Anticipating Tutoring Demands Based on Students’ Difficulties in Online Learning
摘要
Anticipating the tutoring needs in online learning is essential to provide adequate support to students. Feedback and even silence are valuable clues to reveal the level of engagement. Approaches based on Artificial Intelligence (AI) can process this information and alleviate the workload of human tutors. In this study, Natural Language Processing (NLP) techniques were used to assess the performance of classifying students’ difficulties in an Educational Social Network. Difficulties were classified into categories such as “personal”, “technical”, and “others”. The model's performance allows you to anticipate and direct tutoring.