Semantically enriched Massive Open Online Courses (MOOCs) platform

Zhuhadar, Leyla; Kruk, Sebastian Ryszard; Daday, Jerry

doi:10.1016/j.chb.2015.02.067

Cited by 25 publications

(17 citation statements)

References 13 publications

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“…One specific, challenging research topic in this line is concerned with learning structured knowledge by exploring and exploiting social tagging data or folksonomies. There have been numerous methods and techniques to induce semantics from the noisy and unstructured folksonomies, and to construct structured knowledge with rich semantics, which have been shown useful for many application areas, such as domain ontology enrichment [1], information retrieval and navigation [2][3][4], recommender systems [5][6], academic communication [7], e-learning [8], mood mining [9], geotagging [10], etc.…”

Section: Introductionmentioning

confidence: 99%

Learning Structured Knowledge from Social Tagging Data: A Critical Review of Methods and Techniques

Dong

Wang

Liang

2015

2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

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For more than a decade, researchers have been proposing various methods and techniques to mine social tagging data and to learn structured knowledge. It is essential to conduct a comprehensive survey on the related work, which would benefit the research community by providing better understanding of the state-of-the-art and insights into the future research directions. The paper first defines the spectrum of Knowledge Organization Systems, from unstructured with less semantics to highly structured with richer semantics. It then reviews the related work by classifying the methods and techniques into two main categories, namely, learning term lists and learning relations. The method and techniques originated from natural language processing, data mining, machine learning, social network analysis, and the Semantic Web are discussed in detail under the two categories. We summarize the prominent issues with the current research and highlight future directions on learning constantly evolving knowledge from social media data.

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Section: Introductionmentioning

confidence: 99%

Learning Structured Knowledge from Social Tagging Data: A Critical Review of Methods and Techniques

Dong

Wang

Liang

2015

2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

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“…Other researchers are using semantic filtering technologies for building MOOCs' management systems (Zhuhadar, Kruk, & Daday, 2015). Semantic technologies support more flexible information management than that offered by the current MOOCs' platforms and this is crucial for the success of any forum management.…”

Section: Related Work About Moocs and Odl Managementmentioning

confidence: 99%

A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities

Mora

Ferrández

Gil

et al. 2017

IRRODL

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Massive Open Online Courses and e-learning represent the future of the teaching-learning processes through the development of Information and Communication Technologies. They are the response to the new education needs of society. However, this future also presents many challenges such as the processing of online forums when a huge number of messages are generated. These forums provide an excellent platform for learning and connecting students of the subject, but the difficulties in following and searching the vast volume of information that they generate may produce the opposite effect. In this paper, we propose a computational method for enabling the educational process in huge online learning communities. This method analyses the forum information through Natural Language Processing techniques and extract the main topics discussed. The results generated improves the management of the forums, increases the effectiveness of the teachers' explanations and reduces the time spent by students to follow the course. The proposal has been complemented with a real case study that shows promising results.Keywords: natural language processing, topic detection, distance learning, online forum, mooc managing, However, there are still challenges that should be specifically addressed in order to achieve the effective ODL provision and to maintain excellent educational standards. One of the most powerful and popular tools are online forums (Mora, Signes Pont, DeMiguel Casado, & Gilart Iglesias, 2015). Online forums are a communication technology tool in education and provide an excellent platform for learning and connecting students to the subject. The expected roles of the forums are to increase engagement of students in the subject, promote deep learning, and maintain motivation (Onah et al., 2014).Technological advances and computing methods may provide tools for enhancing these roles and facilitating the educational process. In this way, artificial intelligence approaches based on NaturalLanguage Processing (NLP) should deliver tools specifically aimed at students and teachers to make the assimilation of content and course tracking easier for students, and to provide mechanisms to manage the learning platforms by teachers. The working hypothesis of our research is that this kind of solution can be used to better engage the students and teachers in online platforms with huge forums by enabling the knowledge management and learning-teaching processes. Under our approach, the main objective of our work is to provide automatic tools and applications to facilitate tracking and monitoring online learning communities through the automatic processing of forums of lexical, syntactic, and semantic analysis; clustering; and information retrieval techniques. A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities Mora, Ferrández, Gil, and Peral 227The remainder of the paper is structured as follows: Section 2 describes the problem of management and monitoring forums in huge online ...

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“…Barak [5] applied MOOC teaching to English and Arabic language courses, concluding that both the intrinsic motivation and learning autonomy of MOOC participants are improved. Zhuhadar et al [6] envisioned a new generation of MOOCs which support formal semantics interpretability through online social networks and SemanticWeb. Compared with the existing platforms of MOOCs, semantic technology supports more flexible management of information.…”

Section: State Of the Artmentioning

confidence: 99%

MOOC Teaching Mode of News Transmission Based on Network Audio Data Decoding Technology

Shen

2018

Int. J. Emerg. Technol. Learn.

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Abstract-MOOC, an online classroom development mode, has gradually developed due to its unique advantages under the background of big data. However, most online audio data of MOOC are acquired through the application software on PCs, which has limitations in the support of audio format. In the meanwhile, there are still some shortcomings in the existing research on the application and integration of the core technology of MOOC. Therefore, this study constructs the News Transmission MOOC course based on the network audio data decoding technology. Moreover, the course is applied to the actual teaching process to test the teaching effect and realize the organic integration of the core technology of computer and the teaching idea of MOOC. The practical teaching results show that the MOOC course not only improves the teaching effect, but also has significance and value for improving students' ability and learning interest.

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Semantically enriched Massive Open Online Courses (MOOCs) platform

Cited by 25 publications

References 13 publications

Learning Structured Knowledge from Social Tagging Data: A Critical Review of Methods and Techniques

Learning Structured Knowledge from Social Tagging Data: A Critical Review of Methods and Techniques

A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities

MOOC Teaching Mode of News Transmission Based on Network Audio Data Decoding Technology

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