In modern societies, the role of reading is becoming increasingly crucial. Hence, any impairment to the reading ability can seriously limit a person's aspirations. The enormous importance of reading as an essential skill in modern life has encouraged many researchers to try and find more effective intervention approaches. Technology has been used extensively to assist and enhance literacy learning. This analytical review aims at presenting a comprehensive overview of the existing research on technology-based or technology-assisted reading interventions for elementary grades, between 2000 and 2017, along with analyzing various aspects of these studies. After extensive research, 42 articles have met the inclusion criteria, which have evaluated a total of 32 reading programs. The studies are classified into six categories of phonological awareness, phonics, vocabulary, comprehension, fluency, and multi-component. Each reading category begins with a brief introduction. Then, the content and instructional mechanisms of each program in the category is explained, alongside the outcome of its interventions. It is found that vocabulary interventions, as well as using mobile, tablet and other non-computer technologies are massively overlooked. Furthermore, a very limited number of programs focused on fluency, none of them addressed all its components. In addition, despite the required long-term practice for fostering fluency, the reviewed studies have an average intervention time shorter than other intervention categories. This paper provides researchers and solution developers with an extensive and informative review of the current state of the art in reading interventions. Additionally, it identifies the current knowledge gaps and defines future research directions to develop effective reading programs.

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -This paper aims to report the development and key features of a novel virtual reality system for assembly planning and evaluation called Haptic Assembly and Manufacturing System (HAMS). The system is intended to be used as a tool for training, design analysis and path planning. Design/methodology/approach -The proposed system uses the physics-based modelling (PBM) to perform assemblies in virtual environments. Moreover, dynamic assembly constrains have been considered to reduce the degrees of freedom of virtual objects and enhance the virtual assembly performance. Findings -To evaluate the effectiveness and performance of HAMS, the assembly of various mechanical components has been carried out, and the results have shown that it can be effectively used to simulate, evaluate, plan and automatically formalise the assembly of complex models in a more natural and intuitive way.Research limitations/implications -The collision detection performance is the bottleneck in any virtual assembly system. New methods of collision shape representation and collision detection algorithms must be considered. Originality/value -HAMS introduces the use of dynamic assembly constraints to enhance the virtual assembly performance. HAMS also uses features not yet reported by similar systems in the literature. These features include: automatic or manual definition of assembly constraints within the virtual assembly system; the implementation of control panels and widgets to modify simulation parameters during running time to evaluate its influence on simulation performance; assembly data logging such as trajectories, forces and update rates for post-processing, further analysis or its presentation in the form of chronocyclegraphs to graphically analyse the assembly process.

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Physically-based behavior of parts and subassemblies provides the user with realistic virtual assembly planning environment. Parts’ mating is an important phase of the assembly operation. It determines the feasibility of the operation and affects the assembly sequence generated from the interaction with virtual parts. Haptic sensation of forces generated by the contacts between parts, during the mating phase, is a perception cue which assists the operator in locating the parts in their final assembly positions and orientations [1]. The research work reported in this paper focuses on modeling the dynamic behavior of mechanical parts during the execution of virtual assembly operation. The concept of spring-damper model was adopted to preclude the interpenetration of parts during the mating phase. The concept of “visual dynamic behavior” representing the manipulation of real parts was developed. More investigations are required to extend this concept to include the manipulation of subassemblies.

A stroke is a life-changing event that may end up as a disability, with repercussions on the patient’s quality of life. Stroke rehabilitation therapies are helpful to regain some of the patient’s lost functionality. However, in practice stroke patients may suffer from a gradual loss of motivation. Gamified systems are used to increase user motivation, hence, gamified elements have been implemented into stroke rehabilitation therapies in order to improve patients’ engagement and adherence. This review work focuses on selecting and analyzing developed and validated gamified stroke rehabilitation systems published between 2009 and 2017 to identify the most important features of these systems. After extensive research, 32 articles have met the selection criteria, resulting in a total of 28 unique works. The works were analyzed and a total of 20 features were identified. The features are explained, making emphasis on the works that implement them extensively. Finally, a classification of features based on objectives is proposed, which was used to identify the relationships between features and implementation gaps. It was found that there is a tendency to develop low-cost solutions as in-home therapy systems and provide a variety of games. This review allowed the definition of the opportunities for future research direction such as systems addressing the three rehabilitation areas; data analytics to make decisions; motivational content identification based on automatic engagement detection and emotion recognition; and alert systems for patient´s safety.

Novel interaction techniques have been developed to address the difficulties of selecting moving targets. However, similar to their static-target counterparts, these techniques may suffer from clutter and overlap, which can be addressed by predicting intended targets. Unfortunately, current predictive techniques are tailored towards static-target selection. Thus, a novel approach for predicting user intention in movingtarget selection tasks using decision-trees constructed with the initial physical states of both the user and the targets is proposed. This approach is verified in a virtual reality application in which users must choose, and select between different moving targets. With two targets, this model is able to predict user choice with approximately 71% accuracy, which is significantly better than both chance and a frequentist approach. KeywordsDepartment of Psychology, Virtual Reality Application Center, User intention, prediction, Fitts' Law, movingtarget selection, perceived difficulty, decision trees, virtual reality Abstract. Novel interaction techniques have been developed to address the difficulties of selecting moving targets. However, similar to their static-target counterparts, these techniques may suffer from clutter and overlap, which can be addressed by predicting intended targets. Unfortunately, current predictive techniques are tailored towards static-target selection. Thus, a novel approach for predicting user intention in movingtarget selection tasks using decision-trees constructed with the initial physical states of both the user and the targets is proposed. This approach is verified in a virtual reality application in which users must choose, and select between different moving targets. With two targets, this model is able to predict user choice with approximately 71% accuracy, which is significantly better than both chance and a frequentist approach.

This article presents the design and implementation of a handheld Augmented Reality (AR) system called Mobile Augmented Reality Touring System (M.A.R.T.S). The results of experiments conducted during museum visits using this system are also described. These experiments aim at studying how such a tool can transform the visitor's learning experience by comparing it to two widely used museum systems. First, we present the museum's learning experience and a related model which emerged from the state of the art. This model consists of two types of activity experienced by the observer of a work of art: sensitive and analytical. Then, we detail M.A.R.T.S architecture and implementation. Our empirical study highlights the fact that AR can direct visitors' attention by emphasizing and superimposing. Its magnifying and sensitive effects are well perceived and appreciated by visitors. The obtained results reveal that M.A.R.T.S contributes to a worthwhile learning experience.

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