Abstract:

The recent development of e-learning has allowed ubiquitous learning, becoming the centre of the discussion of educational practice (Shen, Wang, and Shen, 2009). Nowadays, all university centres support their face-to-face courses with the use of digital platforms such as Moodle, WebCT. In this sense, e-learning platforms should not only help the generation of excellent academic results but also involve students in the learning process. Certain studies show that students who are fully involved in learning are behaviourally, intellectually and emotionally implied with teaching tasks (Bangert-Drowns and Pyke, 2001).

In adult education the study of theory and practice relegate emotions and put rationality first, reducing the role that emotions play in learning as motivators and in some cases as impediments to learning (Dirkx, 2002). Because in non-attendance courses the emotional signals of the student are represented only by text on the screen, with the absence of facial expressions or body language, content or tone of the dialogue. A growing interest has emerged in the study of the role of emotions in online learning, in which the design of attractive and meaningful learning experiences must achieve cognitive, affective and social engagement (Wang and Kang, 2006).

There is growing interest in the use of neuroscience in educational research (Xu & Zhong, 2018). The present study evaluates the emotional state of the student during autonomous online learning. Specifically, neuroscience devices such as an EEG electrocardiogram (EEG) and a Galvanic skin response (GSR) were used to measure differences in emotional metrics (emotional impact and valence) and cognitive metrics (attention, engagement and memorisation). Specifically, three types of activities found on a Moodle platform were tested: "Assignments", "Lessons" (with text and images) and a "Quiz test". Besides, self-reported metrics were used to assess the student's attitude towards the subject, previous experience and the relationship the student has with e-learning technologies.

The results obtained make it possible to determine the activation, impact and emotional valence, as well as the attention, engagement and memorisation that takes place before the activities to be carried out in the learning platforms. The results obtained allow us to design better learning and evaluation materials, through emotional control and the cognitive load they produce.

Keywords:

EEG, LMS, GSR, attention, engagement, memory.