Supporting mediated peer-evaluation to grade answers to open-ended questions

We show an approach to semi-automatic grading of answers given by students to open ended questions (open answers). We use both peer-evaluation and teacher evaluation. A learner is modeled by her Knowledge and her assessments quality (Judgment). The data generated by the peer- and teacher- evaluations, and by the learner models is represented by a Bayesian Network, in which the grades of the answers, and the elements of the learner models, are variables, with values in a probability distribution. The initial state of the network is determined by the peer-assessment data. Then, each teacher’s grading of an answer triggers evidence propagation in the network. The framework is implemented in a web-based system. We present also an experimental activity, set to verify the effectiveness of the approach, in terms of correctness of system grading, amount of required teacher's work, and correlation of system outputs with teacher’s grades and student’s final exam grade

Collaborative projects and self evaluation within a social reputation-based exercise-sharing system

We present the design issues and motivations of an enhanced version of the web-based system SOCIALX, supporting collaborative and social aspects of learning. This web application allows to share solutions to exercises and development of project(possibly group-) work, through the management of a reputation system. With the aim of enhancing collaboration and to help students working on exercises, we introduce contextual FAQs and micro-forums and a currency-based concretization of the perceived usefulness of other's answers. The tokens exchanged are used also to help the teacher/tutor in choosing the best question/answer pairs to be promoted to the FAQ. To introduce group responsibilities, peer-pressure and self-evaluation we define group-based projects with self/peer-evaluated phases. The different phases of a project are given to different groups, so that the produced deliverables are both self-evaluated when they are submitted and peer-evaluated by the group working on the next phase. The system is its last stages of development and will be tested with real students in the next academic year