1 Bauman Moscow State Technical University (RUSSIAN FEDERATION)
2 Loughborough University (LU) (UNITED KINGDOM)
About this paper:
Appears in: EDULEARN15 Proceedings
Publication year: 2015
Pages: 7330-7335
ISBN: 978-84-606-8243-1
ISSN: 2340-1117
Conference name: 7th International Conference on Education and New Learning Technologies
Dates: 6-8 July, 2015
Location: Barcelona, Spain
The traditional approach to computerised help in teaching is to apply automatic control over the learner's answers to prepared formal questions; most commonly, this is done by choosing from a set of mixed wrong and right answers (multiple choice).

Other learning tools for programming include; theoretical learning materials (text-books , articles, lectures), tests based on fixed questions, homework program writing tasks and computer aided testing during the programming process.

This paper concerns enhanced technology for teaching programmers which uses software for control the students' theoretical knowledge as well as their coding skills.

A new teaching technology is described which allow teachers to carry out tests based on an analysis of events' flow logs. The data about learners’ behaviours has been mined with the use of process mining methodology. Such an approach gives a possibility to check student's retention of learning materials. The adaptive learning model is also described.

The evaluation of teaching materials was considered using many different types of available data: for the tests of theoretical knowledge (subject - time needed to answer - given answer - correct answer label); for the automatic programming tests (number of misprintings -– time between two compilation attempts or number of compiler warnings at every step - time between steps or test's results - correctness label - time of test).

Such data research pointed to weak points in the teaching-learning process and suggested a direction for improvement of teaching methodology.

The research was made with a support of Russian Federation Ministry of Science and Education #14.577.21.0135 dated 24/11/2014.
Programming learning, events flow, process mining, learning material evaluation.