COVID19: testing an adaptive e-learning model to evaluate online student’s performance during the lockdown

COVID19. During the lockdown period, we all have had the oppor- tunity to renew our online teaching strategy and learn something new about the methodology useful to manage the tools (LMS, SCORM, Data Mining) we have to support our students in their study process and, above all, evaluate their per- formance. As long as we took it seriously and put it into practice, we have the opportunity to create some new fundamental principles of e-learning in general. Tutorship and performance evaluation are the key elements in building up a ful- filling strategy in online teaching. This paper describes the process of validation “in vivo” as the natural prose- cution of a previous research project, made in 2012-2016, that defined an adap- tive e-learning model for the evaluation of student's performance [1] [2]. The research team implemented the suggested model of adaptivity, on Moodle with a specific panel of university students, to verify the efficiency method in content and course delivery, validate the results of that research, and the effec- tiveness of the methodology and the technology proposed.