Parental acceptance of digital game-based
learning
Jeroen Bourgonjon*, Martin Valcke, Ronald
Soetaert, Bram de Wever, Tammy Schellens
Department of Educational Studies, Ghent University, H. Dunantlaan
2, 9000 Ghent, Belgium
a b s t r a c t
In research about digital
game-based learning, the likely negative perceptions of parents are
often enlisted as a barrier toward the adoption of games in
classroom settings. Teachers, students and policy makers appear to
be influenced by what parents think about games in the classroom.
Therefore, it is important to study these parental beliefs about
games. The present research develops and validates a path model to
explain and predict parental acceptation of video games in the
classrooms of their children. The hypothetical model was found
reliable and valid, based on a survey of 858 parents with at least
one child in secondary education. Overall, the results show that
59% of the variance in parents’preference for video games can be
explained by the model comprising hypotheses about learning
opportunities, subjective norm, perceived negative effects of
gaming, experience with video games,personal innovativeness, and
gender.
1.
Introduction
A
significant body of research links video games with contemporary
learning theories and especially insights from cognitive
science(Gee, 2003; Paraskeva, Mysirlaki, &
Papagianni, 2010). Video games improve student motivation
(Burguillo, 2010; Kebritchi, Hirumi, & Bai,2010;
Malone, 1980), stimulate deep learning and creative thinking (Eow,
Ali, Mahmud, & Baki, 2009; Papert, 1980), transcend
subject boundaries (Squire, 2004) and provide powerful and
meaningful contexts for learning (Shaffer, 2006). Based on a review
of the literature on“digital game-based learning” (DGBL), Van Eck
(2006) distinguishes between three approaches for integrating games
into the learning process: “have students build games from scratch;
have educators and/or developers build educational games from
scratch to teach students; and integrate commercial off-the-shelf
(COTS) games into the classroom” (p. 57). However, empirical
research concerning the
effectiveness of DGBL is scarce, fragmented and often conflicting
(Hays, 2005; Papastergiou,2009; Tobias & Fletcher,
2008). A variety of factors underlie these conflicting findings.
Current research emphasizes that most of these factors appear to
stem from difficulties with the implementation of games in
classroom settings (Egenfeldt-Nielsen, 2004). Therefore,
researchers are starting to focus on the different barriers that
hinder the straightforward adoption of video games in education.
However, a key issue is whether researchers adopt a sufficiently
broad approach when studying the key actors in an instructional
setting.
Most of these video game
implementation studies have centered around two actors that are
believed to be key players in the integration process: teachers
(Kirriemuir & McFarlane, 2004; Schifter
& Ketelhut, 2009; Schrader, Zheng,
& Young, 2006) and students (Bourgonjon,Valcke,
Soetaert, & Schellens, 2010). So far, little
attention has been paid to the position of the parents.
Notwithstanding, parents play an important role in the school
system. Their involvement ranges from taking on the role of a mere
communicative bridge between the school and home environment, over
decision making as members of the board of governors, to occasional
partnership in the implementation of instructional processes
(Epstein, 2001; Kong, 2008; Mooij & Smeets, 2001).
It is therefore not surprising that in the meta-analysis overview
of Hattie (2009), parental involvement is considered as a critical
variable influencing learning performance. Hattie reports – on the
base of 716 studies – an average effect size of
d .51 (2009, p. 61).
Not much is known about the
acceptation of video games by parents, except that parents’ beliefs
can be very influential at several levels.Firstly, parents’ likely
negative beliefs are listed as one of the main arguments reported
by teachers who do not want to use video games in the classroom
(Williamson, 2009). Secondly, parents’ beliefs about video games
and the rules about playing at home have a profound impact on how
the students perceive video games in the context of learning and
instruction (Scharrer & Leone, 2008). Thirdly,
parents’ beliefs have
served as an argument used by public policy makers for restricting
children’s access to video games with potentially harmful
content(Bijvank, Konijn, Bushman, & Roelofsma,
2009; Kutner, Olson, Warner, & Hertzog, 2008).
Therefore it is remarkable that parental acceptance of video games
is not higher on the research agenda, certainly in relation to
digital game-based education. However, things are starting to
change since the 2009 BECTA study “Computer games, schools and
young people” marked parental acceptance as an important domain for
further educational research (Williamson, 2009).
This article responds to the
call for studying parents’ beliefs about DGBL, by presenting the
results of a cross-sectional survey study among 858 parents of
secondary school students about video games in general, and about
the use of video games in the classroom in particular. The use of
games in the classroom here refers to those approaches within DGBL
that concern actually playing video games in the classroom. Based
on previously established and validated models, a model for
understanding parents’ acceptance of game-based learning is
proposed. In what follows, the theoretical underpinnings for this
model are examined, and the model fit is tested against data that
is gathered from the parents.
2. Literature review
2.1. Parents’ beliefs about games
Parental beliefs about information technology have almost
exclusively been studied in relation to mediation: mostly through
surveys,researchers have tried to find out how parenting styles and
rules affect media use of children and adolescents (Mesch, 2009;
Valcke, Bonte,De Wever, & Rots, 2010). Within this
body of research, video games have been analyzed as a special case,
partly because games are played rather than watched (Bogost, 2007;
Turkle, 1984), and because game experiences are usually shared with
peers, rather than with parents.The latter is in contrast with
watching television, for example, which more often takes place in a
common room (Bickham et al., 2003;Nikken & Jansz,
2006). Given these characteristics, it comes as no surprise that
research concludes that parents feel less knowledgeable about video
games than about television or other media (Nikken
& Jansz, 2006).
Two types of parental
beliefs recur in the literature. It appears that parents
distinguish between both desirable and undesirable effects of media
and video games (Nikken & Jansz, 2006; Skoien
& Berthelsen, 1996; Sneed & Runco,
1992). Besides acknowledging that games can have positive effects,
like enhanced cognitive thinking skills, parents express concerns
about (a) the balance between the children’s video game play and
other activities, (b) the content of games, (c) the potential
harmful effects, and (d) mediation strategies (Kutner et al.,
2008).Their strategies to watch over the game playing habits of
their children more or less resemble traditional mediation
techniques, ranging from downright disapproval and restriction,
over rule setting, to co-playing and talking about games (He,
Piche, Beynon, & Harris, 2010;
Kearney & Pivec, 2007; Kutner et al., 2008;
Nikken & Jansz, 2006; Scharrer &
Leone, 2008; Skoien & Berthelsen, 1996).
2.2. Parents’ beliefs about games in
education
In an educational context,
research on information technology integration has traditionally
considered the home environment as a basis for extending school
activities beyond classroom walls (Blanchard &
Oliver, 1999; Kong & Li, 2009). However, there is a
large difference between teachers’ and parents’ aspirations on the
one hand and the reality on the other hand: “home computers
typically service game
playing – games that appear to have little connection with the
agenda of the school” (Kerawalla & Crook, 2002, p.
753).
Considering the former,
this article will focus on parents’ beliefs about games in general,
and DGBL in particular. The theoretical base builds on two models
that help to describe and explain an individual’s predisposition
toward action: the theory of reasoned action (TRA - Fishbein
&Ajzen, 1975) and the technology acceptance model
(TAM - Davis, 1989). Over the years, both models have been
researched extensively to find reasons for the often-difficult
integration of information technology in a variety of domains. The
former theory, TRA, states that individuals’ intended behavior is
predicted by their perception of their own attitude toward that
behavior and by the perceived social pressure to act. The latter
model, TAM, focuses specifically on the case of information
technology. The model explains people’s behavioral intentions as a
result of two user beliefs: perceived usefulness and perceived ease
of use.
Based on these theories, the research in this article tries to
build an eclectic model for predicting and explaining parents’
acceptance of video games in the classrooms. Serious adaptations
have been made in the present study, not only for matters of
consistency (Legris,Ingham, & Collerette, 2003),
but also to take into account individual, contextual, technology
and task characteristics (Mathieson,Peacock, &
Chin, 2001; McFarland & Hamilton, 2006). For
example, because the decision to use video games in the classroom
is not up to the parents themselves, it was impossible to use the
traditional TAM concepts of behavioral intention, usefulness and
ease of use.
Therefore, the literature
uniting game and technology acceptance studies was consulted in
order to find an alternative approach(Bourgonjon et al., 2010; Ha,
Yoon, & Choi, 2007; Hsu & Lu, 2004;
Wu & Liu, 2007).
3. Research model and hypotheses
3.1. Dependent variable: preference for video games
(PVG)
A useful concept for
studying the acceptance of digital game-based learning in a school
context is that of preference for video games(PVG). It is derived
from Hsu and Lu (2007), who described preference as a measure of
“the degree of users’ positive feelings about participating [in
online game communities]” (p. 1648). To examine students’
acceptance of video games in the classroom, Bourgonjon et al.(2010)
added an intended behavior component that refers to the approval of
game-based learning. This meets the suggestion of Skoien and
Berthelsen (1996) to study whether people are really willing to act
upon their beliefs about games. In this article preference for
video games can be defined as “positive feelings about games for
learning and predicted choice for video games in the classroom”
(Bourgonjon et al.,2010, p. 1147).
3.2. Learning opportunities (LO)
Academics and educators consider video games
as operational translations of certain contemporary learning
theories (Egenfeldt-Nielsen,2007; Gee, 2003; Papert, 1980; Shaffer,
2006; Squire, 2004). In other words, for academics and educators
the main quality of video games is that they foster opportunities
for learning. The concept of “perceived learning opportunities” was
introduced by Bourgonjon et al. (2010) precisely to study how
people think about these process outcomes of using video games in
the classroom. The authors compare perceived learning opportunities
with perceived usefulness – a concept by Davis (1989) that is
focused more on job performance, on the product outcome of using a
certain type of technology. In the case of parental acceptance of
video games usefulness refers to the potential of video gaming to
increase the students’ performance (for example, as reflected in
the students’ grades). Perceived learning opportunities,
however,refers to the degree to which parents believe that using
video games in the classroom will offer their children
opportunities for learning.
Considering both parents’ concerns about good
education, and their preference for information technologies that
explicitly foster learning (Kerawalla & Crook,
2002; Kong, 2008), it follows logically that the degree to which
parents believe that using video games in the classroom offer
children opportunities for learning will highly correlate with and
predict preference for video games (Kong & Li,
2009;Skoien & Berthelsen, 1996).
H1: (Perceived) learning opportunities (LO) positively affects
preference for video games (PVG).
3.3. Negative effects of playing video games
(NEG)
The value of video games is subject to many
debates (McAllister, 2004), in which the popular media play an
important role. In the past,media messages about video games have
predominantly focused on potential negative effects of gaming, and
have eagerly cited studies that hold video games accountable for
health issues – ranging from obesity (Kautiainen, Koivusilta,
Lintonen, Virtanen, & Rimpela, 2005;
Stettler,Signer, & Suter, 2004) to injuries
inflicted by the use of a game controller (Rushing, Sheehan,
& Davis, 2006) – and of course for desensitization
and aggressive behavior (Anderson & Bushman, 2002;
Anderson & Dill, 2000; Colwell &
Payne, 2000; Uhlmann & Swanson, 2004).However,
researchers do not agree about the aggressive behavior hypothesis
(Freedman, 2001; Goldstein, 2001). The debate seems – dixit Nature
– “clouded by overheated rhetoric and exaggerated claims” (A calm
view of video violence, 2003, p. 355).
Unsurprisingly, parents appear to be alarmed
by these media messages, which often directly target parental
responsibilities, by pointing out that parents need to watch over
the type of games children play. Skoien and Berthelsen (1996) found
that the media attention for the potentially harmful effects of
playing video games is an important source influencing parental
beliefs about games. It follows that their beliefs about the
potential negative effects of playing video games (NEG) will have a
profound impact on their acceptance of DGBL.
T he relationship between parents’ beliefs
about the negative effects of gaming and their perception about the
learning opportunities is less straightforward. Squire (2002)
argues, “A fundamental tension facing game studies is that if games
do not promote or “teach” violence,then how can researchers claim
that they might have a lasting impact on students’ cognitive
development?” (Unpacking game play, para. 1).Nevertheless, although
both constructs might in fact be referring to learning, the beliefs
about possible consequences can still be highly contradictory.
H2: Negative effects of playing video games (NEG) negatively
affects preference for video games (PVG).
H3: Negative effects of playing video games (NEG) negatively
affects learning opportunities (LO).
3.4. Subjective norm (SN)
Both the theory of reasoned action (Fishbein
& Ajzen, 1975) and the subsequent theory of planned
behavior (Ajzen, 1991) include subjective norm – which is defined
by the authors as “a person’s perception that most people who are
important to him think he should or should not perform the behavior
in question” (Fishbein & Ajzen, 1975, p. 302) – as
a direct predictor for people’s intentions to act. This assumption
goes back to the work of Triandis (1971), who stated that people
are influenced by messages about what they should or should not do.
However, the generic impact of subjective norm has not always been
confirmed in the literature. A promising reorientation of the
theory is that the impact of subjective norm is more profound in
cases of initial acceptance, in situations where people are not yet
experienced with the new technology and behavior (Hu, Clark,
& Ma, 2003; Triandis, 1971). Video games could be
considered an example of such a technology, and as expected,
subjective norm appears to be a good predictor for the acceptance
of online video gaming (Hsu & Lu, 2004). In
addition to the direct effect of subjective norm on people’s
intentions, it is also likely that an indirect effect exists
through personal belief systems. This is suggested by Venkatesh and
Davis (2000) who reported that people internalize a referents’
beliefs and make it part of their own belief system.
H4: Subjective Norm (SN) positively affects preference for video
games (PVG).
H5: Subjective Norm (SN) positively affects learning
opportunities (LO).
3.5. Experience
Another crucial factor is the amount of
experience parents has with video games. But this variable
reintroduces the debate over how to measure experience (Bajaj
& Nidumolu, 1998; Thompson, Higgins,
& Howell, 1994). Often, the debate centers on the
need to transcend frequency of use as a measurement approach.
Skoien and Berthelsen (1996), for example, also included the depth
of usage in their Parental Experience with Computers scale.
Similarly, Bourgonjon et al. (2010) conceptualized experience with
video games as a combination of time dedicated to video gaming,
playing a diversity of games and identification with game
culture.
Based on previous research that found a
negative correlation between playing games and concerns about media
violence (Nikken &Jansz, 2006), it can be
hypothesized that experience with video games will negatively
affect the perceived negative effects of playing video games. In
addition, experience is expected to lead to a higher valuation of
game related learning opportunities (Skoien &
Berthelsen, 1996). Furthermore, since mediation research has found
that experience might lead to higher levels of involvements
(Nikken& Jansz, 2006; Valcke et al., 2010), it can
be hypothesized that experience with games will also lead to a
preference for using videogames in the classroom.
H6: Experience negatively affects perceived negative effects of
playing video games (NEG).
H7: Experience positively affects learning opportunities
(LO).
H8: Experience positively affects preference for video games
(PVG).
3.6. Personal innovativeness in the domain of
information technology
In his study about innovation diffusion,
Rogers (1995) referred to innovation as a behavior and the time
when an individual adopts an innovation, classifying individuals
into five categories based on their rate of adoption: innovators,
early adopters, early majority, late majority, and laggards. He
also revealed that individuals’ innovation decisions are partly
based on personal characteristics. Innovative people appear to be
more curious and risk-taking by nature (Rogers, 1995; Rosen, 2004),
making it more likely that they will seek information about a
technology (Robinson, Marshall, & Stamps, 2005; van
Raaij & Schepers, 2008) and even actually use it
(Hartman & Samra,2008; van Braak, Tondeur,
& Valcke, 2004). In order to measure an
individual’s level of innovativeness based on self-report rather
than on observing the time of adoption, Agarwal and Prasad (1998)
developed the personal innovativeness in the domain of information
technology scale (PIIT) – and defined it as “the willingness of an
individual to try out any new information technology” (p. 206).
This conceptual definition encompasses both a dispositional, as
well as an intentional dimension. A high level of personal
innovativeness in the domain of IT has been compared to “a form of
openness to change” (van Raaij & Schepers, 2008, p.
841), “pure curiosity and bravery” (Lu, Yao, & Yu,
2005,p. 260), “a tendency to be the first using a new technologies”
(Walczuch, Lemmink, & Streukens, 2007, p. 208), and
the likely seeking out of“new, mentally, or sensually stimulating
experiences” (Tatcher & Perrewé, 2002, p. 385).
Based on this theoretical background, it can be hypothesized that a
person with a higher level of innovativeness will be more inclined
to experiment with new types of technology, and thus – given the
many characteristics of video games that make them both cutting
edge technology and sensory stimulating – have more experience with
video games as well.
H9: Personal innovativeness in the domain of IT (PIIT)
positively affects experience.
3.7. Gender
A lot of research on technology integration
in teaching practice has centered on gender differences.
Information technology use and implementation is often considered a
“male domain”. For example, male students show more positive
attitudes toward computers and report less problems when using IT
(Reinen & Plomp, 1997), and male teachers indicate
that they integrate the computer more often in their teaching
(Tondeur, Valcke, & van Braak, 2008). Although
these gender differences might be gradually disappearing for
mainstream information technology applications like word processing
(Volman & van Eck, 2001; Volman, van Eck,
Heemskerk, & Kuiper, 2005), it seems worthwhile to
examine potential gender differences in the use of new and
unfamiliar types of technology as they seem to persist (Shapka
& Ferrari, 2003). A potential
explanation can be found within recent research on consumer
innovativeness. Several authors present evidence that men generally
express higher levels of innovativeness than woman (Tellis, Yin,
& Bell, 2009) – with an exception for the dimension
of innovativeness targeting functional use (Vandecasteele,
2010).
Studies on video game player behavior have
uncovered a trend also found in technology integration research.
Despite most studies report that males are more interested in video
games, play video games more often and for longer periods, and
display a greater diversity in their choice of games (Bonanno
& Kommers, 2005; Bonanno & Kommers,
2008; Cassell & Jenkins, 1998; Jean, Upitis, Koch,
& Young, 1999), the gender gap is slowly
diminishing (Bryce & Rutter, 2002; Hartmann
& Klimmt, 2006). A possible explanation for the
remaining gender gap is that females dislike both the amount of
combat and violence, as well as the stereotypical way woman are
portrayed in video games (Boyle &Connolly, 2008;
Facer, 2003; Hartmann & Klimmt, 2006). Studies that
focus on parents and their regulation of children’s media usage
reach similar conclusions: mothers display greater support for
media regulation than fathers (Rojas, Shah, &
Faber, 1996; Scharrer & Leone, 2008).
Based on this theoretical basis, it can be
hypothesized that males are more experienced in playing games than
females, and that the effect of gender on experience is partly
mediated through innovativeness, as video games are a type of
technology that is not meant to increase efficiency or
effectiveness in functional tasks. Female issues with the –
sometimes – violent and stereotypical content of video
games,combined with their support for media regulation, lead to the
additional hypothesis that gender will affect the perceived
negative effects of playing video games.
H10: Being male affects personal innovativeness in the domain of
IT (PIIT) positively.
H11: Being male affects experience positively.
H12: Being male affects perceived negative effects of playing
video games (NEG) negatively.
3.8. Research model
The research model under study in this
article is depicted in Fig. 1.
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4. Method
4.1. Research design
Data were gathered with a survey, containing
questions focusing on demographics of the parents, and scales
measuring the variables in the research model. Firstly, the data
from the parents were explored using descriptive statistics.
Secondly, structural equation modeling (SEM) was applied to test
the research model with latent variables against the observed data,
thus providing insight in the interrelations between the different
predictors for parents’ acceptance of video games.
4.2. Participants
To examine parents’ acceptance of video games
as teaching and learning tools in their children’s classroom, 858
parents of secondary school students (age 12 to 20; at least one
currently enrolled) were involved in the study. Trained
interviewers visited families with secondary school children in all
provinces of Flanders – the Dutch speaking part of Belgium –
presenting them a paper questionnaire. The parents were
volunteering to participate in research about their educational
beliefs. Variety in the following variables was pursued when
selecting the families in the convenience sample: the gender of the
child, the age, the school type and school grade. In each family,
one parent was asked to participate. Informed consent was obtained
from all parents, who were promised to remain anonymous. Of the
respondents, 61.3% (n 526) was
female and 38.7% (n 332) was
male. On average, the parents were 46 years old
(SD 4.3). More than 95.3% of
the parents hold a diploma equal to or higher than secondary
education.
4.3. Measures
Firstly, the respondents filled in questions
about demographical information (age, diploma, and gender, coded 0
for female and 1 for male). Secondly, parents responded to the main
part of the survey, which consisted of scales measuring the
different constructs of the model. The items for preference for
video games, learning opportunities, and experience with video
games were based on previous research (Bourgonjon et al.,2010). The
scale for personal innovativeness in the domain of IT was derived
from Agarwal and Prasad (1998). For the concept of subjective norm,
an existing scale (Fishbein & Ajzen,1975) was
slightly adapted to account for the specific context of DGBL.
Finally, in close collaboration with an expert panel consisting of
two independent and experienced researchers and two methodologists,
a new scale was constructed to measure parents’ perceived negative
effects of playing video games. The adapted and new scales can be
consulted in Appendix A. Respondents were invited to rate their
agreement with a statement in each item on a 5-point Likert scale,
ranging from 1 – “Strongly disagree” – to 5 – “Strongly agree”.
4.4. Psychometric quality of the instrument
An examination of the psychometric quality of
the research instrument was necessary, because the questionnaire
comprised of(a) existing scales that were used with a different
target group, and (b) an adapted and newly constructed scale. A
split sample approach was adopted, by performing exploratory factor
analysis (EFA) on the first split-half dataset
(n 429) and confirmatory factor
analysis on the second dataset (n=429). The subject to item ratio
for both split-half samples was 15:1.
4.4.1. Exploratory factor analysis
Exploratory factor analysis was performed on
the first split-half dataset to examine whether these data reflect
the suggested factor structure. With a large enough sample size, a
Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy of .899 and
the Bartlett’s test of sphericity being significant (p
4.4.2. Confirmatory factor analysis
The stability of the factor structure was
confirmed by CFA (in AMOS 17 - AMOS Development Corporation,
1983–2008). As presented in Appendix D, fit measures that are the
least affected by large sample sizes (see for example RMSEA and
CFI) meet the requirements for good fit
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(Fan, Thompson, & Wang, 1999),while the other fit
indices are acceptable (Byrne, 2001; Garson, 2009), indicating a
reasonable match between the data model and the theoretical model.
In addition, all items load sufficiently high on the latent
variables, with pattern coefficients between .67 and .91. Two
exceptions are found, the items NEG 5 and PIIT 3, loading .42 and
.53 respectively. It was decided to remove the NEG 5 item, as it
was not validated in previous research, but to maintain the PIIT 3
item, in order to preserve the original scale of personal
innovativeness in the domain of IT (Agarwal &
Prasad, 1998 - in which PIIT 3 loaded .63).
4.4.3. Reliability analysis
As a final step in the validation procedure,
reliability analysis was performed, building on the data of the
entire sample (N= 858), to examine the internal consistency of the
scales. The results indicate that all scales exhibit high internal
reliability: learning opportunities(a= .91), experience (a= .89),
personal innovativeness in the domain of IT (a= .82), negative
effects of playing video games (a= .85),subjective norm (a= .83),
and preference for video games (a= .91).
5. Results
5.1. Descriptive statistics
From the descriptive statistics (Table 1), it
is clear that the majority of the parents has no experience with
video games. The mean score on each of the five items measuring
experience is lower than 2 (on a 5-point Likert scale). Only 119
parents (13.9%) like to play video games. No correlation was found
between experience and age (r = .076, p
Considering digital game-based learning,
parents believe that their children are in favor of the idea of
using games in the classroom(M= 3.17, SD=1.06, t=4.83,
df 857, p 8.80, df= 857,p
5.2. Model testing
Since the preliminary analyses pointed out
that the instruments are valid and reliable, the hypothetical model
could be tested against the model reflected in the data. Structural
equation modeling was conducted in AMOS 17. The results show an
acceptable fit between the data and the hypothesized relationships
between the different variables (Table 3). A graphical
representation of the model including the path coefficients and
percentage of explained variance is depicted in Fig. 2. This model
explains 59% of the variance in the dependent variable: preference
for video games. In addition, all hypotheses were confirmed (Table
4).
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6. Discussion
The results of the descriptive statistics
show that a minority of the parents has experience with playing
video games. The findings complement a large body of studies about
parental regulation of children’s media usage that report a lack of
knowledge about video games (Byron, 2008; Kearney &
Pivec, 2007; Subrahmanyam, Kraut, Greenfield, &
Gross, 2000), but at the same time, these self-reported figures
contradict the often made suggestion that the majority of gamers
are middle aged woman playing games on the internet (Gee, 2003).
One explanation was given by Gee (2003) himself, who pointed out
that this group does not consider itself as gamers. De Schutter and
Vanden Abeele (2010) confirmed these findings for elderly people.
Other possible explanations are that parents differ from
non-parents (Sneed & Runco, 1992), or that the
respondents had problems with the interpretation of the concept
“video games”. The instruction given to the parents when filling in
the survey, was to think of video games “in general”. It is
therefore possible that parents mainly thought about video games
that received a lot of media attention, such as video games with a
deviating content. It could be interesting, in a follow up study,
to consider the potential effect of motion sensor based gaming
(such as Nintendo’s Wii, Sony Playstation’s Move and Microsoft’s
Kinect) – consumer market products geared toward large audiences,
and focusing more on social gaming – on both parents’ experience
with and beliefs about games (Olson, 2010) as it has been shown
that providing teachers with a Wii can alter their attitude toward
game-based learning (Kenny & McDaniel, 2009).
The descriptive statistics also show that
parents express rather negative beliefs about video games and are
reluctant when it comes to using video gaming in educational
settings. The parents indicate that they are indeed influenced by
the negative image of video games as portrayed in the popular media
and while they do consider some of the advantages (learning
opportunities), their preference for video games remains low. These
mixed feelings toward the effects of video games are in line with
previous research (Nikken & Jansz, 2006;
Skoien& Berthelsen, 1996; Sneed &
Runco, 1992). It is important to point out that the parents filled
in the questionnaire, when thinking about their own adolescent
children, since Sneed and Runco (1992) found that parents think
more negatively about the effects of games when they focus on their
own children.
The current results present empirical grounds
that the fear of teachers concerning parental acceptance of DGBL is
real. However, the path model also helps to find directions to do
something about this. For example, offering parents hands-on
experiences with video games could be a useful approach to reorient
their beliefs about the negative effects, as there is a clear
negative effect from experience on the perceived negative effects
from video gaming. While it appears that the common belief that
negative media messages hinder the acceptance of digital game-based
learning holds true (Byron, 2008), the perspectives about “learning
opportunities” seem to be the single best predictor of parents’
preference for video games. When parents accept that video games
foster learning opportunities, like experimenting with knowledge,
they adopt a more positive attitude toward the use of video games
in the classroom. These findings support the idea that parents
could benefit from projects that raise awareness about games in
general, and DGBL in particular (Byron, 2008; Funk, Brouwer,
Curtiss, & McBroom, 2009). Recent research has
started focusing on the development of frameworks to aid parents in
selecting age and learning appropriate video games (Hong, Cheng,
Hwang, Lee, & Chang, 2009), however, in order to
effectively correct certain biased perspectives, training in media
and game literacy could be necessary as well (Byron, 2008).
The model shows that parents are not
indifferent to what other people think about gaming. Their
perception about the learning opportunities offered by video games
is strongly affected by what others give as advice (e.g., school
teachers and experts). Subjective norm was found to be the best
predictor for learning opportunities, explaining a larger
proportion as compared to the impact of negative media messages or
their own experiences with video games. These findings about the
subjective norm extend the research that attributes major
importance to the visibility of DGBL and its enthusiastic
forerunners (Williamson, 2009) to the case of parental acceptation
of school-based learning with video games.
Despite the fact that several authors suggest
that subjective norm only affects behavioral intention in formal
and mandatory settings(Venkatesh & Davis, 2000;
Venkatesh, Morris, Davis, & Davis, 2003), the
results of the present study underpin the importance of subjective
norm in parents’ acceptance of video games in the classroom.
Earlier research has shown that subjective norm often is a
significant driving force for acceptance of technology when the
latter is perceived as innovative (Hsu & Lu, 2007).
Therefore, it is likely that the effect found in this study will
diminish as soon as parents are more acquainted and more
experienced with video games (Hu et al., 2003).
英文论文 & 翻译" TITLE="孙加梅 英文论文 & 翻译" />
英文论文 & 翻译" TITLE="孙加梅 英文论文 & 翻译" />
The results of the path analysis tests showed
that gender did not affect parents’ experience with commercial
video games in a direct way.Rather, an indirect effect was found
via innovativeness. Fathers report to be more innovative than
mothers, which is in line with the result of numerous other studies
focusing on gender differences in technology use (Venkatesh
& Morris, 2000). Considering the research that
shows that gender does affect the game playing experience in
students (Bourgonjon et al., 2010), we have to consider the
hypothesis that the
importance of gender diminishes with the age of the respondents
(Morris, Venkatesh, & Ackerman, 2005).
7. Limitations and conclusions
This article builds and elucidates a model to
describe and explain parental DGBL acceptance. Based on a survey of
858 parents with at least one child in secondary education (age
12–20), it was found that this model is reliable and valid for
explaining parental beliefs about games and DGBL. The model helped
to test 12 hypotheses about the interrelation between gender,
personal innovativeness in the domain of information technology,
game experience, negative effects, learning opportunities and
subjective norm. The model explained 59% of the variance in
parental preference for video games.
While the descriptive results depict a very
pessimistic picture about parental support for digital game-based
learning, the model also points out that parents could benefit from
receiving specific information. The latter can be derived from the
fact that parents base their acceptance decisions mainly on their
evaluation of the game related learning opportunities. The latter
evaluation is, in turn, influenced by opinions of their children,
the teachers and experts. In addition, it might be valid to give
parents hands-on experiences with computer games. This is expected
to correct rather single-sided negative perceptions about video
games and develop a better understanding of the potential learning
opportunities that are linked to using games in the classroom.
Nevertheless, the results of the present
study should be treated with some caution due to a number of
limitations. First, a cross-sectional approach was adopted, based
on a semi-stratified convenience sample. Therefore, caution is
advised when trying to generalize these findings to a broader
population. Second, the survey builds on self-report instruments to
study behavior, attitudes and beliefs. Third, the study focused
both on general video game acceptance and digital game-based
learning. This might have introduced response bias. A number of
parents indicated that it was not always easy to think of video
games “in general”. Therefore, future research could focus on
specific beliefs concerning specific types of video games.
Conducting this kind of research across the different types of
video games would most likely provide a more fine-grained analysis
of what constitutes parental acceptance of DGBL. More background
information of the parents and their families could also be
considered (number of children, gender of the children, parental
involvement in the child’s schooling). In addition, the data for
this study was gathered in Flanders only. It might be worth
exploring whether measurable differences in parental perceptions on
the use of games in education exist based on location and society
values as well (for example differences between European, North
American and Asian parents).
Appendix A. Items by construct (the items are translated out of
Dutch)
Negative effects of playing video games – Incidents of gun violence
in our country, as well as
abroad, have started a debate about violence in video games.
According to popular media, the offenders were influenced by video
games. For example, the two boys that caused a massacre in
Columbine by the games Doom and Counter-Strike, and Hans Van
Themsche by Grand Theft Auto. What do you think about these
media
messages?
英文论文 & 翻译" TITLE="孙加梅 英文论文 & 翻译" />
英文论文 & 翻译" TITLE="孙加梅 英文论文 & 翻译" />
英文论文 & 翻译" TITLE="孙加梅 英文论文 & 翻译" />
父母对数字游戏化学习的接受度分析
摘要：
在本篇关于数字游戏化学习的研究中，可能父母的消极观念经常被作为在教室中进行游戏的一个障碍。教师、学生和政策制定者似乎受到父母对教室内进行游戏这种想法的影响。因此，去研究这些父母对游戏的信仰是非常重要的。目前研究开发和验证一个路径模型去解释和预测父母对他们孩子在教室中进行视频游戏的接受度。对至少有一个孩子受中等教育的858位父母进行调查，发现这个模型是可靠而有效的，总的来说，研究结果表明：通过模型包含的有关学习计划、主观规范、感知到的游戏的消极影响、视频游戏经历、个人创新性和性别的假设，在父母对视频游戏的接受度中59%的方差可以被解释。
关键词：交互式学习环境；教育媒体；教育学问题；中等教育
1、介绍
一个重要的研究机构把视频游戏与现代学习理论联系起来,特别是认知科学的见解(Gee,
2003 and Paraskeva
et al., 2010)。视频游戏改善学生动机(Burguillo,
2010,
Kebritchi
et al.,
2010 and Malone,
1980)，刺激深度学习和创造性思考(Eow
and Ali,
2009 and Papert,
1980)，超越学科界限(Squire,
2004)并且提供了强有力的和有意义的学习环境(Shaffer,
2006)。基于在“数字游戏化学习”（DGBL）上的文献综述Van
Eck (2006)区别了把游戏合并进学习进程的三种方式：“让学生从头（scratch）创建游戏，让教育者和/或开发者从头创建教育游戏来教学生学习，并且将商业现成的游戏进课堂(p.
57)”。
然而,关于有效性DGBL的实证研究是稀缺的、零碎的并且往往相互矛盾(Hays,
2005,
Papastergiou,
2009 and Tobias
and Fletcher, 2008)。多种因素构成这些相互矛盾的结果。当前的研究强调,大多数这些因素似乎源于在教室内游戏实施的困难(Egenfeldt-Nielsen,
2004)。因此,研究人员开始关注不同的障碍,在教育中这些障碍阻碍了视频游戏的直接使用。然而,一个关键问题在于，当关键人物在一个教学环境学习时，研究人员是否使用一个足够宽泛的方法。
到目前为止,很少有人注意到父母的位置。尽管如此,父母在学校系统中扮演重要的角色。他们的参与范围从承担一个学校和家庭环境间仅起沟通桥梁作用的角色,在决策成员的理事会,到在实施教学过程中偶尔的伙伴关系(Epstein,
2001,
Kong,
2008 and Mooij
and Smeets, 2001)。因此，Hattie（2009）中的元分析概述是毫不奇怪的，父母的参与被视为影响学习性能的一个关键变量。Hattie报道了（基于716项研究）一个平均效应大小d
=.51(2009,
p. 61)。
对于父母对于视频游戏的接受度是不太清楚的,除了在几个级别父母的信仰可能非常有影响力。首先,
可能父母的消极信念被不希望在教室里使用视频游戏的教师报道列为一个主要论点(Williamson,
2009)。其次,父母关于在家里玩的视频游戏和规则的信仰深刻影响了学生在学习和教学环境中是如何看待视频游戏的(Scharrer&Leone,2008)。第三,父母的信仰已经作为一个论据,用于公共政策制定者限制孩子接触带有潜在的有害内容的视频游戏(Bijvank
et al.,
2009 and Kutner
et al., 2008)。因此这是值得注意的,父母接受视频游戏在研究议程上并不高,当然关系到数字游戏化教育。因此这是值得注意的,父母接受视频游戏在研究议程上并不高,当然关系到数字游戏化教育。然而,
事情开始改变，自2009
BECTA研究“电脑游戏、学校和年轻人”标志着父母的接受作为进行进一步教育研究的一种重要领域(Williamson,
2009)。
通过对858名中学生家长做关于一般情况下使用视频游戏和特别地在教室里使用视频游戏的调查研究，呈现了一个具有代表性的结果，本文响应号召去研究父母有关DGBL的信仰。在教室里使用游戏在这里指的是那些在DGBL内的方法，实际上DGBL关注的是在教室里玩视频游戏。基于先前建立和验证的模型,提出了一个解释父母对于游戏化学习接受度的模型。接下来,对该模型的理论基础被检测，该模型的适合度依靠从父母那收集来的数据来检验。
2、文献综述
2.1 父母关于游戏的信仰
父母有关信息技术的信仰几乎独与媒体相联系被研究:主要通过调查,研究人员试图找出父母的风格和规则如何影响儿童和青少年的媒体使用(Mesch,
2009 and Valcke
et al., 2010)。在这个研究团体中,视频游戏被分析作为一种特殊的案例,部分是因为游戏是被玩而不是看
(Bogost, 2007
and Turkle, 1984 )，并且因为游戏体验经常与同龄人分享而不是父母。例如,后者是与看电视相比较更经常发生在一个普通的房间（Bickham
et al., 2003和 Nikken
and Jansz, 2006）。鉴于这些特点,这也就不奇怪,研究得出与电视或其他媒体相比父母感觉不那么了解视频游戏的结论(Nikken
& Jansz,
2006)。
两种类型的父母信仰在文献中采用。似乎父母把良好和不良影响的媒体和视频游戏区分开来。(Nikken
and Jansz, 2006,
Skoien
and Berthelsen, 1996和 Sneed
and Runco, 1992)。除了承认游戏能有积极的效果,如增强认知思维技能,父母表达担忧关于(a)孩子玩视频游戏和其他活动之间的平衡,(b)内容的游戏,(c)潜在的有害影响,(d)媒体策略(Kutner
et al.,
2008)。他们照看孩子游戏习惯的策略或多或少地像传统媒体技术,从完全反对和限制,超出规则设置，到来共同玩和谈论游戏(He
et al., 2010,
Kearney
and Pivec, 2007,
Kutner
et al., 2008,
Nikken
and Jansz, 2006,
Scharrer
and Leone, 2008 和Skoien
and Berthelsen, 1996)。
2.2
在教育中父母对游戏的信仰
在一个教育背景下,信息技术整合研究传统上把家庭环境作为基础去扩展超出教室的学校活动(Blanchard
and Oliver,
1999 and Kong
and Li, 2009)。然而,一方面教师和父母的愿望和另一方面现实间有一个大的区别:“家用电脑特别为游戏服务-游戏似乎与学校议程没有关系”
(Kerawalla
& Crook, 2002, p.
753)。
考虑到前,本文将关注父母对一般游戏的信仰,特别是DGBL。理论基础是建立在两个模型之上，这两个模型有助于描述和解释个人的行为倾向:理性行为理论(TRA
- Fishbein & Ajzen, 1975)和技术接受模型
(TAM - Davis,
1989)。多年来,两种模型都经过了广泛的研究，目的是去找到在各个领域往往很难整合信息技术的原因。前者的理论TRA表明，个人的预期行为由他们感知自己行为的态度和感知社会采取行动的压力来预测。后者模型,TAM,特别注重信息技术的情况。由于两个用户的信念:感知有用性和感知易用性，该模型解释了人们的行为意图。基于这些理论,本文的研究试图构建一个折衷模型去预测和解释在教室父母对视频游戏的接受。在目前的研究中有了严重的适应,不仅对于事务的一致性，也去考虑个人、背景、技术和任务特性(Mathieson
et al.,
2001 and McFarland
and Hamilton, 2006)。例如,因为在教室里使用视频游戏的决定不是取决于父母本身,因此使用传统的行为意向、有用性和易用性TAM概念是不可能。因此,本文咨询了带有统一游戏的文献和技术接受研究去找到一个替代的方法(Bourgonjon
et al., 2010,
Ha
et al., 2007,
Hsu
and Lu,
2004 and Wu
and Liu, 2007)。
3.
研究模型和假设
3.1
因变量:视频游戏偏好
为研究在一所学校环境中对数字游戏化学习的接受情况，一个有用的概念是视频游戏偏好(PVG)。它源于
Hsu and Lu (2007)，Hsu
and Lu描述偏好来衡量“用户积极参与的感受的程度(在在线游戏社区)”(p.1648)。为了去调查在教室里学生对于视频游戏的接受情况，Bourgonjon
et al. (2010)增加了一个赞成游戏化学习的预期行为部分。这与Skoien
and Berthelsen (1996)去研究人们是否真的愿意遵照他们关于游戏的信仰的建议相符合。在这篇文章中偏爱视频游戏可以被定义为“关于游戏学习积极情绪和在教室中视频游戏预测选择”
(Bourgonjon
et al., 2010, p.
1147)。
3.2
学习机会
学者和教育者把视频游戏作为某些当代学习理论操作性翻译。(Egenfeldt-Nielsen,
2007,
Gee,
2003,
Papert,
1980,
Shaffer,
2006 and Squire,
2004)。换句话说,对于学者和教育者视频游戏的主要特性是他们培养学习的机会。“感知学习机会”这个概念的由Bourgonjon
et
al(2010)介绍，正是为了研究在教室里人们如何看待这些使用视频游戏过程的结果。作者把感知学习的机会与感知有用性相比较——Davis(1989)的一个概念，在使用某种技术类型的产品结果上，Davis更专注于工作绩效。父母对于视频游戏有用性的接受是指潜在的视频游戏来增加学生的性能(例如,在学生的成绩作为反映)。然而,感知学习的机会指的是父母相信在教室里使用视频游戏将提供他们的孩子学习的机会的程度。
考虑两个父母关心良好的教育和他们明确对于信息技术促进学习的偏好(Kerawalla
and Crook,
2002 and Kong,
2008)。
从逻辑上推理，父母相信在教室里使用视频游戏为孩子们提供了学习的机会的程度将高度关联和预测对视频游戏的偏爱(Kong
and Li,
2009 and Skoien
and Berthelsen, 1996)。
H1.（感知）学习机会（LO）正面影响视频游戏偏爱（PVG）
3.3
玩视频游戏的消极影响(NEG)
视频游戏的价值受到许多争论(McAllister, 2004
),在这些争论中大众媒体发挥重要作用。在过去,媒体信息对视频游戏主要集中在潜在的负面影响,并急切地引用游戏研究持有的视频游戏负责健康问题——从肥胖(Kautiainen
et al.,
2005 and Stettler
et al., 2004)到使用游戏控制器造成的损伤(Rushing,
Sheehan, & Davis,
2006)——当然也负责脱敏和攻击行为(Anderson
and Bushman, 2002,
Anderson
and Dill, 2000, Colwell and Payne,2000和Uhlmann
and Swanson, 2004)。然而,研究人员不同意关于攻击性行为的假设(Freedman,
2001 and Goldstein,
2001)。这个争论似乎——dixit
Nature——“由于过激的言辞和夸大的索赔而混乱” (A
calm view of video violence, 2003, p.
355)。
不出所料,父母似乎警觉到这些媒体信息通过指出父母需要关注孩子玩游戏的类型，经常直接把父母的责任作为目标。Skoien
and Berthelsen (1996)
发现，媒体对于玩视频游戏的潜在有害影响的关注是影响父母游戏信仰的一个重要来源。由此可见,他们关于玩视频游戏的潜在负面影响的信仰(NEG)将深远的影响他们D对DGBL的接受。
父母对游戏的负面影响的信仰与他们对学习机会的感知之间的关系没有那么直接。Squire
(2002)认为，“面对游戏研究一个基本的顾虑是如果游戏没有促进或“教”暴力,那么研究者怎么会声称他们可能对学生的认知发展有一个持久的影响?”(Unpacking
game play, para.
1)。然而,尽管这两个构造可能事实上是指学习，但是关于可能后果的信仰仍然可以有非常大的矛盾。
H2.玩视频游戏的负面影响(NEG)对视频游戏偏爱呈负面影响(PVG).
H3.
玩视频游戏的负面影响(NEG)对学习机会呈负面影响(LO)。
3.4
主观规范
理性行为理论(Fishbein
& Ajzen,
1975)和随后的计划行为理论(Ajzen,
1991)都包括主观规范——被作者定义为“对他很重要的大多数人认为在问题中他应该或不应该执行这种行为的个人感知”
(Fishbein
& Ajzen, 1975, p.
302)——作为人们行动意图的一个直接预测。这种假设可以追溯到Triandis(1971)的工作,他说人们受到关于什么他们应该或不应该做消息的影响。然而,主观规范的一般影响并不总是在文献中被证实。一个有前途的再定位理论是主观规范在案例的初步接受中具有更深刻的影响,在这种情况下,人们还没有经历新技术和行为(Hu
et al.,
2003 and Triandis,
1971)。视频游戏可能被认为一个这样技术的例子,如预期的那样,主观规范似乎对接受在线视频游戏似乎是一个很好的预测(Hsu
& Lu,
2004)。除了主观规范对人的意图的直接影响,也有可能通过个人信仰系统存在间接影响。这由Venkatesh
and Davis (2000)表明，他认为，人内化了参照物的信仰并且使它成为他们信仰体系的一部分。
H4.
主观规范(SN)对视频游戏(PVG)呈正面影响。
H5.
主观规范(SN)对学习机会（LO）呈正面影响。
3.5
经历
另一个关键因素是父母与视频游戏的数量经验。但是这个变量重新引入了如何测量经验的辩论(Bajaj
and Nidumolu,
1998 and Thompson
et al., 1994)。通常,争论主要集中在需要超越使用频率作为测量方法。例如，Skoien
and Berthelsen (1996)
还包括在他们父母带有电脑规模经验的使用深度。Bourgonjon et
al.(2010)概念化视频游戏的经验作为致力于视频游戏的一个时间的结合,扮演了一个多样性的游戏和游戏文化认同。
基于先前的研究发现,玩游戏和媒体暴力的担忧呈负相关关系(Nikken &
Jansz,2006)。它可以假设视频游戏的经验将对感知视频游戏的负面效应呈负面作用。此外,经验预计将导致有关游戏相关学习机会的更高估价(Skoien
& Berthelsen,
1996)。
此外,因为媒体研究已经发现,经验可能会导致更高水平的关系(Nikken
and Jansz,
2006 and Valcke
et al., 2010)，它可以假设游戏经验也会导致在教室里偏爱使用视频游戏。
H6.
经验对感知视频游戏的负面影响产生负面作用(NEG)。
H7.
经验负面影响学习机会(LO)。
H8.
经验负面影响视频游戏偏好(PVG)。
3.6
在信息技术领域的个人动机
在他的研究中关于创新的扩散,Rogers(1995)提到创新作为一种行为和当一个人使用一种创新时将个人基于他们的采样率分成五类:创新者,早期的使用者,早期的多数派,后期的多数派,落后者。他还透露,个人的创新决策是部分基于个人特征。创新的人似乎有更多的好奇和冒险天性(Rogers,
1995 and Rosen,
2004)，他们将更可能去寻求一种技术信息(Robinson
et al.,
2005 and van
Raaij et al., 2008)并且甚至在实际上使用它(Hartman
and Samra,
2008 and van
Braak et al., 2004)。基于自我报告而不是基于观察采用的时间去测量一个人的创新性水平，Agarwal
and Prasad (1998)
开发了在信息技术规模领域的个人创新精神(PIIT)——并把它定义为“个人去尝试任何新的信息技术的意愿”
(p.206)。这个概念的定义包括一个意向的和一个有意的维度。IT领域里一个高水平的个人创新性被比作“一种开放的态度面对改变”
(van
Raaij & Schepers, 2008, p.
841)、“纯粹的好奇和勇敢”
(Lu,
Yao, & Yu, 2005, p.
260)、“首次使用新技术的倾向”
(Walczuch,
Lemmink, & Streukens,
2007, p. 208)和可能寻找“新地、心理上的或感官上刺激的经历”
(Tatcher
& Perrewé, 2002, p.
385)。基于这个理论背景,它可以假设带有一个更高层次的创新精神的一个人会更倾向于新技术类型的实验,并且因此——考虑到视频游戏的许多特点，这让他们去掉两个前沿技术和感官刺激——也有更多视频游戏经验。
H9.在IT(PIIT)领域中的个人创新精神对经历有正面影响。
3.7 性别
在教学实践中大量的技术整合研究都集中在性别差异。信息技术的使用和实现通常被视为“男性域”。例如,男学生对电脑展示更多积极乐观的态度并且使用IT时报告有较少的难题(Reinen
& Plomp,
1997),，男性教师表明他们在他们的教学中更经常整合计算机(Tondeur,
Valcke, & van Braak,
2008)。虽然这些性别差异可能由于主流信息技术应用程序像文字处理而逐渐消失,但是由于他们去坚持在使用新的和不熟悉的技术类型中检查潜在的性别差异，这似乎是值得的。在最近关于消费者创新性的研究中，一个潜在的解释可以被发现。几个作者提供了证据，男人比女人通常表达高水平的创新性(Tellis,
Yin, & Bell,
2009)——例如，创新性目标功能使用的维度(Vandecasteele,
2010)。
关于视频游戏玩家行为的研究已经发现了一个趋势，这个趋势在技术整合研究中也被发现。尽管大多数研究报告,男生对视频游戏更感兴趣，玩视频游戏更多和更长,并显示他们选择的游戏有一个更大的多样性(Bonanno
and Kommers, 2005,
Bonanno
and Kommers, 2008,
Cassell
and Jenkins,
1998 and Jean
et al., 1999)，性别差距正在慢慢减少(Bryce
& Rutter, 2002;
Hartmann & Klimmt, 2006)。对于女性剩余的性别差距，一个可能的解释是女性不喜欢战斗和暴力,以及在视频游戏中描绘女性的老套的方式(Boyle
and Connolly, 2008,
Facer,
2003 and Hartmann
and Klimmt, 2006)。研究关注父母和他们对孩子媒体使用的监管得出相同的结论:母亲对媒体监管表现出更大的支持，而不是父亲(Rojas
et al.,
1996 and Scharrer
and Leone, 2008)。
基于这一理论基础,可以推测,男性玩游戏比女性更有经验,经验上性别的作用部分是通过创新性被调停,因为视频游戏是一个类型的技术,不是为了提高效率或在功能任务上的效力。女性问题带有——有时——暴力和老套的视频游戏内容,加上她们对于媒体监管的支持,导致这个额外的假说,性别会影响玩视频游戏感知到的负面效应。
H10.男性在IT(PIIT)领域正面影响个人创新性。
H11.男性正面影响经验。
H12.男性正面影响玩视频游戏（NEG）感知到的负面影响。
3.8 研究模型
本篇文章的研究模型在Fig.1中被描述。
4.方法
4.1 研究设计
调查中的数据被收集,包含关注父母的人口统计资料问题和研究模型中测量变量的权衡。首先,使用描述性统计探索了从父母那得来的数据。其次,结构方程建模(SEM)应用于试验带有观测数据的潜在变量的研究模型,从而在不同预测间的相关性中为父母接受视频游戏提供洞察力。
4.2 被试
为了检查父母对视频游戏在教室里作为教学工具的接受情况,858名有中学学生(年龄12至20;目前至少一个被登记)的家长参与了这项研究。受过训练的面试官访问了在弗兰德斯所有省份中带有中学孩子的家庭——the
Dutch speaking part of
Belgium——呈现给他们一张问卷。父母都是自愿参加这项关于他们教育信仰的研究。当选择家庭便利样本时，以下变量的多样性被追踪:孩子的性别、年龄、学校类型和学校等级。每一个家庭,一个父母被要求参加。获得了所有的父母的同意,他们承诺要保持匿名。受访者的61.3%(n
= 526)是女性和38.7%(n = 332)是男性。平均而言,父母是46岁(SD =
4.3)。超过95.3%的父母持有等于或高于中等教育的文凭。
4.3 步骤
首先,被试填写关于人口信息问题(年龄、文凭、性别、编码0为女性和1为男性)。其次,父母回应调查的主要部分,这包括测量模型不同结构的规模。视频游戏偏好、学习机会和视频游戏经验这项项目是基于以前的研究(Bourgonjon
et al., 2010)。个人创新性等级在IT领域里可追溯到
Agarwal and
Prasad (1998)。对于主观规范的概念,现有规模
(Fishbein & Ajzen, 1975
)是稍微适应于解释特定的DGBL背景。最后,在与一个由两个独立的和有经验的研究人员和两个方法学家组成的专家小组密切合作中，构造了一个新的规模去衡量父母感知到的玩视频游戏的负面效应。这个改编的新规模在附录一中可以被咨询。受访者被邀请去评估他们的协议，李克特量表上每一项中带有一条声明,从1
-“强烈不同意”到 5 -“强烈同意”。
4.4 工具的心理测量质量
研究工具的心理测量质量的检查是必要的,因为问卷包括（a）被用于不同的目标群体的现有规模和(b)一个改编的新构造规模。一个分割样本被采用,通过在第一个分割一半的资料组(n
= 429)进行探索性因素分析(EFA)和第二个资料组(n =
429)进行验证性因素分析。两项分割一半样品的比例是15:1。
4.4.1 探索性因子分析
探索性因素分析在第一次分裂一半的资料组中被进行去检查是否这些数据反映了建议的因素结构。一个足够大的样本大小,一个关于0.899采样充分性的Kaiser-Meyer-Olkin(KMO)测量和Bartlett的球形测试是显著的(p
数据证
明适合因素分析。主轴把斜旋转轴作为因素计入被执行(
Conway
and Huffcutt, 2003,
Costello
and Osborne,
2005 and Fabrigar
et al., 1999)。在附录B中描述的结果表明,该理论6个因素的结构可以被重建。总共，在项目中6个因素解释了超过70%的方差。此外,该项目因子载荷都超过了0.40的标准(Stevens,
1992)。在第二或额外的其他因素中没有一项反映高因子载荷。因素间的相互联系在附录C中被报告(Fan,
Thompson, & Wang,
1999)。
4.4.2验证性因子分析
因子结构的稳定性通过CFA(in
AMOS 17 -
AMOS Development
Corporation,
1983–2008)被验证。像附录D显示的，至少被大的样本数量(see
for example RMSEA and CFI)影响的指数测量满足了好的拟合指数的要求(Fan,
Thompson, & Wang,
1999)，然而，其他拟合指数是可以接受的(Byrne,
2001 and Garson,
2009)，这表明了数据模型和理论模型间合理的匹配。另外，所有项目负荷足够高的潜变量,模式系数在0.67到0.91之间。两个异常发现,项目
NEG 5和PIIT
3,符合分别为0.42和0.53。这被决定移除NEG
5项,因为它在之前的研究中没有被确认,但维持PIIT
3项,为了保留在IT领域里原规模的个人创新性(Agarwal
& Prasad, 1998 - in which
PIIT 3 loaded .63)。
4.4.3
信度分析
作为验证过程的最后一步，建立在整个样本数据的基础上(N =
858)进行了信度分析,去检查量表的内部一致性。结果表明,所有量表显示了高度的内部可靠性:学习机会(α=.91)、经验(α=
.89),在IT领域个人创新性(α=
.82),玩视频游戏的负面影响(α=
.85),主观规范(α=
.83),偏爱视频游戏(α=.91)。
5. 结果
5.1
描述性统计
从描述性统计(Table
1)可以看出，很明显大部分父母没有视频游戏经验。每个五项测量经验的平均分数低于2(在李克特量表上)。只有119名家长(13.9%)喜欢玩视频游戏。经验和年龄之间不存在相关性(r
=−.076,p
描述性统计的结果显示,少数家长有玩视频游戏经验。研究结果补充了大量关于父母监管孩子媒体使用的研究,孩子的媒体使用缺乏关于视频游戏的知识(Byron,
2008, Kearney and Pivec, 2007> and Subrahmanyam et
al., 2000 ),但同时,这些自我报告数据与经常提出的大多数玩家都是在互联网上玩游戏的中年女人的意见相矛盾
(Gee, 2003 )。Gee
(2003)自己给出了一种解释,他谁指出这组不把自己当做是游戏玩家。Schutter and Vanden
Abeele(2010)证实了这些对于老年人的发现。其他可能的解释是,家长与家长不同(Sneed &
Runco, 1992),或被试有与“视频游戏”概念的解释有关的问题。在填写该调查时提供给家长的指导是考虑“一般”视频游戏。因此,父母可能主要考虑收到了很多媒体关注的视频游戏,如带有一个偏离内容的视频游戏。在后续的研究中,考虑基于游戏的运动传感器的潜在影响可能是有趣的(
(such as Nintendo’s
Wii, Sony Playstation’s
Move and Microsoft’s
Kinect)——消费者市场产品面向大量观众,更多关注社交游戏——包括父母的经验和关于游戏信仰(Olson,
2010),因为它已被证明,提供教师一个Wii可以改变他们对于游戏化学习的态度(Kenny &
McDaniel, 2009 )。
在描述性统计也表明,父母表达了关于视频游戏的负面信仰和不愿意在教育领域中使用视频游戏。父母表明他们确实是受到在大众媒体中被描绘的视频游戏的负面形象的影响，并且尽管他们考虑到一些优势(学习的机会),但是他们对于视频游戏的偏好仍然很低。这些影响视频游戏的复杂感情符合先前的研究(Nikken
and Jansz, 2006,
Skoien
and Berthelsen,
1996 and Sneed
and Runco, 1992)。需要指出的是,当想到自己的青春期孩子时，家长填写问卷,,因为Sneed
and Runco (1992)发现,当他们专注于他们自己的孩子时，家长考虑到更多负面的游戏影响。
当前的结果表明了经验性的理由：老师害怕父母接受DGBL是真实的。然而,路径模型也有助于找到做此类事情的方向。例如,提供给父母带有视频游戏的实践经验可能是一个有用的方法来调整他们对于负面影响的信仰,因为从感知视频游戏负面影响的经验中获得了明显的负面影响。虽然似乎普遍认为负面的媒体信息阻碍对于数字游戏化学习适用的接受(Byron,
2008)，关于“学习机会”的观点似乎是对父母偏爱视频游戏的最好预测。当父母接受视频游戏促进学习的机会时,如试验知识,他们采取一种更加积极的态度在教室里使用视频游戏。这些发现支持这一观点,父母可以从项目中受益,该项目提高对一般游戏的意识,特别是DGBL
(Byron, 2008 and Funk et al.,
2009)。最近的研究已经开始关注开发框架来帮助父母选择在年龄和学习上适当的视频游戏 (Hong, Cheng, Hwang,
Lee, & Chang,
2009),然而,为了有效地纠正某些偏见的观点,在媒体和游戏识字中的训练也可能是必要的(Byron,
2008)。
该模型表明,父母并非不关心别人怎么想游戏。他们由视频游戏提供的对于学习机会的知觉被别人给的建议强烈影响(如，学校教师和专家)。发现主观规范是学习机会的最好预测因子,与负面媒体信息影响和自身的视频游戏经验相比，其解释了一个更大比例的影响。主观规范的这些发现扩展了本研究，本研究把重要性归咎于DGBL的能见度和它的热情先驱(Williamson,
2009)的案例——家长赞同学校内使用视频游戏进行学习。
尽管事实上,几个作者表明,主观规范仅在正式和强制场所影响行为意向((Venkatesh and Davis, 2000 and Venkatesh
et al., 2003),在父母对在教室内进行视频游戏的接受研究中，目前研究的结果支持主观规范的重要性。早先的研究已经表明,当后者视为创新时，主观规范通常是技术接受的一个重要的驱动力(Hsu
& Lu, 2007)。因此,只要父母更了解和体验视频游戏，本研究发现的这个影响就可能会减少(Hu
et al., 2003)。
路径分析测试的结果表明,性别没有以一种直接的方式影响父母对于商业视频游戏的。相反,一个间接效应通过创新精神被发现。父亲报告比母亲有更多的创新,这与在技术使用中关注性别差异的众多其他研究结果是符合的(Venkatesh
& Morris, 2000)。鉴于研究表明性别确实影响学生的游戏体验(Bourgonjon et
al。,2010年),我们不得不考虑这个假设——性别的重要性随著受访者的年龄而减少(Morris, Venkatesh,
& Ackerman, 2005)。
7.
局限性和结论
本文构建和描述了一个模型去描述和解释父母对于DGBL的接受。基于一项对至少有一个孩子受中等教育(年龄12-20)的858位父母的调查，发现该模型是可靠的和有效的去解释父母对于游戏和DGBL的信仰。该模型有助于测试关于性别、信息技术领域的个人创新性、游戏体验、负面影响、学习机会和主观规范之间相互关系的12个假设。该模型解释了在父母偏爱视频游戏中的59%的方差。
然而关于父母对于数字游戏化学习的支持，这个描述性结果描绘了一个非常悲观的场景,该模型还指出,父母可以从接收特定的信息中受益。后者可以源于这个事实——父母把他们的接受决定主要建立在他们对与学习机会相关的游戏的评价之上。反过来,后者的评价受孩子、老师和专家意见的影响。此外,它可能是有效的给父母亲手体验电脑游戏。这被期望去改正单方面关于视频游戏的负面认知和开发一个更好理解的与在教室里使用游戏相关的潜在学习机会。
然而,由于数量的限制，目前的研究结果应该谨慎地对待。首先,采用横断面的方法,基于一个半分层的便利样本。因此,谨慎被建议当试图对更广泛的人概括这些发现。第二,调查建立在自我报告工具上去研究行为,态度和信仰。第三,这项研究集中在通用视频游戏接受和数字游戏化学习上。这可能造成了反应偏差。一些家长表示,“一般”视频游戏并不总是容易想到的。因此,未来的研究将集中在有关特定视频游戏类型的特定信仰上。进行横跨不同类型的视频游戏的这种研究最有可能提供更细粒度的构成父母接受DGBL的分析。更多父母和他们家庭的背景信息也可以被考虑(儿童数量、孩子性别、父母参与孩子的教育)。此外,本研究的数据仅聚集在Flanders弗兰德斯。在父母对教育游戏的使用的观念中，基于位置和社会价值观，探索可度量的差异是否存在(例如欧洲、北美和亚洲父母的区别)可能是值得。
附录A .设立的项目(项目被用荷兰语翻译)
玩视频游戏的负面影响——枪击暴力事件在我国以及国外已经开始了一个暴力视频游戏的讨论。根据流行的媒体,罪犯受到视频游戏的影响。例如,在科隆比纳，通过游戏厄运和反恐精英,以及Hans
Van Themsche伟大的盗窃，两个男孩导致了一场大屠杀。你认为这些媒体信息怎么样？
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