Editorial

The contributors of this issue have demonstrated great enthusiasm and contributed seven fine papers covering topics of high current interest spanning areas briefly described by keywords executive functions (EF), behavioural and emotional strength, working memory, to strategies for improving reading and mathematics skills.

The work by Chung, Liu, McBride, Wong, and Lo (2017) investigated the relative importance of executive functioning, parent–child verbal interactions, phonological awareness and visual skills on reading and mathematics for Chinese children of different socio-economic backgrounds. Results revealed that children with lower socio-economic status exhibited lower levels of these skills, interactions and achievements than their counterparts. It is suggested that the above skills affect reading and mathematics achievement. Supportive intervention in the classroom is examined in the contribution by Dias and Seabra (2017). The study investigated the effects and benefits of intervention conducted by teachers in terms of improved EF, behaviour and academic achievement and followed up after one year. The results suggested that EF intervention may be a useful tool for promoting improved adjustment and academic achievement. It may seem intuitive that positive student–teacher relationships benefit a student’s academic achievement and behavioural and emotional adjustment. This has been researched in more detail in the paper by Sointu, Savolainen, Lappalainen, and Lambert (2017). They examined this framework, and it is interesting to note that over a two-year observation period, behavioural and emotional strengths demonstrated a positive relationship with student–teacher relationships as well as academic achievement, which also echoed the study by Petersen and Hyde (2017) which found out that mathematics interest and utility value decreased across time, but self-perceived math ability remained. Emotions related to academic performance are especially high in East Asian Confucian societies, such as Taiwan, places that strongly emphasise on the formal value of educational achievements. This leads to a predicament faced by students who fail academically. The article by Fwu, Wang, Chen, and Wei (2017) proposes that this gives rise to a dilemma between ‘feeling bad’ (emotional distress) for exerting too much effort and ‘being bad’ (negative image) for making little effort. The results supported the hypothesis that effort becomes a double-edged sword for students who failed. They are more likely to either ‘feel bad’ or ‘be bad’ after failing academically.

Guzman-Munoz (2017) examines the aspect of how inductive learning can be promoted by a well-thought presentation of study materials. It may also indicate how practice schedules should be individually customised. As is known, mixing examples of different categories promotes inductive learning as opposed to massing. In the present study, three hypotheses are tested whether the advantage of interleaving is exclusively due to the mixing of examples from different categories or to the temporal gap introduced between presentations. In addition, also the role of working memory capacity was taken into consideration. Results showed that the mixing of examples might be the key component that determines improved induction, where participants with high spans of working memory capacity seemed to profit more than participants with low spans. So it seems imperative for the successful implementation of customised practice schedules that a reliable prediction of working memory ability can be achieved at an early age. On a similar line, the work by van der Ven, Klaiber, and van der Maas (2017) is also concerned with the relationships that serve to predict the ability of a person’s visuospatial working memory. Writing down spoken number words (transcoding) is an ability that is predictive of math performance and related to working memory ability.

These studies have highlighted various directions to enhance academic achievement, i.e. implement EF development, customise individual practice schedule to improve working memory, emphasise on student–teacher relationships and behavioural and emotional strengths from early age. EF are also known to correlate strongly with academic abilities (Zuk, Benjamin, Kenyon, & Gaab, 2014). These works employ assessments based on external observations and questionnaires and complement recent efforts to relate such findings to the physiological workings of the brain. Using advances in imaging technologies provides further exiting opportunities to link these findings with physical phenomena of the human brain. The method of choice is the non-invasive functional magnetic resonance imaging (fMRI). As an example, a very recent work by Haist, Wazny, Toomarian, and Adamo (2015) using fMRI data suggests that two different brain systems for non-symbolic numerosity acuity may contribute to individual differences in math with varying contribution across development. Vannest, Karunanayaka, Schmithorst, Szaflarski, and Holland (2009) reviewed fMRI studies on language skills in children from infancy to childhood. The neural basis of academic achievement motivation was investigated by Mizuno et al. (2008) using fMRI resulting in the finding that motivation to learn correlates with bilateral activity of a region in the forebrain called the putamen. It is also reflected by Noble, Wolmetz, Ochs, Farah, and McCandliss (2006) that individual differences in skill result in large differences in brain activation. The fMRI study by Rama et al. (2001) suggests that different brain locations are active in the working memory processing of emotional content of different aurally presented information. Nystrom et al. (2000) used the fMRI to probe working memory verbal/non-verbal, and spatial/non-spatial dissociation. By and large, the findings made by fMRI support those based on educational psychology and it can be hoped that stronger integration of these approaches will give rise to further exciting discoveries and insights. Broader opening of studies to cross-boundary research approaches may be seen as the future trend in academic achievement studies.

I am confident that the papers highlighted here contribute to the advance of knowledge in the community in regard to the identification of learning progression through learning assessment, teaching and curriculum, and the diagnosis of learning difficulty, but also be enablers for the improvement of teaching quality and improved students’ effective learning. It is my conviction that with the assistance of fMRI, educational psychology can highly accelerate our understanding of learning and greatly enhance learning assessment, teaching and curriculum development. This advance provides a golden opportunity to lead students towards most effective learning strategies.

Ying-Yao Cheng
[email protected]