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A new decade
for social changes
9 772668 779000
ISSN 2668-7798
www.techniumscience.com
Vol. 30, 2022
Working memory interventions via physical activity and
ICTs: Α strategic issue for the improvement of school
students’ learning performance
Effrosyni Angelopoulou1, Athanasios Drigas2
1 2Net Media Lab Mind - Brain R&D ΙΙΤ - N.C.S.R. "Demokritos", Athens, Greece
efrosynagge@yahoo.gr1, dr@iit.demokritos.gr2
Abstract. Nowadays, there is a great need for schools to be transformed into more innovative
learning environments with more innovative approaches to learning and teaching so as students
to be allowed to develop their various skills and abilities to their fullest extent. Therefore, we
present the role of physical activity and ICT-based interventions for working memory
enhancement as a strategic issue for the improvement of students’ learning outcomes. According
to research findings, multi-component exercise and ICT-based intervention programs can
significantly contribute to the improvement of children’s and adolescents’ working memory and
thus can have a positive effect on children’s and adolescents’ learning performance. Finally, this
paper could trigger educators and policy-makers towards the ideal planning of innovative multi-
component physical activity and ICT-based intervention programs and their incorporation into
the school curriculum aiming at the working memory enhancement in children and adolescents
and the improvement of their learning outcomes.
Keywords. working memory interventions, physical activity, ICTs, learning performance,
school students, children, adolescents
1. Introduction
In today's society, the need to transform schools for the participation of young people
becomes imperative. Therefore, schools should promote more innovative approaches to
learning and teaching (Timperley, Kaser, & Halbert, 2014) so that all students’ learning needs
are met (Drigas, Argyri, Vrettaros 2009). One such innovative approach could be the integration
of ICT-based physical activity and working memory interventions into the school curriculum
to enhance students’ working memory and thus improve their learning performance since,
according to Gathercole, Lamont, and Alloway (2006), working memory is linked to academic
learning.
Working memory constitutes a brain system responsible for the temporary storage and
manipulation of the information necessary for language comprehension, learning, and
reasoning, which are complex cognitive tasks (Baddeley, 1992; 2010). Chronic aerobic exercise
can enhance children’s working memory capacity (Guiney & Machado, 2013), while highly
intense and structured physical activities are especially relevant for working memory
enhancement in adolescence (Lopéz-Vicente, Garcia-Aymerich, Torrent-Pallicer, Forns,
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Ibarluzea, Lertxundi, Gonzalez, Valera-Gran, Torrent, Dadvand, Vrijheid, & Sunyer, 2017).
Notably, the use of ICTs, such as computer-based tools, mobile training apps, video games
(Pappas, Drigas, Malli, & Kalpidi, 2018, Drigas et all 2004, 2009, 2013 Papoutsi, et all 2018),
and serious games (Chaldogeridis & Tsiatsos, 2020) can significantly contribute to working
memory enhancement.
In the current paper, we focus on the crucial role of physical activity and ICTs in school
students’ working memory and present it as a strategic issue for their learning improvement.
We chose to focus on physical activity and ICT-based interventions for the enhancement of
school students’ working memory because school students’ way and quality of life are affected
by today’s digitalization and sedentary lifestyles, which also have a profound impact on their
learning progress.
More specifically, the rapid development of ICTs has led to computers becoming part
of daily life (Drigas & Ioannidou, 2012, 2013; Player-Koro, 2012) and has pushed ICTs and
computers into classrooms at all educational levels (Player-Koro, 2012, Kefalis & Drigas 2019).
Ιn fact, technologies within the domain of interactive, remote and on line science such as
interactive whiteboards and related applications are extensively adopted in education’s
everyday life (Drigas & Papanastasiou, 2014).
In addition, today’s daily life is characterized by decreased or low physical activity
levels because of the increased use of motorized transport and screens for work, education and
recreation. Research findings indicate that in children and adolescents, physical activity, which
is defined as “any bodily movement produced by skeletal muscles that requires energy
expenditure”, can improve mental health and cognitive functions (WHO, 2021), such as
working memory. Physical activity’s positive impact on cognitive functions is based on several
mechanisms, including angiogenesis, oxygen saturation, glucose delivery, cerebral blood flow,
and neurotransmitter levels (Diamond, 2015).
This paper also reflects an effort to raise reader’s awareness of the significance of
children’s and adolescents’ daily physical activity engagement in school environments and
highlights the need for multi-component exercise and ICT-based working memory intervention
programs to be incorporated into the school curriculum targeting the effective enhancement of
working memory in children and adolescents and thus their positive learning outcomes.
2. Working memory in children and adolescents
Working memory is a brain system responsible for the temporary storage and
manipulation of the information necessary for language comprehension, learning, and
reasoning, which are complex cognitive tasks (Baddeley, 1992; 2010). Working memory is
inextricably linked to attention (Angelopoulou, & Drigas, 2021), but is distinguished from
short-term memory, because these two memory systems represent different cognitive functions
(Aben, Stapert & Blokland, 2012). More specifically, short-term memory is responsible for
storing information for a short period of time (e.g., remembering a phone number), while
working memory refers to handling information during a complex cognitive process (e.g.,
remembering numbers while reading a paragraph) (Goldstein, 2011).
Many researchers present working memory as a mental laboratory (Μασούρα, 2010)
that stores and manipulates information for short periods of time (Baddeley, 1986; Μασούρα,
2010; Gathercole & Alloway, 2007). It is also involved in almost every activity of daily life and
is subjected to gradual changes during the period of 5 and 19 years of human development
(Alloway & Alloway, 2013).
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Only a small amount of information can working memory hold either abstract ideas or
objects that can be counted (Cowan, 2014). It has been estimated that adults’ working memory
capacity is in the range of 3 or 4 objects (Cowan, 2001; Luck & Vogel, 1998; see Cowan 2016,
p. 7), while preschoolers and early elementary school children can maintain in their working
memory 2 or 2.5 items (Cowan, Nugent, Elliott, Ponomarev, & Saults, 1999; Cowan, Elliott et
al., 2005; Riggs, McTaggart, Simpson, & Freeman, 2006; Simmering, 2012; see Cowan 2016,
p.7). Working memory capacity increases during infancy but then regresses during
childhood (Cowan 2016). The minimum age at which a reliable measurement of working
memory can be made is 4 years (Alloway, Gathercole, & Kirkwood, 2016). Research has shown
the existence of linear increase in the performance of the phonological loop, central executive,
and visuo-spatial sketchpad from the age of 4 years to adolescence (Gathercole, Pickering,
Ambridge & Wearing, 2004). During adolescence, working memory capacity is close to that of
an adult and more than twice the working memory capacity of a four year old child (Gathercole
et al., 2007).
Older children can hold more bits of information than younger children. More
specifically, the child at the age of 4 years can recall 3 digits in a row, while at the age of 12
years the number of digits doubles and at the age of 16 years the range of digits reaches 7 to 8
digits (Hulme & Mackenzie, 1992, as cited in Dehn, 2008). Research findings suggest that
recall-guided action for single units of spatial information develops until 11 to 12 years, and the
ability to maintain and manipulate multiple spatial units develops until 13 to 15 years. These
findings are related to the maturation of distinct prefrontal regions and the organization of the
prefrontal cortex by level of processing (Luciana, Conklin, Hooper, & Yarger, 2005).
Furthermore, visual working memory ability continues to develop throughout
adolescence. However, it cannot reach the corresponding adult level even at the age of 16. That
indicates the U-shaped developmental row of visual working memory, according to which it
approaches higher performance levels earlier in life. But then it declines during adolescence
and rises again in adulthood (Isbell, Fukuda, Neville, & Vogel, 2015).
3. Working memory and school students’ learning performance
Working memory is closely associated with academic learning (Gathercole, Lamont,
& Alloway, 2006). Learning might be assumed to be the formation of new concepts. These new
concepts occur when existing concepts are joined or bound together. For the various types of
concept formation, then, the cauldron is considered to be working memory, which is linked to
fluid intelligence that is closely related to crystallized intelligence (Cowan, 2014).
Fluid intelligence refers to the ability to reason and to solve new problems
independently of previously acquired knowledge (Carpenter, Just, & Shell, 1990), while
crystallized intelligence refers to the type of intelligence that involves what an individual knows
(Cowan, 2014). Good working memory, then, is critical to learning because a good working
memory assists in problem-solving (hence fluid intelligence); fluid intelligence and working
memory then assist in new learning (hence crystallized intelligence) (Cowan, 2014).
Several studies have shown that the majority of children with poor working memory
are slow to learn in the areas of reading, maths and science, across both primary and secondary
school years (see Gathercole et al., 2006). For children, reading comprehension is a complex
activity and, once basic decoding skills have been sufficiently acquired and automated, it
requires several cognitive processes, one of which is working memory (Carretti, Borella,
Elosúa, Gómez-Veiga, & García-Madruga, 2017).
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Poor phonological working memory (Nicolielo-Carrilho, Crenitte, Lopes-Herrera, &
Hage, 2018) and poor verbal working memory can lead to poor reading performance (Giofrè,
Donolato, & Mammarella, 2018), whereas poor working memory capacity (Mousavi,
Badarudin, & Malt, 2012; Alamolhodaei, 2009; Alloway, 2006; Holmes & Adam, 2006;
Swanson, 2004; Wilson & Swanson, 2001); in fact, poor visuo-spatial working memory can
lead to poor mathematical performance (Giofrè et al., 2018).
Loosli, Buschkuehl, Perrig, and Jaeggi (2012) showed that working memory training
improves school students’ reading abilities, while Söderqvist and Bergman Nutley (2015)
claimed that working memory training can help optimize long term attainments in maths and
reading. According to Carretti et al. (2017), training working memory and its executive
processes during reading comprehension activities is a promising approach to sustaining
reading comprehension. Notably, a study by Alloway, Bibile, and Lau (2013) demonstrated that
computerized working memory training could lead to gains in academic performance.
4. Working memory interventions via physical activity and ICTs
4.1. The benefits of physical activity for children’s and adolescents’ working
memory
Physical activity is defined as “any bodily movement produced by skeletal muscles that
requires energy expenditure, which can be measured in kilocalories” (Caspersen, Powell, &
Christenson, 1985). In the light of this definition, physical activity can be linked to organized
physical activities (e.g., handball and football) and transportation (e.g., cycling and walking).
Also, physical activity can be considered as part of domestic tasks, such as cleaning and
carrying (Lahti, 2019).
Furthermore, physical activity can be subdivided into moderate (Caspersen et al.,
1985), such as walking (Dencker, Thorsson, Karlsson, Lindén, Eiberg, Wollmer, & Andersen,
2006) and vigorous intensity (Caspersen et al., 1985), such as running (Dencker et al., 2006),
and can be quantified using metabolic equivalents (METs) (Jetté, Sidney, & Blümchen, 1990).
1 MET is defined as the amount of oxygen consumed at rest, when sitting quietly, and equals
to approximately 3.5 ml 02/kg/min (1.2 kcal/min for a 70-kg person) (Jetté et al., 1990). Two
studies conducted by Dencker et al. (2006, 2008) defined 8-11 years old children’s moderate
physical activity as 3-6 METs and their vigorous physical activity as > METs.
Physical activity has a positive effect on cognition as well as brain structure and
function (Donnelly, Hillman, Castelli, Etnier, Lee, Tomporowski, Lambourne, & Szabo-Reed,
2016; Haverkamp, Wiersma, Vertessen, van Ewijk, Oosterlaan, & Hartman, 2020). Its impact
on cognitive functions has been widely studied (Lambourne, 2006; Chacón-Cuberos, Zurita-
Ortega, Ramírez-Granizo, & Castro-Sánchez, 2020). Such cognitive functions that benefit from
physical activity are attention, memory, and concentration. It is noteworthy that physical
activity tasks that feature higher cognitive demands and involve gross motor skills are more
effective on cognitive performance (Chacón-Cuberos et al., 2020).
A study by López-Vicente et al. (2017) showed that low physical activity levels at
preschool age could be associated with poorer working memory performance at primary school
age. The same study also showed that low physical activity levels at primary school age are
related to lesser working memory in adolescents, while highly intense and structured physical
activities are especially relevant for working memory enhancement in adolescence.
Also, sedentary behavior, such as increased screen time, has detrimental effects on
cognitive development during childhood (Carson, Kuzik, Hunter, Wiebe, Spence, Friedman,
Tremblay, Slater, & Hinkley, 2015). Therefore, obese and overweight children have poor
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working memory abilities (Christina, Sangeetha, Kumaresan, Varadharaju, & Hemachandrika,
2021) due to the fact that obesity, which is linked to an increased amount of time spent in
sedentary behaviors (Sahoo, Sahoo, Choudhury, Sofi, Kumar, & Bhadoria, 2015), affects
cognition through altering the brain structures and functions, as well as motor performance
(Christina et al., 2021).
Furthermore, chronic physical activity interventions can have larger effect sizes on a
broader range of cognitive outcomes in children and adolescents (Haapala, 2012; Haverkamp
et al., 2020). In addition, response times, during information processing, inhibitory control and
working memory tasks, are quicker in adolescents with a higher physical fitness, when
compared to their low-fit counterparts (Williams, Cooper, Dring, Hatch, Morris, Sunderland, &
Nevill, 2020).
However, despite the benefits of physical activity, globally, 81% of adolescents aged
11-17 years were insufficiently physically active in 2016. Notably, adolescent girls were less
active than adolescent boys, with 85% vs. 78% not meeting WHO recommendations of at least
60 minutes of moderate to vigorous intensity physical activity per day (World Health
Organization, 2020).
4.1.1. Physical activity - based working memory interventions
All the above benefits of physical activities for the working memory enhancement, as
well as the WHO statistics regarding the physical activity rates in children and adolescents,
confirm that the need for children’s and adolescents’ daily engagement in physical activity
becomes imperative. According to Guiney and Machado (2013), chronic aerobic exercise can
enhance children’s working memory capacity; in fact, Ludyga et al. (2018) showed that
adolescents’ daily engagement in a short aerobic and coordinative exercise program following
the school lunchtime break contributes to their working memory maintenance and task
preparations.
In addition, by applying 10 weeks of 3 × 45 minutes of after-school cardiovascular
exercise and a motor-demanding activity for preadolescent children, Koutsandréou, Wegner,
Niemann, and Budde (2016) found a positive effect of both cardiovascular and motor exercises
on working memory in preadolescent children.
Another intervention study by Lind, Geertsen, Ørntoft, Madsen, Larsen, Dvorak, Ritz,
and Krustrup (2018) also reported positive effects on working memory performance after an
11-week intervention, the “FIFA 11 for Health” for Europe program, which comprised small-
sided football games, drills and on-pitch health education, and it combined cardiovascular
exercise and motor and cognition demands. Moreover, this study showed that a physical activity
program based on a well-established team game, such as football, can have a positive effect on
cognitive performance in preadolescent children. It is noteworthy that Chen, Chen, Chu, Liu,
and Chang (2017) observed that a multi-component exercise intervention involving a jump rope
can positively affect obese children’s cognitive functions.
Of great interest is a study conducted by Ruiz-Ariza, CasusoSuarez-Manzano, and
Martínez-López (2018), which reported positive effects of an 8-week intervention using the
augmented reality game “Pokemon GO” on cognitive performance and sociability in
adolescents aged 12-15 years. Augmented reality games allow players to interact with the world
through their device’s camera (Lanham, 2017), contributing to increased physical activity (Ni,
Hui, Li, Tam, Choy, Ma, Cheung, & Leung, 2019).
Finally, Chacón-Cuberos et al. (2020), considering the aforementioned studies of Chen
et al. (2017), Lind et al. (2018), and Ruiz-Ariza et al. (2018), detected two basic requirements
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for physical activity to generate positive effects on cognition. More specifically, the first lies in
the load of the intervention performed, involving a minimum of 150 minutes per week of work,
in which the intensity is moderate (Chen et al., 2017; Lind et al., 2018), while the second
requirement is related to the cognitive demands of the task to be performed, that is, a
cooperation sport with an opponent can contribute to more cognitive improvements (Ruiz-Ariza
et al., 2018).
4.2. ICT - based working memory interventions
It is broadly agreed that Information and Communications Technology (ICT) can
enhance students’ educational, social and cultural experiences (Drigas & Ioannidou, 2013) and
can contribute effectively to the learning process (Drigas et al., 2013; Chaidi, Drigas, &
Karagiannidis, 2021). The term “ICT” is defined as “the study, design, development,
implementation, support or management of computer-based information systems in order
information to be converted, stored, protected, processed and retrieved” (Shuja, 2009).
In the field of education the term “ICT” refers to all types of technological means used
in teaching methods such as computers, tablets, interactive whiteboards (Galitskaya & Drigas,
2019), mobile applications (Drigas & Kokkalia, 2016; Karabatzaki, Stathopoulou, Kokkalia,
Dimitriou, Loukeri, Economou, & Drigas, 2018), artificial intelligence (AI) applications
(Drigas & Angelidakis, 2017), serious games (Kokkalia, Drigas, Economou, Roussos, & Choli,
2017). Prolonged exposure to technology and media devices probably has a great impact on
cognition (Alexopoulou, Batsou, & Drigas, 2020) that is the mental process of acquiring
knowledge and understanding (Titilayo, 2016), with which working memory is fundamentally
related (Bouchacourt & Buschman, 2019). Notably, computer-based tools, mobile training
apps, and video games could significantly contribute to cognitive improvement (Pappas et al.,
2018, 2019) and, thus, to working memory enhancement.
Taking into consideration that working memory is engaged during simultaneous
processing and storage of information, ICT use facilitates working memory capacity
amplification because it provides the necessary amount of repeated practice in simultaneous
processing and storage of information on a massive scale (García, Nussbaum, & Preiss, 2011).
Electronic tools for working memory training, such as Cogmed
(http://www.cogmed.com/), are highly effective. In particular, Cogmed is used in schools to
enhance student’s learning performance (Drigas, Kokkalia, & Lytras, 2015). It consists of the
Cogmed JM and Cogmed RM types for children and the Cogmed QM type for adults (Shipstead,
Hicks & Engle, 2012) and includes visuo-spatial tests (e.g. “Asteroids”) and verbal memory
tasks (e.g. “Input Module”) (Shipstead et al., 2012) that can be conducted in 25, 30 and 45
minute sessions over a period of five weeks (Aksayli, Sala & Gobet, 2019).
Video games also play a pivotal role in improving working memory capacity and
performance (Karyotaki & Drigas, 2015). More specifically, video games positively impact
visuo-spatial skills, which have been identified as a core part of working memory (García et al.,
2011); in fact, they allow individuals to exploit the potential of their visual working memory
(Blacker & Curby, 2014). In particular, research conducted by Nouchi and Kawashima (2014)
using a brain training video game called "Brain Age" (Nintendo Co. Limited, Kyoto, Japan),
also known as Dr. Kawashima’s Brain Training (Himmelmeier, Nouchi, Saito, Burin, Wiltfang,
& Kawashima, 2019) showed improved executive functions, enhanced working memory, and
increased processing speed.
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Furthermore, video games can be used effectively in school settings because they have
a particular goal that children must try to reach, as well as a faster speed than traditional games.
Children can understand instructions implicitly without reading them. Also, video games are
independent from physical laws, capture players’ attention and continue to do so as the game
builds a world with its own rules and regulations (Rosas, Nussbaum, Cumsille, Marianov,
Correa, Flores, Lagos, Lopez, López, Rodríguez, & Salinas, 2003).
Additionally, serious games, which are defined as “a mental contest, played with a
computer in accordance with specific rules, that uses entertainment to further government or
corporate training, education, health, public policy, and strategic communication objectives”
(Zyda, 2005), can be used effectively for working memory training (Boendermaker, Gladwin,
Peeters, Prins, & Wiers, 2018; Chaldogeridis & Tsiatsos, 2020).
5. Discussion and Conclusion
In this article, we presented the role of physical activity and ICT-based working
memory interventions as a strategic issue for the improvement of students’ learning
performance and thus their effective active presence at school and society. Because, nowadays,
there is a great need for students not to be evaluated by the nation as an economic asset (Moyle,
2010) but to be considered as its valuable members, who can significantly contribute to its
development.
Working memory refers to our ability to maintain and manipulate information,
necessary for an action, for short periods of time in the order of seconds (Bhandari & Badre,
2016) and is closely associated with academic learning (Gathercole et al., 2006) as it plays a
crucial role in the formation of the learning process (Drigas & Pappas, 2017). Working memory
abilities in children and adolescents are benefited from physical activity, yielding higher
improvements by chronic physical activity interventions (Haapala, 2012; Haverkamp et al.,
2020). ICTs also significantly contribute to working memory enhancement and thus to the
improvement of learning outcomes.
Additionally, working memory training plays a pivotal role in the development of
metacognition, which is very important for the acquisition of knowledge (Drigas et al., 2017)
and thus the improvement of the academic performance (Mitsea & Drigas, 2019) (Drigas &
Karyotaki 2014). Furthermore, metacognition can be considered as the vehicle that could lead
to consciousness (Mitsea et al., 2019), which is very important for the improvement of an
individual’s quality of life.
To conclude, the catalytic role of working memory training in the development of
consciousness, that is, the higher metacognitive processes of control, regulation and adaptation
of the individual, according to the stratified model (8 Layer Model) of Drigas and Pappas
(2017), could trigger educators and policy makers towards the ideal planning of working
memory intervention programs adapted in school settings. Finally, taking into consideration the
contribution of physical activity and ICTs to children’s and adolescents’ working memory
abilities, physical activity and ICT-based working memory intervention programs that combine
cognitive demands, motor-demanding activities and cardiovascular exercises could be
incorporated into the school curriculum targeting the enhancement of school students’ working
memory and the improvement of their learning performance.
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References
[1] Aben, B., Stapert, S., & Blokland, A. (2012). About the distinction between working
memory and short-term memory. Frontiers in Psychology, 3(301), 1-9.
https://doi.org/10.3389/fpsyg.2012.00301
[2] Aksayli, N.D., Sala, G., & Gobet, F. (2019). The cognitive and academic benefits of
Cogmed: A meta-analysis. Educational Research Review, 27, pp. 229–243.
DOI:10.1016/j.edurev.2019.04.003
[3] Alamolhodaei, H. (2009). A working memory model applied to mathematical word problem
solving. Asia Pacific Education Review, 10(2), 183-192.
https://dx.doi.org/10.1007/s12564-009-9023-2
[4] Alexopoulou, A., Batsou, A., & Drigas, A. (2020). Mobiles and Cognition: The Associations
Between Mobile Technology and Cognitive Flexibility. International Journal of
Interactive Mobile Technologies (iJIM), 14(03), pp. 146–156.
https://doi.org/10.3991/ijim.v14i03.11233
[5] Alloway, T. P. (2006). How does working memory work in the classroom?. Educational
Research and Reviews, 1(4), 134-139. https://doi.org/10.5897/ERR.9000188
[6] Alloway, T.P. & Alloway, R.G. (2013). Working memory across the lifespan: A cross-
sectional approach. Journal of Cognitive Psychology, 25(1), 84–93.
https://doi.org/10.1080/20445911.2012.748027
[7] Alloway, T.P., Bibile, V., & Lau, G. (2013). Computerized working memory training: Can
it lead to gains in cognitive skills in students? Comput. Hum. Behav., 29, 632-638.
[8] Alloway, T.P., Gathercole, S.E., & Kirkwood, H.J. (2016). Κλίμακα Αξιολόγησης
Εργαζόμενης Μνήμης: Εγχειρίδιο (ελληνική έκδοση). Αθήνα: Μοτίβο Αξιολόγηση.
[9] Angelopoulou, E. & Drigas, A. (2021). Working memory, attention and their relationship:
A theoretical overview. Research, Society and Development, 10(5), e46410515288.
https://doi.org/10.33448/rsd-v10i5.15288
[10] Baddeley, A. Working memory (2010). Current Biology, 20(4), R136-R140.
https://doi.org/10.1016/j.cub.2009.12.014
[11] Baddeley, A. (1992). Working memory. Science, 255(5044), 556-559.
https://doi.org/10.1126/science.1736359
[12] Baddeley, A. (1986). Working memory. Clarendon Press/Oxford University Press.
[13] Bhandari, A., & Badre, D. (2016). A Nimble Working Memory. Neuron, 91(3), 503-505.
https://doi.org/10.1016/j.neuron.2016.07.030
[14] Blacker, K.J. & Curby, K.M. (2014). Effects of Action Video Game Training on Visual
Working Memory. Journal of Experimental Psychology: Human Perception and
Performance, 40(5), pp. 1992-2004. DOI:10.1037/a0037556
[15] Boendermaker, W.J., Gladwin, T.E., Peeters, M., Prins, P.J.M., & Wiers, R.W. (2018).
Training Working Memory in Adolescents Using Serious Game Elements: Pilot
Randomized Controlled Trial. JMIR Serious Games 6(2):e10.
https://doi.org/10.2196/games.8364
[16] Bouchacourt, F. & Buschman, T.J. (2019). A flexible model of working memory. Neuron,
103(1),. 147–160. https://doi.org/10.1016/j.neuron.2019.04.020
[17] Carpenter, P.A., Just, M.A., & Shell, P. (1990). What one intelligence test measures: A
theoretical account of the processing in the Raven Progressive Matrices Test.
Psychological Review 97(3), 404–431. https://doi.org/10.1037/0033-295X.97.3.404
[18] Carretti, B., Borella, E., Elosúa, M.R., Gómez-Veiga, Ι., & García-Madruga, J.A.
(2017). Improvements in Reading Comprehension Performance after a Training
207
Technium Social Sciences Journal
Vol. 30, 200-213, April, 2022
ISSN: 2668-7798
www.techniumscience.com
Program Focusing on Executive Processes of Working Memory. Journal of Cognitive
Enhancement, 1, 268–279. https://doi.org/10.1007/s41465-017-0012-9
[19] Carson, V., Kuzik, N., Hunter, S., Wiebe, S.A., Spence, J.C., Friedman, A., Tremblay,
M.S., Slater, L.G., & Hinkley, T. (2015). Systematic review of sedentary behavior and
cognitive development in early childhood. Preventive medicine, 78, 115–122.
https://doi.org/10.1016/j.ypmed.2015.07.016
[20] Caspersen, C.J., Powell, K.E., & Christenson, G.M. (1985). Physical activity, exercise,
and physical fitness: definitions and distinctions for health-related research. Public
health reports (Washington, D.C.: 1974), 100(2), 126–131.
[21] Chacón-Cuberos, R., Zurita-Ortega, F., Ramírez-Granizo, I., & Castro-Sánchez, M.
(2020). Physical Activity and Academic Performance in Children and Preadolescents:
A Systematic Review. Apunts. Educación Física y Deportes, 139, 1-9.
https://doi.org/10.5672/apunts.2014-0983.es.(2020/1).139.01
[22] Chaidi, I., Drigas, A., & Karagiannidis, C. (2021). ICT in special education. Technium
Social Sciences Journal, 23(1), 187–198. https://doi.org/10.47577/tssj.v23i1.4277
[23] Chaldogeridis, A. & Tsiatsos, T. (2020). Implementation and Evaluation of a Serious Game
for Working Memory Enhancement. Applied Sciences, 10(24).
https://doi.org/10.3390/app10249128
[24] Chen, F. T.; Chen, S. R.; Chu, I. H.; Liu, J. H.; Chang, Y. K. Multicomponent exercise
intervention and metacognition in obese preadolescents: A randomized controlled
study. Journal of Sport & Exercise Psychology, v. 39, n. 4, p. 302-312, 2017.
https://doi.org/10.1123/jsep.2017-0013
[25] Christina, S.D., Sangeetha, A., Kumaresan, M., Varadharaju, B., & Hemachandrika, C.
(2021). Association between Working Memory and Obesity among Secondary School
Children, Journal of Pharmaceutical Research International, 33(29B), 79-84.
https://doi.org/10.9734/jpri/2021/v33i29B31592
[26] Cowan, N. (2016). Working memory maturation: Can we get at the essence of cognitive
growth? Perspectives on Psychological Science, 11(2), 239-264.
https://doi.org/10.1177/1745691615621279
[27] Cowan N. (2014). Working Memory Underpins Cognitive Development, Learning, and
Education. Educational psychology review, 26(2), 197–223.
https://doi.org/10.1007/s10648-013-9246-y
[28] Dehn, M.J. (2008). Working memory and academic learning assess-
ment and intervention. New Jersey: John Wiley & Sons, Inc.
[29] Dencker, M., Thorsson, O., Karlsson, M.K., Lindén, C., Eiberg, S., Wollmer, P., &
Andersen, L.B. (2006). Daily physical activity related to body fat in children aged 8-
11 years. The Journal of pediatrics, 149,(1), 38–42.
https://doi.org/10.1016/j.jpeds.2006.02.002
[30] Dencker, M., Thorsson, O., Karlsson, M.K., Lindén, C., Wollmer, P., & Andersen, L.B.
(2008). Daily physical activity related to aerobic fitness and body fat in an urban
sample of children. Scandinavian journal of medicine & science in sports, 18(6), 728–
735.
[31] Diamond, A.B. (2015). The Cognitive Benefits of Exercise in Youth. Current sports
medicine reports, 14(4), 320–326. https://doi.org/10.1249/JSR.0000000000000169
[32] Donnelly, J.E., Hillman, C.H., Castelli, D., Etnier, J.L., Lee, S., Tomporowski, P.,
Lambourne, K., & Szabo-Reed, A.N. (2016). Physical Activity, Fitness, Cognitive
Function, and Academic Achievement in Children: A Systematic Review. Medicine
208
Technium Social Sciences Journal
Vol. 30, 200-213, April, 2022
ISSN: 2668-7798
www.techniumscience.com
and science in sports and exercise, 48(6), 1197–1222.
https://doi.org/10.1249/MSS.0000000000000901
[33] Drigas, A. & Angelidakis, P. (2017). Mobile Applications within Education: An Overview
of Application Paradigms in Specific Categories. International Journal of Interactive
Mobile Technologies (iJIM), 11(4), 17–29. https://doi.org/10.3991/ijim.v11i4.6589
[34] Drigas, A., & Ioannidou, R. E. (2013). Special Education and ICTs. International Journal
of Emerging Technologies in Learning (iJET), 8(2), 41–47.
https://doi.org/10.3991/ijet.v8i2.2514
[35] Drigas, A., & Ioannidou, R. (2012). Artificial intelligence in special education: a decade
review. International Journal of Engineering Education, 28, 1366-1372.
https://doi.org/10.1007/978-3-642-35879-1_46
[36] Drigas, A. & Kokkalia, G. (2016). Mobile Learning for Special Preschool Education.
International Journal of Interactive Mobile Technologies (iJIM), 10(1), 60–67.
https://doi.org/10.3991/ijim.v10i1.5288
[37] Drigas, A., Kokkalia, G. & Lytras, M.D. (2015). ICT and collaborative co-learning in
preschool children who face memory difficulties. Computers in Human Behavior, 51,
pp. 645–651. DOI:10.1016/j.chb.2015.01.019
[38] Drigas, A., & Papanastasiou, G. (2014). Interactive White Boards in Preschool and Primary
Education. International Journal of Online and Biomedical Engineering (iJOE), 10(4),
46–51. https://doi.org/10.3991/ijoe.v10i4.3754
[39] Drigas, A.S., & Pappas, M.A. (2017). The Consciousness-Intelligence-Knowledge
Pyramid: An 8x8 Layer Model. International Journal of Recent Contributions from
Engineering Science & IT (iJES), 5(3), 14-25. https://doi.org/10.3991/ijes.v5i3.7680
[40] Galitskaya, V., & Drigas, A. (2019). ICTs and Geometry. International Journal of
Engineering Pedagogy (iJEP), 9(5), pp. 103–111.
https://doi.org/10.3991/ijep.v9i5.11241
[41] García, L.E., Nussbaum, M., & Preiss, D.D. (2011). Is the use of information and
communication technology related to performance in working memory tasks?
Evidence from seventh-grade students. Comput. Educ., 57, 2068-2076.
https://doi.org/10.1016/j.compedu.2011.05.009
[42] Gathercole, S.E, Pickering, S.J, Ambridge, B, & Wearing, H.(2004). The structure of
working memory from 4 to 15 years of age. Developmental Psychology, 40(2), 177‐
190. https://doi.org/10.1037/0012-1649.40.2.177
[43] Gathercole, S.E & Alloway, T.P. (2007). Κατανοώντας την εργαζόμενη μνήμη: Ένας
οδηγός για τη σχολική τάξη (Ε. Μασούρα, επιμ. και μετ.). Αθήνα: Μοτίβο Εκδοτική
Α.Ε.
[44] Gathercole, S.E., Lamont, E. & Alloway, T.P. (2006). Working memory in the classroom.
In S. Pickering (Ed.) Working memory and education. London: Academic Press.
[45] Giofrè, D., Donolato, E., & Mammarella, I.C. (2018). Verbal and visuospatial WM &
academic achievement. Trends in Neuroscience and Education, 12, 1–6.
https://doi.org/10.1016/j.tine.2018.07.001
[46] Goldstein, B.E. (2011). Cognitive Psychology: Connecting Mind, Research, and Everyday
Experience, Third Edition. Wadsworth: Cengage Learning.
[47] Guiney, H. & Machado, L. (2013). Benefits of regular aerobic exercise for executive
functioning in healthy populations. Psychonomic bulletin & review, v. 20, n. 1, p. 73–
86. https://doi.org/10.3758/s13423-012-0345-4
209
Technium Social Sciences Journal
Vol. 30, 200-213, April, 2022
ISSN: 2668-7798
www.techniumscience.com
[48] Haapala, E.A. (2012). Physical activity, academic performance and cognition in children
and adolescents. A systematic review. Baltic Journal of Health and Physical Activity,
4, 53-61. https://doi.org/10.2478/V10131-012-0007-Y
[49] Haverkamp, B.F., Wiersma, R., Vertessen, K., Van Ewijk, H., Oosterlaan, J., & Hartman,
E. (2020). Effects of physical activity interventions on cognitive outcomes and
academic performance in adolescents and young adults: A meta-analysis. Journal of
sports sciences, 38(23), 2637–2660. https://doi.org/10.1080/02640414.2020.1794763
[50] Himmelmeier, R.M., Nouchi, R., Saito, T., Burin, D., Wiltfang, J., & Kawashima, R.
(2019). Study Protocol: Does an Acute Intervention of High-Intensity Physical
Exercise Followed by a Brain Training Video Game Have Immediate Effects on Brain
Activity of Older People During Stroop Task in fMRI?-A Randomized Controlled
Trial With Crossover Design. Frontiers in aging neuroscience, 11, 260.
https://doi.org/10.3389/fnagi.2019.00260
[51] Holmes, J. & Adams, J.W. (2006). Working memory and children’s mathematical skills:
Implications for mathematical development and mathematics curricula. Educational
Psychology, 26(3), 339-366. https://doi.org/10.1080/01443410500341056
[52] Isbell, E., Fukuda, K., Neville, H.J., & Vogel, E.K. (2015). Visual working memory
continues to develop through adolescence. Frontiers in Psychology, 6(696), 1-10.
https://doi.org/10.3389/fpsyg.2015.00696
[53] Jetté, M., Sidney, K., & Blümchen, G. (1990). Metabolic equivalents (METS) in exercise
testing, exercise prescription, and evaluation of functional capacity. Clinical
cardiology, 13(8), 555–565. https://doi.org/10.1002/clc.4960130809
[54] Karabatzaki, Z., Stathopoulou, A., Kokkalia, G., Dimitriou, E., Loukeri, P.I., Economou,
A., & Drigas, A. (2018). Mobile Application Tools for Students in Secondary
Education. An Evaluation Study. International Journal of Interactive Mobile
Technologies (iJIM), 12(2), 142–161. https://doi.org/10.3991/ijim.v12i2.8158
[55] Karyotaki, M., & Drigas, A. (2015). Online and other ICT Applications for Cognitive
Training and Assessment. International Journal of Online and Biomedical
Engineering (iJOE), 11(2), 36–42. https://doi.org/10.3991/ijoe.v11i2.4360
[56] Kokkalia, G., Drigas, A., Economou, A., Roussos, P., & Choli, S. (2017). The Use of
Serious Games in Preschool Education. International Journal of Emerging
Technologies in Learning (iJET), 12(11), 15–27.
https://doi.org/10.3991/ijet.v12i11.6991
[57] Koutsandréou, F.; Wegner, M.; Niemann, C.; Budde, H. Effects of motor versus
cardiovascular exercise training on children’s working memory. Medicine and Science
in Sports and Exercise, v. 48, n. 6, p. 1144–1152, 2016.
https://doi.org/10.1249/MSS.0000000000000869
[58] Lahti, A. (2019). Physical Activity in Childhood and Adolescence. Lund University:
Faculty of Medicine. Available in http://
www.activelivingresearch.org/files/Active_Ed.pdf. Accessed November 19, 2021.
[59] Lambourne, K. (2006). The relationship between working memory capacity and physical
activity rates in young adults. Journal of sports science & medicine, 5(1), 149–153.
[60] Lanham, M. (2017). Augmented Reality Game Development: Create your own augmented
reality games from scratch with Unity 5. Packt Publishing,
[61] Lind, R. R.; Geertsen, S. S.; Ørntoft, C.; Madsen, M.; Larsen, M. N.; Dvorak, J.; Ritz, C.;
Krustrup, P. Improved cognitive performance in preadolescent Danish children after
the school-based physical activity programme “FIFA 11 for Health” for Europe–A
210
Technium Social Sciences Journal
Vol. 30, 200-213, April, 2022
ISSN: 2668-7798
www.techniumscience.com
cluster randomised controlled trial. European Journal of Sport Science, v. 18, n. 1, p.
130-139, 2018. https://doi.org/10.1080/17461391.2017.1394369
[62] Loosli, S.V., Buschkuehl, M., Perrig, W.J., & Jaeggi, S.M. (2012). Working memory
training improves reading processes in typically developing children. Child
Neuropsychology, 18, 62 - 78. https://doi.org/10.1080/09297049.2011.575772
[63] López-Vicente, M., Garcia-Aymerich, J., Torrent-Pallicer, J., Forns, J., Ibarluzea, J.,
Lertxundi, N., González, L., Valera-Gran, D., Torrent, M., Dadvand, P.,Vrijheid, M.,
& Sunyer, J. (2017). Are Early Physical Activity and Sedentary Behaviors Related to
Working Memory at 7 and 14 Years of Age? The Journal of pediatrics, 188, 35–41.e1.
https://doi.org/10.1016/j.jpeds.2017.05.079
[64] Luciana, M., Conklin, H.M., Hooper, C.J., & Yarger, R.S. (2005). The development of
nonverbal working memory and executive control processes in adolescents. Child
development, 76(3), 697–712. https://doi.org/10.1111/j.1467-8624.2005.00872.x
[65] Ludyga, S., Gerber, M., Brand, S., Pühse, U., & Colledge, F. (2018). Effects of Aerobic
Exercise on Cognitive Performance Among Young Adults in a Higher Education
Setting. Research quarterly for exercise and sport, 89(2), 164–172.
https://doi.org/10.1080/02701367.2018.1438575
[66] Μασούρα, Ε. (2010). Εργαζόμενη μνήμη: μπορεί να εργαστεί ακόμα πιο σκληρά; Στο Γ.
Βογινδρούκας, Α. Οκαλίδου και Σ. Σταυρακάκη (Επιμ.), Αναπτυξιακές γλωσσικές
διαταραχές: Από τη βασική έρευνα στην κλινική πράξη (σσ. 321-344). Θεσσαλονίκη:
Επίκεντρο.
[67] Mitsea, E., & Drigas, A. (2019). A Journey into the Metacognitive Learning Strategies.
International Journal of Online and Biomedical Engineering (iJOE), 15(14), 4–20.
https://doi.org/10.3991/ijoe.v15i14.11379
[68] Mousavi, S., Radmehr, F., & Alamolhodaei, H. (2012). The role of mathematical
homework and prior knowledge on the relationship between students’ mathematical
performance, cognitive style and working memory capacity. Electronic Journal of
Research in Educational Psychology, 10(3), 1223–1248.
https://doi.org/10.25115/ejrep.v10i28.1532
[69] Moyle, K. (2010). Building innovation: Learning with technologies. In C. Glascodine
(Ed.), Australian education review, 56. Camberwell, VIC: Australian Council for
Educational Research.
[70] Ni, M.Y., Hui, R., Li, T.K., Tam, A., Choy, L., Ma, K., Cheung, F., & Leung, G.M. (2019).
Augmented Reality Games as a New Class of Physical Activity Interventions? The
Impact of Pokémon Go Use and Gaming Intensity on Physical Activity. Games for
health journal, 8(1), 1–6. https://doi.org/10.1089/g4h.2017.0181
[71] Nicolielo-Carrilho, A.P., Crenitte, P., Lopes-Herrera, S.A., & Hage, S. (2018).
Relationship between phonological working memory, metacognitive skills and reading
comprehension in children with learning disabilities. Journal of applied oral science :
revista FOB, 26, e20170414. https://doi.org/10.1590/1678-7757-2017-0414
[72] Pappas, M., Drigas, A., Malli, E., & Kalpidi, V. (2018). Enhanced Assessment Technology
and Neurocognitive Aspects of Specific Learning Disorder with Impairment in
Mathematics. International Journal of Engineering Pedagogy, 8(1), 4-15.
https://doi.org/10.3991/ ijep.v8i1.7370
[73] Player-Koro, C. (2012). Factors Influencing Teachers’ Use of ICT in Education. Education
Inquiry, 3(1), 93-108. https://doi.org/10.3402/edui.v3i1.22015
211
Technium Social Sciences Journal
Vol. 30, 200-213, April, 2022
ISSN: 2668-7798
www.techniumscience.com
[74] Rosas, R., Nussbaum, M., Cumsille, P., Marianov, V., Correa, M., Flores, P., Lagos, F.,
Lopez, X., López, V., Rodríguez, P., & Salinas, M. (2003). Beyond Nintendo: design
and assessment of educational video games for first and second grade students.
Computers & Education, 40(1), 71–94. https://doi.org/10.1016/S0360-
1315(02)00099-4
[75] Ruiz-Ariza, A., Casuso, R.A., Suarez-Manzano, S., Martínez-López, E.J. (2018). Effect
of augmented reality game Pokémon GO on cognitive performance and emotional
intelligence in adolescent young. Computers & Education, 116, 49-63.
https://doi.org/10.1016/j.compedu.2017.09.002
[76] Sahoo, K., Sahoo, B., Choudhury, A.K., Sofi, N.Y., Kumar, R., & Bhadoria, A.S. (2015).
Childhood obesity: causes and consequences. Journal of family medicine and primary
care, 4(2), 187–192. https://doi.org/10.4103/2249-4863.154628
[77] Shipstead, Z., Hicks, K.L. & Engle, R.W. (2012). Cogmed working memory training: Does
the evidence support the claims? Journal of Applied Research in Memory and
Cognition, 1(3), pp. 185–193. DOI:10.1016/j.jarmac.2012.06.003
[78] Shuja, M.A (2009). Connecting people with disabilities: ICT opportunities for all. Munich
Personal RePEc Arch, 1-20. https://mpra.ub.uni-muenchen.de/id/eprint/17204
[79] Söderqvist, S. & Bergman Nutley, S. (2015). Working Memory Training is Associated
with Long Term Attainments in Math and Reading. Frontiers in Psychology, 6(1711).
https://doi.org/10.3389/fpsyg.2015.01711
[80] Swanson, H., & Beebe-Frankenberger, M. (2004). The relationship between working
memory and mathematical problem solving in children at risk and not at risk for serious
math difficulties. Journal of Educational Psychology, 96, 471-491.
https://doi.org/10.1037/0022-0663.96.3.471
[81] Timperley, H.,Kaser, L., & Halbert, J. (2014). A Framework for Transforming Learning
in Schools: Innovation and the Spiral of Inquiry: Seminar Series 234. Melbourne
Victoria, Australia: Centre for Strategic Education.
[82] Titilayo, O. (2016). Cognitive processes paper. Dept of Counseling and human
development, University of Ibadan. Retrieved February 24, 2020, from
https://www.academia.edu/30328244/COGNITIVE_PROCESSES_PAPER_submit.d
ocx
[83] Tytler, R., Symington, D., & Smith, C.A. (2011). Curriculum Innovation Framework for
Science, Technology and Mathematics Education. Research in Science Education, 41,
19–38, 2011. https://doi.org/10.1007/s11165-009-9144-y
[84] Williams, R.A., Cooper, S.B., Dring, K.J., Hatch, L., Morris, J.G., Sunderland, C., &
Nevill, M.E. (2020). Effect of football activity and physical fitness on information
processing, inhibitory control and working memory in adolescents. BMC Public
Health, 20(1). https://doi.org/10.1186/s12889-020-09484-w
[85] Wilson, K. M., & Swanson, L. (2001). Are mathematics disabilities due to a domain-
general or a domain-specific working memory deficit? Journal of Learning
Disabilities, 34, 237-248. https://dx.doi.org/10.1177/002221940103400304
[86] World Health Organization. Physical activity fact sheet. 2021. Accessed November 30,
2021. https://apps.who.int/iris/bitstream/handle/10665/346252/WHO-HEP-HPR-
RUN-2021.2-eng.pdf?sequence=1
[87] World Health Organization (2020). Physical activity factsheet. Accessed November 19,
2021. http://www.who.int/mediacentre/factsheets/fs385/en/
212
Technium Social Sciences Journal
Vol. 30, 200-213, April, 2022
ISSN: 2668-7798
www.techniumscience.com
[88] Zyda, M. (2005). From visual simulation to virtual reality to games. IEEE Computer, 38(9),
25-32. https://doi.org/10.1109/mc.2005.297
[89] Drigas, A., & Karyotaki, M. (2014). Learning Tools and Applications for Cognitive
Improvement. International Journal of Engineering Pedagogy (iJEP), 4(3), 71-77.
https://doi.org/10.3991/ijep.v4i3.3665
[90] Kefalis C., Drigas A. (2019). Web Based and Online Applications in STEM Education.
International Journal of Engineering Pedagogy (iJEP), 9(4), pp. 76-85. https://doi.org/
10.3991/ijep.v9i4.10691
[91] Drigas, A. S., & Ioannidou, R. E. (2013). A review on artificial intelligence in special
education. Communications in Computer and Information
Science. https://doi.org/10.1007/978-3-642-35879-1_46.
[92] Drigas, A. & Vrettaros, J. (2004). "An Intelligent Tool for Building e-Learning Contend-
Material Using Natural Language in Digital Libraries," WSEAS Trans. Inf. Sci. Appl.,
5(1), 1197–1205.
[93] Chara Papoutsi, Athanasios S. Drigas, Charalabos Skianis. (2018). Mobile Applications to
Improve Emotional Intelligence in Autism – A Review. International Journal of
Interactive Mobile Technologies. 12(6): 47-61.
https://doi.org/10.3991/ijim.v12i6.9073
[94] Drigas, A. S., Argyri, K., & Vrettaros, J. (2009). Decade review (1999-2009): Artificial
intelligence techniques in student modeling. Communications in Computer and
Information Science, 49, 552–556.
[95] Vrettaros, J., Tagoulis, A., Giannopoulou, N., & Drigas, A. (2009). An empirical study on
the use of Web 2.0 by Greek adult instructors in educational procedures. World
Summit on Knowledge System (WSKS), 49, 164-170. http://dx.doi.org/10.1007/978-
3-642-04757-2_18
[96] Drigas, A., et al., 2013. Web 2.0 learning strategies for disabled students. Journal of applied
mathematics and bioinformatics, 3 (4), 125–140. Available from: https://pdfs.
semanticscholar.org/e7a5/9623c4e56055c31744a1e1bcfb 84053e623b.pdf
[97] Pappas M, Drigas A. 2019 Computerized Training for Neuroplasticity and Cognitive
Improvement. International Journal of Engineering Pedagogy. (4):50-62
213
Technium Social Sciences Journal
Vol. 30, 200-213, April, 2022
ISSN: 2668-7798
www.techniumscience.com