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De Marsico, Maria; Sciarrone, Filippo; Sterbini, Andrea; Temperini, Marco – EURASIA Journal of Mathematics, Science & Technology Education, 2017
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…
Descriptors: Evaluation Methods, Peer Evaluation, Models, Grading
Azevedo, Ana, Ed.; Azevedo, José, Ed. – IGI Global, 2019
E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…
Descriptors: Higher Education, Computer Assisted Testing, Multiple Choice Tests, Guides
Wang, Jianjun – 1995
Effects of blind guessing on the success of passing true-false and multiple-choice tests are investigated under a stochastic binomial model. Critical values of guessing are thresholds which signify when the effect of guessing is negligible. By checking a table of critical values assembled in this paper, one can make a decision with 95% confidence…
Descriptors: Bayesian Statistics, Grading, Guessing (Tests), Models

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