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This study examined teachers’ epistemic understanding of scientific arguments. Twenty-seven middle and high school science teachers evaluated student-generated scientific arguments. Through a survey and an interview, the teachers discussed what epistemic criteria they used to evaluate arguments and why the arguments were good or bad. Although the teachers listed several basic conditions of scientific arguments such as the need for a claim and evidence, they showed less understanding of the epistemic criteria required to make a good scientific argument. For example, few teachers mentioned the possibility of interpreting the same data in multiple ways. Consequently, few teachers understood the possibility of multiple justifications linking data and claims. The study examined why teachers have difficulty guiding students in understanding argumentation as a means of enhancing epistemic understanding in terms of the teachers’ own decreased understanding. Finally, the need for a teacher education or professional development program that emphasizes epistemic features of scientific arguments, while dealing with the structural and dialogical dimensions of scientific arguments, is proposed.

The SE and NLP are newer research areas in computer science and engineering. This paper tries to raise and answer the interrelation between Software Engineering and Natural Language Processing. The stakeholders of both the research areas which will be affected are provided. An attempt is made to highlight the possibility of joint research in both the areas.

This study is designed to suggest how to organize and manage the coursework of ‘Lifelong Education Program Development’. For this purpose, we examined the effects of developing and applying its course contents based on the theory of systems program development.

Kinect v2 sensor does not provide depth information and skeletal traction function in near distance from the sensor. That is why many researches, to recognize hand gestures, are focused on the skeletal tracking only inside the range of detection. This paper proposes a method which can recognize hand gestures in the distance less than 0.5 meter without conventional skeletal tracking when Kinect v2 sensor is used. The proposed method does not use the information of depth sensor and infrared sensor, but detect hand area and count the number of isolated areas which are generated by drawing a circle in the center of the hand area. This method introduces new detectable gestures without high cost, so that it can be a substitute for the existing mouse-movement controlling and dynamic gesture recognition method such as clicking a mouse, clicking and dragging, rotating an image with two hands, and scaling an image with two hands in near distance. The gestures are appropriate for the user interface of smart devices which employ the interactions based on hand gestures in near distance.

How does one start a new business online without thinking about its profit? Numbers of retailers with limited research, or asking enough details and questions, to make sure their product is something that is more likely to be sold and if does one considers enough storage to cater each customer needs. Why do facebook and amazon require Big Data in their business online? Right now, aspiring entrepreneurs are planning their paths to a more productive business using social commerce and taking it to the next level. It's a journey that requires a lot of hard work, and many people end up failing, but the business that is taking risks will end up reaping the cream of their crops. In this paper, we discuss the process of improving the production of an online business using big data in social media to increase sales and operating margin. That retailer, using Big Data to its current potential could gain a competitive edge to possibly gain opportunities for business and customers. Thus, we identify the advantages of using big data in social commerce.We also include the Java-based programming framework (Hadoop) that supports the processing and storage of a larger data set in a distributed computing environment. Naming it as next-generation enterprise data architecture that links the systems business transactions and business intelligence.

Technology analysis is to understand target technology by analyzing diverse information of developed technologies. Using the results of technology analysis, we can perform the technology management such as technology forecasting, technological innovation, and technology valuation for research and development (R&D) planning. In addition, the R&D planning is built uponin order to improve technological competitiveness of a company. Patent analysis is a popular approach to technology analysis. Many researches on patent analysis have been done because patent documents contain diverse and complete information on developed technology. However, the documents are not suitable for patent analysis based on statistics. So, in much of the work on patent data analysis, the researchers transformed the patent documents into structured data using text mining techniques. Generally, thestructured data set has a sparsity problem, that is, most elements of the data are zero valued. The existing researches in patent analysis have not considered this zero-inflated problem, but it places serious limits on performance when we analyze the patent data. In this paper, to overcome this problem, we propose a methodology for patent analysis using zero-inflated Poisson and negative binomial regressions. We apply the proposed methodology based on zero-inflated Poisson and negative binomial regression models to Apple’s technology analysis.

Cloud Computing has an expanding future in both business and Information Technology. With the expanding hybrid cloud model offering better services and convenience there are also a number of security problems associated with cloud standardization, multi-tenancy third party privity/sub-contracting, data-controller, outages, availability, monitoring and the service level agreements. This paper focuses on Hybrid Cloud Computing security in the context of a Tenant-Vendor-Third-Party environment and service level agreements. Limitations, opportunities and suggestions to mitigate the security risks are discussed and summarized.

Reputation computation model facilitates vehicles to broadcast traffic information in a vehicular ad hoc network (VANET) in order to improve road safety and efficiency. In this paper, a probabilistic-based reputation computation model for VANETs has been evaluated. The uncertainty of reputation is transformed into a probability distribution over possible reputed states that are hidden from observation but determined by a vehicle’s expected experience in VANET are addressed in this work. HMM is utilized to evaluate the level of reputation in VANET exhibiting dynamic behaviour. The proposed mechanism is probability distribution centric, though the later mechanism is docile to predict accurate trust value of messages. The time taken by the proposed scheme is significantly less and transmission over the shared wireless channel is in the order of milliseconds. Extensive results and simulation show that efficacy of the proposed model.

Flipped learning is a type of blended learning that has recently emerged as an innovative teaching and learning method. In this study, a mobile-based learning management system (LMS) is developed in order to support flipped learning for mobile-friendly learners. The purpose of the study is to investigate the effects of flipped learning focused on a problem-solving approach on the affective pathway. In addition, the study examines the ways in which mobile-based LMS facilitates flipped learning compared to the PC-based Web environment. A series of instructional design of flipped learning for a math class was developed and implemented for undergraduate students at C University in South Korea. The participating students were asked to write self-reflection journals for 6 weeks (12 periods). In-depth interviews were conducted with the students and the contents of the discussion board in the mobile-based LMS were analyzed using Nvivo, in order to track a series of changes of the affective pathway. The results obtained from the qualitative data revealed that students gained high self-esteem, motivation, and interest regarding academic activities, which eventually cultivated a positive local affect. Furthermore, there was convincing evidence of changes from the “flipped classroom” to “flipped learning”, where students were able to take advantage of the mobile-based LMS. Compared to the PC-based Web environment, students were able to overcome the limitation of time and space, using the new environment proactively and creatively.