2,119 research outputs found

    Lecture instrumentation based on synchronous speech transcription

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    International audience—Speech transcription can now be achieved quickly enough to generate subtitles in real-time. Research presented in this paper aims to explore the potential of synchronous transcription in instrumenting learning environments, specifically in the context of hybrid lectures. Considering available technologies, we designed a toolset in order to answer the existing needs of students and teachers. This toolset is built around the transcription of the teacher's speech, which acts as a support for interactions and provides data needed by other functionalities. We present here the different interfaces and their components, as well as the results of the user test carried out in real life conditions

    Instrumentation of learning situation using automated speech transcription : A prototyping approach

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    International audienceThis paper presents the ongoing conception of a set of tools, based on live transcription of speech during lectures and designed to instrument traditional lectures as well as web conferences or hybrid learning situations. The toolset exploits speech and interactions taking place during courses, keeps track of them and facilitates their reuse both in students' studies and in future iterations of the course delivered by the teacher. Its goal is to help students stay focused on the teacher's explanations and offer them greater possibilities of interactions. The prototype was conceived with an approach based on the analysis of communicational and informational needs of the end users, especially in regard to the instrumentation possibilities offered by the innovative technologies considered in the project. In this paper, we detail the different tools produced in order to offer synchronous and asynchronous support to the learning activity. We describe a real-life test as well as changes brought to the device afterwards, and finally we describe the first experiment conducted with the device

    Performance Following: Real-Time Prediction of Musical Sequences Without a Score

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    (c)2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

    Elaboration d'une méthodologie d'instrumentation pédagogique en contexte universitaire,

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    National audienceNous proposons dans cet article les premières étapes de l'établissement d'un canevas méthodologique permettant d'assister les acteurs de l'instrumentation de situations pédagogiques à l'aide d'outils reposant sur des technologies innovantes. Afin d'atteindre cet objectif, il a été entrepris une modélisation des différentes parties prenantes ainsi que l'environnement dans lequel s'inscrit cette instrumentation, dans ses dimensions organisationnelles et matérielles. Nous présentons le contexte de la genèse de ce modèle : l'instrumentation par un environnement outillé basé sur la transcription de la parole en direct, ainsi que d'autres technologies à l'état de prototypes de recherche. Abstract. This article presents the first steps in building a methodological framework aiming to assist contributors instrumenting pedagogical situations using tools based on innovative technologies. This framework ought to be used in various possible situations. This variety is described by a model of various stakeholders and the environment where the process is taking place, considering organizational or equipment constraints. Furthermore, we present the context leading to the creation of this model: instrumentation using a toolset based on synchronous speech transcription among other technologies in the research prototype stage

    A Survey of Smart Classroom Literature

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    Recently, there has been a substantial amount of research on smart classrooms, encompassing a number of areas, including Information and Communication Technology, Machine Learning, Sensor Networks, Cloud Computing, and Hardware. Smart classroom research has been quickly implemented to enhance education systems, resulting in higher engagement and empowerment of students, educators, and administrators. Despite decades of using emerging technology to improve teaching practices, critics often point out that methods miss adequate theoretical and technical foundations. As a result, there have been a number of conflicting reviews on different perspectives of smart classrooms. For a realistic smart classroom approach, a piecemeal implementation is insufficient. This survey contributes to the current literature by presenting a comprehensive analysis of various disciplines using a standard terminology and taxonomy. This multi-field study reveals new research possibilities and problems that must be tackled in order to integrate interdisciplinary works in a synergic manner. Our analysis shows that smart classroom is a rapidly developing research area that complements a number of emerging technologies. Moreover, this paper also describes the co-occurrence network of technological keywords using VOSviewer for an in-depth analysis

    A Single-Case Experimental Investigation of Sketch and Speak Expository Intervention for Adolescents with Language-Related Learning Disabilities via Telepractice

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    This study investigated the effects of Sketch and Speak expository language intervention for adolescent students with language-related learning disabilities (LLD). Students with LLD have trouble understanding and using academic language for reading and writing and often benefit from explicit instruction in these areas. Sketch and Speak is an expository language intervention that teaches students to take notes in two forms and to systematically use oral practice to facilitate understanding and memory of notes. First, students learn to take notes using simple sketch writing, or pictography, which allows them to focus on the ideas of the text rather than the spelling, letter formulation, and other cognitive demands of written language. Students then generate full oral sentences from their pictographic note and practice saying the sentences aloud to solidify the information in their memory. In the second session, students transfer their pictography notes and full sentences to the more traditional form of bulleted notes by identifying key words from their well-formed oral sentences. Students are also scaffolded into practicing full oral reports from their notes in each session. This combination of repeated oral practice of sentences and full reports and two types of note-taking helps students to comprehend and express information from complex informational texts. This study is a multiple baseline across participants single-case experiment. Participants completed three, six, or nine baseline sessions before moving into the treatment phase. All participants completed 12 45-minute sessions of intervention. This study is the first to investigate Sketch and Speak with adolescent students. Three ninth grade students with LLD participated in one-on-one instruction sessions via telepractice in the summer of 2021. Data was collected in each baseline and treatment session on participants’ abilities to generate Oral Reports and answer Short-Answer Recall questions about a novel topic. In baseline, participants followed along with a read-aloud informational text and then took notes on the article with no further instructional support prior to the Independent Session Test. In treatment, participants were provided with instruction on two different types of notes and systematic oral practice prior to the Guided Session Tests (Oral Report and Short-Answer Recall). Additionally, participant’s notes were examined for Note Quantity and Note Quality across session types (i.e., baseline and treatment). All three students significantly improved on their ability to compose accurate oral reports and generate more high-quality notes about the topic after participating in the intervention. Participants also completed an expository oral reporting task about a different expository content area at pre-/post-treatment. This semi-standardized activity allows for comparisons of oral report performance to typically developing peers of the same age. Though a pre-/post-treatment test is not common in a single-case design like this one, this test allowed the researcher to examine whether learned note-taking and oral reporting skills were used independently by the students in a different expository content area than was taught in treatment. All three students made significant gains in note-taking and oral reporting at post-test when compared to their independent pre-test performance. The perceived importance of the intervention and delivery mode was also examined through social validity questionnaires. Participants, parents, and speech-language pathologists answered social validity questions about the intervention and study strategies for adolescents at pre- and post-test. Responses for all three groups indicated that the intervention was viewed as meaningful. Participants reported that they had learned strategies that they could apply independently in the high school setting. The participants also answered questions about the telepractice delivery mode, with most responses indicating that it was viewed as a positive experience. This study provides evidence for the use of Sketch and Speak intervention with older students and lays the groundwork for future studies with this population. This study also contributes to the literature base on telepractice service delivery for intervention, which is important as this delivery style has become more popular after the onset of COVID-19

    Health Sciences Handbook 2009

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    Annotation of multimedia learning materials for semantic search

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    Multimedia is the main source for online learning materials, such as videos, slides and textbooks, and its size is growing with the popularity of online programs offered by Universities and Massive Open Online Courses (MOOCs). The increasing amount of multimedia learning resources available online makes it very challenging to browse through the materials or find where a specific concept of interest is covered. To enable semantic search on the lecture materials, their content must be annotated and indexed. Manual annotation of learning materials such as videos is tedious and cannot be envisioned for the growing quantity of online materials. One of the most commonly used methods for learning video annotation is to index the video, based on the transcript obtained from translating the audio track of the video into text. Existing speech to text translators require extensive training especially for non-native English speakers and are known to have low accuracy. This dissertation proposes to index the slides, based on the keywords. The keywords extracted from the textbook index and the presentation slides are the basis of the indexing scheme. Two types of lecture videos are generally used (i.e., classroom recording using a regular camera or slide presentation screen captures using specific software) and their quality varies widely. The screen capture videos, have generally a good quality and sometimes come with metadata. But often, metadata is not reliable and hence image processing techniques are used to segment the videos. Since the learning videos have a static background of slide, it is challenging to detect the shot boundaries. Comparative analysis of the state of the art techniques to determine best feature descriptors suitable for detecting transitions in a learning video is presented in this dissertation. The videos are indexed with keywords obtained from slides and a correspondence is established by segmenting the video temporally using feature descriptors to match and align the video segments with the presentation slides converted into images. The classroom recordings using regular video cameras often have poor illumination with objects partially or totally occluded. For such videos, slide localization techniques based on segmentation and heuristics is presented to improve the accuracy of the transition detection. A region prioritized ranking mechanism is proposed that integrates the keyword location in the presentation into the ranking of the slides when searching for a slide that covers a given keyword. This helps in getting the most relevant results first. With the increasing size of course materials gathered online, a user looking to understand a given concept can get overwhelmed. The standard way of learning and the concept of “one size fits all” is no longer the best way to learn for millennials. Personalized concept recommendation is presented according to the user’s background knowledge. Finally, the contributions of this dissertation have been integrated into the Ultimate Course Search (UCS), a tool for an effective search of course materials. UCS integrates presentation, lecture videos and textbook content into a single platform with topic based search capabilities and easy navigation of lecture materials
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