 Subjects -> ELECTRONICS (Total: 207 journals)
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PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Semantic Navigation of PowerPoint-Based Lecture Video for AutoNote
Generation-
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Authors:
Chengpei Xu;Wenjing Jia;Ruomei Wang;Xiangjian He;Baoquan Zhao;Yuanfang Zhang;
Pages: 1 - 17
Abstract: With the increasing popularity of open educational resources in the past few decades, more and more users watch online videos to gain knowledge. However, most educational videos only provide monotonous navigation tools and lack elaborating annotations. This makes the task of locating interesting contents time consuming. To address this limitation, in this article, we propose a slide-based video navigation tool that is able to extract the hierarchical structure and semantic relationship of visual entities in videos, by integrating multichannel information. Features of visual entities are first extracted from the presentation slides by a novel deep learning framework. Then, we propose a clustering approach to extract hierarchical relationships between visual entities (e.g., formulas, texts, or graphs appearing in educational slides). We use this information to associate visual entities with their corresponding audio speech text, by evaluating their semantic relationship. We present two cases where we use the structured data produced by this tool to generate a multilevel table of contents and notes to provide additional navigation materials for learning. The evaluation experiments demonstrate the effectiveness of our proposed solutions for visual entity extraction, hierarchical relationship extraction, as well as corresponding speech text matching. The user study also shows promising improvement in the autogenerated table of contents and notes for facilitating learning.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Low-Cost Open-Source Robotic Platform for Education
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Authors:
Luka Čehovin Zajc;Anže Rezelj;Danijel Skočaj;
Pages: 18 - 25
Abstract: This article describes an open-source robotic manipulator platform aimed at different levels of STEM education and popularization. It presents the hardware that was used to make a suitable low-cost low-weight manipulator and an evaluation of its capabilities, as well as the software components that were developed to make the platform accessible at different levels of education and in various usage scenarios. Finally, the results of a comprehensive user evaluation study spanning over several years are presented. The system was tested in several different educational scenarios, ranging from a summer school for primary-school students to a university-level course. The results of the study show that the introduction of the system into the educational process improves the motivation as well as the acquired knowledge of the participants.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Leveraging Semantic Facets for Automatic Assessment of Short Free Text
Answers-
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Authors:
Chen Qiao;Xiao Hu;
Pages: 26 - 39
Abstract: Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a “black box” manner without analyzing their semantic components, which at least partially limit the prediction performance. In this article, we focus on fine-grained semantic facets in free text answers that correspond to knowledge to be mastered. Using a dataset with semantic facet annotation, we first show the correspondence of semantic facet matching states and answer quality, as well as the importance of semantic facets in automatic assessment of answer quality. We then extend the work to a dataset without semantic facet annotation and demonstrate the effectiveness of proposed automated methods in assessing answer quality, including semantic facet extraction, matching state prediction based on a neural framework, and feature engineering with semantic facets. The contribution of this research is twofold: 1) the proposed methods improve state-of-the-art performance of automatic assessment of free text answers and 2) it delves into fine-grained semantic components of free text answers, making it possible to explain the scores and generate detailed feedback.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Generation of Multiple-Choice Questions From Textbook Contents of
School-Level Subjects-
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Authors:
Dhawaleswar Rao CH;Sujan Kumar Saha;
Pages: 40 - 52
Abstract: Multiple-choice question (MCQ) plays a significant role in educational assessment. Automatic MCQ generation has been an active research area for years, and many systems have been developed for MCQ generation. Still, we could not find any system that generates accurate MCQs from school-level textbook contents that are useful in real examinations. This observation motivated us to develop a system that generates MCQs to assess the student's recall of factual information. Also, the available systems are often domain, subject, or application-specific in nature. Although the MCQ generation task demands a specific setup, we expect a level of generalization can be achieved. In this development, we also focus on this issue. We propose a pipeline for automatic generation of MCQs from textbooks of middle-school level subjects, and the pipeline is partially subject-independent. The proposed pipeline comprises four core modules: preprocessing, sentence selection, key selection, and distractor generation. Several techniques have been employed to implement individual modules. These include sentence simplification, syntactic and semantic processing of the sentences, entity recognition, semantic relationship extraction among entities, WordNet, neural word embedding, neural sentence embedding, and computation of intersentence similarity. The system is evaluated using the National Council of Educational Research and Training (NCERT), India, textbooks for three subjects. The quality of system-generated questions is assessed by human experts using various system-level and individual module-level metrics. The experimental results demonstrate that the proposed system is capable of generating quality questions that could be useful in a real examination.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- WebART: Web-Based Augmented Reality Learning Resources Authoring Tool and
Its User Experience Study Among Teachers-
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Authors:
Enrui Liu;Su Cai;Zifeng Liu;Changhao Liu;
Pages: 53 - 65
Abstract: Augmented reality (AR) has been incorporated into the educational context for years. Numerous studies have demonstrated the effectiveness of AR in different disciplines, learning styles, and learning environments. However, few studies have focused on the problem of generating AR applications in authentic educational contexts. In this study, an AR learning resource authoring tool called WebART was designed and developed to help teachers with no prior programming experience create and share AR learning resources. This study collected feedback and opinions on WebART from 51 K-12 teachers through questionnaires and interviews. Multiple linear regression was used to measure the relationships between teachers’ intentions to use technology and the user experience of the proposed WebART tool. The questionnaire results revealed that multiple variables in teachers’ intentions are predictive of user experience. Interview results showed that teachers had a positive attitude toward the AR learning resources authoring tools inspiring novel ways of teaching and learning.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Exploring the Potential of Tangible and Multitouch Interfaces to Promote
Learning Among Preschool Children-
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Authors:
Chung-Ming Own;Tingting Cai;Cheng-Yu Hung;
Pages: 66 - 77
Abstract: Studies have highlighted the possible advantages of tangible user interfaces (TUIs) over multitouch interfaces (MTIs) in preschool education; however, more objective evidence is required to establish the superiority of TUIs. In this article, we design a mathematical application called THE NUMBERS to compare preschool children's learning potential and employed the eye-tracking method to assess the cognitive differences between the TUI and MTI versions. The results demonstrate that the TUI version participants made more attempts in the task, which was a significant predictor of learning outcomes. Furthermore, using TUIs leads to lower cognitive load, increases attention on key areas, and provides higher entertainment value, which has long-term effects on promoting preschool children's learning. The results of the perception questionnaire show that the TUI version is easier to use, more interesting, and more motivating for them to learn mathematics than the MTI version is. On the other hand, the interview results show that 62.5% of students prefer to use the TUI version to learn mathematics. The results can provide educators with a deeper understanding of the mental characteristics involved in MTIs and TUIs to enable them to design educational applications that are more suitable for preschool children.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Development of a Computer-Aided Education System Inspired by Face-to-Face
Learning by Incorporating EEG-Based Neurofeedback Into Online Video
Lectures-
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Authors:
Hodam Kim;Younsoo Chae;Suhye Kim;Chang-Hwan Im;
Pages: 78 - 91
Abstract: Owing to the rapid development of information and communication technologies, online or mobile learning content is widely available on the Internet. Unlike traditional face-to-face learning, online learning exhibits a critical limitation: real-time interactions between learners and teachers are generally not feasible in online learning. To overcome this issue, we implemented an online learning system based on electroencephalography (EEG)-based passive brain-computer interface technology referred to as the “adaptive neuro-learning system (ANLS).” It monitors the current mental states of learners seamlessly using EEG signals. Then, it adaptively provides natural and interactive video feedback rather than simple alarms or pop quizzes following the current mental conditions of a learner. In this article, a total of 60 university students were assigned randomly to one of four groups: two experimental groups, for which either ANLS based on attention state estimation or ANLS based on both attention and comprehension states estimation was tested, and two control groups, the students in which were taught using either the conventional online lecture without feedback or an online course with randomized video feedbacks. Each member of these groups attended a 53 min open courseware video lecture. Then, the educational effects of the proposed system were evaluated quantitatively via a written examination. Our results revealed a significantly higher learning performance for the experimental group (average test score of the experimental groups = 83.83 and that of the control groups = 56.67), demonstrating the feasibility of the proposed education strategy.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Adaptive Learning Support System Based on Automatic Recommendation of
Personalized Review Materials-
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Authors:
Fumiya Okubo;Tetsuya Shiino;Tsubasa Minematsu;Yuta Taniguchi;Atsushi Shimada;
Pages: 92 - 105
Abstract: In this study, we propose an integrated system to support learners' reviews. In the proposed system, the review dashboard is used to recommend review contents that are adaptive to the individual learner's level of understanding and to present other information that is useful for review. The pages of the digital learning materials that are estimated to be insufficiently understood by each learner and the webpages related to those pages are recommended. As a method for estimating such pages, we consider extracting the pages related to the questions that were answered incorrectly. We examined the accuracy of matching each question with the pages of the learning materials. We also conducted an experiment to verify the usefulness of the system and its effect on learning using a review dashboard. In the experiment, the evaluation of the review dashboard indicated that at least half of the participants found it useful for most types of feedback. In addition, the rate of change in quiz scores was significantly higher in the group using the review dashboard, which indicates that using the review dashboard has the effect of improving learning.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Assessing the Quality of Student-Generated Content at Scale: A Comparative
Analysis of Peer-Review Models-
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Authors:
Ali Darvishi;Hassan Khosravi;Afshin Rahimi;Shazia Sadiq;Dragan Gašević;
Pages: 106 - 120
Abstract: Engaging students in creating learning resources has demonstrated pedagogical benefits. However, to effectively utilize a repository of student-generated content (SGC), a selection process is needed to separate high- from low-quality resources as some of the resources created by students can be ineffective, inappropriate, or incorrect. A common and scalable approach is to use a peer-review process where students are asked to assess the quality of resources authored by their peers. Given that judgments of students, as experts-in-training, cannot wholly be relied upon, a redundancy-based method is widely employed where the same assessment task is given to multiple students. However, this approach introduces a new challenge, referred to as the consensus problem: How can we assign a final quality to a resource given ratings by multiple students' To address this challenge, we investigate the predictive performance of 18 inference models across five well-established categories of consensus approaches for inferring the quality of SGC at scale. The analysis is based on the engagement of 2141 undergraduate students across five courses in creating 12 803 resources and 77 297 peer reviews. Results indicate that the quality of reviews is quite diverse, and students tend to overrate. Consequently, simple statistics such as mean and median fail to identify poor-quality resources. Findings further suggest that incorporating advanced probabilistic and text analysis methods to infer the reviewers' reliability and reviews' quality improves performance; however, there is still an evident need for instructor oversight and training of students to write compelling and reliable reviews.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- An Immersive Virtual Field Experience Structuring Method for Geoscience
Education-
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Authors:
Rafael Kenji Horota;Pedro Rossa;Ademir Marques;Luiz Gonzaga;Kim Senger;Caroline Lessio Cazarin;André Spigolon;Maurício Roberto Veronez;
Pages: 121 - 132
Abstract: Digital outcrop models (DOMs) have facilitated quantitative and qualitative studies in digital and virtual environments of source and reservoir rock analogs important to the oil industry. The use of immersive virtual reality (iVR) to extend field experiences has motivated several research groups to develop software integrating iVR techniques with tools to interpret and derive geological information from DOMs. This virtual approach can also contribute to the development of geological and spatial thinking skills taught in the classroom and during field trips. The immersive virtual field trips (iVFTs) can provide students access to outcrops and additional data restricted to field learning activities while allowing additional interactions impossible in the field. iVFTs have been developed recently; however, the structuring of iVFTs for geology classes has not been presented in a way that inexperienced iVR users can make use of such systems. In this scenario, our work proposes a method to structure an iVFT using georeferenced data containers and the virtual reality software Mosis LAB while evaluating users' perceptions during an iVFT study case. The evaluation using technology acceptance model questionnaires showed that users were positively impacted by the observational iVFT experience, effectively supporting e-learning, and class field learning activities and preparations. This approach allows field trip experiences in less accessible study sites, especially in less favorable conditions like the ones during the Coronavirus 2019 pandemic where many geoscience departments had their field trips hampered.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Leveraging Extended Reality for Autistic Individuals: A Scoping Review of
Technical Features and Technology Affordances-
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Authors:
Peidi Gu;Xinhao Xu;Xueqin Qian;Tsung-Han Weng;
Pages: 133 - 149
Abstract: Multiple studies have examined learning and training for autistic students to improve their quality of life by using eXtended-Reality (XR) technologies, which mainly include virtual reality (VR), augmented reality (AR), and mixed reality (MR). Nevertheless, little is known about how technical features and technology affordances of the XR environment are used and addressed in these studies. In this article, we had reviewed 66 empirical studies regarding XR for autistic individuals and examined the corresponding research designs from 3 major dimensions, namely, autonomy (i.e., the degree of freedom users have), human–computer interaction, and the sense of presence. We then investigated the technical features and technology affordances in these studies through the lenses of these three dimensions. Fifty-four (81.82%) studies used VR as their interventional tool, eleven (16.67%) studies used AR, and only one (1.52%) study used MR. Results showed that the use of different XR platforms is closely related to the technical features, technology affordances, and study characteristics. We further provided an extraction of the essentials that serve as a practical reference for educational researchers and practitioners to inspect the design and implementation of XR technologies in learning and training environments for autistic students.
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
- Are you interested in Immersive Learning'
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Pages: 150 - 151
PubDate:
Feb. 1 2023
Issue No: Vol. 16, No. 1 (2023)
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