This systematic review study synthesizes research findings pertaining to the use of augmented reality (AR) in language learning. Published research from 2014 to 2019 has been explored and specific ...inclusion and exclusion criteria have been applied resulting in 54 relevant publications. Our findings determined: (a) devices and software employed for mastering AR; languages and contexts in which AR had been applied; theoretical perspectives adopted for guiding the use of AR; the number of participants in AR activities and benefits from using AR as an educational tool in the language classroom; (b) alignment of the affordances of Augmented Reality with the KSAVE (Knowledge, Skills, Attitudes, Values, Ethics) 21st‐century skills framework; (c) future directions in AR research and practice. The main findings from this review demonstrate the popularity of mobile‐based AR for supporting vocabulary (23.9%), reading (12.7%), speaking (9.9%) writing (8.5%) or generic language skills (9.9%). Our findings also uncovered areas that merit future attention in the application of AR in language learning – for instance learning theories were not often considered in the implementation of AR. The study concludes with suggestions for future research especially in the areas of instructional design and user experience.
Lay Description
What is currently known about the subject matter
Augmented reality (AR) has become an attractive trend in language learning.
A number of reviews on AR in education have been conducted.
The state of current research on AR in language learning lacks a comprehensive review.
What their paper adds to this
The paper presents a systematic review of relevant academic literature on AR in the field of language learning.
The paper provides empirical evidence on the benefits of AR in language learning based on selected literature.
The findings revealed that the majority of AR studies are mobile‐based.
The main findings from this review demonstrate the popularity of mobile‐based AR for supporting vocabulary, reading, speaking writing or generic language skills.
Future research in AR is needed with focus on instructional design and user experience.
Implications of study findings for practitioners
The systematic review adds to the body of knowledge a firm review of recent research findings in the field.
Given the increased potential of AR, future research needs to focus on the development of under‐studied skills and competencies.
AR is an optimal means to implement communicative language learning, through continuous dialogue about augmented information.
This paper presents an abstract framework for the optimization of actuating and sensing devices in distributed parameter systems. The optimization is performed on the repositioning of these devices ...throughout the spatial domain. It is assumed that a network of mobile sensing and actuating devices is available to obtain measurements from the spatially distributed process and dispense control signals to the spatially distributed process. By taking advantage of the properties that the spatial operator that governs the process dynamics possesses, namely symmetry, coercivity and boundedness, a scheme for the guidance of a mobile actuator-plus-sensor network is developed and used for the performance enhancement of the spatial process. The class of systems is governed by diffusion PDEs equipped with actuators having a boxcar spatial distribution and a collocated sensing device that provides the spatially averaged state measurement over the range of the actuating device. Using Lyapunov stability arguments, a stable guidance scheme is provided for each of the mobile agents. Due to the specific structure of the closed loop system operator with time-varying input and output operators, the same guidance schemes are applicable to the dual problem of mobile sensors employed for enhancing the state estimation problem. Both a centralized state estimator with mobile sensors and a network of consensus distributed estimators are considered, since both filters can be shown to result in the specific algebraic structure of a symmetric spatial operator with collocated input and output operators. Extensive numerical simulations for a 1-D diffusion equation with two actuator/sensor agents, a 2-D diffusion equation with one collocated actuator/sensor agent plus a centralized filter for a 1-D diffusion equation are included to verify the effectiveness of a such a mobile actuator-plus-sensor network in suppressing the effects of spatially varying disturbances and enhancing the system's performance.
The regression-based reconstruction of spatial fields by static sensors requires the number of measurements be at least equal to the number of unknown parameters in order to provide a unique ...solution. Improvements include the use of mobile sensor networks to arrive at higher accuracy estimates. An alternate approach utilizes adaptive techniques to update the parameter estimates online. Such adaptive techniques need persistence of excitation to ensure convergence of the parameter and function estimates. It is shown that the motion of just a single sensor is a necessary condition for persistence of excitation and, subsequently, of function convergence. Having a prescribed sensor guidance is also a sufficient condition for function convergence. First, a Lyapunov-based adaptation and guidance is presented and it is shown that persistence of excitation necessitates the time dependence of the outer product of the regressor vector with itself and which in turn requires the motion of the sensor within the spatial domain. Subsequently, a gradient-based adaptive scheme relaxes the Lyapunov-based sensor guidance to any user-defined guidance as long as the outer product of the associated rank-one regressor vector with itself has a uniformly positive definite integral. The latter adaptation is conducive to the inclusion of platform dynamics resulting in a vehicle control design needed to attain parameter convergence. Extension of the centralized solution to distributed estimation using a network of mobile sensors is also examined. These results are demonstrated with simulations in one and two dimensions.
The main focus of this work is on the inclusion of vehicle dynamics for the control of spatially distributed processes utilizing mobile actuators and sensors. It is assumed that spatially collocated ...actuator/sensor pairs, affixed on vehicles, are capable of moving within the spatial domain and a combined control law-plus-guidance law is proposed in order to better address the effects of spatiotemporally varying disturbances. The proposed control architecture is simplified by using static output feedback combined with adaptation of the feedback gains. A Lyapunov redesign approach is employed to derive the guidance laws via the appropriate use of the vehicle control torques. Such guidance laws are gradient-based and tend to move the vehicle to spatial locations with large spatial gradients. The novelty here is that vehicle dynamics are directly coupled to the process dynamics and their motion is solely and explicitly dictated by the control performance of the spatially distributed process. Extensive numerical studies of a 2-D diffusion PDE with a mobile robot are included and which demonstrate the effectiveness of the proposed combined control law-plus-guidance law.
This review presents an outline of executive function (EF) and its application to autism spectrum disorder (ASD). The development of the EF construct, theoretical models of EF, and limitations in the ...study of EF are outlined. The potential of EF as a cognitive endophenotype for ASD is reviewed, and the Research Domain Criteria (RDoC) framework is discussed for researching EF in ASD given the multifaceted factors that influence EF performance. A number of executive-focused cognitive models have been proposed to explain the symptom clusters observed in ASD. Empirical studies suggest a broad impairment in EF, although there is significant inter-individual variability in EF performance. The observed heterogeneity of EF performance is considered a limiting factor in establishing EF as a cognitive endophenotype in ASD. We propose, however, that this variability in EF performance presents an opportunity for subtyping within the spectrum that can contribute to targeted diagnostic and intervention strategies. Enhanced understanding of the neurobiological basis that underpins EF performance, such as the excitation/inhibition hypothesis, will likely be important. Application of the RDoC framework could provide clarity on the nature of EF impairment in ASD with potential for greater understanding of, and improved interventions for, this disorder.
This work considers a class of networked distributed parameter systems with structured perturbations and disturbances. These systems are assumed to have identical unknown structured perturbations and ...unknown disturbances but different initial conditions. The multi-task controllers aim to adaptively compensate both structured perturbation and disturbance effects. Additionally, to follow a virtual leader by ensuring the asymptotic convergence of each of the networked states to the leader’s state. Finally, to synchronize in the sense of the convergence of the pairwise state errors. A four-part controller is proposed to address all tasks and provides many new elements for control of networked spatially distributed systems. The adaptive estimates of both the disturbance and the structured perturbation terms include a consensus term in their adaptive laws which provide the first coupling of the networked systems and aims at providing a weak version of persistence of excitation. The consensus protocol included in the synchronization component of the controller addresses the communication burden by transmitting output signals to its communicating systems instead of entire states and further, adapts the synchronization weights in proportion to the pairwise state disagreement, as a means to minimize the control effort. An abstract theoretical framework is established which handles a wide class of infinite dimensional systems including PDEs with both in-domain and boundary control and observation, and is conducive to well-posedness and stability analysis. Using the proposed multi-component controllers, the convergence of the networked states to the leader’s state is established using Lyapunov stability arguments for infinite dimensional systems, along with the boundedness of all signals. The well-posedness of all networked closed loop systems is shown by using established results on an analytic semigroup approach. A numerical example involving five networked partial differential equations with boundary observation, control, and disturbances and structured perturbations at the boundary, is presented and which provides insights on the control and synchronization of networked PDE systems.
This article proposes a new type of a consensus protocol for the synchronization of distributed observers in systems governed by parabolic partial differential equations. Addressing the goal of ...sharing useful information among distributed observers, it delves into the details governing the modal decompositions of distributed parameter systems. Assuming that two different groups of sensors are available to provide process information to the two distributed observers, the proposed modal consensus design ensures that only useful information is transmitted to the requisite modal components of each of the observers. Without any consensus protocol, the observers capture different frequency content of the spatial process in differing degrees, as it relates to the concept of modal observability. Their modal components exhibit different learning behavior toward the process state. In the extreme case, it turns out that certain modal components of the distributed observers occasionally behave as naïve observers. To ensure that, both collectively and modal componentwise, the observers agree both with the process state and with each other, a modal component consensus protocol is proposed. Such a consensus protocol is mono‐directional and provides only useful information necessary to the appropriate modal component of the distributed filters that behaves as a naïve modal observer. This protocol, when ed and applied to different state decompositions can be viewed as mono‐directional projections of information transmitted and received by the participating distributed observers. Detailed numerical studies of advection PDE in one and two spatial dimensions are included to elucidate the details of the proposed modal consensus observers.
•Extends earlier result on unknown input observer of structural systems to include velocity measurements.•Proposes a more general version of natural unknown input functional observer for structural ...systems.•Demonstrates the reduction of the UIFO to a natural FO, a natural UIO or a natural observer.•Presents a minimum order compensator using the functional output as the control input.
This paper considers a class of linear time invariant systems that describe the dynamics of mechanical systems. Due to their algebraic structure, the dynamics of such systems are written in their natural second order framework in order to exploit this structure with the obvious computational benefits in controller and observer design. A functional observer along with an unknown input observer are combined and are presented for this class of systems. The additional advantage of this combined observer is that when certain conditions are imposed, it reduces to the standard natural second observer. This translates to guaranteeing that the derivative of the estimated position vector coincides with the estimate of the velocity vector, a case not always ensured when such system is brought in a first order realization. An added benefit resulting from the second order formulation is the minimum order compensator whose order is dictated by the rank of the control input matrix, when the proposed functional estimate is used in place of a full state control signal.
This work establishes an abstract framework that considers the distributed filtering of spatially varying processes using a sensor network. It is assumed that the sensor network consists of groups of ...sensors, each of which provides a number of state measurements from sensing devices that are not necessarily identical and which only transmit their information to their own sensor group. A modification to the local spatially distributed filters provides the non-adaptive case of spatially distributed consensus filters which penalize the disagreement amongst themselves in a dynamic manner. A subsequent modification to this scheme incorporates the adaptation of the consensus gains in the disagreement terms of all local filters. Both the well-posedness of these two consensus spatially distributed filters and the convergence of the associated observation errors to zero in appropriate norms are presented. Their performance is demonstrated on three different examples of a diffusion partial differential equation with point measurements.
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