درخت حوزه‌های تخصصی

Regarding to design an applicable electronic book reading system for children and adolescent, this study’s struggle is to prepare a conceptual model. We used quantitative approach and Delphi method in order to analyze data. In this regard, criterion based sampling is used to identify the research population. 15 experts were identified which had criteria such as having subjective publications, teaching experience, and so on. We supposed that these experts could present more information that we expected to collect. Moreover, 8 electronic book systems were selected to be reviewed, because of their plenty of active audiences, and their international and also standard presence. Firstly identified practical criteria in designing electronic books by extracting them from related resources and checking active systems. These data helped us to prepare primitive version of the checklist and it completed after passing validity control step with participation of three experts. Then the checklist presented to experts in Delphi panel. Finally, consensus on the components was reached after three rounds of Delphi panel. The results showed that in designing electronic books for children, there are five original components. The components are display screen features with 12 criteria, screen organization with 13 criteria, interaction and feedback with 8 criteria, search and retrieval features with 10 criteria, and help and guidance features with 10 criteria. Consequently, display screen features with score of 3,706 and interaction and feedback with score of 3,700 were selected as the most important components in designing electronic book systems by the viewpoints of Delphi experts.

Purpose: The research aims to visualize and analyze co-word network, and thematic clusters of the intellectual structure in the field of digital content management during 2010-2020. Method: The study is applied research with a descriptive approach which is conducted by techniques of co-word, and social network analysis. Data analysis and visualization of the co-word network were represented by SPSS, UCINet, and Python programming language. Findings: 8 main clusters are identified. The cluster multimedia content management & retrieval is the most mature and central thematic cluster. The USA and various sub-categories of Computer Science are located in the top ranks of WOS in the field. Most productions were published in 2020. Generally, the Clusters were labeled in two contexts of health and LAM (Libraries, Archives, Museums, and cultural heritage). Conclusion: Content-based management and retrieval are focused on artificial intelligence, decision-supported, knowledge-based and ontological techniques which are conducted as novel approaches and underlying trends in the field.