Horta Bartomeu, Raquel2024-09-182024-09-182023-09Horta Bartomeu, Raquel (2023) A Time-Aware Approach to Detect Help-Seeking Behaviour from Student-Platform Interaction. Trabajo Fin de Máster. Universidad de Educación a Distancia (UNED)https://hdl.handle.net/20.500.14468/23781Seeking help when needed is a crucial skill, especially in unsupervised learning scenarios. It is known that some students do not ask for assistance when they need it, which can lead to counterproductive learning sessions. This work addresses the challenge of detecting help-seeking behaviour by learning from student-platform interaction events using deep learning models. This is the first work to predict help-seeking by considering the temporal nature of student behaviour while being independent of the topic being taught and the task at hand. We depict student-platform interaction as sequences of actions and evaluate five distinct approaches alongside various data representation techniques. Our research yields a model for detecting help-seeking behaviour solely from action sequences. We hypothesise that this approach has the potential for further improvement, especially when combined with pedagogical data and personalised features. Furthermore, we introduce a novel knowledge representation technique for categorical sequence analysis.eninfo:eu-repo/semantics/openAccess12 Matemáticas::1203 Ciencia de los ordenadores ::1203.04 Inteligencia artificial12 Matemáticas::1203 Ciencia de los ordenadores ::1203.17 Informáticatesis de maestríahelp-seeking behaviourstudent behaviouradaptive learningevent predictionsequence classificationrecurrence plots