DOI
https://doi.org/10.1007/s40593-020-00219-x

Summary
The influence of technology in learning solo or in group is discussed in this article. To demonstrate the case of individual learners, an intelligent tutoring system BioWorld for medical students is presented. The system is focused on helping medical students to practice their reasoning skills when analyzing virtual patient cases in comparison to the experts’ decision. The importance of considering individual learning paths in such systems is emphasized. The group learning approach is illustrated by an online platform HOWARD which supports problem-based learning approach. This system is designed to practice communication with the patients, especially, delivering bad news and supports small-group discussions. In addition, the author states that the analysis of educational data and its visualizations are an important part of learner modeling. It helps not only to identify proficiency levels, but also to present the learning guidelines based on the individual cognitive skills.

Relevance for Complex Systems Knowledge
The author describes student modeling for individuals and groups in the interactive learning environment with artificial intelligence (unsupervised learning and machine learning) methods used in the background to classify students’ and groups’ profiles, identify learning strategies and activities. The author discusses a learning environment which is used in medical training and is dedicated to simulating specific cases, the response to the student’s action and verifies student’s competences to solve cases using system thinking approach. Such learning environments helps to develop statistical and data mining, process mining, reasoning, collaborative and argumentative skills together with the subject knowledge.
The author also provides insights on self-regulative learning approach and its relation to students’ emotions.

Point of Strength
The article presents interactive virtual learning environment enriched with the classification and other artificial intelligence methods for student modelling.