A Tool for Assessing Student Learning in Computing Sciences Distance Education Classes

Brook Wu, Xin Chen


To promote STEM higher education, avenues such as distance education must be visited. Students in most of the distancelearning classes generate great amounts of textual messages for class interaction, discussion and assignments which take up most of instructors time to respond and grade. Researches in distance learning and computer-aided grading have been well developed, but little work has been done to apply automated text process techniques to solve the problem of evaluating students performance in virtual classrooms. This paper introduces a software application that features the assessment of student learning in distance education classes by analyzing online class messages. The assessment model is described and its implementation is discussed. Functionalities of the software for learning assessment are illustrated with examples. The result shows that the software application is a useful supplementary teaching tool.


Distance Learning, Learning Assessment, Text Processing, Keyword Density

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JSTEM. ISSN: 1557-5284