Mobile Social Network Site (MSNS) is introduced into teaching and learning as a kind of innovative pedagogical tool, called MSNS-based ubiquitous learning, which allows students to learn at anytime and anywhere. Continuous use is the success of an innovative tool. Nevertheless, several previous studies have indicated factors and mechanism affecting students' continuance intention in the context of MSNS-based ubiquitous learning. In this study, a behavioral model based on "cognitionaffect-conation" framework is proposed to interpret factors' impacts on students' continuance intention, along with the clarification of the mechanism. Both qualitative (focus group interview) and quantitative (survey) methods are employed in this study. Confirmatory factor analysis, hierarchical confirmatory factor analysis, and full model of structural equation modeling are applied to validate the research model and hypotheses. Results reveal that perceived convenient function, teachers' participation, interaction expansion, course content fit, and information richness are reflective constructs to the perceived quality of a MSNS-based pedagogy, which put impacts on students' continuance intention through perceived value and users' satisfaction, perceived value mediates the impact of perceived quality of an MSNS on satisfaction, and satisfaction also mediates the impact of perceived value on continuance intention.
Instructional technology can make teachers do their jobs easier, better, faster and more effectively. Students can also benefit from its application. However, some college teachers do not adopt instructional technologies in their teaching as we expected. They like to teach the way they were taught as students before. Why and what factors really influence their adoption of instructional technology? This study offered a model suggestiong instructional technology adoption by college teachers depends on: the student, the teacher, the technology and the surroundings. An experiment was designed to verify the model. Samples were selected from teachers at a mid-sized university. Experimental data was collected by interviewing fifteen teachers (samples). Those interviewed represented five high-level users, five medium-level users, and five lowlevel users of instructional technology. Quantitative methods such as frequency counting were used to analyze and sort the data. Finally, conclusions can be drawn that different components in the model had different influential degree to the different levels of users of instructional technology.
Abstract:Cache is an important component in computer architecture. It has great effects on the performance of systems.Nowadays, Least Recently Used (LRU) Algorithm is one of the most commonly used one because it is easy to implement and with a relatively good performance. However, in some particular cases, LRU is not a good choice. To provide references for the computer architecture designer, the study proposed a new algorithm named Fully Replacement Policy (FRP) and then analyzed various factors of effects on cache performance, carried out the simulation experiment of cache performance based on SimpleScalar toolset and SPEC2000 benchmark suite. The study compared the effects of Fully Replacement Policy with Least Recently Used (LRU) Algorithm when set size, block size, associativity and replacement methods are changed separately., By experimentally analyzing the results, it was found that FRP outperforms LRU in some particular situations.
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