient attention to the contexts of learning. In this project, the focus has been on the learning practices of the classroom and the contexts of ICT-supported learning. The study reports an analysis of 85 lesson logs, in which teachers recorded their use of space, digital technology and student outcomes in relation to student engagement and learning. The teachers who filled in the logs, as well as their schools’ senior managers, were interviewed as part of a ‘deep audit’ of ICT provision conducted over two days. One-hour follow-up interviews with the teachers were carried out after the teachers’ log activity. The aim of this was to obtain a broader contextualisation of their teaching

Making Presentation Math Computable

This Open-Access-book addresses the issue of translating mathematical expressions from LaTeX to the syntax of Computer Algebra Systems (CAS). Over the past decades, especially in the domain of Sciences, Technology, Engineering, and Mathematics (STEM), LaTeX has become the de-facto standard to typeset mathematical formulae in publications. Since scientists are generally required to publish their work, LaTeX has become an integral part of today's publishing workflow. On the other hand, modern research increasingly relies on CAS to simplify, manipulate, compute, and visualize mathematics. However, existing LaTeX import functions in CAS are limited to simple arithmetic expressions and are, therefore, insufficient for most use cases. Consequently, the workflow of experimenting and publishing in the Sciences often includes time-consuming and error-prone manual conversions between presentational LaTeX and computational CAS formats. To address the lack of a reliable and comprehensive translation tool between LaTeX and CAS, this thesis makes the following three contributions. First, it provides an approach to semantically enhance LaTeX expressions with sufficient semantic information for translations into CAS syntaxes. Second, it demonstrates the first context-aware LaTeX to CAS translation framework LaCASt. Third, the thesis provides a novel approach to evaluate the performance for LaTeX to CAS translations on large-scaled datasets with an automatic verification of equations in digital mathematical libraries. This is an open access book

A Culturally Aware Approach to Learning System Interface Design

This mixed methods research explored interface design strategies for users from different cultures and localized settings. Guided by the cultural-historical development theory and HCI research, four critical factors—navigation design, information organization, layout design, and visuals—were investigated in designing culturally relevant interfaces for Americans and Taiwanese. American and Taiwanese groups—both contained two sub-groups of 30 participants—were recruited for the quantitative phase. Each participant was exposed to only one interface with content composed in their native language. However, one sub-group in each ethnic group was exposed to a culturally relevant interface and another was exposed to an alien interface. MANOVA on overall performance in both American and Taiwanese groups were significant. Americans performed better using the American interface (Wilks’s Λ=.85, F= 5.15, p< .01). They had significantly shorter performance time in the American (M=775) than the Taiwanese (M=1003) interface (F=6.29, p<.05), but differences on performance accuracy were not significant (F=2.74, p=.103). Taiwanese performed better using the Taiwanese interface (Wilks’s Λ=.67, F=14.06, p< .01). They had shorter performance time in the Taiwanese (M=743) than the American (M=1353) interface (F=6.29, p<.05), and they also had higher performance accuracy on the Taiwanese (M=11.7) than the American (M=10.0) interface (F=7.94, p<.01). In addition, t-test on overall preference in both American and Taiwanese groups were significant. Americans preferred the American (M=58.5) over the Taiwanese (M=53.0) interface (t=2.11, p< .05). And Taiwanese preferred the Taiwanese (M=58.7) over the American (M=46.9) interface (t=3.48, p<.01). Qualitative interviews of six American and six Taiwanese participants revealed three themes: First, when searching, Taiwanese were explorative and relied on hierarchical relationships; while Americans relied on prior experiences and analytical categorizations. Second, both groups have higher affiliation with design features matching their preferences. Finally, matching design features with users’ expectations and needs promotes positive perceptions and enhances interface usability. Both quantitative and qualitative Results imply that user interface designers should consider cultural perspectives when designing interfaces for online learning systems. Further studies might consider the relative impacts of the navigation, information structure, layout, and visual design on a broad range of user differences might have on learning

Usability and digital inclusion: standards and guidelines

This article aims at discussing e-government website usability in relation to concerns about digital inclusion. E-government web design should consider all aspects of usability, including those that make it more accessible to all. Traditional concerns of social exclusion are being superseded by fears that lack of digital competence and information literacy may result in dangerous digital exclusion. Usability is considered as a way to address this exclusion and should therefore incorporate inclusion and accessibility guidelines. This article makes an explicit link between usability guidelines and digital inclusion and reports on a survey of local government web presence in Portugal

Visualisation of Interactions in Online Collaborative Learning Environments

Much research in recent years has focused on the introduction of ‘Virtual Learning Environments’ (VLE’s) to universities, documenting practice and sharing experience. Communicative tools are the means by which VLE’s have the potential to transform learning with computers from being passive and transmissive in nature, to being active and constructivist. Attention has been directed towards the importance of online dialogue as a defining feature of the VLE. However, practical methods of reviewing and analysing online communication to encode and trace cycles of real dialogue (and learning) have proved somewhat elusive. Qualitative methods are under-used for VLE discussions, since they demand new sets of research skills for those unfamiliar with those methods. Additionally, it can be time-intensive to learn them. This thesis aims to build an improved and simple-to-use analytical tool for Moodle that will aid and support teachers and administrators to understand and analyse interaction patterns and knowledge construction of the participants involved in ongoing online interactions. After reviewing the strengths and shortcomings of the existing visualisation models, a new visualisation tool called the Virtual Interaction Mapping System (VIMS) is proposed which is based on a framework proposed by Schrire (2004) to graphically represent social presence and manage the online communication patterns of the learners using Moodle. VIMS produces multiple possible views of interaction data so that it can be evaluated from many perspectives; it can be used to represent interaction data both qualitatively and quantitatively. The units of analysis can be represented graphically and numerically for more extensive evaluation. Specifically, these indicators are communication type, participative level, meaningful content of discussion, presence of lurkers, presence of moderators, and performance of participants individually and as a group. It thus enables assessment of the triangular relationship between conversationcontent, online participation and learnin

Math expression retrieval using symbol pairs in layout trees

We have developed a layout-based math retrieval system by indexing on pairs of symbols in mathematical expressions. Existing approaches to layout-based retrieval include tree edit distance-based matching on MathML trees (Kamali and Tompa, 2013) and longest common subsequence matching in LATEX strings (Kumar et al., 2012). In our work, we compare our new layout-based retrieval method with a math retrieval system built using the conventional text-based retrieval system Lucene (Zanibbi and Yuan, 2011), as such systems are commonly used for math search. We show that the search results returned by our system are scored by participants in a study as significantly more similar than those of the comparison system and that our system is fast enough to be used in real time

Making Presentation Math Computable

This Open-Access-book addresses the issue of translating mathematical expressions from LaTeX to the syntax of Computer Algebra Systems (CAS). Over the past decades, especially in the domain of Sciences, Technology, Engineering, and Mathematics (STEM), LaTeX has become the de-facto standard to typeset mathematical formulae in publications. Since scientists are generally required to publish their work, LaTeX has become an integral part of today's publishing workflow. On the other hand, modern research increasingly relies on CAS to simplify, manipulate, compute, and visualize mathematics. However, existing LaTeX import functions in CAS are limited to simple arithmetic expressions and are, therefore, insufficient for most use cases. Consequently, the workflow of experimenting and publishing in the Sciences often includes time-consuming and error-prone manual conversions between presentational LaTeX and computational CAS formats. To address the lack of a reliable and comprehensive translation tool between LaTeX and CAS, this thesis makes the following three contributions. First, it provides an approach to semantically enhance LaTeX expressions with sufficient semantic information for translations into CAS syntaxes. Second, it demonstrates the first context-aware LaTeX to CAS translation framework LaCASt. Third, the thesis provides a novel approach to evaluate the performance for LaTeX to CAS translations on large-scaled datasets with an automatic verification of equations in digital mathematical libraries. This is an open access book

Querying Large Collections of Semistructured Data

An increasing amount of data is published as semistructured documents formatted with presentational markup. Examples include data objects such as mathematical expressions encoded with MathML or web pages encoded with XHTML. Our intention is to improve the state of the art in retrieving, manipulating, or mining such data. We focus first on mathematics retrieval, which is appealing in various domains, such as education, digital libraries, engineering, patent documents, and medical sciences. Capturing the similarity of mathematical expressions also greatly enhances document classification in such domains. Unlike text retrieval, where keywords carry enough semantics to distinguish text documents and rank them, math symbols do not contain much semantic information on their own. Unfortunately, considering the structure of mathematical expressions to calculate relevance scores of documents results in ranking algorithms that are computationally more expensive than the typical ranking algorithms employed for text documents. As a result, current math retrieval systems either limit themselves to exact matches, or they ignore the structure completely; they sacrifice either recall or precision for efficiency. We propose instead an efficient end-to-end math retrieval system based on a structural similarity ranking algorithm. We describe novel optimization techniques to reduce the index size and the query processing time. Thus, with the proposed optimizations, mathematical contents can be fully exploited to rank documents in response to mathematical queries. We demonstrate the effectiveness and the efficiency of our solution experimentally, using a special-purpose testbed that we developed for evaluating math retrieval systems. We finally extend our retrieval system to accommodate rich queries that consist of combinations of math expressions and textual keywords. As a second focal point, we address the problem of recognizing structural repetitions in typical web documents. Most web pages use presentational markup standards, in which the tags control the formatting of documents rather than semantically describing their contents. Hence, their structures typically contain more irregularities than descriptive (data-oriented) markup languages. Even though applications would greatly benefit from a grammar inference algorithm that captures structure to make it explicit, the existing algorithms for XML schema inference, which target data-oriented markup, are ineffective in inferring grammars for web documents with presentational markup. There is currently no general-purpose grammar inference framework that can handle irregularities commonly found in web documents and that can operate with only a few examples. Although inferring grammars for individual web pages has been partially addressed by data extraction tools, the existing solutions rely on simplifying assumptions that limit their application. Hence, we describe a principled approach to the problem by defining a class of grammars that can be inferred from very small sample sets and can capture the structure of most web documents. The effectiveness of this approach, together with a comparison against various classes of grammars including DTDs and XSDs, is demonstrated through extensive experiments on web documents. We finally use the proposed grammar inference framework to extend our math retrieval system and to optimize it further