377 research outputs found
COMPUTER - INFORMATICS LITERACY AND POSSIBILITIES OF COMPUTING EXTRA-CURRICULAR ACTIVITIES
The following article analyzes some of the results of investigation “Present State and Trends of Using Computers in Slovenia Primary and Secondary Schools”. This work is elaborated by the author every two years for Ministry of education and sport and national project “Informatization of Slovenian Educational System”. Article analyzes some didactic criteria of teaching computer science and first of all performing computing extra-curricular activities at primary, secondary and boarding schools in sense of improvement on computer – informatics literacy
The importance of interdisciplinary frameworks in social media mining: An exploratory approach between Computational Informatics and Social Network Analysis (SNA)
Social media content is one of the most visible sources of big data and is often used in health studies to draw inferences about various behaviors. Though much can be gleaned from social media data and mining, the approaches used to collect and analyze data are generally strengthened when examined through established theoretical frameworks. Health behavior, a theory driven field, encourages interdisciplinary collaboration across fields and theories to help us draw robust conclusions about phenomena. This pilot study uses a combined computer informatics and SNA approach to analyze information spread about mask-wearing as a personal mitigation effort during the COVID-19 pandemic. We analyzed one week’s worth of Twitter data (n = 10,107 tweets across 4,289 users) by using at least one of four popular mask-support hashtags (e.g., #maskup). We calculated network-measures to assess structures and patterns present within the Twitter network, and used exponential random graph modeling (ERGM) to test factors related to the presence of retweets between users. The pro-mask Twitter network was largely fragmented, with a select few nodes occupying the most influential positions in the network. Verified accounts, accounts with more followers, and those who generated more tweets were more likely to be retweeted. Contrarily, verified accounts and those with more followers were less likely to retweet others. SNA revealed patterns and structures theoretically important to how information spreads across Twitter. We demonstrated the utility of an interdisciplinary collaboration between computer informatics and SNA to draw conclusions from social media data
Pioneer of Scientific Module of Islamic Religious Education Based on Computer Informatics Technology (ICT)
This study aims to explore the pioneering scientific module of Islamic Religious Education based on Informatics Technology Computer (ICT) at MI Al Ahmad Krian Sidoarjo. Module-like teaching can be seen as feedback for classical teaching with classes that are too large, such as at MI Al-Ahmad, where each class contains an average of 25-29an students. So that teachers cannot provide individual assistance and often do not even know their students, especially Islamic Religious Education teachers. This research uses a quantitative descriptive approach. This study discusses (1) what is the process of developing ICT-based Scientific Islamic Religious Education modules for sixth-grade students at MI Al-Ahmad Krian Sidoarjo?, (2) how effective is the application of ICT-based Scientific Islamic Religious Education modules to sixth-grade students. The results of this study indicate that the development of the Islamic Religious Education Scientific module refers to the 4-D model developed by Thiagarajan and Sammel with four stages namely; definition, design, development, and deployment. But the development in this study stopped at the third stage until the development had not yet spread. The Islamic Religious Education Scientific Module developed in this study is effective. This is shown by the teacher's activity fulfilling the effectiveness criteria with an average value of 3.80. Student activities in learning modules have met the criteria of effectiveness with a percentage of 85.9%.
 
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