Assessment of Open-Ended Questions using a Multidimensional Approach for the Interaction and Collaboration of Learners in E-Learning Environments
Currently, the assessment of learners in conventional e-learning systems is only one dimension in which learners are required to produce answers, for example, by selecting multiple-choice, true/false, or matching answers or by giving short answers. This type of assessment still lacks interactions among the learners, and thus, it might not fully support learning. Many researchers have endeavored to propose an open-ended question method for evaluation, but their methods still focus on content assessment rather than learners' activities, which again lacks interactions among the learners. This paper concentrates on creating a new assessment method using open-ended questions with the aim of enhancing collaborations, activities and interactions of learners at the same time. The objectives are as follows: 1) to develop a process model for multidimensional assessment (M-DA) to enable effective learning; 2) to develop free-text answer assessments using a vector space model and a semantic extraction model; and 3) to develop an algorithm for evaluating learners based on a M-DA to encourage learners' activities. In addition, we created an environment for learners to be actively assessed and to interact with others when studying online. Two groups of parallel learners taking an e-course were tested on the two systems in a virtual learning environment. The results of the experiment noted that the system with multidimensional assessment showed a better outcome than the system without M-DA.
multidimensional assessment (m-da) free-text answers assessment vector space model e-learning collaboration collaborative virtual environment