The use of digital technology such as augmented reality AR technology has been an important topic of research in several fields, uncovering diverse benefits regarding its impacts. Although there have been numerous empirical studies on the design and evaluation techniques of the AR approach to enhance physical, cognitive, personal, social abilities in science education, their outcomes varied in different science disciplines, and there is a lack of reviews on how the AR has been applied in the field of science education. The aim of this study is to conduct a scoping review on the positivity of AR applications in science education. This study presents a scoping literature review of 26 studies published between 2015-2020 on AR in science education. The results indicated an overall positive impact of AR in science education. The results from this systematic review are expected to provide valuable information regarding the AR usage in science fields.
Over the past decades, social media attracted individuals to express their feelings on any topic or item, resulting in an incremental growth in the size of created data. These feelings and unstructured data paved the path for business organizations to gather information and build statistical analysis. Various machine learning and natural language processing-based approaches are used for sentiment and emotion analysis. Moreover, deep learning-based approaches recently gained popularity due to their remarkable performance in text analysis. This paper provides a comprehensive overview of the prominent machine learning models applied in emotion analysis. It explores various emotion analysis taxonomies, in addition to the constraints of prevalent deep learning architectures. The paper also reviews some of the previously presented contributions in emotion analysis with a focus on deep learning methodologies as well as the most common datasets. It presents a comprehensive comparison between several emotion analysis models. This paper demonstrates the effectiveness of learning-based techniques in tackling emotion analysis challenges.
MRTRICKSangiography is a very reliable tool to identify patients with severeTR by the imaging of retrograde appearance of contrast agent in the hepatic veins. Sensitivity and specificity of this approach is very high with no intra- and interobserver variability.
Special education settings have experienced technological innovation that have advanced the development of various skills. Gamification is increasingly used to enhance the skills of individuals with special needs. There have been some studies and limited systematic reviews of gamification in general and special needs settings in particular, however, gamification design applied to special needs lacks a comprehensive systematic review. This article conducts a Literature review of gamification in special needs settings to investigate the effect of gamification in special needs as well as to identify gamification domains, groups and trends for individuals with special needs. Valuable data has been highlighted concerning the technology techniques used in enhancing the skills of individuals with a disability. However, further studies are still needed to examine areas, where research is lacking in the gamification field. The preferred reporting items for literature reviews and meta-analysis PRISMA standard was adopted for inclusion and exclusion criteria’ in this study such as including, eligibility, screening, dentification, and inclusion and exclusion steps. The results revealed that gamification design facilitates the development of various skills among individuals with special needs. Additionally, gamification design was mostly used to enhance the learning skills of individuals with a disability.
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