# Automatic Clustering of Students by Level of Situational Interest Based on Their EEG Features
## 1 Introduction  
The existence of a close relationship between interest and learning has been recognized by literature as early as the beginning of the 19 th century. Interest theorists believed that promoting interest in the classroom increases students' essential motivation to learn. They had differentiated between two main types of interest: situational interest and personal interest. Situational interest (SI) appears in response to features in an environment and can be activated immediately [1, 2]. In contrast, personal interest has a less spontaneous and dispositional quality and resides in the person across situations. Although research on situational interest in educational psychology has been expanding in the beginning of 20 th century, there is a lack of focus on how general contextual factors, such as the condition of the classroom or the type of instruction, can stimulate interest in learning. The current methods used to assess interest can be divided into two: (1) psychological measures and (2) physiological measures. Usage of a text-based method as one of the psychological measures for situational interest is limited to individual student assessment. Thismethod is not assessing the situational interest within the actual classroom environment. Self-reports and questionnaires are also commonly used tools in psychological measures; however, these tools are known for being susceptible to subjective bias [3]. [PERSON] [4] has developed one of the recognized questionnaires to measure situational interest in mathematics classrooms among secondary school students. [PERSON] [5] found situational interest is positively related to knowledge acquisition. [PERSON] [6] highlights a deceptive performance of the self-report assessment method due to students pretending to engage. Alternatively, physiological measures, such as EEG, Pupil Diameter, and Electrocardiogram (ECG) had overcome the drawbacks of psychological measures. A detailed discussion on the usage of neurophysiological over the traditional methods in experimental design can be found in [PERSON] [7]. Not only due to its portability, high temporal resolution, non-invasiveness, and low cost, the EEG is also capable to quantify subjectivity in evaluative situations [8]. The results obtained from EEG cannot be manipulated by participants and this method does not require an interruption during performing the task with the participant's attention, interest, or the session flow [9]. Studies showed that EEG has been increasingly used in interest research related to preference during web searching and advertisement [10; 11]. The EEG has also been used to examine the relationship between precursor emotions towards student enthusiasm in learning mathematics and science [12]. This work will positively explore the assessment of situational interest in real classroom settings using the EEG precisely. Rather than personal interest, this study focuses on SI, since it can have a spontaneous impact on students' learning. It can be effectively activated and assessed using physiological detectors. From [PERSON] [1], it was reported that the students that accomplished situational interest were better in recalling thought and elaboration. Logical thinking recommends that if the interest of a student is piqued when learning a topic, the student will participate more enthusiastically with that topic when compared to another student who is less intrigued by the topic. Greater commitment will be invested, which would lead to higher academic achievement. \"Situational interest is construed as a motivational response to a perceived knowledge deficit\" [5]. Psychological researchers found that situational interest comprises together an attentional and effective reaction to the situation [1; 4; 13]. Many studies reported the examination of these two aspects alone, but the question of how effective the study is if one of the important elements of SI is abandoned.