Advances in technology have led to continuous innovation teaching and learning methods. For instance, the use of tablet PCs (TPCs) classroom instruction has been shown be effective attracting motivating students' interest increasing their desire participate activities. In this paper, we used a TPCs game – an iPad app called Motion Math: Hungry Fish help young students learn theoretically understand practically implement mathematical concepts addition subtraction. Based on findings from pilot...

Abstract Background Previous research has examined the use of augmented reality (AR) and virtual (VR) in English language teaching. However, to best our knowledge, none earlier studies that investigated integrating AR VR “wearables” into teaching learning based on attention, relevance, confidence, satisfaction (ARCS) motivation model compared differences performance between traditional methods those using AR‐ VR‐based wearables. Objectives To create a thematic environment learners' lived...

This study aimed to investigate the effect of flipped classrooms integrated with massive open online courses (MOOCs) and game-based learning on motivation outcomes students from different backgrounds (in terms gender, grade, self-confidence indicators in mathematics, roles played process). Surveys a semi-structured questionnaire were used for data collection, including basic information (to understand participants' backgrounds), (the Motivated Strategies Learning Questionnaire, MSLQ), test...

This study, based on Taiwanese geographical concepts, develops a multi-touch interactive jigsaw puzzle (MIJP) to assist primary school students in solving puzzles. The MIJP, which has operating characteristics and provides two kinds of scaffolding tools, each with different level difficulty, can problems the games prevent them from feeling stuck frustrated. In addition, it explores influence game approach (three levels difficulty) learning performance satisfaction. results indicated that...

We investigate the MIMO antenna selection using space shift keying (SSK) modulation and amplitude/phase (APM). In joint SSK APM, both constellation of APM indexes convey information. The multiple-input multiple-output (MIMO) system increases capacity data rates at cost multiple RF chains, which can be reduced by techniques. this paper, techniques are jointly designed with SSK-based systems, decoding scheme achieving maximum-likelihood (ML) criterion is explicitly described. proposed criteria...

Rubrics can guide teachers to provide effective feedback and students' peer- self-assessment. This paper examines the effect of rubric use in flipped learning activities on achievement, metacognitive awareness, cognitive load through a quasi-experiment. A total 83 university students were randomly assigned an experimental group or control group. The given rubrics performing pre-class cloud platform, while those used post-class assessment modification their finished works. results show that...

The maximum likelihood (ML) detection for multiple-input multiple-output (MIMO) system achieves the optimal performances at cost of high computational complexities, while linear detectors attain low complexities with degraded performances. In this paper, we propose two low-complexity schemes based on minimum-mean-square-error (MMSE) MIMO systems. Using MMSE-detected data as starting point, first scheme searches constellation subspace using ML criterion. To further reduce complexity, second...

Multi-touch technology has become increasingly popular interactive of applied in digital game and education. The displays with multi-touch are responsive enough to support a wide variety applications. Digital offers instant feedback interactivity game-based learning environment. In this study, we have designed jigsaw for the geographical location cities Taiwan by providing effective feedbacks as scaffolds learners order reduce their frustration. Based on combination operations scaffolds,...

A new multiple-input multiple-output (MIMO) detection scheme combining minimum-mean-square-error (MMSE) and the K-best algorithm is proposed. The proposed leverages MMSE results to ease demand of a large K in conventional achieve satisfactory performance. post-detection SNR obtained after consulted determine symbols upon which reduced-dimension (h-best algorithm) performed obtain final results. Parameters associated with are empirically chosen make fair comparison algorithm. Extensive Monte...

This study investigated two science teachers' meta-strategic knowledge (MSK) of argumentation teaching by applying the repertory grid technique (RGT). One teacher was a novice, while other experienced in argumentation. Using RGT, we elicited objectives and strategies teachers regarding their involving social scientific issue (SSI) scenarios. The results showed that had more varied organised MSK for than novice teacher. Meanwhile, indicated belief learning should occur student-centred manner,...

Studies have highlighted the possible advantages of tangible user interfaces (TUIs) over multitouch (MTIs) in preschool education; however, more objective evidence is required to establish superiority TUIs. In this article, we design a mathematical application called THE NUMBERS compare children's learning potential and employed eye-tracking method assess cognitive differences between TUI MTI versions. The results demonstrate that version participants made attempts task, which was...

A major limitation of most methods exploiting sparse signal or spectral models for the purpose estimating directions-of-arrival stems from fixed model dictionary that is formed by array response vectors over a discrete search grid possible directions. In general, responses to actual DoAs will likely not be members such dictionary. this work, with uncertainty linearized parameter mismatch considered, and matrix reformulated into multiplication base matrix. Based on double-sparsity model, an...

Most audio recognition/classification systems assume a static and closed-set model, where training testing data are drawn from prior distribution.However, in real-world problems, such distribution is unknown, limited incomplete at time.As it difficult to collect exhaustive samples train classifiers.Datasets prediction time evolving the trained model must deal with an infinite number of unseen/unknown categories.Therefore, desired have open-set classifier that not only accurately classifies...

In this work, combined calibration and DoA estimation is approached as an extension of the formulation for Single Measurement Vector (SMV) model self-calibration to Multiple Model (MMV) case. By taking advantage multiple snapshots, a modified nuclear norm minimization problem proposed recover low-rank larger dimension matrix. We also give definition linear operator MMV model, its corresponding matrix representation generate variant convex optimization problem. order mitigate computational...

This paper presents a new learning strategy for the Sound Event Detection (SED) system to tackle issues of i) knowledge migration from pre-trained model target and ii) sound events without forgetting previously learned ones re-training scratch. In order migrate source one, neural adapter is employed on top model. The are merged via this layer. layer facilitates learn with minimal training data maintaining performance similar Our extensive analysis DCASE16 US-SED dataset reveals effectiveness...

The purpose of this study was to compare the influence a single-player game with that collaborative on students' motivation, attention levels, and relaxation levels in motion-sensing learning environment. Participants were 20 college students higher education institution southern Taiwan. A Kinect-based technology incorporated help enhance their reduce anxiety. Results showed when worked collaboratively, they achieved motivation. In addition, brainwave data revealed during gaming activities,...

The problem of recovering directions-of-arrival in the sparse signal model with multiple snapshots is considered. Based on theory super resolution, are used to jointly estimate continuous domain. Instead uniformly discretizing search range, interpolation preprocessing estimated super-resolution directions suggested leading a convex optimization formulation. Moreover, first order iterative algorithm employed reduce computational time. A good selection regularization parameter guaranteed via...

In this paper, a MIMO detection scheme is proposed based on combination of Monte Carlo technique and list detection. Specifically, Gaussian samples are first generated to determine the search range constellation points in which transmitted symbol most likely locate. Linear equalizations then applied equalize effect caused by channel mixing, detector used within determined range. By varying parameters method, different error rate (SER) versus complexity tradeoff can be obtained account for...

A low-complexity, effective detection method for multiple-input multiple-output (MIMO) systems based on eigenspace search and linear equalization-based schemes is proposed in this paper. Based the observation that solutions yielded by detectors are corrupted color noise, introduces a new constellation procedure to augment detectors. Specifically, calibrated conducted around initial solution detectors, directions guided eigenvectors corresponding dominant eigenvalues of covariance matrix...

Estimation of directions-of-arrival (DoA) in the spatial co-variance model is studied. Unlike compressed sensing methods which discretize search domain into possible directions on a grid, theory super resolution applied to estimate DoAs continuous domain. We reformulate spectral covariance Multiple Measurement Vector (MMV)-like model, and propose block total variation norm minimization approach, analog Group Lasso super-resolution framework that promotes group-sparsity. The can be estimated...

Digital simulation technology is widely used in science education and has enormous potential for its development. Numerous studies have shown that the use of digital an environment, especially scientific education, conducive to intuitive interaction improves students' participation their learning activities. This study investigated effects with different interactive modes (based on gesture button simulation) cognitive concepts, attention, anxiety levels elementary physics course. To collect...