1.1 Cognitive load theory and measurement
Since the concept of cognitive load came into being, it has attracted many researchers to study the process of its generation. With the deepening of research, researchers began to explore how cognitive load affects information processing and problem solving, and thus put forward the cognitive load theory. In order to improve learning effect by reducing cognitive load, objective measurement and effective intervention of cognitive load are needed.
As the most complex organizational structure of the human body, every activity is directly or indirectly under the control of the brain. Among them, PFC is considered to be the core region for processing many advanced cognitive abilities(Miller & Cohen, 2001), and the increase and full load of cognitive load must also produce corresponding changes in the brain. As one of the most important organs, the brain’s internal tissue transformation cannot be observed by experimental dissection or other operations. we need to use relevant instruments to concrete the internal structure of brain. With the emergence of MRI, EEG and other hypercanning instruments, physiological measurement as a new way to measure the neural mechanism has been gradually favored by researchers. (Lin & Zhang, 2017). However, due to the technical and cost limitations of hyperscanning equipment, its application in the field of education is still very rare. In this study, we would like to use the hyperscanning instruments to supervise the variable of the subjects’ brain when they are doing the memory tasks. Then, it can be compared to the field of education to explore the physiological state of the cognitive load acquired by learners in the learning process and To provide more divergent ideas for the teaching intervention measures.
Cognitive load is an important factor that affects the learning effect of learners in the learning process. Sweller put forward the cognitive load theory (CLT) for the first time after a detailed analysis of cognitive load. CLT believes that cognitive load can be divided into internal cognitive load, external cognitive load and associated cognitive load(Sweller, 1994). There are three cognitive load measurement methods accepted by researchers at present: subjective measurement, task performance measurement and physiological measurement(F. Paas, E. Tuovinen, & Tabbers, 2003). Sweller measured cognitive load based on the difficulty level of the learning material and the learner's performance results. On this basis, Brunken believes that analyzing the correlation between learners' behavioral changes, physiological changes and learning process is also one of the objective and indirect methods to measure cognitive load, and proposes a dual-task analysis method(Brunken, L. Plass, & Leutner, 2003). One of the above two measurement methods is based on the external behavior of learners to complete the task; the other is based on the multi-dimensional self-report of learners. The former method is not widely applicable due to the limitations of the subject and the influence of task introduction on the learning process of learners. The latter method will affect the objectivity of the results because of the subjective judgement. In order to avoid the disadvantages of the above two methods, researchers are interested in physiological measures. Tang et al. tested the cognitive ability of Alzheimer's patients through EEG and evaluated it by stepwise multiple regression(Tang et al., 2001).With the help of MRI, Li explored the relationship between the development of cognitive ability and the characteristics of brain structure and function, bringing enlightenment to the cognitive development of children(LI & LI, 2010).
1.2Functional NIRS as a Highly Flexible Device to measure cognitive load
Functional near infrared spectral imaging technology (fNIRS) as a new type of hyper- scanning technology, has the advantage of noninvasive, flexible, portable. It is a non-invasive, real-time monitoring of local tissue blood oxygen saturation (rSO2) optical imaging technology. It has attracted the attention of more and more experts at home and abroad, and has been used in psychology, verbal, cognitive function, executive ability, clinical fields and other fields. It can be used for age groups from infants to the elderly. Compared with other neuroimaging technologies, fNIRS imaging has greater potential. Originally used in biomedics, the relatively high transparency of biological tissue open an "optical window" in the near-infrared region of the spectrum to allow enough photons to be transmitted to help doctors perform clinical examinations(Jobsis, 1977). Ferrari has for the first time applied this technique to quantitative measurements of changes in oxygen levels in the brain, which can be used to determine brain activity(Ferrari, Giannini, Sideri, & Zanette, 1985).
With the continuous development and progress of technology and the continuous crossover between disciplines, fNIRS technology has been applied in the fields of psychology, sports and education because of its high elasticity to body movement and good tolerance to electromagnetic noise. Bai et al. adopted the emotion interference method and found that the dorsolateral prefrontal lobe was not involved in the processing of emotion and behavior inhibition, and believed that the prefrontal lobe was not the key brain region of emotion and behavior inhibition(Bai et al., 2016). Emotion, as a human's behavioral response to objective things, will affect people's processing of information. The appearance of negative emotions will have an impact on working memory, and increase the difficulty of the task and increase the workload, which will reduce the impact of negative emotions(Liu, 2017). Because of its size and non-invasive of the experiment and its mobility, it is feasible to introduce the technology into the field of education. As a new way of teaching, the effective combination of educational games and fNIRS technology can enable researchers to continuously improve the connection between educational games and learning science according to the brain imaging results of learners when using educational games(Kesler, Sheau, Koovakkattu, & Reiss, 2011; Noah et al., 2015; Pei, Shang, & Zhou, 2017; Witte, Ninaus, Kober, Neuper, & Wood, 2015). N-back paradigm is a classic paradigm of working memory task in psychology, which is used by many researchers to study cognitive load(Owen, McMillan, Laird, & Bullmore, 2005; Song, 2011). Based on this paradigm, measurements of the prefrontal cortex not only reveal an interaction between emotion and cognition(Tseng et al., 2018), but also provide hemodynamic evidence that women can master verbal working memory tasks faster than men(Gao, Zhang, Luo, Liu, & Gong, 2016).
However, few researchers have used this technique to measure cognitive load. With the help of fNIRS technology, this study hopes to explore the brain changes of subjects under different states of cognitive load, that is, the activation of related brain regions when cognitive load is overloaded. We hypothesized that the working memory task elicited prefrontal activation and that it changed with difficulty.