Object The authors present the results of 400 consecutive neuroendoscopic interventions performed by a single surgeon in 373 patients during the last 8 years. Methods The study is based on a retrospective analysis of a continuously updated electronic database that includes patient history and radiological files. The success rate of the interventions is calculated. Conclusions The underlying pathological condition was hydrocephalus of various origins. The success rate within patient groups is given and the factors leading to successful surgery are emphasized. Recommendations on indications for neuroendoscopic operations are discussed.

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In this paper the issue of bias-variance trade-off in building and operating Moodle Machine Learning (ML) models are discussed to avoid traps of get-ting unreliable predictions. Moodle is one of the world’s most popular open source Learning Management System (LMS) with millions of users. Although since Moodle 3.4 release it is possible to create ML models within the LMS system very few studies have been published so far about the conditions of its proper application. Using these models as black boxes hold serious risks to get unreliable predictions and false alarms. From a comprehensive study of differently built machine learning models elaborated at the University of Dunaújváros in Hungary, one specific issue is addressed here, namely the in-fluence of the size and the row-column ratio of the predictor matrix on the goodness of the predictions. In the so-called Time Splitting Method in Moo-dle Learning Analytics the effect of varying numbers of time splits and of predictors has also been studied to see their influence on the bias and the variance of the models. An Applied Statistics course is used to demonstrate the consequences of the different model set up.

In today’s modern world, the pace of technological development can be con-sidered exponential. Education must constantly adapt to this dynamic devel-opment. It must be able to innovate, to use modern tools and methods that are effectively integrated into the learning process. Education should provide an appropriate learning environment to meet changing needs, one way of which is e-learning. This environment can be an excellent support for the learning process; however, it will hardly be effective without developing the right student learning attitude. The e-learning environment gives freedom and independence to the individual, at the same time. For the learner's individual endeavor to be successfully completed as expected, control and continuous feedback are needed. One way to do this is through self-quizzing. Self-quizzes, divided into units, related to the learning material, with appropriate difficulty and amount, can help to understand and engrave the processed material, and thus improve the effectiveness of learning. Self-quizzes create the opportunity for imme-diate feedback, which is a very important feature of an e-learning environ-ment. According to many scientific research, immediate feedback can greatly help maintain interest and motivation, and quizzes are suitable tools for this purpose. In our research, we sought to answer the question of how the continuous, self-monitoring practice opportunity provided by online quizzes affects stu-dent achievement. In the case of an online course held at the University of Dunaújváros in 2019, we examined whether students who continuously per-form self-quizzes will be more effective by the end of the learning process than their peers who are less receptive to independent self-quizzing. We also addressed the effect of the nature of time spent on self-reflexive quizzing on learning success.