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Young children’s conceptions of computers, code, and the Internet

Mertala, P. (accepted). Young childrens conceptions of computers, code, and the Internet.
International Journal of Child-Computer interaction
1. Introduction
Today, children are growing up surrounded by versatile digital technologies [1,2], and at an early age,
children start to form conceptions of how these technologies work and their basic capabilities [3]. Therefore,
teaching children about digital technologies should consider children’s initial mental models of the
technologies [4], as well as the role the technologies play in children’s everyday experiences [5].
This paper explores five- to seven-year-old children’s concepts of computers, code, and the Internet. The
rationale behind focusing on these concepts is grounded on the changed nature of children’s digital life-
worlds and recent curricular reforms. Computers that once were clumsy stand-alone machines have
transformed into ubiquitous technologies, such as mobile devices (i.e., tablets and smartphones) and
computer-integrated household devices (i.e., washing machines, refrigerators, and toys). Thus, it is important
to study whether and how this development is reflected in children’s concepts of computers. Additionally,
whereas once games and movies were bought or rented from specialty stores, today they are downloaded,
played, and watched online [1,2]. In other words, as the Internet is one of the meaningful life-worlds of 21st-
century children, it is important to deepen our understanding of how they conceptualize this environment.
Last, the “learning to code” agenda was recently introduced in school curricula across Western contexts
[5,6]. The pedagogics of elementary programming for young children are in the emerging stage [5,7], and to
develop appropriate and research-based methods, up-to-date knowledge of children’s initial concepts of code
and programming is needed.
These three concepts should be examined within the same study because thus far, children’s conceptions of
these concepts have been studied separately. As children’s concepts of computers, code, and the Internet
appear to be deeply intertwined, this division is artificial. This viewpoint is well illustrated when papers by
Edwards et al. [8], Robertson et al. [9], and Sheehan [10] are compared. In all these papers, children
expressed that they watched videos and played games when they used computers. However, in Edwards et
al.’s [8] study, these activities were categorized as conceptions of the Internet, whereas Robertson et al. [9]
classified these activities as children’s conceptions of computers, and Sheehan [10] classified these activities
as children’s conceptions of computer programs. It appears that the research objective not the content of
children’s answers—determines how the information is interpreted and categorized. More holistic
approachessuch as the one used in this studyare needed to better understand children’s conceptions.
1.1. Research questions
The research questions that guided the research process are as follows:
What conceptions do five to seven-year-old children have about
a) computers,
b) code,
c) and the Internet?
How are these conceptions related to each other?
What are the foundations of these conceptions?
This study begins by summarizing the current state of research on children’s conceptions of computers, code,
and the Internet. Then, the research questions, data, and analysis methods are introduced. Then, the findings
are provided. The paper concludes by discussing the implications of the study’s findings for pedagogical
practices and future research.
2. Background
2.1. Children’s conceptual development
One of the most frequently applied frameworks for children’s conceptual development is Vygotsky’s [11]
work on children’s everyday concepts and scientific concepts. Everyday concepts refer to those that derive
from children’s daily practices and tool use [8,12]. When it comes to scientific concepts, two different
interpretations can be found from previous research: Some scholars have demarcated scientific concepts as
those that children are taught in school [12] whereas others have defined scientific concepts as children’s
rationales for how and why things work [8]. This study follows the latter approach which is commonly used
in research on children’s concepts of digital technologies [3,8,13,14]. In this interpretation, everyday
concepts and scientific concepts are not treated as mutually exclusive categories but are understood to
interact and work together for development [11,15]. In the chosen interpretation, a concept categorized as
“scientific” does not have to be accurate. Put differently, instead of pinpointing the level of conceptual
accuracy, the term “scientific” refers to a type of a concept that describes and explains the functional features
of the phenomenon under discussion.
To form a scientific concept (accurate or not), children must identify cause-and-effect relationships,
formulate hypotheses, make generalizations, and draw interpretations from their observations and
experiences. All of these processes can be defined as higher-order thinking skills [16]. Thus, although
children’s scientific concepts may appear to us adults as simple and inconsistent abstractions of everyday
experiences [17], deeming these concepts “naïve” or as evidence of “minimal” understanding [14] is
disrespectful. Instead, these concepts should be treated as a valuable source of information regarding how
children perceive and analyze their life-world.
Respecting children’s initial scientific concepts does not mean that it is not important or necessary to teach
children about accurate scientific concepts. This understanding is necessary for children to develop mature
concepts in which everyday concepts and (accurate) scientific concepts merge and for children to understand
how scientific perspectives explain everyday concepts [10,12]. The Internet can be used as an example: The
everyday concept of the Internet refers to the online activities that children carry out and observe, whereas
the (accurate) scientific concept of the Internet refers to the understanding that the Internet is a complex
technical and social system and a network of digital technologies that provides various services and socially
mediated practices through the exchange of data [8,14]. Children who possess a mature concept of the
Internet “understand that their practices and tool use when engaged with the internet involves a network of
technologies sharing data designed and used by people” [8, p. 53].
One of Vygotsky’s main arguments was that children’s concepts do not develop independently but through
social interaction [11,12]. This argument also applies to learning about digital technologies. Although
statements about children being “native speakers of the digital language of computers, video games and the
Internet” [18, p. 2] have been made, a body of evidence suggests that young children’s learning about digital
technologies is derived from intentional or unintentional tutoring from parents and siblings [1,8,19].
Sometimes, learning from others can take place accidentally, but children also try to actively synthesize the
information they receive from adults and from their everyday experiences into coherent mental models [17].
2.2. Children’s conceptions of computers, code, and the Internet: A literature review
The earliest attempts to understand children’s conceptions of computers can be traced back to the 1960s [20]
and the first studies that explored children’s understanding of the Internet date back to the early 2000s [21].
Since then, both themes have been studied regularly [e.g. 3,14, 22]. This section provides an overview of the
previous research the basic information of which is comprised in Table 1 and Table 2. As can be seen from
them, all but one computer-related study is at least 10 years old [9], and Internet-related studies, in turn, have
mainly concentrated on older children [8,23].
Table 1. Studies on children’s concepts of computers (including programming)
Children’s age
Reference no
Seventh graders (exact ages not provided)
Mawby et al.
Hyson & Morris
van Duuren & Scaife
van Duuren et al.
Hammond & Rogers
Bernstein & Crowley
Levy & Mioduser
Robertson et al.
Table 2. Studies on children’s concepts of the Internet
Reference no:
Dodge et al.
Diethelm et al.
Kodama et al.
Oliemat et al.
Edwards et al.
Murray & Buchanan
In a recent review, Rücker and Pinkwart [3]
identified the following types of scientific rationales from
children’s conceptions of computers: 1) Computers are intelligent, 2) computers are mechanical, 3)
computers are omniscient databases, and 4) computers are programmable. Children also characterize
computers according to what the children do with them, meaning that children understand computers as
devices that can be used to play games, retrieve information, and watch videos [9], which in this study are
understood as everyday concepts.
The conception of computers as intelligent machines refers to an animistic understanding in which
computers are seen as agentive and conscious artifacts that engage in independent thinking. Such concepts
are found in the oldest and the most recent research papers and expressed by children of various ages [9,20].
According to Turkle [33], such concepts are formed when psychological reasoning dominates physical
reasoning: The more complex and opaque the technology, the more likely children rely on psychological
reasoning when they explain the technology’s functional capabilities [33,35], and the time spent with
computers strengthens children’s psychological reasoning if no alternative explanations are provided [26].
Nevertheless, contrasting findings have been provided by previous research. The most prominent example is
Bernstein and Crowley’s [34] study in which four- to seven-year-old children ranked computers low in
intelligence and psychological characteristics. This discrepancy may have been caused by methodological
differences, as, unlike in other studies, Bernstein and Crowley [34] asked children to compare computers
with people who, in turn, were ranked high in intelligence and psychological characteristics. Additionally,
the questions asked of the children may have had influenced their answers. For example, Robertson et al. [9]
asked children whether they think that computers want to do things and think like humans. As noted by
There was also a fifth category in Rücker and Pinkwart’s [3] categorization: Computers are wired networks. However,
in this paper, this category is included in the computers are mechanical category due to the notable overlap of the
Vosniadou and Brewe [17], children can read such questions as prompts of the implicit demands of the
Children also reason that computers are omniscient databases that have all the answers to everything stored
in their memory [4,28,39]. Depending on the study, such a concept is more or less common with the
youngest children. Mawby et al. [24, p. 30] described how children “spoke as if computers know specific
facts, such as the product of 23 times 45, rather than having general algorithms that generate specific answers
to specific questions,” a feature that was most prominent among the youngest participating children (eight-
year-olds). In contrast, none of the five-year-old participants in a study by vanDuuren et al. [29] believed that
computers have the answers typed in. Given the methodological differences between the studies, it is
impossible to point out exact reasons for these contrasting findings.
Some children consider computers to be mechanical, as the children equate computers with other mechanical
devices, such as refrigerators [9], or make clear distinctions between computers and things the children
consider biological, namely, people and animals [34]. In both cases, the children (four- to seven-years-old)
relied on categorization- and classification-based reasoning by sorting based on similarities (computers are
like refrigerators) or differences (computers are not like people). In addition, young children conceptualize
computers as wired networks [9,24,31]. These conceptions suggest that the functions and nature of
computers areto a notable extentdescribed and analyzed by relying on their physical features. In
addition to wires, children name electricity, batteries, plugs, monitors, and keyboards as essential features of
a functional computer [9,10,13, 25,26]. One explanation for the prevalence of these components is that they
are either visible (i.e. wires, keyboard, and plugs) or familiar to children from other devices (i.e., batteries
and electricity) [3].
Computers are also conceptualized as programmable machines that receive commands from humans
[9,28,33]. Even young children are usually able to name examples of their everyday use of computer
programs, including playing games, using a word processor, and using drawing software [10,28]. However,
the scientific conception of computer programming requires a conception of computers as something that can
be programmed [3]. It appears that children, especially young children, do not have this conception. For
example, almost half of the six- to 10-year-old children in Sheehan’s [10] study were not able to answer the
question, “what are computer programs?” Similarly, none of the five- and eight-year-old participants in van
Duuren et al.’s [29] study were able to explain what programming is. Instead, they either claimed not to
know or described what their favorite software applications were. Although the conception of computers as
programmable machineswhich can be considered the most complex and accurate scientific conceptionis
most common among older children, it appears that children rarely come up with the idea of programming
by themselves but have been told about it or have engaged in programming-related activities
Research on young children’s technology use suggests that although children use Internet-based services
(i.e., play online games and watch programs and movies from on-demand services) regularly, they have little
to no understanding of the scientific concepts of the Internet or what it means to be “online” [1,38]. The few
scientificbut not necessarily accurateconcepts that have been identified by previous literature are the
Internet as a big central computer, the Internet as a network of two or more computers, the Internet as a
network of computer networks, and the Internet as a giant search engine [4,8,40]. Such concepts are typically
expressed by older children (10- to 16-year-olds).
Younger children, in turn, use slightly different rationales. Four- and five-year-old children in Edwards et
al.’s [8] study conceptualized the Internet by referring to its mechanical features. They, for example, noted
that electricity or wires are required for the Internet to function properly [8]. As discussed, the prominence of
such features relates to their visibility (wires) and general familiarity (electricity) [3]. Another finding by
Edwards et al. [8] was that children often possess tool-based concepts in which the Internet is understood as
a feature of the device they use for [see also 4,23,37]. Last, some children (five- to eight-year-olds) in
Oliemat et al.’s [23] study conceptualized the Internet as a connection that is needed to download games and
stream videos, to give two examples.
To conclude, previous research has identified that children have various concepts of computers, code, and
the Internet. The different concepts are not mutually exclusive, and children can possess conceptual blends
that are combinations of two or more concepts [3]a phenomenon familiar to non-technology-related
concept research as well [17]. In addition, there are no unambiguous explanations behind how these
conceptual categories emerge. Depending on the study, factors such as historical context [3], quantity of
computer use [26], quality of computer experiences [28], and the age of the children [29] have been named
as possible factors leading to the development of different concepts. Furthermore, these factors appear to be
more interlinked than independent. For example, Yan’s [14] study results suggest that the quantity and
quality of children’s online experiences are related to children’s age: The younger the children, the more
filtered and regulated their Internet use [41]. This may explain why younger children have a narrower
understanding of the Internet than older children [37]. Synthesis of previous research also suggests that data
collection methods, for instance, the questions asked of children, play a role in shaping children’s concepts.
3. Method
3.1. Participants, data, and data collection
The data consists of drawings produced by and interviews conducted with 65 five to seven-year-old children
from five preschool groups from northern Finland. Table 3 presents basic information regarding the age and
gender distribution of the participating children.
Table 3. The participating children
Total %
12 %
74 %
14 %
Total %
55 %
45 %
The teachers of the preschool groups were attending to an in-service training coursein which I acted as a
trainerand volunteered to collect the data as part of their course assignments. Having teachers to
implement the data collection instead of an outsider-researcher was believed to provide the children a safe
and familiar environment to express their views [42]. Written consent to participate in the study was
requested from the municipal education departments as well as from the children’s guardians. Moreover, oral
consent to participate in the study was requested from the children. From an ethical point of view, it was
crucial that the children were informed of the objectives of the research project and knew who was carrying
out the study [43,44]. As I was not able to visit all the groups in person, I sent every group a personal video
greeting in which I introduced myself and explained why I was interested in hearing their thoughts. I also
emphasized that if the children agreed to give their drawings as data, then the original drawings would be
returned to them right after I made digital copies of those drawings. Later, I sent another video to the
children in which I expressed my gratitude for having the opportunity to study their drawings and interviews.
The data collection was conducted from January to February 2017.
Children’s drawings are a useable tool for knowing what children are telling us and gives us adults a chance
to take a glance to their thinking and understanding of the world [45]. Drawing can be described as a child-
centered data collection method, as it is an enjoyable and beneficial activity for most children [46]. Children
are often interviewed based on what they have drawn. The strength of combining visual and verbal narration
is that by using the drawingor some other visual mediumas a mediating tool, different parties can
understand each other’s thinking by creating a transitional space in which their thoughts and ideas can be
externalized into concrete form [47]. Drawings and interviews are a commonly used form of data in research
regarding children’s understandings of technologies [10,31,48].
In the context of the present paper, a procedure known as the draw and tell conversation method (DTC) [49]
was applied to explore the children’s conceptions. In DTC, children are first given a specific art directive that
reflects the study purpose. When the drawing is ready, a conversation facilitated by an interviewer is carried
out. In this case, the directive was the following:
Your task is to draw how computers work. What are the different parts that computers
contain? What is inside the computer? You can also write if you want.
More questions about computers, code, and the Internet were included in the interview sheet. To obtain rich
data [50], the children’s conceptions were explored using various trigger questions summarized in Table 4.
The questions were designed to be as open and non-descriptive as possible because the way questions are
asked influence children’s explanations [9,17]. For example, in Robertson et al.’s [9] study many children
stated that computers are programmed with “computer chips,” a concept they had been introduced to in the
previous section of the interview. The children’s answers were written down on the drawings and on an
interview sheet [42,45].
Table 4. Interview questions
What are computers like? How do computers work? What can be done using computers? What have you done
using computers? How do you know these things?
The Internet
What is the Internet? How does the Internet work? How can you use the Internet? What can be done using the
Internet? What have you done using the Internet? How do you know these things?
What do you understand about code? What do you understand about coding? What do you understand about
programs? What do you understand about programming?
3.2 Analysis
The analysis process was guided by an abductive approach, in which the researcher moves between and
combines inductive reasoning and existing theoretical models to develop new ways of theorizing the
phenomenon under investigation [51,52]. In practice, the data was analyzed via monotype mixed analysis
(MMA) [53]. In MMA, the databe it qualitative or quantitativeis analyzed by using both qualitative and
quantitative methods. The use of MMA requires that qualitative data is altered into a form that can be
analyzed statistically and that quantitative data is transformed into a form that can be analyzed qualitatively
[41]. This mixing can be characterized as a combination of measurement and interpretation [54] that allows
rich and comprehensive views of the phenomena under investigation to be constructed. In the present study,
transforming the data meant quantifying the occurrence of how often different types of features related to
computers were drawn and mentioned, and these frequency counts were then converted to percentages to
calculate the frequency effect size [55]. However, a high frequency was not a requisite for certain
conceptions or themes to be meaningful, as from an interpretative point of view, what is not found in the data
is as important as what is found.
Interpretative analysis was carried out by reading the databoth the drawings and interviewsby applying
the method of constant comparison [56]. The comparisons were made in three levels: 1) within the data from
the individual participants; 2) between the data from different participants, and 3) between the data and
theory. These levels were more overlapping than sequential by nature. Comparison within the data from the
individual participants meansfor examplethat the children’s explanations of what could be done using
computers were compared with their explanations of what could be done using the Internet. Put differently, if
a child commented that a computer could be used to buy things, it was investigated whether she or he
understood that this particular activity required an Internet connection (see Section 4.1.3 for further
discussion). Comparison between the data from different participants refers to how interpretations made
from the data from an individual child were compared with the data from others to identify possible patterns
or “special cases.” One example is the notion that children who had encountered problems with Internet
connection appeared to have a more accurate scientific concept of the Internet than others (see Section 4.2
for further discussion). Comparison with the data and theory refers to how all data-driven interpretations
were compared with previous research on children’s conceptions of digital technologies to identify
similarities and differences.
4. Findings and discussion
In this section, the findings of the study are provided. The section is divided into two subsections: The first
subsection (4.1.) focuses on the question of what the children thought computers, code, and the Internet were
(i.e. the children’s scientific concepts of computers, code, and the Internet). The second subsection (4.2)
examines children’s conceptions of what can be done using computers and the Internet (i.e. the children’s
everyday concepts of computers, code, and the Internet). The findings related to the foundations of children’s
concepts and knowledge are discussed within these two sections.
4.1 Children’s conceptions of what computers, code, and the Internet are
4.1.1 Computers
The term “computer” typically referred to either a desktop computer or a laptop computer for the children:
46% (n=30) of the children drew or mentioned a laptop, and 40% (n=26) of the children drew or mentioned a
desktop. In nine cases, it was not possible to identify the type of the computer. Only one child drew a tablet
computer, and 25% (n=16) of the children named tablets as a distinctive form of technology when asked how
one could use the device to connect to the Internet. None of the children expressed that computers could be
found in other forms of technology, such as cars, washing machines, or toys. Unlike in earlier studies,
conceptions of computers being intelligent machines [9] or omniscient databases [4,24,28,39] were rare and
rather indicative by nature: 8% (n=5) of the children explained that computers could be used to seek
information with no references to using the Internet, which suggested that these children believed that
information was located inside the computer (see Section 4.2 for further discussion).
Only two drawings contained information about how computers might look inside. In both drawings, the
child had drawn a square shape with wires inside it and referred to the drawing as the interior of the
computer (see Fig. 1). However, using the drawings and interviews, it was impossible to determine which
part of the computer the drawing referred to.
Fig. 1. Inside the computer (Boy#4 6y7m)
Two-thirds of the children included wires in their drawings [see also 9,31]. Other prominent features were
monitors and keyboards, which were found in 88% and 75% of the drawings, respectively. In addition, more
than half of the children conceptualized computers as electrical [see also 9,10,26]. Most of the children drew
the computer from the user’s perspective, which is a common feature in children’s drawings of digital
devices [10,48]. This explainsat least partiallywhy the drawings included elements that resembled
monitors and controllers (keyboards and mice). One explanation for the prominence of electricity and wires
in the drawings is that they are both vital for the computer to work properly: If the power cord is detached,
then the computer will not start, and if the wire of the mouse or the keyboard is loose, then the user cannot
execute desired functions. This explanation is piquantly captured in the following extracts:
Computer works when you plug the chord into the wall. Writing transfers on the screen
because there are wires between them. A wire goes from the mouse into the computer
(Boy#26 7y0m).
[computers] are like electrical, and they need to have something to write on. I mean, how else
could those pictures come into it? It needs cords. Otherwise, they can turn off entirely.
(Boy#30 6y7m)
Table 5 summarizes the distribution of parts and other mechanical features included in the children’s
Table 5. Distribution of parts and other mechanical features
(3 %)
While 40% of the children conceptualized a computer as a desktop computer and drew detailed pictures, only
two of the children included a central processing unit (CPU)
in their drawings. Such a drawing is presented
in Fig. 2, whereas Fig. 3 is a drawing of a desktop computer without a CPU.
Fig. 2. Desktop computer with a CPU (Boy#22 6y4m).
A CPU can refer to either the CPU chip or the computer tower inside of which the CPU chip is located. In this paper, a
CPU refers to the latter.
Fig. 3. Desktop computer without a CPU (Girl#51 6y6m).
There is no single, unambiguous explanation for the missing CPUs. However, Hammond and Rogers [13]
found that children sometimes consider the monitor as the computer. This notion is supported by the present
study. One child, for example, called the foot of the display as the “thing that holds the computer up”
(Girl#20 7y0m), whereas another child referred to the foot of the display as the “bottom of the computer”
and explained: Computers are like that there is a black block and another one in it. In between them is the
screen. And then there is the holder under it so that it stays up (Boy#10 7v0m). When these narratives are
compared with the drawings produced by the other children (see Fig. 4), it appears that the “black blocks”
are the frames of the monitor and that the holder is the foot of the monitor.
Fig. 5. Monitor (Girl#25 6y2kk).
Again, there is no unequivocal explanation for what makes children believe that the monitor is the computer.
One possible explanation is that children often cannot see a computer’s CPU. In laptops, the CPU is hidden
under the keyboard and there are also “all-in-one” desktop computer models in which the monitor and the
CPU are integrated. Examples of such computers are Apple’s iMacs and Envy 27-b110no by Hewlett and
Packard. In traditional desktops, the CPU is located under the table or behind the monitor. Another possible
explanation is that children seldom operate the CPU. Some of the children commented that the power button
of the display is the one that turns on the computer (see Fig. 3), and some of the children said that the
computer turns on when the password is entered. Both examples suggest that when these children use
computers, the CPU is already running, and all the children have to do is to turn on the monitor and/or enter
the password.
4.1.2. Code
The meaning of the terms “coding” and “programming” were unfamiliar to the children, and 46% (n=30) of
the participating children could not provide an answer to questions of what programming and/or coding were
[see also 10,29]. In addition, most of the provided answers did not have much to do with computing. The
terms “code” and “coding” were most often connected to pin codes and passwords needed to log into a
computer or un-lock touchscreen devices. In the following extract, the child understands a code as a pattern
lock, which is a typical safety feature in tablet computers and mobile phones (see Appendix 1 for a reference
picture): “You need a code for opening the pad. I can’t open it because I don’t know the code. The code can
have, like, spots from which you have to draw the figure.” (Girl#47 6y7m.).
The words “program” and “programming”, in turn, were connected to watching programs, as one child stated
that “programming means that one watches some program” (Boy#5 6y7m). Moreover, the terms were
connected to reading manuals, as one child state that “programming can be also that somebody reads a
manual” (Girl#53 6y2m). In these cases, the children appeared to use conceptual similarities as the basis of
their reasoning, as in Finnish the terms programming (ohjelmointi), program (ohjelma), and manual (ohje)
are similar. Only 5% (n=3) of the children appeared to have some understanding that programming was
about giving commands.
I have played a game in which one has to program a wasp to find a flower. You have to move
it, for example, forward and to side. When you push the buttons is starts moving. (Boy#12
Programming means that you program something in the way you want. Like a robot. (Girl#6
When you push the buttons, the thing you program is programmed. Coding is perhaps
someone’s job. (Girl#17 6y1m)
All these examples, most prominently the first one, suggest that these children had played coding games
had played with programmable toys. In the first example, the game involving a programmable wasp is likely
either the web-based emulator
or mobile application
of a programmable floor robot called “BeeBot” (see
Appendix 2 for a reference picture). This notion is line with previous research that suggests that having some
scientific understanding of programming requires that children have had first or second-hand experience with
programming activities [10,26,28,30,32,33,35].
4.1.3. The Internet
When the children were asked about what the Internet was and how it worked, most of them provided
examples of what could be done using the Internet, which in this paper was categorized as everyday concepts
and discussed in Section 4.2. Nevertheless, the data included some conceptualizations of the functional
principles of the Internet. Some of the children used tool-based concepts [see also 8] and conceptualized the
Internet as something that is located inside the computer [see also 4,37,38]. As put by one child, the Internet
is inside the computer --- and you can get in there by pressing the icon” (Boy#10 7y0m).
The question of “how the Internet works” inspired some of the children to describe occasions when their
home Internet connection had not worked properly or what was required to connect to the Internet. These
descriptions revealed information about the children’s understandings of the Internet. The following extract
is an example of the first rationale: Sometimes it says that no Internet connection. Then you can’t go to
the Internet and you can’t play games or watch videos” (Girl#7 6y9mm). While the word “connection” was
frequently used in such descriptions, it did not refer to an understanding of the Internet as connected
networks [see also 4] butas illustrated in the previous quoteto an understanding that one has to be
Such games include Lightbolt, Kodable, and the Foos.
connected to the Internet to be able to conduct online activities [see also 23]. Experiences with a broken
network allowed the children to observe their parents attempts to recover the connection, which provided the
children with subtle information regarding how the Internet worked. One child explained that “sometimes it
[Internet connection] breaks. Mommy and daddy then shut it down, but it doesn’t always help” (Boy#32
6y3m). Another child, in turn, said that when facing broken connection “one has to go to the settings. Then it
[Internet connection] works” (Girl#47 6y7m).
Further, it appears that children’s conceptions of the Internet were mainly conceptions about wireless
connection, which is the most common type of broadband connection in Finnish households [57]. One child,
for example, described a mobile router by saying that “we have an Internet device at home. It is for the
iPads—we can take it with us at the cottage as well” (Boy#30 7y1m). Another child included a detailed
picture of a router in his drawing and explained that “when this [router] is shut down nothing works except
phone and televisions” (Boy#9 7y0m) (Fig. 6) Some children also commented that Internet connection can
be shared via smart phones: “We can share the Internet from mommy’s phone” (Boy#12 6y5m). Only two
children expressed that an Internet connection could be a wired broadband connection. According to the first
one one has to put the cord in the wall and then click the picture of the Internet (Girl#18 6y6m) while the
second one commented that “there is this internet and the cord” (Girl#52 6y2m) [see also 8].
Fig. 6. Router (Boy#9 7y0m)
Experiences with the Internet as a wireless home network made some of the children believe that the Internet
was located in a specific area, such as home, as the connection did not work when one moved too far away
from the access point. According to one child, “the Internet woks if you are not too far away from the
Internet” (Girl#49 6y8m), whereas another child commented that I can put the Internet on from my phone --
- It [the Internet] doesn’t work far away from home” (Girl#56 5y6m).
4.2 Children’s conceptions of what can be done using computers and the Internet
As discussed in the beginning of this paper, one deficiency in previous research is that identical forms of
computer usefor instance, playing digital gameshave been categorized either as children’s concepts of
computers [9] or children’s concepts of the Internet [8] depending on the research objective. Thus, one of the
objectives of the present study was to improve and clarify the state of knowledge by exploring children’s
everyday concepts of computers and the Internet side by side. This was done by categorizing children’s
descriptions of computer use based on whether the children thought that an Internet connection was required.
The categorization and distribution of the answers are presented in Table 6, which also contains examples
from the data.
Table 6. Children’s conceptions of what can be done using computers and the Internet
Data examples
Play games
You can play a tank game (computer) (Boy#36 6y9m)
Consume content (i.e. watch
videos, listen to music)
Go to YouTube (Internet) (Girl#38 6y9m)
Bills, shopping etc.
Daddy has ordered ski boots for me (Internet) (Boy#64 6y0m).
One can do important stuff, like work stuff (computer) (Boy#32 6y3m)
Write my own name (computer) (Boy#50 6y4m).
Information retrieval
You can check the weather forecast (computer) (Boy#8 6y8m)
Communication (email,
video calls etc.)
Read e-mail (computer) (Girl#47 6y7m)
Use Internet
Go to the Internet (computer) (Girl#55 6y10m)
Do homework (computer) (Boy#26 7y0m)
A comparison of the relative number of examples of computer and Internet-based activities suggested that it
was difficult for some of the children to distinguish whether they were online or not when they use a
computer (or observe others computer use). For instance, 20% (n=13) of the children commented that
computers could be used for communication purposes (i.e., writing e-mail), whereas only 8% (n=5)
expressed that an Internet connection was required for such activities. Similarly, 31% of the children (n=20)
said that computers can be used to pay bills or buy and sell stuff, but only 18% (n=12) connected these
activities with Internet use, although an Internet connection is a prerequisite for online shopping. Data from
one child (Boy#32 6y3m) provides a piquant example of this phenomenon. When asked what can be done
with computers, he stated, Daddy has bought flights to America and to Disney on Ice.” However, when he
was asked about what can be done on the Internet, he said, “I don’t know much about it because we have not
talked about it at home, but he was able to reply that the Internet can be found from the TV, [desktop]
computers, and laptops.” In other words, the child was aware that his family had an Internet connection at
home, and that they had various devices that were connected to the Internet. He had also observed his
father’s online activities. This information, however, was not enough for the boy to create an understanding
of which activities require an Internet connection. The data suggests that two main factors influence
children’s onlineoffline conceptsand technological concepts in general: 1) the fluidity of the user
experience, which refers to the user-friendly and intuitive nature of modern technologies, and 2) learning
from others, which refers to the social foundations of children’s conceptual development [11,12]. Both
themes are discussed in more detail in separate subsections.
4.2.1. Fluidity of the user experience
Fluidity, in the context of digital technologies, refers to a smooth and effortless user experience [58]. This is
something that modern high-speed wireless connections and intuitive mobile devices can provide.
Sometimes, the experience can be so smooth that the user does not even realize that he or she is online. For
example, a study by Chaudron et al. [1] showed that it is typical for the devices children use at home
tablets, smartphones, and laptopsto automatically connect to the wireless home network, and children, as
well as their parents, are not aware if and when children are online and offline at home. This notion is
supported by the present study. Whereas 97% (n=63) of the children reported having first-hand experiences
of using computers, only 48% (n=31) said they had first-hand experiences of being online. The latter number
is likely much smaller than reality, as, according to the most recent Finnish Children’s Media Barometer
[46], all five to six-year-olds have been online, and 66% are online on a weekly basis. Some of the children
said that they did not know whether they were online when they used a computer. A child stated, I have
written something, but I don’t know if it was on the Internet” (Girl#3 6y4m). Others commented that they
did not know what the term “the Internet” meant. A child stated, “I have heard that word, but I don’t have
that much experience” (Girl#55 6y10m).
To conclude, it is a logical outcome that the fluidity of the (wireless) Internet connection makes being online
or offline an opaque phenomenon for children. Put differently, how can children become aware of whether
they are online or not if nothing is required from them to go online? As discussed in Section 4.1.3, it seems
that understanding the differences between being online or offline requires that the fluidity of the Internet
must be disturbed. Take, for example, the child (Girl#56 5y6m) who reported that she first needs to connect
her phone to the wireless home network and not move too far away from the hotspot to remain connected.
This brief example includes illustrations of two disturbances to the flow. First, being connected to the home
network is not the default setting but something she needs to do manually. Second, fluidity can be achieved
only within specific geographic limits.
4.2.2. Learning from others as the source of conceptual development
Concepts are not formed and learned independently from the social context in which children live [11,12].
This was something the participating children were aware of; 75% (n=49) explicitly commented that their
knowledge of computers and the Internet was the result of intentional or unintentional tutoring from their
parents, siblings, grandparents, or other close relatives. Children, for example, explained that they had
learned things by observing their parents computer and online practices. A child said, “I know this because I
have watched Mommy working (Boy#36 6y9m). In addition, explicit statements that parents had told them
about computers and the Internet and what could be done using computers and the Internet were found in the
data. Quotes such as, “Daddy has shown me (Boy#4 6y2m) and “my parents have taught me” (Girl#17
6y1m), are typical examples.
Parents are also the ones who determine how and how often children can use computers and/or be online.
Previous research suggests that younger children’s computer and Internet use is more filtered and regulated
than older children’s [14,41], and the nature of these experiences influences the kinds of concepts children
are able to develop [14]. This argument is supported by the present study as children reported their first-hand
experiences of computer use and online activities being mainly playing digital games and watching movies
and children’s programs. The data also suggests that children understand that their computer and Internet use
is controlled and filtered and that the children are aware that some practices are for adults only [see also 23].
A child said, “I can play children’s games, and Daddy plays adults’ games. Adults can also use Facebook
(Girl#56 5y6m). Eighteen (28%) of the children explained that a password is needed to either open the
computer or connect to the Internet. Several children also commented that only adults knew what the
password was. All these themes are comprised illustratively in the following extract:
I have only played games and watched children’s programs. I can’t use the computer by
myself anymore because Mommy has to do school stuff. I might accidently push some button
and delete Mommy’s school stuff. (Girl#48 6y6m)
It appears that parental concern and rules for keeping the computer and its files safe had steered some
children to conceptualize computers as delicate and unreliable machines. One child, for example, said that
computers “can go crazy sometimes” (Girl# 6y4m) while another commented that computers are “really
fragile. If You throw it on the floor it won’t work anymore” (Boy# 6y2m).
These findings are in line with previous research, which suggests that much of children’s learning about
digital technologies takes place at home [1,8,19]. Nevertheless, data from five children (8%) suggests that
preschool is also a place where children learn about what can be done with digital technologies. One child
commented that she had used a computer to print papers in preschool, and another child said that she had
learned in preschool that computers can be used for writing. Moreover, three children explained that they had
played learning games in preschool. These three examples constitute half of all the references (n=6) to
computers and the Internet as tools for studying things.
5. Conclusions
This paper explored five to seven-year-old children’s conceptions of computers, code, and the Internet.
Unlike in previous research, this study examined all three topics simultaneously. The findings suggest that
most of the children had no idea how code and programming related to computers. Accordingly, many
children found it difficult to distinguish between online and offline practices. I conclude this paper by
summarizing the key findings of the study, discussing what these findings mean in terms of pedagogical
implications and suggestions for future research, and addressing the limitations of the present study.
5.1 Traditional conceptions of computers
Interestingly, the computers the children drew did not reflect the contemporary digital landscape of
children’s life-worlds, in which mobile touchscreen devices are the most commonly used computers [1,8].
Forty-six percent of the children conceptualized computers as laptop computers, and 40% of the children
conceptualized computers as desktops. Only one child conceptualized a computer as a tablet computer,
whereas several of the children considered computers a distinguished form of technology when expressing
their views about the Internet. Accordingly, none of the children expressed that computers could be located
inside other technologies (i.e. cars, washing machines, or toys).
Although the data provided no unequivocal explanation for why tablets were not considered computers, one
possible reason is related to children’s conceptualization of computers as the “whole package” consisting of
a monitor, a keyboard, and wires (mentioned by 88%, 75%, and 66% of the children, respectively). The
children participating in this study thought computers were required to have all these components [see also
9,10,13, 25,26]. To teach children about contemporary ubiquitous computing, children’s initial scientific
concepts must be challenged. Previous research suggests that if children are taught that computers are
programmable chips (and shown what the chip looks like), the children are able to identify a range of
devices, including tablets, phones, video cameras, traffic lights, clocks, and watches, that might contain such
chips [9]. It is possible that the non-descriptive questions used in the data collection (see section 3.1) may
have not provided the children enough concreteness for them to be able to distinguish between the meanings
given for computers in colloquial language and in scientific language. This notion needs to be considered a
potential limitation of the present study.
5.2. The role of linguistic cues in children’s concepts of coding and programming
There is an ongoing discussion whether elementary programming should be introduced as “coding” or as
“programming” to young children [7]. Some have opted for coding because it contains existing connotations
of mysteries (secret codes) and achievements (cracking the code) that are believed to capture children’s
interest [7]. According to the present study, linguistic cues appear to play an important role in children’s
concepts of code and programming as several of the children related code and coding to PIN codes and
programming to watching (television) programs. This means that investigating children’s preconceptions of
the terms “coding” and “programming” is a prerequisite for effective teaching.
Moreover, the three children who connected programming and coding giving commands had played with
coding games or programmable toys. This notion supports previous research that argues that children rarely
come up with the idea of programming by themselves but that having this idea requires involvement in
programming activities [10,26,28,30,32,33,35]. However, in the present study, the children were not able to
transform these experiences into scientific concepts of computers as programmable machines. While the
pedagogically well-designed use of such games and toys may support children’s algorithmic thinking and
memory [59,60], it is not likely that children would recognize the connection between programming a
BeeBot and the principles of computer programs and programming without adult mediation and guidance.
5.2 Dysfunctional technology as a source of accurate scientific concepts
This paper supports previous research suggesting that young children seldom possess an accurate scientific
understanding of the Internet [1,38]. However, the present study provides newalbeit indicative
information about how children’s accurate scientific concepts of the Internet begin to emerge. It appears that
children become aware of the Internet as a network and the difference between online and offline activities in
situations in which the Internet connection does not function properly. In some cases, the children had made
such conclusions by themselves. For example, two children reported that the Internet connection did not
work well if they were too far away from the access point, which indicated that these children had developed
an accurate scientific concept about the limits of the coverage of a wireless network. In addition, there was
subtle evidence in the data that suggested that in such occasions parents explained to the children why the
connection was not working and began to fix the problem by providing the children the opportunity to
observe what was required for the Internet connection to work properly (i.e. circuitry, computer settings).
Such experiences appear to be meaningful for the development of a mature concept, in which the everyday
concept and (accurate) scientific concept merge [11].
This notion provides interesting pedagogical possibilities that support the development of mature concepts of
computers, code, and the Internet. In other words, the learning affordances of dysfunctional technology can
be operationalized into intentional pedagogical approaches to teach children about the functional properties
of computers and the Internet. This, however, requires that instead of mere observation children should
engage in problem solving. Working with real-life technological problems overlaps with the trending
makerspace ideology, which prescribes “a model of learning-by-doing in which individuals can work on
creative design projects that are personally and/or collectively meaningful” [61, p. 14].
5.3 Children’s awareness of the role of adults in their learning
The present study suggested that much of the children’s learning about technology was based on
observations of their parents’ computer routines and that the children were fully aware that they learned from
their parents. This finding locates this study within the growing body of research debunking the myth of
children as “digital natives” [18] who learn the language of computers only by being born around digital
technologies [62,63]. Challenging this myth is vital for at least two reasons. First, parents often
underestimate their direct or indirect role in children’s learning. Parents tend to consider children to be just
picking it up” when it comes to learning about technology [19]. Future studies can introduce children’s
conceptions to parents to determine whether and how this knowledge shapes parents’ views about children
and technology, as well as parents’ technology practices at home. Second, preservice [64] and in-service [65]
teachers often consider children born-savvy technology users, and these unfounded views have been found to
lead to pedagogically inappropriate practices [66]. In other words, these notions are also vital in considering
the question of how children’s learning about technology should be supported in early years education in
preschool and in primary school. Today, notable amounts of daily administrative tasks are performed with
computers and via the Internet. Newsletters for families are sent via e-mail or by using another digital
platform (i.e., a blog), and children’s attendance is recorded using near-field communication tags and
smartphones [48,67]. These daily routines should be recognized as pedagogically valuable moments for
teaching children about computers, code, and the Internet.
I wish to express my gratitude to all the children, teachers, and parents who made this study possible. This
study was supported by the Jenny and Antti Wihuri foundation.
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Appendix 1
Patter recognition lock screen
Appendix 2
Retrieved from:
A screenshot from Bee bot app
retrieved from:
... If students have a misconception prior to learning a subject, this may prevent them from learning the new subject properly, thereby leading to new misconceptions (Biber et al., 2013). Research on children's initial conceptions of abstract digital technologies like the Internet (Eskelä-Haapanen & Kiili, 2019), search engines (Kodama, 2016) the Internet of Things (Mertala, 2020), digital data (Pangrazio & Selwyn, 2018), and programming / coding (Mertala, 2019) suggest that informal encounters provide children only a limited understanding of what these technologies actually are. AI as an "opaque technology'' (Long & Magerko, 2020) and a "fuzzy concept" (Kaplan & Haenlein, 2019) should not be an exception. ...
... Indeed, many of the non-technological misconceptions described different kinds of cognitive acts and actions (e.g., regulation of immediate and intuitive instincts). This explanation is supported by Mertala's (2019) finding that Finnish preschoolers' used conceptual similarities as the basis of their reasoning of what programming is, as in Finnish the words for programming ("ohjelmointi"), program ("ohjelma"), and manual ("ohje") are notably similar. ...
... It should be also noted that the data fails to tell much about the foundations of the misconceptions. While our findings imply that conceptual connotations, media representations, and hands-on experiences with AI solutions like voice assistants have a role in students misconceptionsan interpretation supported by previous research (e.g., Cave et al., 2020;Mertala, 2019;Mertala et al., 2022)more research is needed to verify (or confront) these observations. When making conclusions based on our findings, it is important to note that placing the focus on misconceptions tells only a partial tale about the variety of conceptions the students had. ...
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Research on children's initial conceptions of AI is in an emerging state, which, from a constructivist viewpoint, challenges the development of pedagogically sound AI-literacy curricula, methods, and materials. To contribute in resolving this need in the present paper, qualitative survey data from 195 children were analyzed abductively to answer the following three research questions: What kind of misconceptions do Finnish 5th and 6th graders' have about AI?; 2) How do these misconceptions relate to common misconception types?; and 3) How profound are these misconceptions? As a result, three misconception categories were identified: 1) Non-technological AI, in which AI was conceptualized as peoples' cognitive processes (factual misconception); 2) Anthropomorphic AI, in which AI was conceptualized as a human-like entity (vernacular, non-scientific, and conceptual misconception); and 3) AI as a machine with a pre-installed intelligence or knowledge (factual misconception). Majority of the children evaluated their AI-knowledge low, which implies that the misconceptions are more superficial than profound. The findings suggest that context-specific linguistic features can contribute to students' AI misconceptions. Implications for future research and AI literacy education are discussed.
... Research shows that children develop their own conceptions of abstract digital technologies like the Internet, code, and ubiquitous computing before their formal introduction in (pre)school (e.g., Edwards et al., 2018;Eskelä-Haapanen & Kiili, 2019;Mertala, 2019Mertala, , 2020Wennås Brante & Walldén, 2021). This stands for AI as well (Kreinsen & Schultz, 2021;Ottenbreit-Leftwich et al., 2021). ...
... Such conceptions are inaccurate and are likely the result of spontaneous observations instead of intentional teaching. In the Vygotsky (1987) tradition, these are called everyday concepts that arise either from hands-on experiences or via other sources (see also, Edwards et al., 2018;Mertala, 2019). Students in Kreinsen and Schultz (2021) stated that AI manifests itself in everyday life in the form of cookies in web browsers, and voice assistants in smartphones -all examples that are representative of the everyday digital realm in Western contexts (see also Edwards et al., 2018). ...
... Instead, theory and previous research are treated as "threads" (Grönfors, 2011), which can provide working categories for the initial analyses but are a subject to be refined via data-driven interpretations (Mertala, 2020). The main theoretical threads in this study were the stages of AI (Kaplan & Haenlein, 2019), "Big Ideas" in AI (Touretzky et al., 2019) Vygotskian-based idea of everyday concepts (Edwards et al., 2018;Mertala, 2019), existing research on people's conceptions of AI Kreinsen & Schultz, 2021;Zhang and Dafoe, 2020 ), and the public representations of AI (e.g., Brokensha, 2020;Chuan et al., 2019;Fast & Horvitz, 2017;Jokela, 2018;Obozintsev, 2018;Slotte Dufva & Mertala, 2021). ...
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In the present paper, we report the findings of a qualitative survey study of 195 Finnish 5th and 6th grade students' pre-instructional conceptions of artificial intelligence (AI). An exploration of these initial conceptions provides insight into students' preliminary understanding of the topic and informs curriculum designers and teachers about misconceptions that might jeopardize student learning. The findings suggest that students' initial conceptions of AI are varied and often uninformed. For instance, references to the role of data in training AI applications were practically nonexistent. Instead, AI was often described as an anthropomorphic technology that possesses cognitive qualities equivalent to those of humans––a conception that notably resembles how AI is portrayed in the media. As a pedagogical implication, our findings suggest that it would be valuable to “demystify” AI by exploring its technical principles (i.e., the role of data) of the “human-like” AI solutions students encounter in their everyday lives.
... In comparison to the above areas of research, there are fewer studies that have addressed the understanding of the internet among young children (Dodge et al., 2011;Edwards et al., 2018;Eskelä-Haapanen & Kiili, 2019;Mertala, 2019;Yan, 2006Yan, , 2009. These studies use different data collection techniques, ranging from questionnaires (Yan, 2006(Yan, , 2009 and focus groups (Murray & Buchanan, 2018) to semi-structured interviews (Eskelä-Haapanen & Kiili, 2019;Yan, 2009), and with the exception of Yan (2009), handle typically modest samples (fewer than 65 participants). ...
... Esta preocupación se ha visto acentuada, sin duda, desde la pandemia por Covid-19, debido el incremento de tiempo que pasan online los más pequeños (e.g., Király et al., 2020). En comparación con estas líneas de investigación, existen muy pocos estudios que hayan abordado la comprensión de internet en los niños pequeños (Dodge et al., 2011;Edwards et al., 2018;Eskelä-Haapanen & Kiili, 2019;Mertala, 2019;Yan, 2006Yan, , 2009. Estos estudios emplean diferentes técnicas de recogida de datos, desde cuestionarios (Yan, 2006(Yan, , 2009, grupos focales (Murray & Buchanan, 2018) hasta entrevistas semiestructuradas (Eskelä-Haapanen & Kiili, 2019; Yan, 2009); y a excepción de Yan (2009), la mayoría de los trabajos se han realizado con muestras muy pequeñas (menos de 65 participantes). ...
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The internet has become a key environment for children’s learning and leisure at an increasing early age. Yet, little is known about what children understand about the internet. We conducted semi-structured interviews with 111 children aged five to nine to assess their notions about the internet, the authorship of online content and the trustworthiness they attribute to it. Considering the socio-cognitive advances throughout these ages, we expected a significant improvement in children’s concept of the internet. However, the results showed modest age differences, and only in some basic notions (e.g., internet functions). Misconceptions about the internet and naïve ideas about the reliability of its content were present at all ages. Only a very few older children envisaged the risk of finding malicious information online and the need to consult other sources in case of doubt. We discuss the necessity to address children’s misconceptions at least from the beginning of primary school, when most of them are cognitively ready to understand many of the issues addressed in this study, provided they receive guided instruction.
... In a time when many elementary, primary and high school classrooms, especially in public schools, include almost no digital literacy instruction in an African context, especially Nigeria, we believe this work could provide a model for considering how to engage pupils in project-based and design thinking issues, which may even foster youth activism through machine learning concepts. While the study was carried out in informal settings, interventions in informal settings can serve to challenge abstract knowledge of the inner workings of technology by disrupting children's conception of what it means for young learners to engage in digital literacy through understandings of computers, code and the internet (Mertala, 2019) and meaning-making practices of emerging technology for new forms and functions. Studies in informal settings have attracted a considerable amount of research. ...
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Background and context: Researchers have been investigating ways to demystify machine learning for students from kindergarten to twelfth grade (K–12) levels. As little evidence can be found in the literature, there is a need for additional research to understand and facilitate the learning experience of children while also considering the African context. Objective: The purpose of this study was to explore how young children teach and develop their understanding of machine learning based technologies in playful and informal settings. Method: Using a qualitative methodological approach through fine-grained analysis of video recordings and interviews, we analysed how 18 children aged 3–13 years constructed their interactions with a machine-based technology (Google’s Teachable Machine). Findings: This study provides empirical support for the claim that Google’s Teachable Machine contributes to the development of data literacy and conceptual understanding across K–12 irrespective of the learners’ backgrounds. The results also confirmed children’s ability to infer the relationship between their own expressions and the output of the machine learning-based tool, thus, identifying the input-output relationships in machine learning. In addition, this study opens a discussion around differentials in emerging technology use across different contexts through participatory learning. Implications: The results provide a baseline for future research on the topic and preliminary evidence to discern how children learn about machine learning in the African K–12 context.
... (Ofcom, 2011;Danby et al., 2013;Chaudron et al., 2018;Erstad et al., 2020), and children may be exposed to misinformation and disinformation in different digital environments. However, young children have little understanding of the internet (Mertala, 2018;Murray & Buchanan, 2018;Eskelä-Haapanen & Kiili, 2019), and individual children's trust in online information varies markedly (Eskelä-Haapanen & Kiili, 2019). Children around nine to 12 years old begin to gain a better understanding of the internet's technical and social complexity (Yan, 2005) and start to be aware of its negative aspects and to develop different coping strategies (Murray & Buchanan, 2018). ...
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Many children are active on the internet and on social networks, but their capacity to evaluate online information is limited. However, in the current era of post-truth and the infodemic, even young children are exposed to inaccurate information online. They need to understand how the internet works and how to evaluate the information they find there. In the digital information age, critical literacy is important for everyone. In this article, I focus on an aspect of critical literacy that has been neglected in the field of media education, namely epistemic cognition. I argue that children—even young ones—need to learn epistemic cognition skills and epistemic practices. I also argue that the AIR model of epistemic cognition theory and theories of making thinking visible could be used as a basis for teaching children critical literacy and metacognition in the post- truth era. I use these theories to create a framework that also includes principles of reliable science and journalism. Science and journalism are part of the so-called Constitution of Knowledge, an epistemic operating system that establishes rules for transforming disagreement into knowledge. In addition to critical literacy, children need scientific literacy, which can help them understand how accurate information and knowledge are (in ideal situations) created and evaluated, both on and offline.
Purpose Computing technology is becoming ubiquitous within modern society and youth use technology regularly for school, entertainment and socializing. Yet, despite societal belief that computing technology is neutral, the technologies of today’s society are rife with biases that harm and oppress populations that experience marginalization. While previous research has explored children’s values and perceptions of computing technology, few studies have focused on youth conceptualizations of this technological bias and their understandings of how computing technology discriminates against them and their communities. This paper aims to examine youth conceptualizations of inequities in computing technology. Design/methodology/approach This study analyzes a series of codesign sessions and artifacts partnering with eight black youth to learn about their conceptualizations of technology bias. Findings Without introduction, the youth demonstrated an awareness of visible negative impacts of technology and provided examples of this bias within their lives, but they did not have a formal vocabulary to discuss said bias or knowledge of biased technologies less visible to the naked eye. Once presented with common technological biases, the youth expanded their conceptualizations to include both visible and invisible biases. Originality/value This paper builds on the current body of literature around how youth view computing technology and provides a foundation to ground future pedagogical work around technological bias for youth.
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The innovative educational programming environment called ScratchJr offers young children the possibility to programme their own interactive stories and games. This study aims to investigate the acceptance of ScratchJr by pre-service kindergarten teachers as a tool with which to produce interactive, multimedia learning content for science teaching, as well as a tool for learning and teaching Computational Thinking. Also, the effects of using ScratchJr for future teachers' attitudes in terms of perceived ease of use and usefulness are explored. The study was conducted during the winter term of the academic year 2016-2017 at a university department of early childhood education in Greece. The results show not only that the use of ScratchJr has a statistically significant increase in pre-service kindergarten teachers' self-efficacy in Computational Thinking, but also that they are willing to use it in their future daily practice for science education. Also, the study reveals that pre-service teachers have positive acceptance scores in terms of usefulness and ease of use of ScratchJr. Additionally, no significant difference between the acceptance scores of the participants in terms of programming background, and their studies in the high school from which they graduated, as indicators of programming experience was found. Preliminary analysis of the data shows that ScratchJr is an appropriate educational environment for pre-service kindergarten teachers to learn programming basics as well as a platform for the development of educational resources to support the learning of science teaching.
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While children are living more of their lives online, little is known about what they understand about the implications of their online participation. Here we report on the Best Footprint Forward project which explored how children come to understand the internet. Thirty-three children (ranging in age from 10 to 12 years old) from three primary schools in regional Australia participated in focus groups and created a work sample depicting the internet. Analysis of the focus group transcripts and work samples revealed that while the children's understanding of the internet was not technical, their knowledge was developed through the social activities that they engaged in online, and influenced by the interactions they have in their 'real life' with parents, teachers and friends. The children in the study demonstrated an ambivalence about the internet; they regularly went online for a variety of purposes but these positive experiences were tempered by concerns and fears. This research presents a nuanced perspective of children's knowledge of the internet; by rejecting the notion that children are naïve, passive consumers of digital culture, analysis of their understanding reveals it to be balanced and sophisticated.
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Education policy increasingly takes place across borders and sectors, involving a variety of both human and nonhuman actors. This comparative policy paper traces the ‘policy mobilities,’ ‘fast policy’ processes and distributed ‘policy assemblages’ that have led to the introduction of new computer programming practices into schools and curricula in England, Sweden and Australia. Across the three contexts, government advisors and ministers, venture capital firms, think tanks and philanthropic foundations, non-profit organizations and commercial companies alike have promoted computer programming in schools according to a variety of purposes, aspirations, and commitments. This paper maps and traces the evolution of the organizational networks in each country in order to provide a comparative analysis of computing in schools as an exemplar of accelerated, transnationalizing policy mobility. The analysis demonstrates how computing in schools policy has been assembled through considerable effort to create alignments between diverse actors, the production and circulation of material objects, significant cross-border movement of ideas, people and devices, and the creation of strategic partnerships between government centres and commercial vendors. Computing in schools exemplifies how modern education policy and governance is accomplished through sprawling assemblages of actors, events, materials, money and technologies that move across social, governmental and geographical boundaries.
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The need for media education in early childhood teacher education has been regularly emphasized. However, the questions of what and how student teachers should be taught about media education have remained unanswered. This paper contributes to resolving these questions by introducing the concept of media educational consciousness which we argue to be crucial for 21st century early childhood teachers and, thus, for teacher education. A compulsory digital media course for first year student teachers provides the empirical context for this paper. By using students’ learning diaries as data we will demonstrate that the more aware teachers are of their underlying conceptions, the more potential there is for personal professional reflection and development.
Conference Paper
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The innovative educational programming environment called ScratchJr offers young children the possibility to program their own interactive stories and games. This study aims to investigate the acceptance of ScratchJr by pre-service kindergarten teachers as a tool to produce interactive, multimedia, learning content for science teaching as well as a tool for learning and teaching Computational Thinking. Also, the effects of using ScratchJr for future teachers' attitudes in terms of perceived ease of use and perceived usefulness are explored. The study was conducted during winter semester of the academic year 2016-2017 at a university department of early childhood education in Greece. The results show not only that the use of ScratchJr has a statistically significant increase in preservice kindergarten teachers' self-efficacy in Computational Thinking but also that they are willing to use it in their future daily practice for science education. Also, the study reveals that pre-service teachers have positive acceptance scores in terms of usefulness and ease of use of ScratchJr. Additionally, no significant difference between the acceptance scores of the participants in terms of programming background, and their studies in high school they graduated from as indicators of programming experience was found. Preliminary analysis of the data shows that ScratchJr is an appropriate educational environment for pre-service kindergarten teachers to learn programming basics as well as a platform for the development of educational resources to support the learning of science teaching.
American society is rapidly becoming computer-oriented, and this fact has implications for the school curriculum. It is safe to predict that the basic concepts of computer science will eventually become a part of the elementary and secondary curriculum.
Play is an important part of early childhood education and has been defined from different perspectives and paradigms. However, definitions of play have been studied more from adults’ perspectives than from those of children themselves. This ethnographic research, with children aged three to five years and built on sociological constructs, will explore children’s views on play in two preschool settings in Iceland. Video-stimulated recordings were used to support children’s conversations about their different activities in the settings, to explore which activities they considered play. Most of the children said that they were playing when they took on roles and could decide what to do with the material. When the children were preparing the play or were drawing, they usually said they were not playing. These findings add to the understanding of play from children’s perspectives and are valuable to the research field and for educators working with young children.
Current discussions about educational policy and practice are often embedded in a mind-set that considers students who were born in an age of omnipresent digital media to be fundamentally different from previous generations of students. These students have been labelled digital natives and have been ascribed the ability to cognitively process multiple sources of information simultaneously (i.e., they can multitask). As a result of this thinking, they are seen by teachers, educational administrators, politicians/policy makers, and the media to require an educational approach radically different from that of previous generations. This article presents scientific evidence showing that there is no such thing as a digital native who is information-skilled simply because (s)he has never known a world that was not digital. It then proceeds to present evidence that one of the alleged abilities of students in this generation, the ability to multitask, does not exist and that designing education that assumes the presence of this ability hinders rather than helps learning. The article concludes by elaborating on possible implications of this for education/educational policy.