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15 Minutes of Attention in Class: Variability of Heart Rate, Personality, Emotion and Chronotype

Until today, almost all studies on Sustained Attention (SA) in the classroom were based on the time management by the teacher and its effect on student attention, but almost none report objective and conclusive data on physiological factors that intervene and modulate the student’s AS during class; which led the pedagogical sciences to consider that AS depends almost exclu-sively on the teacher’s methodology. In this study, an AS Detection System in the classroom was designed and validated based on Heart Rate Variability (HRV) and through a non-parametric analysis of time, frequency and entropy measures, in A sample of 30 subjects, it was shown that the physiological response that promotes AS in students is activated between the first 15 to 20 minutes of a conventional class. In addition, it was verified that the Positive Affection, the Tension and the Chronotype modulate the AS in the first minutes, in the middle and at the end of the classes, and that there is a significant difference in the 40th minute for the morning and evening groups.


Introduction
In the educational demand of the Teaching/Learning processes there is a need

Attention and HRV Studies
Several studies have sought to determine the time of AS in the classroom; for example, in the year 1976, Johnstone and Percival (cited by Bunce, Flens, & Neiles, 2010) measured student attention during 90 different classes by observers external that recorded attention subjectively. A decrease in attention was observed in the first five minutes and another around 10 to 18 minutes. Bunce et al. (2010) investigated the attention lapses reported by the same students during a class time of 50 minutes and found that students do not pay attention continuously for 10 to 20 minutes during a class. Instead, their attention alternates between being attentive and not attentive in shorter and shorter cycles along a 50-minute class segment. Additionally, Wilson and Korn (2007) reviewed several investigations with different types of attention measures: student annotations, observations of students during classes and self-reports of student attention and physiological measures. These authors state that student attention decreases approximately 10 to 15 minutes in class. They also reported that the research, on which the calculation of attention is based during classes, provides little support for the belief that student attention decreases after 10 to 15 minutes, as most studies did not take into account the individual differences of the subject.
It should be noted that the physiological measure of SA, such as Heart Rate (HR) is considered an excitation indicator as a component of SA (Wilson & Korn, 2007;Bradbury, 2016). Thus, the HR or variation of the time intervals measured between heartbeats (Capuana, Dwyan, Tays, Elmers, Witherspoon, & Segalowitz, 2014;Shaffer & Venner, 2013;Shaffer, McCraty, & Zerr, 2014;Holzman & Bridgett, 2017), is considered by the "Porges Polyvagal Perspective" (Porges, 1995(Porges, , 2001(Porges, , 2007 and the "Neurovisceral Integration Model" (Thayer & Lane, 2000;Thayer, Hansen, Saus-Rose, & Johnsen, 2009) as part of the pre-frontal cortical substrates of top-down self-regulation, influenced by the Autonomous Nervous System-ANS (subdivided into Parasympathetic Nervous System-PNS and Sympathetic Nervous System-SNS) (Cardinali, 2018;Holzman & Bridgett, 2017), which influences the psychological (Capuana et al., 2014) and emotional processes (Appelhans & Luecken, 2006). In this way, the activation of the SNS produces an increase in the HR and the PNS decreases the HR; This fluctuation is known as HR Variability-HRV (Fonfría, Poy, Segarra, López,  The analysis of the HRV and its relationship with attention was also used by Chang and Huang (2012), who in a laboratory procedure, presented the participants with two types of tasks (low and high attention); The study concluded that both the demand for tasks regarding the operation of care processes result in changes in the HRV.

Studies on Personality, Emotion and HRV
At the same time, personality has been studied as a structural dimension of the psychology of the individual (Matthews, 2016;Linden, Dunkel, & Petrides, 2016;Revelle, 2016) and emotions are understood as a set of events that arise at the level of psychological description constituted by neurobiological processes, with holistic empirical approach (Barrett, Mesquita, Ochsner, & Gross, 2007;LeDoux, Phelps, & Alberini, 2016;Purnamaningsih, 2017;LeDoux & Brown, 2017) that are related to SA, perception, cognition and personality (Pessoa, 2018), which should be approached comprehensively (Cowen & Keltner, 2017) in the interaction with the school context in which the student develops (Scott-Parker, 2017) and the way in which together with the Personality modulates attention (Mogg & Bradley, 1999).
Today we know, for example, that there is interaction between negative affectivity and attention control (Lonigan & Vasey, 2009). Therefore, an individual's ability to regulate emotion can modulate the extent to which attention is directed toward any stimulus or threat (Cisler & Koster, 2010;Peers & Lawrence, 2009) and unless attention control in highly anxious individuals, the processing of stimuli that are not threatening will be low (Ortega, Ramírez, Colmenero, & García-Viedma, 2012)  For example, in an exploratory study by Ramírez, Ortega and Reyes (2015) found that High Frequency HRV modulates the association between anxiety and SA control in situations involving neutral stimuli, and risk aversion in the taking of decisions. Similarly, the HRV of the High Frequency band was positively associated with the attentional control and was negatively associated with the risk aversion. It was also found that High Frequency HRV modulates the influence of anxiety both in the control of attention to neutral stimuli and in risk aversion in decision making, which is consistent with Mather and Thayer (2018), who found that individuals with high HRV tend to have better emotional well-being than those with low HRV.
Another study based on the reinforcement model, speed of learning in decision-making, modulated by positive and negative emotions, it was concluded that a low resting HRV shows a higher negative motivational value in response to negative images (Katahira et al., 2015), which somehow agrees with Quintana, Guastella, Outhred, Hickie and Kemp (2012) who verified association of the HRV with the recognition of emotions.

Chronotype and HRV
The Chronotype is the variation in the temporal organization of sleeping behavior, attributed to differences in circadian oscillation, sleep/wake cycle, related to  (Araújo & Almondes, 2012) and in the decision making among other multiple aspects (Ingram et al., 2016) and in Attention (Vollmer, Pötsch, & Randler, 2013 (Roeser et al., 2012). In another study developed by Henelius, Sallinen, Huotilainen, Müller, Virkkala and Puolamäki (2014), they examined the use of spectral measures of the HRV to measure the sleepiness under chronic partial sleep restriction, concluding that the spectral power of the HRV reflects the SA in individuals exposed to partial sleep restriction (Henelius et al., 2014). On the other hand, Hasler, Allen, Sbarra, Bootzin and Bernert (2010)  (2010) reports that circadian rhythms can also be related to the Behavior Activation System and Positive Affection, but not with the Behavioral Inhibition System or Negative Affection, and it is concluded that the morning activity it is associated with depression through indirect multi-step routes.
This study is based on two fundamental premises: 1) The HRV is the result of the interactions between the Autonomic Nervous System (ANS) and the heart's functioning mechanism; and the activity of the ANS is based on the balance of the SNS and SNP.
2) The activity of the ANS plays a fundamental role in SS, in emotional responses, in cognition and in learning. In this way, the objective of the study was: To examine the truth that the time of SA in students, in the classroom, can be measured from the HRV and modulated by personality, emotion and chronotype.

Participants
In

Instruments and Techniques
ADS-HRV1. It is designed for recording heartbeat in a natural environment, based on Arduino Technology. It is a platform for electronic prototypes of free hardware and single board, designed with a microcontroller by integrated input and output gate and standard programming language (Geddes, 2017;MacRoberts, 2015). The components of the ADS-HRV1 are: 1) Arduino: Open source electronic prototype based on flexible hardware and software. It was programmed using the "Arduino Programming Language" (based on Wiring) and the "Arduino Development Environment" (based on Processing

Data Processing
The hertz; reflects the activity of the SNS and its emotional reactions (Shaffer et al., 2014). c) of the spectra LF/HF Ratio: Additional measure to assess the balance between sympathetic and parasympathetic activity of the heart. When the value of the LF/HF Ratio is low, it presupposes PNS dominance and when the value of the relationship is high, the predominance is of the SNS.
3) Nonlinear measurements. Entropy; parameters and statistics developed by Pincus (1991) based on chaos theory, which presents an explanatory model of the complexity of biological dynamics, related to the entropy of Kolmogorov, which offers a measure of the irregularity of a series of data. The algorithms are Approximate Entropy (ApEn) and Sample Entropy (SampEn), which are patterns to characterize the complexity and irregularity of the HRV signals.

Information Processing
The ADS-HRV1 validation was based on

Results
The lowest number of heart pulses was 5338 and the highest was 8678. The overall average was 6444. The GM of Interval RR was 683.3 ± 61.95. Table 1 shows  (Figure 1(A-1)). In the same way, the HR parameter showed a significant difference in the time series [F = 57.845 (11) (Figure 1(A-2)). In the SDD-RR parameter, a significant difference in the time series was verified [F = 20.515 (11); p = 0.039], however, p-Adj showed no significant difference between the associated temporal segments (Figure 1(A-3)). In the RMSDD-RR parameter,  (Figure 1(A-4)).
The non-linear results of the VFC (Entropy), the analysis of variance showed that there is no significant difference in the time series for the ApEn parameter [F = 11 (11); p = 0.443]. On the contrary, a significant difference was found in the variance of the time series for the SampEn parameter [F = 23.692 (11); p = 0.014]. However, no significant difference was found between the time segments of the series using p-Adj (Figure 1(C-7)).
Regarding the results of the Psychological data, 100% of the subjects had a score in the intelligence profile test, that is, they are defined by abstract thinking.   Through Spearman's bivariate correlation, six (6) significant correlations were identified ( Figure 2). No significant correlations were found between the different behavioral variables and the variables of the subject Sex and Age.
Verifying how SA is modulated by personality, emotion and the Chronotype,  with categorical Psychological variables.

Discussion
In the present study, a progressive decrease of the HR calculated in 7.3% reduction (from the 10 th minute to the 60 th minute of the class) is verified, which corroborated for Bligh in a year 200 (Bradbury, 2016)  In the present study, the time measurements of the VFC, mainly the values offered by Intervalos RR and of the FC, are susceptible to be able to determine the significant differences between the time segments by non-parametric methods. For example, significant differences were identified between three initial time segments (10, 15 and 20) and the last three time segments (50, 55 and 60).
There was also a significant difference between half of the class and the final one, based on the RMSDD-RR parameter; which suggests that the individual differences of the subject may be modulating the HRV and therefore the SA in the students.
The HRV frequency measurements (%LF, %HF and LF/HF Ratio) provide confirmatory data of the significant differences between initial and final time segments, that is, between the first 15 minutes of the class and the last 15 minutes. In addition, time segments 15 and 50 respectively, were more susceptible to identify significant variations. This demonstrates that the HRV systematically decreases throughout a class with classical methodology in a duration of 60 minutes, and that the students pay more attention in the first 15 minutes, as opposed to the conclusions of Johnstone and Percival in a year 1976 (Bunce et al., 2010), which observed, subjectively, a decrease in attention in the first five minutes and another around 10 to 18 minutes.
The data found in the present study suggest that the general characteristic of the students' personality (Abstractedness and Tension), are configured through skills that are acquired through extended practice over time, as proposed by Matthews (2016). In turn, the reasoning was inversely correlated with Tension and Positive Affect, which means that as the rationale score increases, stress levels and negative affect tend to be lower; that is: Abstractedness is a protective or modulating factor of emotions. This is further corroborated by the positive correlation found between reasoning and Positive Affect.
Positive Affect is positively associated with Abstractedness and inversely with Negative Affect and with Tension. This suggests that positive emotions have a preponderance as a protective factor of multiple social situations, in accordance with the evidence of Rico, Alzate and Sabucedo (2017) and with the proposal of Scott-Parker (2017) who propose that the emotions experienced as internal subjective states, can be outsourced through behaviors in response to relatively stable personality characteristics (trait), less stable factors (status) or in response to context-specific activators (teacher/peer interaction). Current evidence suggests that emotional processing is intertwined with perception, cognition and personality (Pessoa, 2018). This was identified in the present study.  (Ortega et al., 2012), or between the interaction between negative affectivity and attention control (Lonigan & Vasey, 2009), as well as the data that suggest emotion as an SA modulator (Cisler & Koster, 2010;Peers & Lawrence, 2009).
Although some studies suggest that the frequency domains of the HRV (mainly of the HF band) modulates the association between anxiety and SA (Ramírez et al., 2015), no evidence was found in the present study.
Another important result was to identify from the measures of the frequency of the HRV, from the domain of %HF, a significant difference between evening and morning in the 40th minute, supporting the studies by Roeser et al. (2012); what seems to be that the increase in physiological arousal in nocturnal types could contribute to a greater vulnerability to psychological disorders (Roeser et al., 2012). This study reveals that the morning show a greater activation of the SNS at the end of the class, which allows a physiological condition for the AS, This study represents an important input for the methodological processes of teaching activity, by demonstrating that AS decreases over time, after the first 15 minutes of pedagogical activity. And in addition to this, individual factors of the psychological structure of the students modulate the SA in the classroom. However, more studies are necessary to demonstrate whether various teaching methods are involved or not in the SA during classes. Likewise, the notion that long classes should be discarded because students only have an attention period of 10 to 15 minutes is an accelerated conclusion. What is suggested is to combine expository and dynamic methods to modify physiological alert activations in students; or present relevant content to students in no more than 15 minutes.
Similarly, you should inquire more about the influence of the Morning and Evening chronotypes on the HRV, and how they modulate the SA during different hours of classes in the day. And finally, the analysis of the Entropy of the HRV is a sensitive method to identify significant differences between the psychological structure and the HRV; therefore, it is suggested to conduct more research and deepen these methods of analysis to understand more psychobiological associations in natural and experimental contexts.

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