Analyzing concept complexity, knowledge ageing and diffusion pattern of Mooc

Guo, Shuying; Zhang, Ganzhou

doi:10.1007/s11192-017-2385-z

Cited by 12 publications

(12 citation statements)

References 42 publications

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“…Secondly, TF can also emphasize technology to analyze the causes and influences of technology’s invention, innovation, and evolution in the whole system [ 35 , 36 ], and to evaluate the maturity or life cycle of technology [ 37 , 38 ]. Thirdly, TF can track the evolution of technology in a certain period [ 39 , 40 ]; show the internal relationship among the market, product, and technology in the form of the technology roadmap [ 41 , 42 ]; and study the diffusion mechanisms of technology [ 43 , 44 ]. Finally, the use of TF in technical cooperation and competition [ 45 ], knowledge management [ 34 ], and decision support is gradually increasing [ 46 ].…”

Section: Resultsmentioning

confidence: 99%

A Review of Technological Forecasting from the Perspective of Complex Systems

Feng

Wang

et al. 2022

Entropy

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Technology forecasting (TF) is an important way to address technological innovation in fast-changing market environments and enhance the competitiveness of organizations in dynamic and complex environments. However, few studies have investigated the complex process problem of how to select the most appropriate forecasts for organizational characteristics. This paper attempts to fill this research gap by reviewing the TF literature based on a complex systems perspective. We first identify four contexts (technology opportunity identification, technology assessment, technology trend and evolutionary analysis, and others) involved in the systems of TF to indicate the research boundary of the system. Secondly, the four types of agents (field of analysis, object of analysis, data source, and approach) are explored to reveal the basic elements of the systems. Finally, the visualization of the interaction between multiple agents in full context and specific contexts is realized in the form of a network. The interaction relationship network illustrates how the subjects coordinate and cooperate to realize the TF context. Accordingly, we illustrate suggest five trends for future research: (1) refinement of the context; (2) optimization and expansion of the analysis field; (3) extension of the analysis object; (4) convergence and diversification of the data source; and (5) combination and optimization of the approach.

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Section: Resultsmentioning

confidence: 99%

A Review of Technological Forecasting from the Perspective of Complex Systems

Feng

Wang

et al. 2022

Entropy

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“…Various authors (e.g., De-Castaneda et al, 2015;Guo & Zhang, 2017;Moore & Wang, 2021) mention that MOOCs facilitate the assimilation of knowledge and development of skills under the distance modality. In particular, 44.44% of the teachers (n = 24) think that MOOCs facilitate very much the creation of new school activities.…”

Section: Moocsmentioning

confidence: 99%

“…Today, the planning, organization and updating of the courses with the support of technology have great relevance due to the emergence of the COVID-19 pandemic (Beneria et al, 2020;Bergsman & Chudler, 2021;Chandrasinghe et al, 2020;Colomo-Magaña et al, 2021). In particular, teachers design new school activities under the distance modality in order to facilitate the learning process (Daniel, 2020;Guo & Zhang, 2017;Zuo et al, 2021). Likewise, universities use CVWs and MOOCs to carry out creative school activities from anywhere (De-Witt & Koh, 2020;Pottier et al, 2020;Zhu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Teachers’ Opinion About Collaborative Virtual Walls and Massive Open Online Course During the COVID-19 Pandemic

Salas-Rueda

De-La-Cruz-Martínez

Eslava-Cervantes

et al. 2021

ONLINE J. COMMUN. MEDIA TECHNOL

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“…The latest approach proposed examining the degree of complexity of MOOC in terms related to education and IT, and determining Mooc diffusion pattern at international and country-specific levels. The research used social network analysis, bibliometrics, text mining and idea of epidemic model (Guo & Zhang, 2017).…”

Section: Development Of Learning Content and The Task For Moocsmentioning

confidence: 99%

Distance Learning – the Current Status and Directions for Further Research

Szulc

2020

IJREL

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The article aims to discuss current research trends in the field of Distance Learning (DL). It consists of the following parts: (1) the definitions and characteristics of DL; (2) current directions of research in the field of DL, among others: measuring transactional distance in Web-Based Learning Environments, Problem-Based Learning (PBL) in DL, development of learning content and the task for MOOCs, effects of online course efficiency perceptions on Student Evaluation of Teaching (SET) measures, new technologies for the DL, the use of metacognitive and affective model Self-Regulated Learning (MASRL), questionnaire (Constructivist Learning on a Scale Higher Settings of Education [CLHES]) as a method of research of constructivist learning environment in higher education, Transactional Distance (TD) theory in DL and online community culture; (3) summary and conclusions with a particular focus on the use of DL methods in higher education. The article is based on the study of literature registered in the databases ERIC, LISA, and LISTA.

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Analyzing concept complexity, knowledge ageing and diffusion pattern of Mooc

Cited by 12 publications

References 42 publications

A Review of Technological Forecasting from the Perspective of Complex Systems

A Review of Technological Forecasting from the Perspective of Complex Systems

Teachers’ Opinion About Collaborative Virtual Walls and Massive Open Online Course During the COVID-19 Pandemic

Distance Learning – the Current Status and Directions for Further Research

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