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Given the popularity of PHP frameworks used in developing webbased applications, a comparative study is conducted to determine which framework is best suited for incorporation into the curriculum of an undergraduate software engineering course that uses project-based learning. The top six PHP frameworks (Zend, Yii, CakePHP, CodeIgniter, PRADO, and Symphony) were initially considered and then narrowed down to two (CakePHP and CodeIgniter) based on their alignment with common functionality in previous class projects, framework complexity for those new to frameworks (learning curve), and developer friendliness (availability of documentation and online resources). An in-depth comparative study is conducted by developing a functionally-equivalent web application using each of the two frameworks as well as plain PHP (no framework). This work was motivated by the difficulties that were encountered in an evolving, content-rich software engineering course and discusses the educational changes that were made to align student learning with sound software engineering principles and current software development practices used in the computing industry. Copyright © 2013 ACM.
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In this paper, we examined why information searchers perceive search tasks as difficult, and what factors/reasons make them perceive tasks as difficult. We also examined if task difficulty reasons vary across different tasks (task types). Data was collected through a controlled laboratory experiment in which tasks were designed following a classification scheme. A total of 32 undergraduate students participated, each was given 4 search tasks, and they were asked in questionnaires both before and after the tasks for task difficulty ratings and why they gave those ratings. We developed a coding scheme based on the difficulty reasons users gave, which covered various aspects of task, user, and user-task interaction. Difficulty reasons were categorized following this scheme. Results showed that searchers had some common reasons for task difficulty in different tasks, but most of the difficulty reasons varied across tasks. For each task, there were also common reasons for task difficulty, although there was some variation here as well. Task difficulty was also found to be negatively correlated with users topic knowledge, previous experience, and topic interest. Our findings help understand search task difficulty, as well as the relationships between task difficulty and task type, knowledge background, etc. These can also be helpful with experiment task design. © 2013 ACM.
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This paper reports on an examination of why information searchers find search tasks difficult and the specific reasons they feel difficult. Data was collected through a controlled laboratory experiment with 32 participants, each working with 4 search tasks. They were asked in questionnaires, both before and after the tasks, for task difficulty ratings and their reasoning for giving those ratings. We developed a coding scheme based on the difficulty reasons users gave, which covered various aspects of task, user, and user-task interaction. This helps us understand search task difficulty, as well as provides a scheme for task difficulty control in experiment task design.
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Research and training in atmospheric lidar remote sensing requires highly versatile software environments for both experimentation and analysis. Experimentation and analysis may be conducted either directly on site at the location of the lidar equipment and/or institutional computer center or remotely from a distant location. The requirements for lidar software environments depend not only on type of user access (remote or onsite) but also on the nature of the teaching or research missions they support and the characteristics of the lidar systems for which they are used. The software environments discussed in this paper have been used to support lidar aerosol studies in settings ranging from urban locations to a remote atmospheric baseline station. Experiments and data analysis studies have been conducted for two different ground-based lidar systems, a monostatic Micro Pulse Lidar system and a bistatic imaging lidar system. © 2013 IEEE.
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