Supporting Online Video e-Learning with Semi-automatic Concept-Map Generation

Hayama, Tessai; Sato, Sunao

doi:10.1007/978-3-030-50513-4_5

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…A trade-off to balance cost and utility is using a semi-automatic approach, that we also currently adopt when high accuracy is required. Semi-automathic concept map generation is used for instance by Hayama and Sato [18]. The authors propose a system that allows the creation of a concept map by the learner, not from scratch but with the support of a series of candidate components such as concept-labels and related words from lecture speech texts.…”

Section: Related Workmentioning

confidence: 99%

Video augmentation to support video-based learning

Torre

Galluccio

Coccoli

2022

Proceedings of the 2022 International Conference on Advanced Visual Interfaces

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Multimedia content and video-based learning are expected to take a central role in the post-pandemic world. Thus, providing new advanced interfaces and services that further exploit their potential becomes of paramount importance. A challenging area deals with developing intelligent visual interfaces that integrate the knowledge extracted from multimedia materials into educational applications. In this respect, we designed a web-based video player that is aimed to support video consumption by exploiting the knowledge extracted from the video in terms of concepts explained in the video and prerequisite relations between them. This knowledge is used to augment the video lesson through visual feedback methods. Specifically, in this paper we investigate the use of two types of visual feedback, i.e. an augmented transcript and a dynamic concept map (map of concept's flow), to improve video comprehension in the first-watch learning context. Our preliminary findings suggest that both the methods help the learner to focus on the relevant concepts and their related contents. The augmented transcript has an higher impact on immediate comprehension compared to the map of concepts' flow, even though the latter is expected to be more powerful to support other tasks such as exploration and in-depth analysis of the concepts in the video.

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Section: Related Workmentioning

confidence: 99%

Video augmentation to support video-based learning

Torre

Galluccio

Coccoli

2022

Proceedings of the 2022 International Conference on Advanced Visual Interfaces

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“…Reconstructing a reading's knowledge structure in a concept map format is difficult since it requires a higher level of thinking to discover key ideas of a learning material (Cañas et al 2017;Carr-Lopez et al 2014). However, it is possible to discover facts, relationships, and assertions in textual data with help from text mining and NLP (Hayama and Sato 2020;Hearst 1999) to support concept mapping composition activities within a short time. NLP can analyze the information of a human language and help the computer understand or communicate with humans (Collobert et al 2011;Manning and Schutze 1999).…”

Section: Semi-automatic Concept Map Generation With Concept Map Miningmentioning

confidence: 99%

“…In addition to providing keywords as suggestions to concepts, the authoring tool being developed in this study also provided assistance at proposition level. The tool suggested subject-relation-object triples to the author as the candidates of concept map propositions that were not explicitly provided in prior studies (Hayama and Sato 2020;Presch 2020). This study targeted English teachers as its users who use Kit-Build in teaching EFL reading comprehension and the experiment was also more robust due to the use of multiple texts and uses.…”

Section: Semi-automatic Concept Map Generation With Concept Map Miningmentioning

confidence: 99%

Design and development of semi-automatic concept map authoring support tool

Pinandito

Prasetya

Hayashi

et al. 2021

RPTEL

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This research, to design and develop a concept map authoring support tool, adopts a semi-automatic concept mapping approach to help teachers create concept maps from English readings. A concept map is widely regarded as a useful teaching and learning tool. It offers many potential advantages apart from representing the students’ knowledge and understanding during learning. Students’ engagement in using and creating concept maps with a computer-enabled concept mapping tool raises concept maps’ potential benefits. It contributes to the learning process and improves the students’ meaningful learning. The Kit-Build concept map framework, which incorporates a technology-enabled concept mapping tool, uses concept map recomposition as its essential learning activity. In learning with Kit-Build, teachers compose concept maps that they want the students to achieve. The teachers’ maps are then decomposed into components from which the students recompose and reflect deeply on their understanding. The difference between teacher’s and students’ concept maps depicts the gap between teachers’ expected understanding and students’ actual understanding. Hence, the teachers’ concept map becomes an essential part of learning with Kit-Build. For some teachers, creating a good concept map for learning is difficult and time-consuming. Hence, support to improve teachers’ productivity in creating concept maps is essential. The findings suggest that the support tool yields better concept mapping efficiency while maintaining concept maps of similar quality. Teachers also found that the support tool was useful. Therefore, semi-automatic concept mapping with the supported Kit-Build concept map authoring tool has been shown to be a better approach.

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“…However, as discussed in detail in Sect. 2, it is typically difficult for a certain number of learners to create concept maps from scratch, and it is almost impossible for them to create an appropriate concept map while watching a lecture video [11]. Thus, we employed a fill-in-the-blank questiontype concept map in which some labels that are important for understanding learning contents are punched out from a completed concept map, encouraging learners to think about them while watching the video.…”

Section: Introductionmentioning

confidence: 99%

Practical Application of an e-Learning Support System Incorporating a Fill-in-the-Blank Question-Type Concept Map

HASEGAWA,

HAYAMA

2024

IEICE Trans. Inf. & Syst.

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E-learning, which can be used anywhere and at any time, is very convenient and has been introduced to improve learning efficiency. However, securing a completion rate has been a major challenge. Recently, the learning forms of e-learning require learners to be introspective, deliberate, and logical and have proven to be incompatible with many learners with low completion rates. Thus, we developed an e-learning system that incorporates a fill-in-the-blank question-type concept map to deepen learners' understanding of learning contents while watching learning videos. The developed system promotes active learning reflectively and logically by allowing learners to answer blank question labels on concept maps from video content and labels associated with the blank question labels. We confirmed in the laboratory experiment by comparing with a conventional video-based learning system that the developed system encouraged a learner to do more system operations for rechecking the learning content and to better understand the learning contents while watching the learning video. As the next step, a field experiment is needed to investigate the usefulness and effectiveness of the developed system in actual environments in order to boost the practicality of the developed system. In this study, we introduced the developed system into the two class of the uviversity course and investigated the level of understanding to the learning contents, the system operations, and the usefulness of the developed system by comparing with those in the laboratory experiment. The results showed that the developed system provided to support the understanding to learning content and the usefulness of each function in the field experiment, as in the laboratory experiment. On the other hand, the students in the field experiment gave lower usefulness of the developed system than those in the lab experiment, suggesting that the students who attempted to thoroughly understand the learning contents in the field experiment were fewer than those in the lab experiment from their system operations during the learning.

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Supporting Online Video e-Learning with Semi-automatic Concept-Map Generation

Cited by 6 publications

References 13 publications

Video augmentation to support video-based learning

Video augmentation to support video-based learning

Design and development of semi-automatic concept map authoring support tool

Practical Application of an e-Learning Support System Incorporating a Fill-in-the-Blank Question-Type Concept Map

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