Abstract Computer-based training (CBT) has become a common form of instructional delivery in business and educational environments. A standard practice during the design and development of CBT, is to incorporate the multimedia principle to aid learning. However, a recent meta-analysis by Pastore, Briskin, and Asino (2016) revealed that very little research has actually examined the multimedia principle (single vs. multiple representations) on adult learners... Computer-based training (CBT) has become a common form of instructional delivery in business and educational environments. A standard practice during the design and development of CBT, is to incorporate the multimedia principle to aid learning. However, a recent meta-analysis by Pastore, Briskin, and Asino (2016) revealed that very little research has actually examined the multimedia principle (single vs. multiple representations) on adult learners in a computer-based environment. Instead, much of the research has focused on K-12, used paper and pencil rather than a computer, did not compare single vs multiple representations, or had methodological issues (i.e. did not report the type of knowledge assessed). As a result, the current study examines the multimedia, modality, and redundancy principles in a computer-based environment with adult learners on learning (high- and low- level knowledge) and cognitive load measures. The results of the low (recall) and high (transfer) level learning tasks in this study supported the multimedia principle. Multiple representations were found to better support learning than just one. However, this was not the case for modality or redundancy principles. Learners presented duplicate text and narration or text with optional narration performed just as well as those with no duplication, indicating reverse redundancy. Additionally, the narration and images groups did not outperform text and image groups. Read More Read Less

Abstract eCourse’s designers are facing great challenges related to readability and acceptable design. They need to account for graphic elements like colors, contents and screen backgrounds, contrasts, typography, number of rows and columns and also for type and place for every single element within the web page. This work discusses also elements of the web pages that would enhance readability for users that suffer... eCourse’s designers are facing great challenges related to readability and acceptable design. They need to account for graphic elements like colors, contents and screen backgrounds, contrasts, typography, number of rows and columns and also for type and place for every single element within the web page. This work discusses also elements of the web pages that would enhance readability for users that suffer from certain visual disorders like dichromacy, i.e. its types like deuteranopia (daltonism), protanopia and tritanopia. Read More Read Less

Abstract This paper focuses on a Natural Language Processing (NLP) system and Image Recognition using python and Raspberry Pi. NLP Engines are widely used in various tech domains such as surveillance, defense, advanced medical diagnosis, virtual assistant and machine learning. Open CV based image processing algorithm is applied for image recognition, facial comparison, pattern recognition, security system, object detection and deep... This paper focuses on a Natural Language Processing (NLP) system and Image Recognition using python and Raspberry Pi. NLP Engines are widely used in various tech domains such as surveillance, defense, advanced medical diagnosis, virtual assistant and machine learning. Open CV based image processing algorithm is applied for image recognition, facial comparison, pattern recognition, security system, object detection and deep learning. In this proposed system to implement intelligent QAS system, NLP and Image processing are integrated. Read More Read Less

Abstract This paper focuses on a Natural Language Processing (NLP) system and Image Recognition using python and Raspberry Pi. NLP Engines are widely used in various tech domains such as surveillance, defense, advanced medical diagnosis, virtual assistant and machine learning. Open CV based image processing algorithm is applied for image recognition, facial comparison, pattern recognition, security system, object detection and deep... This paper focuses on a Natural Language Processing (NLP) system and Image Recognition using python and Raspberry Pi. NLP Engines are widely used in various tech domains such as surveillance, defense, advanced medical diagnosis, virtual assistant and machine learning. Open CV based image processing algorithm is applied for image recognition, facial comparison, pattern recognition, security system, object detection and deep learning. In this proposed system to implement intelligent QAS system, NLP and Image processing are integrated. Read More Read Less