research about educational games

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• Published: 21 January 2022

The effect of educational game design process on students’ creativity

• Derman Bulut   ORCID: orcid.org/0000-0002-6235-3923 1 ,
• Yavuz Samur   ORCID: orcid.org/0000-0003-4269-7099 1 &
• Zeynep Cömert   ORCID: orcid.org/0000-0002-1841-4194 1  

Smart Learning Environments volume  9 , Article number:  8 ( 2022 ) Cite this article

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In the 2020s, it is clear that children now spend most of their days in front of the screen. During screen time, playing games is one of the most important activities of children. However, technology is developing day by day and innovations are quickly becoming a natural part of life. Therefore, children now need to be creative people who produce innovation, rather than just consuming themselves with the digital content offered to them. For this reason, students need to improve their creative thinking skills. Also, they need guidance for producing with technology. Considering this circumstance, this research, which was aimed at 5th and 6th grade school students designed educational games in a blended learning environment, employed a single group pretest posttest experimental design research. At the beginning and end of the research, the creativity level of students was examined by using the Torrance Test of Creativity. The study tries to seek an answer to the following question: “How does the educational game designing process affect 5th and 6th grade students’ creative thinking development?”. As a result, it was determined that there was a statistically significant difference in the creative thinking skill scores of those who designed their own educational game. This result is tangible evidence that the game is not only a drill and practice activity but it also presents a creative thinking environment for students.

Introduction

With the twenty-first century introducing many innovations and conveniences into the mainstream of human living, it also presented challenges that need to be overcome. For example, as the borders between countries are disappearing, multiculturalism, being able to do multiple tasks at the same time, and most importantly, being able to think creatively, have become the most basic characteristics that define individuals living in this century. It is possible to say that creative thinking skills have become much more important for new generations, especially since creative thinking has been chosen as the innovative field for the 2021 International Student Assessment Program (PISA) by the Organization for Economic Cooperation and Development (OECD, 2019 ). Additionally, creative thinking skills come to the fore among the future transformative competencies that are determined (OECD, 2018 ; Vincent-Lancrin et al., 2019 ). What makes the creative thinking skill so important is the need for creative and innovative solutions in order to achieve the Sustainable Development Goals determined by the United Nations (UN, 2015 ). Therefore, it can be said that many countries have to aim for the new generation to develop creative thinking skills. Along with that educators and teachers need to design a new learning experience which aims to develop these skills. However, creative thinking skills is a multidisipliner content, that's the reason why designing this kind of learning experience is a complex procedure. While designing a learning activity for this skill, support can be obtained from the contexts that today's students are interested in. For example, digital games are a very popular issue among children (Cömert & Akgün, 2021 ). Because the children of today do not have the opportunity to play outdoors as much as their own parents due to unplanned urbanization, increasing population and security issues (Karsten, 2007 ; Samur & Özkan, 2019 ). That's the reason why, it can be argued that children start to get acquainted with digital games at an early age. According to Rideout ( 2017 ), children aged 0–2 play a digital game for 25 min every day, while children aged 5–8 amuse themselves with a digital game for 42 min every day. Similarly, children aged 8–12 relax playing games for about 90 min every day (Rideout, 2015 ). Therefore, as children get older, they spend more time playing digital games. Considering that digital technologies are used much more profusely in human life today, it seems likely that children's digital game playing time will increase even more.

On the other hand, families have become strangers to many of the digital games that stand out among the game preferences of children today. This situation induces anxiety for families, educators and experts. In addition, there are studies in the literature that suggest digital games having a bolstering effect on children's violent behavior and an adverse effect on their physical health (Carnagey et al., 2007 ; Swing et al., 2010 ). Naturally, these results instigate concern about digital games. However, there are also studies verifying that playing digital games with content suitable for the age of the child supports the development of many different skills such as problem solving, strategic thinking, time and resource management, large-small muscle harmony, verbal expression, and quick decision making (Blumberg & Fisch, 2013 ; Bunt & Gouws, 2020 ; Flynn et al., 2019 ; Majid & Ridwan, 2019 ).

Considering the constructive and supportive effect of games on the development of the individual, even before reaching the first quarter of the twenty-first century, the question of "Can digital games be used in education?" dissipated (Öztürk, 2007 ). As a concrete example of this situation, the use of games developed by teachers in accordance with the learning content or adapted to the learning environment can be given. A perusal of the literature yields many studies that report that game-based learning activities have a positive effect on variables such as academic achievement, class participation, motivation and attitude when compared to traditional methods (Becker, 2017 ; Khenissi et al., 2015 ). In fact, Mayer ( 2020 ) emphasizes the need for more in-depth research by stating that a saturation point has been reached in the studies comparing traditional methods and game-based learning activities in the literature. In other words, for today's educators, the question of "How can games be used more effectively in the learning-teaching environment?" must be answered. At this point, van Eck ( 2006 ) suggests that in addition to the games conceived by the teachers, game-based learning activities can be created by enabling students to design their own games. However, when the literature is reviewed, it can be found that the number of studies that explore students’ level of learning by designing games is quite restricted. For example, Robertson and Howells ( 2008 ) revealed in their research that when 10-year-old students designed their own educational games for eight weeks, success and motivation in the course increased. Similarly, Baytak and Land ( 2010 ) also ascertained in their research that developing their own educational game impacted positively on students' success and motivation. In addition, in the same research, it was demonstrated that the game design process also supported the formation of classroom culture and the cooperation of students (Baytak & Land, 2010 ). An ( 2016 ), on the other hand, revealed in his research with secondary school students that developing their own educational computer games improved students' multidimensional thinking skills. On the other hand, Ruggiero and Green ( 2017 ) described in their research involving students aged 14–17 that students' problem solving skills have improved. In addition, both Walfisz et al. ( 2006 ) and López and Fabricatore ( 2012 ) studies indicated that the creative thinking skills of university students who designed their own educational games improved. Lastly, Kalmpourtzis ( 2019 ) states that after the game design experience of preschool children, not only their creative thinking skills are supported, but also their skills such as harmonious and collaborative work.

The results of the studies discussed up to this point accentuate the positive effects of having the students create their own games on the formation of the classroom climate, the development of cooperation and problem-solving skills as well as their academic success. The positive effects stem from the fact that the game design is a process that requires interdisciplinary teamwork, multidimensional thinking and creativity. In addition, considering the society's need for individuals who not only consume the content offered to them, but also devise the content and produce added value (Tor & Erden, 2004 ), it becomes clear that assigning game design tasks to students turns out to be a potent implementation. However, in order to raise individuals who can innovate, it is necessary to cultivate creativity in education (Aktamış & Ergin, 2006 ). In the traditional education system, which is called the education system in which technological opportunities are utilized minimally, creative thinking skills are blunted by accepting that all students possess the same qualifications (Ngeow & Kong, 2001 ). Within the scope of this study, it is aimed to examine the effect of designing educational games on the development of students' creative thinking skills, taking into account the above-mentioned need. For this purpose, "(1) How is the effect of game design on the creative thinking skills of middle school 5th and 6th grade students?" and “(2) How is the effect of game design on the sub-dimensions (fluency, flexibility, elaboration, originality) of students’ creative thinking skills?” answers to the questions were sought. It is envisioned that the results obtained as a result of the research will present a roadmap to teachers and parents who will design learning activities to develop students' creative thinking skills.

Methodology

This section covers the research design, participants, application process, data collection tool and analysis process.

Research design

This study, which was carried out with the participation of secondary school 5th and 6th grade students, employed a single group pretest posttest experimental design research. It subsumed the steps of comparing and analyzing the measurements related to the study group before and after the experimental procedure in single-group pre-test post-test experimental design research (Büyüköztürk et al., 2016 ). The activities to be carried out within the scope of the study are designed as an after-school activity for volunteer participants. For this reason, the number of participants in the study is limited to 23 students.

Participants

This study was carried out with the voluntary participation of 5th and 6th grade students of a private school in Istanbul who were members of a "Game Design Club" that included 23 students, conducting their extra-curricular activities.

Application process

As a pre and post-test, Torrance Test of Creative Thinking (TTCT) Figural-A form was administered to the volunteering 5th and 6th grade students who agreed to participate in the research. After the pre-test application, the game design curriculum was followed for 14 weeks. With this curriculum, students designed games on three different platforms: (1) on paper, (2) Pixel Floors, and (3) Prototyping. After the completion of all learning activities in the curriculum, TCFT was applied to the students as a post-test. The products produced by the students as a result of this learning experience are presented in Figs. 1 , 2 and 3 . The research was completed in a total of 15 weeks, including one class-hour per week, pre-test and post-test applications.

Participants' game design product on paper

Participants' game prototype

Participants’ Pixel floors game design example

Data collection tool

Torrance Test of Creative Thinking, semi-structured observation and semi-structured interview form were employed within the scope of the research.

Torrance test of creative thinking

Consisting of a paper and pencil test, it measures creativity from different dimensions. The duration of the TorranceTest of Creative Thinking is approximately 75–80 min and incorporates two parts, verbal and figural (Aslan, 2001 ). Torrance Test of Creative Thinking figural-A activities 2 and 3 are employed for data collection and were applied by the researcher to the participating 5th and 6th grade students. In this study, the figural form A of the TCTT was employed and this was administered to the students who were urged to complete it in 30 min as a pre and post-test. Figural form A test comprises three different types of questions: Drawing Activity, Figure Completion Activity and Repeated Shapes Activity (Torrance, 1974 ). Additionally, within the scope of the study, the pre and post-test responses of the students to the figure completion are presented in Figs. 4 and 5 .

Pre-test responses of the figure completion

Post-test responses of the figure completion

While evaluating the activities of the test, the total scores of the participants in four different dimensions, namely, fluency, flexibility, originality and elaboration were calculated. Evaluation was carried out according to the criteria in the scoring guide for Torrance Tests of Creative Thinking, Figural Test, Booklet A (Torrance, 1974 ).

Semi-structured observation

The observation form was developed to determine the classroom learning behaviors of the students. For the observation form, the opinions of 2 faculty members and experts from various universities and faculties were taken. With this data collection tool, a group of 34 students were observed. The students were observed in the classroom where the application was made. The form was examined by field experts, corrections were made in line with their recommendations and the final version of the observation form was attained. With the observation form prepared by the researcher to be used in the follow-up evaluation phase, 23 students in the 5th and 6th grades were observed for 15 weeks.

Semi-structured interview

In this study, interviews were held with each student in order to get the opinions and suggestions of the game design workshop students about the game design course. Audio recordings of 10–15 min semi-structured interviews with 23 students in total were made. The data coded were reviewed and interpreted by the researcher.

Analysis process

In this section, the tests used in the analysis of research data, namely the Wilcoxon signed-rank test and the paired sample T-test, are explained.

Paired samples T-test

When the measurements of the dependent variable of the same subjects are taken before and after an experimental procedure, repeated measurements of the subjects over time are needed and these measurements are related (Büyüköztürk, 2010 ). The researcher assessed the change in the creative thinking skills of the students before (pre-test) and after (post-test) the program he applied, and investigated whether the observed change was significant, and such a repeated measurements pattern was obtained with the related samples t-test. Since the Kolmogorov–Smirnov test results should be taken into account in cases of large sample population, this test was used to decide normality. As a result of the Kolmogorov–Smirnov test, it was determined that the data showed normal distribution ( p  > 0.05).

In this section, the findings secured as a result of the statistical analysis applied to each subscale of the data obtained from the students participating in the research were presented and comments on these findings were included. First of all, the scores of the participants were analyzed with Kolmogorov–Smirnov test which verified that they showed a normal distribution ( p  > 0.05), and then t-test analysis was applied to the dependent sample groups. Table 1 presents the data for this process.

The results of the dependent sample test in Table 1 show that there is a significant difference between the pre- and post-experiment scores of the students from the Torrance Test of Creative Thinking ( p  < 0.05). In other words, according to the results, it is clear that the post-test scores were significantly higher than the pre-test scores. TCTT.

Then, in the statistical analysis of the collected data, the mean values and standard deviations of the fluency, flexibility, originality and elaboration scores of the students, which are the subscales of the TCTT scale, were found, and the normality assumptions were examined to understand whether there was a difference between the scores (fluency, flexibility, originality and elaboration). It was ascertained that the subscale scores of the participants also showed a normal distribution in line with the Kolmogorov–Smirnov test ( p  > 0.05) results. The dependent sample t-test was repeated in order to compare the mean scores of the students for the subscales of the TCTT scale, and the data related to this analysis are presented in Table 2 .

If the statistics presented in Table 2 are examined respectively, it might be determined that the students' post-test fluency mean scores were significantly higher than their pre-test fluency mean scores ( p  < 0.05). Then, when the flexibility scores were examined, it might be observed that the post-application scores of the students were significantly higher than before the application ( p  < 0.05). From this perspective, it was concluded that after the application, the students were able to think multi-dimensionally, they had no difficulty in evaluating the different items, and they were able to express their thoughts comfortably. When the statistics on the originality dimension, which is associated with the students' ability to think in detail, were analyzed, it was established that the post-application scores were statistically significantly higher than the pre-application scores, since p  < 0.05. Finally, the participants' pre- and post-application score averages regarding the elaboration dimension were explored. In the light of these examinations, the effect of the application was found to be significant in terms of the "Detailing" dimension ( p  < 0.05). Therefore, one finding validated was that the students made a statistically significant improvement in all sub-dimensions of the TCTT scale.

Findings from the observation form

During the implementation process of the research, 23 students were observed by the researchers using a semi-structured observation form for 14 weeks. According to the data obtained through observation, the students who voluntarily participated in this extra-curricular activity demonstrated positive behaviors during in-class equipment controls. Managing to keep the attention of the students at the same level throughout the lesson, the class teacher enabled the formation of a positive observation that the students assimilated the course material. During the lesson, it was observed that the students followed the lesson well and took notes.

Findings from the interview

Student opinions about the application process were documented using a voice recording system. Audio recordings were analyzed by the researchers after they were transcribed. In the answers obtained from the students, codes such as 1 k and 2e were given to the students in order to keep the identity information of the students confidential.

First of all, the question "What are your impressions about the game design application?" was posed to the students who participated in the interview. Themes and frequencies related to the analyzed data obtained from the answers given by the students are presented in Table 3 .

More than half of the students stated that the practice was both entertaining and pleasant, and that it contained instructive activities. Nearly half of the students indicated that they continued to participate in the practice with great enthusiasm without getting bored, that the content of the applied course was easy and understandable, and that they might recommend this course to others. They asserted that it was different from the games played in digital environments, and that the educational digital game used included Science course topics and instructive information. One student expressed that the game design course was different from the usual courses and therefore he had difficulty in adapting. The students were asked the question “ What did they like about the practice ?” The themes and frequencies related to the analyzed data obtained from the answers given by the students are presented in Table 4 .

It was observed that the students generally liked the facts that the course was not offered in form of lecturing, that the students' perspectives were sought after via video presentations and that game designing was recognized as a creative and collaborative effort. It was also discerned that some of the students especially liked the game activities at the end of the lessons and the opportunity to work as a group during the game design phase. Two of the students stated that they gained very interesting information about games and game design during the course.

The question “Would you like other lessons to be taught with educational games?” was put to the students and the themes and frequencies related to the analyzed data obtained from the answers given by the students are shown in Table 5 .

Most of the students advocated that learning other lessons that incorporate educational games can be both fun and easier to understand. Three of the participating students expressed the idea that they got used to the working order of other lessons and that processing other lessons with the help of educational games would distract their attention.

When the question “Which lessons would you like to study by playing games like this?” was put to the students, it appeared generally that it would be more entertaining to process the lessons they learned at school by playing digital games. They especially said that mathematics courses can be easier to grasp with the help of games. One of the students stated that physical activities in Physical Education classes can be both visual and more fun with games.

Finally, the views of the students about the improvement that the course contributed to their creative thinking skills were explored. The majority of the students indicated that their creative thinking skills improved compared to the pre-application. Two of the students declared that they did not think that their creative thinking skills had improved compared to the pre-application. Students who thought that their creative thinking skills improved reported that their ability to instantly generate ideas in the face of a problem in their social life and school environment was enhanced, their communication skills especially with their friends in school, and their ability to use different objects and things for different purposes were upgraded.

Discussion and conclusion

The results of this research exploring the effects of having an individual design his/her educational games on creative thinking skills was the increase in participants' post-test scores. Similar to the research of Meishar-Tal and Avital Kesler ( 2021 ), in this study, after the students designed their own educational games, when the pre and post-test scores were compared, a significant difference in favor of the post-test scores was established with the related sample t-test. Across the sample of 23 people, the post-test scores of creativity in the dimensions of fluency, flexibility, originality and elaboration were found to be significantly higher than the pre-test scores (t = 5,263, p  < 0.05). When the students' fluency scores, one of the sub-dimensions of creativity, were examined, their post-test scores were found to be significantly higher than their pre-test scores. The increase in fluency scores indicates a progress in students' ability to produce a lot of ideas on a topic (t = 4.298, p  < 0.05). Flexibility post-test scores, which is another one of the sub-dimensions of creativity, were found to be significantly higher than the pre-test scores (t = 3,708, p  < 0.05). This result demonstrates that students' abilities to bring different approaches to a problem has proliferated. When the originality scores, which is the third sub-dimension of creativity, were examined, the post-test scores were found to be significantly higher than the pre-test scores. This result reveals that students' thinking skills have advanced positively (t = 7.666, p  < 0.05). When the students' elaboration scores, a fourth sub-dimensions of creativity, were investigated, their post-test scores were found to be significantly higher than their pre-test scores. This result indicates that the upturn in students' ability to think beyond the box has improved constructively (t = 3,495, p  < 0.05). When the scores of 23 subjects in all 4 sub-dimensions of creativity were compared, it was ascertained that the increase in originality scores was higher than the other sub-dimensions (X = 21.30; 68.60). The increase in the originality dimension indicates that the students' ability to produce new, unusual and rare ideas has increased compared to the pre-application (Torrance & Goff, 1989 ).

At the end of the application, the students' opinion and satisfactions about the application process were registered via semi-structured interviews. Short interviews of 10–15 min were held with all the participants and these were audio-recorded. The students were queried mostly for their thoughts on the sub-dimensions of creativity, and their perceptions about the application following which the coding phase was initiated. In general, students reported that their creativity increased compared to before the application and they started to get positive results of this increase in their school and social life. The participants declared that they enjoyed the activity very much and demanded the inclusion of the game design workshop to the curriculum as a lesson. This finding proves that game-based learning is an important tool to be used in the lessons, especially for teaching subjects that are considered difficult to understand. Studies in the literature indicate that students display a positive attitude towards game-based learning. For example, Triantafyllakos et al. ( 2011 ) state that the educational game design process supports students' ability to develop rational solutions for the difficulties they encounter in the learning process. Similarly, Kafai and Peppler ( 2012 ) also emphasize that educational game design helps students to use their academic knowledge by transferring them to different situations. Also, Guha et al. ( 2013 ) state that the game design process is important for the development of communication skills, as it directs students to communicate with different individuals such as both their peers and field experts. Lastly, Baytak and Land ( 2010 ), who used game design to help students gain nutritional habits, resolved that students were positively motivated by the games they made to gain their eating habits at the end of the study. Considering this situation, games can be delineated as auxiliary materials for students to develop positive attitudes towards the course or learning content.

In addition, the results of the research on game-based learning denotes that game-based learning activities are more effective than traditional methods in terms of academic achievement, class participation, interest and motivation development (Bado 2019 ). When the designs of these studies are examined, it is observed that their purpose is to discern the difference between the effects of the games integrated into the learning environment by the teacher using pertinent applications and the effects of learning activities performed via the traditional methods on student achievement and motivation (Mayer, 2020 ). In addition, in these studies, games are used as a platform where the learning content is presented to the student or as a media that facilitates the learning behavior towards the learning goal. For this reason, the role of students within the scope of the research is limited to playing the game, in other words, they are not designers but consumers of the content offered to them. Considering all this, it is possible to surmise that different research designs are needed for research on game-based learning. Mayer ( 2020 ) advocates that as a starting point for researchers, establishing research questions for game design features or skill development of students may be beneficial for the development of the field.

According to current studies, in order for learning to be permanent, students must be involved by doing and living the experiences themselves during the learning practice (Merrill, 1991 ). In addition, the world now needs individuals who not only consume the content presented to them, but also produce the content and create added value, and who can think creatively and multi-dimensionally (Aktamış & Ergin, 2006 ; Tor & Erden, 2004 ). Therefore, instructional designs are required to entice students into productive processes. At this point, games have been preferred as an effective solution partner in numerous experimental studies. A limited number of studies revealed the presence of positive effects on the development of multidimensional thinking, creativity and communication skills of students who can design their own educational games (An, 2016 ; Baytak & Land, 2010 ; López & Fabricatore, 2012 ; Walfisz et al., 2006 ). Since the game design process requires interdisciplinary work due to its nature, the development of students' computer literacy, research and collaborative working skills are also supported in the educational game design process (Edmonds & Smith, 2017 ; Matuk et al., 2020 ). On the other hand, in the research conducted by Meishar-Tal and Avital Kesler ( 2021 ), it became apparent that the self-confidence and self-efficacy of the students who participated in the game design activities improved positively. Therefore, game design can be defined as an experience that supports the development of the individual in many different areas.

Research shows that both children and adolescents spend a significant amount of time playing digital games in their daily lives (Işıkoğlu et al., 2021 ). However, games are not limited to the activities that students prefer to have a pleasant time in the last few years. For example, when the university preferences of young people in the past years are examined, the enrollment rates of "game design" programs transcend most other programs (Student Selection and Placement Center, 2020 ). Similarly, it is observed that some programs within the scope of computer science such as user experience design, graphic design and digital product development prevail over others in massive open online course platforms (Coursera, 2020 ). In that sense, it is possible to say that today young people are interested in being the party that produces games. Therefore, providing more opportunities for this field that students are interested in and curious about will also lead to the recognition of talented young people in game design.

Suggestions

As revealed in this study, designing games subsumes development of creativity in multiple dimensions, not just in one. For this reason, there is a need for road maps prepared with a systematic perspective in order to raise individuals who can think creatively. For example, students can be asked to design educational games in areas such as mathematics, history and geography, and studies can be conducted to gauge whether their learning about those areas have increased. A study can be formulated by means of a questionnaire which reveals the motivations and attitudes of the students in the game design process. Within the game design process, similar studies can be realized by investigating not only the creativity of the students, but also their problem solving or critical thinking skills.

In addition, the development of technology offers numerous advantages to the whole world such as employing games for educational purposes and also making games and game design a part of curricula. Furthermore, this research has established that the applied game design process has a positive effect on students' creativity. The instructional design developed within the scope of this study can be generalized by applying it in more schools as an after-school activity. Professional development programs that support teachers' digital competencies can be enhanced and implemented so that teachers can better transfer the game-design course to students.

Finally, economic indicators around the world point out that technology companies are the most important drivers. In addition, with the 2020s, the investments made by technology giants in the game industry drew attention. For this reason, game design contents can be included in the curriculum both as a constructive step towards the national economy and to support the human capital of young people.

Availability of data and materials

This article was produced from Bulut's ( 2015 ) thesis titled “The effect of educational game design process on student's creativity”. As Supplementary Materials, the measurement tools used in the research have been uploaded.

Abbreviations

Torrance Test of Creative Thinking

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How to Use Gameplay to Enhance Classroom Learning

Research shows that using games in teaching can help increase student participation, foster social and emotional learning, and motivate students to take risks.

What happens when a gorilla goes into a battle with a brown hyena in an Australian rain forest?

Tanya Buxton’s high school biology students could find out as they embark on March Mammal Madness (MMM), a virtual game modeled after the annual NCAA basketball championship that aims to educate U.S. students about the importance of biodiversity and endangered species.

This is the second year in a row that Buxton has enrolled her Atherton, California, students in the tournament to deepen their understanding of global ecosystems while building community and camaraderie among peers.

Gameplay in school isn’t just about having fun though, say Buxton and other teachers, who are increasingly using games and gaming principles to enhance instruction. From Minecraft to the Game of Life and Werewolf , effective games like March Mammal Madness link content with low-stakes competition and can provide a more collaborative, engaging classroom experience—especially for students who may struggle to focus or find their niche in learning. During the pandemic, games have also provided an important outlet that keeps kids connected and motivated remotely .

These claims aren’t just anecdotal. According to research , using games in teaching can help increase student participation, foster social and emotional learning , and motivate students to take risks. One study of the popular multiple-choice quiz game Kahoot found that it improved students’ attitudes toward learning and boosted their academic scores. In addition, studies have found that virtual games can improve focus and attention for students with ADHD and help students with dyslexia improve spatial and temporal attention, which can translate into improved reading.

But games aren’t substitutes for other forms of learning. Like any educational tool, they need to be well-planned and integrated only when they’re relevant to the learning objectives.

Think of games not as Band-Aids to fix what’s broken in the classroom but as “a pedagogical approach that might help people think differently about what’s possible... limited only by a player’s imagination and by what a gaming set of rules allows,” says Antero Garcia , an assistant professor at the Stanford Graduate School of Education who studies the impact of technology and gaming on youth literacy and civic identities.

Want to integrate well-developed games or just a few gaming principles into your lessons? Here are some approaches to consider to make games a valuable teaching tool.

Test and Learn

In many games , players encounter scenarios that involve making in-the-moment decisions that let them quickly see the impact of their choices in a low-risk setting and then try (and try again) if they falter—skills that are valuable as they go through life, says Garcia.

Teachers, for example, can use role-playing games in the classroom to help students inhabit different perspectives and understand them as part of larger, holistic systems of thought, explains Matthew Farber, a former teacher and assistant professor at the University of Northern Colorado who studies the intersection of game-based learning and SEL. This system of thinking can become a good entry point for students to learn about their own agency as they weigh possibilities and consider alternate plans of action.

Because games are interactive—unlike books or movies that involve more passive consumption—they may also encourage students to explore new topics and approaches to learning that they otherwise would not consider, he says.

In the virtual game Alba: A Wildlife Adventure , for example, players launch mini-missions where they discover and protect species of endangered animals. Though students might not consider themselves adventurers or conservationists when they play the game, the low-risk setting can get them thinking about larger-scale impacts they could have in the real world, adds Farber. As a follow-up activity, students could conduct further research on animals they encountered or even take local nature walks to identify smaller ecosystems of local wildlife.

Even if teachers aren’t using a fully developed game in their class, they can use a process known as gamification , or weaving components of games such as points, leaderboards, and badges into lessons to boost students’ motivation. Because students get excited about the competition from earning badges or embarking on a quest, they tend to take more risks—and, in turn, learn from their mistakes, says Manju Banerjee, an associate professor and vice president of educational research and innovation at Landmark College in Putney, Vermont.

When students are researching a topic and conducting a literature analysis, teachers can design curricula to send them on a quest—instead of framing it as a typical assignment—or rethink assessment and “tell a student that he is at a ‘novice’ level rather than a grade of C-” to reduce academic pressure and encourage participation,” says Banerjee.

Learning in Disguise

Though it’s not the only reason to play games, the fun of gameplay is a critical part of why they are so successful with children, according to educators, who say that games can help disguise the learning of essential but challenging skills that kids might otherwise resist.

Teachers Joe Dillon and Marina Lombardo, for instance, created a poem-writing activity using Minecraft: Education Edition, in which students move through a maze and visit rooms to learn how to make their writing more descriptive. This game, inspired by Georgia Heard’s Six-Room-Poem activity , guides students through specific writing prompts, such as describing an object by focusing on the ambience of its surroundings.

Many games involve a compelling storyline that can quickly hook kids, which is what makes teaching with them so effective, explains Kendra Cameron-Jarvis, an instructional technologist for Buncombe County Schools in western North Carolina. In a game she designed called Discovering the Ancient Pyramids Adventure , sixth-grade students use Google Maps Treks—which provide a 360-degree view of the ancient structures—to go on a quest inside the Great Pyramid and solve a mystery while they explore. The game reinforces what they’re learning in class about ancient Egypt, she says.

“It’s kind of sneaky—they don’t realize they’re learning,” she says. “Kids are going to have a really good time, and they’re going to learn along the way.”

Teachers are also increasingly using apps and interactive game platforms like Kahoot and Quizizz —Kahoot says that more than 6 million teachers in 200 countries use its app to date—as fun formative assessment tools to ensure that students are on track with their learning, especially during the pandemic. Cameron-Jarvis says teachers are reporting that the platforms are so engaging, students frequently request to play them as part of their learning.

To increase the likelihood of all students participating, teachers can scaffold the difficulty levels of a game, calibrated to the current ability of the student. For students with special needs in particular, games can be beneficial because they disrupt traditional learning approaches and introduce opportunities for them to succeed where they have often struggled, says Banerjee, who has more than 29 years of experience in the field of learning disabilities.

Banerjee recommends that teachers use a myriad of low-stakes leaderboards—scoreboards that show the names and scores of participants—to highlight often-overlooked activities or skills in a way that recognizes contributions from students who typically do not perform well on traditional assignments. Teachers can give credit to the student with “the most creative calculation error” in a math class, for example, which not only makes learning more entertaining but acknowledges that all students can contribute meaningfully within a classroom.

Bringing Students Together

Though students can play games alone, most education games encourage players to collaborate effectively in teams—a building block for creating strong relationships and skills like cooperation that will be valuable as they progress through school and life, studies show.

These social interactions have been crucial during distance learning, according to Douglas Kiang, a high school computer science teacher at the Menlo School. Since schools went virtual last spring, Kiang has used Minecraft to give students a chance to interact with each other while learning social skills such as teamwork, negotiation, and respect for others. He also plays Among Us with his advisory group of about 10 students.

“I think games are useful in that respect for bonding and for allowing kids to socialize and communicate with each other,” says Kiang, who is a nationally recognized expert on game-based learning and technology integration.

Integrating more community-building elements into your classroom doesn’t always require playing a multiplayer video game, though, says Cameron-Jarvis. She suggests posting questions in the stream of popular tools like Google Classroom, Flipgrid, and Nearpod, and letting students respond, interact, and debate ideas. Other teachers have used Google tools to make their own versions of traditional games like Connect Four or Tic Tac Toe so that students get a brain break from academic learning.

The important part of using games in the classroom is trying not to gamify everything and to start small, using games with rules that students understand, says Cameron-Jarvis. The mix of games also matters, adds Farber, who says teachers should aim for variety. If you do let kids play games in class, he says, “think about the emotions those games evoke besides strategy and procedure.”

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Educational games for brain health: revealing their unexplored potential through a neurocognitive approach

Patrick fissler.

1 Institute of Psychology and Education, Clinical and Biological Psychology, Ulm University, Ulm, Germany

Iris-Tatjana Kolassa

Claudia schrader.

2 Institute of Psychology and Education, Serious Games, Ulm University, Ulm, Germany

Educational games link the motivational nature of games with learning of knowledge and skills. Here, we go beyond effects on these learning outcomes. We review two lines of evidence which indicate the currently unexplored potential of educational games to promote brain health: First, gaming with specific neurocognitive demands (e.g., executive control), and second, educational learning experiences (e.g., studying foreign languages) improve brain health markers. These markers include cognitive ability, brain function, and brain structure. As educational games allow the combination of specific neurocognitive demands with educational learning experiences, they seem to be optimally suited for promoting brain health. We propose a neurocognitive approach to reveal this unexplored potential of educational games in future research.

The Power of Educational Games

Playing games is one of the most popular leisure activities. For example, 59% of Americans play video games ( Entertainment Software Association, 2014 ). In contrast to watching a video or reading a book, video games afford interactive exploration and challenge due to user control, competition, levels of difficulty, and reward ( Malone, 1981 ; Lucas and Sherry, 2004 ). These design characteristics are essential for player’s motivation in games ( Sweetser and Wyeth, 2005 ).

Educational games aim to use this motivational quality of games for educationally relevant learning purposes (knowledge and skill acquisition). They are a branch of serious games which are defined as “games that do not have entertainment, enjoyment or fun as their primary purpose” ( Michael and Chen, 2006 , p. 21). Domains of learning include history, engineering, biology, math, and language ( Young et al., 2012 ; Wouters et al., 2013 ). For example, Re-mission aims to improve cancer-related knowledge ( Beale et al., 2007 ) and Twelve a Dozen 1 teaches mathematical operations. The number of these games increased exponentially since the 1990s in industry and in research ( Laamarti et al., 2014 ). A recent meta-analysis by Wouters et al. (2013) investigated the effectiveness of educational games in terms of learning. It included 77 studies with more than 5,500 participants and found that the games induced even more knowledge and skill acquisition than conventional instruction methods.

In this perspective article, however, we go beyond educational games’ effects on learning of knowledge and skills (i.e., plasticity of representations, cf. Craik and Bialystok, 2006 ; Lövdén et al., 2010 ). We review research which suggests the currently unexplored potential of educational games for brain health (i.e., plasticity of processes, cf. Craik and Bialystok, 2006 ; Lövdén et al., 2010 ) and propose a neurocognitive approach to reveal this potential.

First, we briefly review evidence for the beneficial effect of games with specific neurocognitive demands on brain health. Second, we depict the positive impact of educationally relevant learning experiences on brain health. Educational games enable both specific neurocognitive demands and educational learning experience. However, to our knowledge, there are currently no studies exploring their potential for brain health. Hence, in the last section, we propose a two-step neurocognitive approach to identify appropriate educational games that should be rigorously tested in randomized controlled clinical trials (see Figure ​ Figure1 1 ).

A neurocognitive approach to reveal the unexplored potential of educational games for brain health. In a two-step approach, a cognitive task analysis of educational games is followed by their validation through objective methods. This second step consists of a behavioral analysis to determine the association between game performance and neuropsychological test performance and/or a brain imaging approach to determine the recruited neuronal networks for task completion. Based on this approach, appropriate educational games can be selected to enable randomized controlled clinical trials that assess the efficacy of educational games to improve brain health markers including cognitive ability, brain function, and brain structure.

Gaming with Specific Neurocognitive Demands Promotes Brain Health

The supply-demand mismatch model of cognitive plasticity assumes that neurocognitive demands which are greater than the brain’s functional supply induce beneficial neuroplastic changes ( Lövdén et al., 2010 ). It is assumed that this supply-demand mismatch needs to be prolonged (at least more than several hours for small effect sizes) to overcome the inertia and sluggishness of plasticity ( Lövdén et al., 2010 ). Games can pose prolonged neurocognitive demands on working memory, perceptual speed, and episodic memory ( Baniqued et al., 2013 ). Thus, games might induce respective neurocognitive benefits. For example, games that heavily tap executive control processes such as working memory are thought to induce positive plastic changes in these cognitive processes and their underlying prefrontal network. Such changes may range from more efficient brain function ( Bavelier et al., 2012 ; Anguera et al., 2013 ) to benefits in brain structure such as increases in gray matter volume ( Kühn et al., 2013 ), cortical thickness ( Kühn et al., 2014 ), and neurotransmitter receptors ( McNab et al., 2009 ).

Current advances in gaming research support the supply-demand mismatch model (see Powers et al., 2013 ; Bisoglio et al., 2014 for a meta-analysis and a review). Cognitively demanding digital games as well as non-digital board and card games improved cognitive abilities ( Cheng et al., 2013 ; Fissler et al., 2013 ; Powers et al., 2013 ). These gaming-induced benefits comprised lower-order abilities such as visual perception ( Green and Bavelier, 2012 ) and higher-order abilities such as selective visual attention ( Green and Bavelier, 2003 ), switching ability ( Basak et al., 2008 ; Green et al., 2012 ; Strobach et al., 2012 ), sustained attention ( Anguera et al., 2013 ), short-term and working memory ( Basak et al., 2008 ; Anguera et al., 2013 ; Cheng et al., 2013 ), executive control ( Fissler et al., 2013 ), reasoning, and spatial abilities ( Feng et al., 2007 ; Shute et al., 2015 ).

For example, a study by Shute et al. (2015) showed that a commercial off-the-shelf game called Portal 2 with process-specific demands on spatial reasoning improved cognitive abilities even more than an intentionally-designed cognitive training program (i.e., repeated practice of standardized cognitive task paradigms for specific cognitive abilities with adapting difficulty levels, Gates and Valenzuela, 2010 ). In contrast to participants following the cognitive training program, Portal 2 players improved more in performance on non-trained problem solving and spatial ability tests. Furthermore, playing the video game was more enjoyable than the cognitive training program ( Shute et al., 2015 ).

Recent studies provide first insights into the neuronal underpinning of game-induced cognitive benefits. They range from plastic changes in brain structure to brain function. Kühn et al. (2013) found that playing Super Mario 64 increased gray matter of the right hippocampal formation and dorsolateral prefrontal cortex as well as of the cerebellum bilaterally. These brain areas are known to play an essential role in spatial memory, executive function, and fine-tuned motor skills. Using electrophysiological methods, Anguera et al. (2013) demonstrated functional brain benefits in the prefrontal cognitive control system through a dual-task driving game called NeuroRacer . Importantly, non-trained neuropsychological test performance improved through training and these gains were positively associated with the neurofunctional changes.

These experimental findings are backed by observational studies on the association of gaming with brain health markers. Frequent players of board games, in contrast to rare players, showed a reduced cognitive decline and incidence of dementia ( Verghese et al., 2003 ; Dartigues et al., 2013 ). Bavelier et al. (2012) investigated associations of brain function with gaming experience. Frequent gamers, in contrast to non-gamers, showed reduced neuronal recruitment of the fronto-parietal network in attentionally challenging tasks which indicates more efficient attentional processing. Finally, associations of gaming with brain structure were recently revealed. The duration of video gaming (hours per week) was positively associated with left prefrontal cortical thickness ( Kühn et al., 2014 ). The number of years spent video gaming was positively related to entorhinal cortex, hippocampal, and occipital gray matter volume ( Kühn and Gallinat, 2014 ).

In sum, these recent advances in gaming research emphasize the potential of cognitively challenging games to improve different markers of brain health ranging from cognitive ability, brain function, and brain structure to incidence of dementia. In the following, we will outline the impact of educationally relevant learning of knowledge and skills on brain health markers.

Educational Learning Experiences Promote Brain Health

Extensive learning experiences are thought to require prolonged activation of basic neurocognitive abilities such as executive control processes and long-term memory ( Park et al., 2014 ). These prolonged neurocognitive demands may induce positive plastic changes in accordance with the supply-demand mismatch model ( Lövdén et al., 2010 ). Successful learning experiences may enhance brain health by additional mechanisms as evidenced in animal models. Learning novel information increased survival of newborn cells in the hippocampus, an area that plays an essential role for episodic memory (see Shors, 2014 , for a review). In addition, intrinsic plasticity—a metaplasticity mechanism which changes the threshold for intrinsic neuronal excitability—is increased in the hippocampus through successful learning experiences (see Sehgal et al., 2013 , for a review). Furthermore, an enriched environment, which provides a range of learning opportunities, reduced pathological processes that are associated with Alzheimer’s disease ( Lazarov et al., 2005 ; Costa et al., 2007 ) and reduced the detrimental effect of Alzheimer’s disease-related Aβ oligomers on long-term potentiation ( Li et al., 2013 ).

A positive effect of educationally relevant learning experiences on markers of brain health has also been found in experimental studies with humans. Diverse interventions targeting at knowledge and skill acquisition improved cognitive abilities. Extensive learning experiences within a senior computer course improved working memory and episodic memory ( Klusmann et al., 2010 ). A digital-photography and quilting course improved episodic memory ( Park et al., 2014 ). A tablet course improved speed and episodic memory ( Chan et al., 2014 ) and extensive training of a foreign language enhanced associative memory ( Mårtensson and Lövdén, 2011 ). For example, Park et al. (2014) investigated the cognitive benefits of acquiring digital-photography skills by the use of a single-lens reflex camera and photo-editing software 15 h a week for 3 months. Compared to a group which completed activities that relied on activation of prior knowledge (e.g., listening to music, watching DVDs, or completing word-meaning puzzles), their episodic memory performance improved more ( Park et al., 2014 ).

In addition, extensive educational learning interventions induced plasticity in brain function (i.e., increased activity in the anterior cingulum, Carlson et al., 2009 ) and brain structure ( Draganski et al., 2006 ; Woollett and Maguire, 2011 ). The hippocampus increased in volume after extensive learning for medical exams ( Draganski et al., 2006 ) and after successful training for a London taxi driver license ( Woollett and Maguire, 2011 ).

This interventional evidence is backed by robust observational evidence regarding the relationship of education with brain health markers. Strong positive associations between years spent in education and risk for cognitive decline ( Valenzuela and Sachdev, 2006 ) as well as dementia ( Caamaño-Isorna et al., 2006 ) have been demonstrated. Low education represents the single most preventable risk factor for Alzheimer’s dementia. Worldwide, 19% of affected individuals are potentially attributable to low education ( Barnes and Yaffe, 2011 ). In addition, acquisition of skills such as speaking a second language and playing a musical instrument predicted a reduced future risk of cognitive decline ( Bak et al., 2014 ) and dementia (see e.g., Balbag et al., 2014 , for a population-based twin study). Furthermore, more years spent in education was associated with greater brain weight ( Brayne et al., 2010 ) and, in one pilot-study, also with lower markers of Alzheimer’s disease pathology ( Yasuno et al., 2014 ).

In the last two sections, we reviewed evidence for beneficial effects on brain health a) through gaming-induced neurocognitive demands and b) through educationally relevant learning of knowledge and skills. As educational games allow the combination of both, they seem to be optimally suited to promote brain health. However, to our knowledge, no study investigated the impact of educational gaming on brain health markers, yet. Hence, we propose a two-step neurocognitive approach in the following section that aims to reveal their unexplored potential.

A Neurocognitive Approach to Reveal the Potential of Educational Games for Brain Health

We have outlined above that games which induce learning of novel information and pose specific neurocognitive demands seem to be optimally-suited for brain health purposes. Clearly, not all educational games pose specific neurocognitive demands and appropriate games need to be identified from the large and growing market (cf. Wartella, 2015 ). We propose a two-step approach to elucidate the neurocognitive demands of educational games (see Figure ​ Figure1 1 ).

In the first step, a cognitive task analysis should be conducted for a wide range of educational games in order to determine the most appropriate cognitively challenging games for the more cost-intensive second step. Cognitive task analysis is a set of methods aiming to determine the cognitive demands to perform a task proficiently ( Militello and Hutton, 1998 ). We briefly depict one approach of a cognitive task analysis suited for educational games (cf. Baniqued et al., 2013 ) and exemplify this method with DragonBox2 , an educational game which aims to teach algebra in a fun way 2 .

First, a game diagram is created to determine the cognitively demanding tasks of the respective educational game. Here, an expert for the game (1) breaks the game down into its major tasks (usually between one and five tasks) and (2) determines which tasks pose substantial demands on cognitive abilities such as attention, speed or memory (cf. task diagram method; Militello and Hutton, 1998 ). In DragonBox2 , there is one major task (i.e., isolating a dragon captured in a box on one side of the screen, or in other words, solving an algebraic equation for the x ) and this task poses substantial cognitive demands.

Subsequently, neuropsychologists should rate the major tasks of appropriate educational games on their specific neurocognitive demands. The rating should be based on a validated taxonomy of neurocognitive abilities. For example, executive functions can be subdivided in three components including updating, inhibition, and shifting ( Miyake et al., 2000 ; Miyake and Friedman, 2012 ). Memory can be subdivided in the two components declarative memory and procedural memory ( Squire, 1992 ; Robertson, 2009 ). DragonBox2 poses high demands on executive function (frontal brain systems) and memory (mediotemporal and basal ganglia systems). For example, monitoring multiple items which are added and deleted from working memory through the mental application of algebra rules poses demands on updating; flexibly switching between multiple algebra rules which are cued by a given stimulus set requires shifting; selecting the application of non-dominant rules instead of more prepotent rules poses demands on inhibition; knowledge acquisition for the game’s 24 algebra rules taps declarative memory; skill acquisition regarding arithmetics, factorization, or the creation of parameters poses demands on procedural memory.

In the more cost-intensive second step, two objective methods—a behavioral and/or a brain imaging approach—can be used to substantiate the assumed neurocognitive demands revealed by the cognitive task analysis. In the behavioral approach, associations between game performance and performance in neuropsychological tests are assessed (cf Jaeggi et al., 2010 ; Baniqued et al., 2013 ; Rode et al., 2014 ). The pattern of the game-test associations enables the validation of the games’ neurocognitive demands.

The brain imaging approach aims to reveal the neuronal networks recruited by the games. Different brain imaging methods such as electroencephalography ( Anguera et al., 2013 ), near-infrared spectroscopy ( Ekkekakis, 2009 ), or functional magnetic resonance imaging ( Dahlin et al., 2008 ; Voss et al., 2012 ) can be used. Finally, after successful identification of appropriate educational games through behavioral analysis and/or brain imaging, long-term randomized controlled clinical trials should examine their effects on brain health markers (see Moher et al., 2010 , for methodological issues).

In this perspective article, we reviewed two lines of research that indicate an unexplored potential of educational games to improve brain health. First, games with specific neurocognitive demands and second, educationally relevant learning experiences positively impact brain health markers including cognitive abilities, brain function, and brain structure. Future research should use a neurocognitive approach to identify cognitively challenging educational games. These should be rigorously examined in randomized controlled long-term clinical trials regarding their effects on brain health.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank Laura Loy for her valuable and fruitful comments on the manuscript and Heather Foran for English proofreading.

1 http://www.bossastudios.com/games/twelve/

2 http://www.dragonboxapp.com/

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Game-Based Learning Experiences

Fostering intrinsic motivation in students.

While gamification is the art of embedding game mechanics into everyday learning, game-based learning is an experience that is embedded within a game framework. Keep reading to learn more about the benefits of game-based learning and how it can amplify learning across the curriculum.

What is Game-Based Learning?

Simply put, game-based learning means learning by playing a game. Since devices like iPads and Chromebooks became commonplace in schools, digital educational games have started appearing thick and fast.

In practice, this might be a one-off digital game designed to teach students a specific skill, allow them to try out a career role virtually, or transport them to an impossible time or location.

It could also be a learning platform that takes the form of a game, such as a Coding course with a linear or narrative structure and levels to complete. Games like these can take students on a longer journey over an entire course, a school year, or even follow them up through school, building on their profile and achievements.

5 Reasons Educators Turn to Game-Based Learning

1. they’re motivating..

A new report from Pew Research Center suggests that 47% of teachers think students show little or no interest in learning (and 58% in high school). The top reason teachers say students are struggling to stay engaged is lack of intrinsic motivation . Intrinsic motivation is what drives each of us to explore, ask questions, and succeed simply for the satisfaction and self-affirmation that it brings – and not because of the proverbial carrot and stick. While many gamification techniques rely on external motivators such as rewards and badges, true game-based learning is able to immerse students so deeply into an experience that their internal desire for accomplishment takes over, and they learn along the way.

2. They’re up-to-date.  

While textbooks remain a popular teaching resource, they don’t change with the times very often – games (especially web-based ones) are quick to update as new information is discovered, as trends develop, or as new practices are favored.

3. They’re familiar.  

Some educators may feel more at home with digital games than others, but students have shown a 38% increase in game playing outside of school since Oct 2020.   The rules, features and interfaces present in educational games are almost always grounded in classic gaming styles, and students take to them like ducks to water.

4. They’re experiential.

With game-based learning, students are learning to problem-solve, make decisions and think critically at the same time as absorbing the topical content. Consider a game which asks students to build the best habitat for an endangered creature. Not only are they analyzing the adaptations and needs of the animal, but they may also be: learning to use trial and error to achieve success; improving their computing skills; creating fair tests by controlling variables; taking on the role of a real career professional and developing an ambition for the future… the list goes on.

5. They’re personal.

Teacher workload and shortages is a constant concern. Games can differentiate content for the learner and allow the student to carve their own memorable journey through the learning. They can also provide real-time, personalized, visually engaging feedback to students immediately and suggest next steps. Inside the game, students have the safety to fail and try again, learning from their mistakes and testing their skills.

How Often Is Too Often?

Worried about screen time? That’s not surprising – research suggests that the average preschooler in the US spends just under two days a week using screens . By the time children are 15 years old, this jumps up to 4.5 days per week.

But no one is saying that the entire curriculum should be taught through a screen. You’re still the teacher: just as you might select a text extract to read, you can select game-based learning experiences that you see value in. For everything else, there’s always gamification, which can be integrated into your teaching without a single screen or device.

Game-based learning creates a game to help students learn a specific skill or information, and educators are infusing this type of experience into their lessons to reinvigorate their students. Some of the best learning can occur when it feels like play!

Learn More About Gamification!

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Articles on Educational games

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Review bombing is a dirty practice, but research shows games do benefit from online feedback

Christian Moro , Bond University and James Birt , Bond University

Home schooling is hundreds of years old – here’s what its history teaches us about learning through play

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Andrea Juan , Human Sciences Research Council

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Inez Harker-Schuch , Australian National University and Will J Grant , Australian National University

Playing ‘serious games,’ adults learn to solve thorny real-world  problems

Lawrence Susskind , Massachusetts Institute of Technology (MIT) and Ella Kim , Massachusetts Institute of Technology (MIT)

Which apps are educational and why? It’s in the eye of the beholder

Nicola Yelland , Victoria University

Can toys really be ‘educational’? Well that depends on the parents

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Natalia Kucirkova , The Open University

Brain training games won’t help children do better at school

Emma Blakey , University of Sheffield

BAFTA wins reflect British flavour in modern gaming

Nick Robinson , University of Leeds

Console yourself: videogames have social benefits

Edith Cowan University

Edu-games hit the market, but not all are are created equal

Dean Groom , UNSW Sydney

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Professor of Early Childhood Studies, The University of Melbourne

Associate Professor in Politics, University of Leeds

Manager, Educational Development, UNSW Sydney

Associate Professor of Science & Medicine, Bond University

Professor of Reading and Children’s Development, The Open University

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Associate Professor of Computer Games and Associate Dean Engagement, Bond University

Professor of Urban and Environmental Planning, Massachusetts Institute of Technology (MIT)

PhD Candidate, Massachusetts Institute of Technology (MIT)

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PhD candidate, Australian National University

PhD Candidate, Learning Design & Technology & Comparative & International Education, Learning Performances Systems Department, College of Education, New York Public Library

Research Assistant, Department of Education, Concordia University

Professor, Department of Education, Concordia University

PhD Candidate in Recreation and Leisure Studies, University of Waterloo

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Ready or not? Investigating in-service teachers’ integration of learning analytics dashboard for assessing students’ collaborative problem solving in K–12 classrooms

• Open access
• Published: 10 July 2024

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• Yiming Liu   ORCID: orcid.org/0000-0003-2604-7993 1 ,
• Xiao Hu 1 ,
• Jeremy Tzi Dong Ng 1 ,
• Zhengyang Ma 2 &
• Xiaoyan Lai 3  

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Collaborative problem solving (CPS) has emerged as a crucial 21st century competence that benefits students’ studies, future careers, and general well-being, prevailing across disciplines and learning approaches. Given the complex and dynamic nature of CPS, teacher-facing learning analytics dashboards (LADs) have increasingly been adopted to support teachers’ CPS assessments by analysing and visualising various dimensions of students’ CPS. However, there is limited research investigating K-12 teachers’ integration of LADs for CPS assessments in authentic classrooms. In this study, a LAD was implemented to assist K-12 teachers in assessing students’ CPS skills in an educational game. Based on the person-environment fit theory, this study aimed to (1) examine the extent to which teachers’ environmental and personal factors influence LAD usage intention and behaviour and (2) identify personal factors mediating the relationships between environmental factors and LAD usage intention and behaviour. Survey data of 300 in-service teachers from ten Chinese K-12 schools were collected and analysed using partial least squares structural equation modelling (PLS-SEM). Results indicated that our proposed model showed strong in-sample explanatory power and out-of-sample predictive capability. Additionally, subjective norms affected technological pedagogical content knowledge (TPACK) and self-efficacy, while school support affected technostress and self-efficacy. Moreover, subjective norms, technostress, and self-efficacy predicted behavioural intention, while school support, TPACK, and behavioural intention predicted actual behaviour. As for mediation effects, school support indirectly affected behavioural intention through self-efficacy, while subjective norms indirectly affected behavioural intention through self-efficacy and affected actual behaviour through TPACK. This study makes theoretical, methodological, and practical contributions to technology integration in general and LAD implementation in particular.

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1 Introduction

Collaborative problem solving (CPS) is a socio-cognitive process in which group members utilise their shared knowledge, experiences, and skills, and navigate through a series of steps to reach a mutually agreed-upon solution to a particular problem (Fiore et al., 2017 ; Graesser et al., 2018 ; Griffin & Care, 2015 ; OECD, 2017a ). Scholars and educators recognise CPS as a critical competence for the younger generation in the 21st century (Cukurova et al., 2018 ; Fiore et al., 2018 ). As a domain-general competence (Graesser et al., 2017 ; Greiff et al., 2014 ), CPS skills are essential in various active learning approaches (e.g., project-based learning, inquiry-based learning) (Song, 2018 ; Saleh et al., 2022 ) and prevail in diverse disciplines (e.g., language, mathematics, and computer science) (see review by Baucal et al., 2023 and Tian & Zheng, 2023 ). More educational and governmental initiatives worldwide, including the Programme for International Student Assessment (PISA), Assessment and Teaching of 21st Century Skills (ATC21S), and Educational Testing Service (ETS), have increasingly emphasised the importance of students mastering CPS competence (von Davier & Halpin, 2013 ; Griffin & Care, 2015 ; OECD, 2017a ). Students competent in CPS are likely to not only excel academically but also become better equipped to effectively address communication issues and navigate interpersonal conflicts in future teamwork scenarios (Fiore et al., 2018 ; OECD, 2017b ; Sun et al., 2022 ). To achieve successful CPS, students are required to engage both effectively and collectively in the processes of identifying and representing problems, planning, execution, and monitoring (Hesse et al., 2015 ; OECD, 2017a ). Cognitive and social skills play pivotal roles during CPS activities, enabling teams to coordinate and communicate effectively and pool individual knowledge, experiences, and skills, thereby arriving at better solutions more efficiently than when individuals work alone (Andrews-Todd & Forsyth, 2020 ; Care et al., 2016 ; Hesse et al., 2015 ). However, given the interactive, interdependent, and temporal nature of CPS (Swiecki et al., 2020 ), it is challenging for teachers to assess and support students’ CPS skills and performance at both individual and group levels during their actual instruction (Scoular & Care, 2018 ), particularly in classroom settings (Care & Kim, 2018 ; Martinez-Maldonado, 2019 ).

In recent years, well-designed games have gained recognition as suitable vehicles for assessing and fostering students’ higher-order skills, including CPS (see review by Qian & Clark, 2016 and Gomez et al., 2022 ). As an active learning approach, digital game-based learning creates an immersive and playful environment, attracting students’ attention and promoting their engagement in learning tasks, thereby facilitating them to stay focused on the learning objectives (Hsu et al., 2021 ; Kaimara et al., 2021 ; Stieler-Hunt & Jones, 2017 ). More importantly, as students interact with games and teammates, they generate a substantial amount of multimodal gameplay data, such as clickstreams and conversations (Sun et al., 2022 ; see review by Tlili et al., 2021a ). Such multimodal gameplay data can be captured, analysed, and visualised through learning analytics dashboards (LADs), providing teachers with meaningful and actionable information about students’ demonstration of higher-order skills and learning attainments (Chen et al., 2022 ; Lee-Cultura et al., 2023 ; Ruipérez-Valiente et al., 2021 ; Tlili et al., 2021b ). LADs, harnessing the power of both learning analytics and visual analytics (Sun & Liu  2022 ), can illustrate various metrics that reflect different aspects of students’ CPS. Not only do they display students’ individual skills and contributions to collaborative learning along with their changes over time (Hu et al.,  2022 ), but they also illuminate team performance and group dynamics during the collaborative learning processes (Liu et al.,  2024 ; Bao et al., 2021 ; Zheng et al., 2021 ).

In CPS contexts, teachers play a guiding role in facilitating students’ collaboration and problem solving (Griffin, 2017 ). With the assistance of LADs, teachers can monitor students’ CPS progression and evaluate individual contributions and team performance more accurately (Liu et al.,  2024 ; Martinez-Maldonado, 2019 ). This enables teachers to identify students who are struggling with CPS tasks or ‘gaming the system’ in a timely manner and provide actionable feedback as well as adaptive and personalised support (Chen et al., 2021 ; Huang et al., 2023 ). Teacher-facing LADs are widely regarded as effective tools that can aid teachers in facilitating students’ CPS practices (Kaliisa & Dolonen, 2023 ; Van Leeuwen et al., 2019 ). However, teachers’ sensemaking of the LADs relies on how they associate dashboard information with their own pedagogical decisions and actions (Van Leeuwen, 2019 ), and multiple factors can influence this sensemaking process. For example, existing studies (e.g., Zheng et al., 2021 ) have found that teachers often struggle with complex visualisations in LADs. Some have reported the misalignment between visual representations of LADs and teachers’ diagnoses (Li et al., 2022 ), whereas others have demonstrated that teachers might find it difficult to use LADs, suggesting the necessity of providing professional training and technological support for those working with LADs (Rienties et al., 2018 ).

Despite the substantial findings in LAD research, there exists a critical gap between the potential role of LADs designed for CPS assessments and their actual usage by teachers. According to person-environment fit theory (P-E fit theory), the degree of compatibility between a person’s individual characteristics and external environments can shape the person’s actual behaviour (Kristof-Brown et al., 2005 ; Kristof-Brown & Guay, 2011 ). Accordingly, this study posits that both teachers’ personal and environmental factors play critical roles in determining their usage behaviour of LADs for CPS assessments. Moreover, through reviewing previous literature on the P-E fit theory (e.g., Al-Fudail & Mellar, 2008 ; Chou & Chou, 2021 ; Dong et al., 2020 ; Govender & Mpungose, 2022 ) and determinants of teacher-facing LAD adoption (e.g., Kaliisa et al., 2021 ; Rienties et al., 2018 ; Van Leeuwen et al., 2021 ), this study identified several specific personal and environmental factors that may affect teachers’ LAD usage and constructed an integrated conceptual model (see Fig. 1 ). Specifically, teachers’ personal attributes include technological pedagogical content knowledge (TPACK), technostress, and self-efficacy, while the environmental factors include subjective norms and school support. In light of the potential of LAD for supporting teachers’ CPS assessments and the possible impacts of these factors on their LAD usage, this study aims to examine how these personal and environmental factors and their relationships shape the LAD usage intention and behaviour of K-12 in-service teachers in the classroom context of game-based CPS assessments.

Our paper is structured as follows: first, we define collaborative problem-solving, describe its prevalence in education across learning approaches and contexts, and introduce how educational games can develop and assess learners’ CPS competence. Then, we illustrate the potential of teacher-facing learning analytics dashboards (LADs) for supporting teachers’ assessment of learners’ CPS skills and problematize the gap between their potential and teachers’ actual usage. Next, we present our literature review on the affordances of teacher-facing LADs for facilitating computer-based collaborative learning and the person-environment fit theory, encompassing various environmental and personal factors influencing teachers’ technology integration. Then, we articulate our research aims, conceptual model and hypotheses, and our methodology for examining our model hypotheses and addressing our research objective. Next, we present the results of our analysis, including the structural and mediation effects of the environmental and personal factors on teachers’ LAD usage intention and behaviour. Finally, we discuss these results and make concluding remarks regarding the contributions of this study, its limitations, and our recommendations for future research.

2 Literature review

2.1 teacher-facing lads for computer-based collaborative learning.

Teacher-facing LADs function as a supportive tool, enabling teachers to assess and intervene in students’ learning processes effectively and efficiently based on timely visualizations (Van Leeuwen et al., 2019 ). These LADs provide fine-grained insights that empower teachers to understand, rationalise, and make informed decisions based on the complex data derived from student online learning trajectories and activities (Calvo-Morata et al., 2019 ; Li et al., 2022 ). Research has underscored the benefits of integrating LADs into computer-based collaborative learning. For instance, a study by Van Leeuwen et al. ( 2019 ) unveiled a teacher-centric LAD aimed at tracking students’ collaborative endeavours and providing indirect support within the classroom setting. The dashboard offers teachers an overview of students’ collaborative learning situations derived from computational analytics, assisting them in detecting students’ problematic learning situations. Kaliisa and Dolonen ( 2023 ) introduced university instructors to a LAD designed for online problem-oriented discussions. This dashboard, equipped with visualisations of team interaction and automated discourse analysis of students’ discussion content, facilitated teachers in interpreting students’ learning dynamics within collaborative discussions. While LADs were deemed beneficial for teachers to gain a deeper understanding of student learning and interactions within computer-supported collaborative learning environments, teachers might encounter multiple challenges when attempting to utilise LADs in their teaching (Zheng et al., 2021 ). For instance, Liu et al. ( 2023 ) found that teachers’ resistance to embracing LADs might result from a deficit in supportive knowledge and skills, such as data visualisation literacy, and possible stress and anxiety induced by technology adoption. Li et al. ( 2022 ) revealed that teachers viewed the complexity of visualisations from LADs and the inadequacy of LAD capabilities as barriers to interpreting their information. Thus, the identification of these challenges and the implementation of corresponding solutions are crucial in enhancing teachers’ capacity to integrate LADs into teaching practices.

2.2 Person-environment fit theory

Built on various theories and models of technology integration, previous studies have identified numerous factors that may facilitate or impede teachers’ effective use of LADs (e.g., Liu et al., 2023 , 2024 ; Li et al., 2022 ). Certain factors are tied to teachers’ personal attributes, encompassing their knowledge, skills, and literacy in relation to LADs, as well as psychological aspects like self-efficacy beliefs. On the other hand, some factors derive from external environments around teachers, such as the availability of school support or broader social conditions. To better conceptualise and situate these factors, we employ the P-E fit theory as the theoretical ground for this study. The P-E fit theory refers to the compatibility that arises when people and their environments are well matched (Kristof-Brown et al., 2005 ). It stresses that compatibility between individual and work environment characteristics influences behaviour and psychological functions, with a higher congruity associated with improved performance and increased productivity (Edwards et al., 1998 ; Kristof-Brown & Guay, 2011 ). In this study, the P-E fit theory offers a lens to investigate how individual and environmental factors influence teachers’ use of LADs for assessing and supporting students’ CPS skills. Past research has typically leveraged technology acceptance models (TAMs) to delve into various psychological drivers of technology adoption among teachers (Scherer et al., 2019 ). While both TAM and P-E fit theories underscore influential factors related to technology integration, P-E fit theory offers added value by clustering these factors and further clarifying the relationships between these clusters. In the following sections, we will elaborate on the personal and environmental factors influencing teachers’ technology integration into teaching practices.

2.3 Environmental factors: subjective norms and school support

Ajzen and Fishbein ( 1980 ) defined subjective norms (SN) as one’s normative belief that ‘specific individuals or groups think he should or should not perform the behaviour and his motivation to comply with the specific referents’ (p. 8). A systematic review conducted by Wijnen et al. ( 2021 ) highlighted the pivotal role of subjective norms in shaping teachers’ acceptance and adoption of technologies designed to foster primary school students’ higher-order thinking skills. Jeong and Kim ( 2017 ) found that teachers with a stronger sense of subjective norms were more inclined to utilise information and communication technologies (ICT) for instructional purposes in early childhood education. Shin’s ( 2015 ) study disclosed that a substantial proportion of elementary school teachers perceived the attitudes of administrators towards technology use as a vital determinant in achieving high-quality technology integration.

School support (SS) refers to material and psychological support provided by school administrators for teaching-related technology use (Chou & Chou, 2021 ). Empirical research has demonstrated that school support can facilitate teachers’ utilisation of technology (Atman Uslu & Usluel, 2019 ; Hew et al., 2017 ; Porter & Graham, 2016 ). For instance, Lam et al. ( 2010 ) discovered that secondary school teachers exhibited greater motivation and willingness to adopt technological innovations when they perceived their schools as being more supportive of their competence and autonomy. Koh et al. ( 2017 ) revealed that the primary school teachers’ integration of technology was fostered by peer support in teacher professional development activities organised by the schools. Regarding pre-service teachers, their intent to use technology was positively influenced by a range of facilitative conditions, such as the availability of infrastructure, technical assistance, and encouraging policies (Kaimara et al., 2021 ).

2.4 Personal factors: TPACK, self-efficacy, and technostress

Teachers’ technological, pedagogical, and content knowledge (TPACK) emphasises the affordances of using technologies to improve teaching practices (Archambault & Crippen, 2009 ; Schmidt et al., 2009 ). Well-developed TPACK is commonly associated with the successful integration of educational technologies in teaching and learning (Anthony et al., 2021 ; Koh et al., 2017 ), as TPACK not only informs teachers about what technologies to use but, more importantly, fosters teachers to think, analyse, and reflect on the use of technology (Huang et al., 2021a ). Consequently, TPACK is widely discussed when researchers evaluate teachers’ technology usage and integration. For instance, Schmid et al. ( 2021 ) revealed that pre-service teachers’ TPACK skills were associated with how they implemented technologies in lesson plans. Furthermore, previous research has emphasised the positive impact of TPACK on teachers’ attitudes, behavioural intentions, and actual behaviours towards technology integration among K-12 and higher education teachers (e.g., Hsu et al., 2021 ; Jung et al., 2019 ; Zhang & Chen, 2022 ). In other words, teachers with a high level of TPACK are more likely to form favourable perceptions of the value technology can add to teaching and learning. Conversely, the lack of TPACK often poses obstacles to successful technology integration (Liu et al., 2024 ).

Perceived self-efficacy (SE) was defined as ‘beliefs in one’s capabilities to organise and execute the courses of action required to produce given attainments’ (Bandura, 1997 , p. 3). Numerous studies have suggested that teachers’ self-efficacy positively influences their intentions to incorporate educational technologies into actual teaching (e.g., Panisoara et al., 2020 ; Wijnen et al., 2021 ). For instance, Joo et al. ( 2018 ) found that pre-service teachers’ perceived self-efficacy was positively related to their intention towards technology integration. The same positive relationship between self-efficacy and technology use can also be observed in K-12 educational contexts. Petko et al. ( 2018 ) reported that primary school teachers’ perceived technology-related beliefs strongly predicted their short-term and long-term technology use for teaching project-based learning. Similarly, Kwon et al. ( 2019 ) demonstrated that teachers’ self-efficacy for technology integration significantly affected their actual use of computing devices (e.g., smartphones and tablets) in secondary schools.

Technostress (TS), particularly in educational settings, has garnered significant research attention due to the pervasive infiltration of new technologies into classrooms spanning various subjects and educational levels (see review by Fernández-Batanero et al., 2021 ). Weil and Rosen ( 1997 ) defined technostress as ‘any negative impact on attitudes, thoughts, behaviors, or body psychology caused directly or indirectly by technology’ (p. 5). Ayyagari et al. ( 2011 ) suggested that a high level of technostress leads to users’ lower performance in their actual usage and diminished behavioural intention towards future adoption. Similar findings have likewise been noted within the realm of educational research (e.g., Chou & Chou, 2021 ; Joo et al., 2016 ). In particular, technostress could lead to K-12 teachers’ psychological frustration and an inability to cope with teaching tasks (Al-Fudail & Mellar, 2008 ). Similarly, a large-scale survey on the technology integration behaviour of K-12 teachers showed that teachers’ efforts to integrate technologies were hindered by technostress, which diminished satisfaction with educational technology usage and adversely affected their perceptions of using ICT for teaching (Wu et al., 2022 ).

2.5 The current study

With the complex and dynamic nature of CPS, there is a growing trend towards the development of teacher-facing LADs to analyse and visualise multimodal data related to students’ CPS skills (e.g., clickstreams, group conversations) collected from learning technologies, including educational games (Liu et al., 2024 ; Azevedo & Gašević, 2019 ; Chen et al., 2022 ; Tlili et al., 2021b ). Meanwhile, when attempting to adopt LADs for their teaching, teachers often encounter various barriers and challenges (Kaliisa et al., 2021 ; Lee-Cultura et al., 2023 ; Li et al., 2022 ), often due to the misfit between personal and environmental characteristics (Chou & Chou, 2021 ; Dong et al., 2020 ; Govender & Mpungose, 2022 ). The misfit in turn influences teachers’ technology usage intention and performance (Chou & Chou, 2021 ; Li & Wang, 2021 ; Joo et al., 2016 ). Consequently, to maximise the utilities of LADs and mitigate their stress from integrating LAD, it is necessary to identify personal and environmental stressors and predict teachers’ LAD usage from a person-environment fit perspective. Despite the substantial existing findings on the influence of personal and environmental factors on teacher’s technology acceptance and adoption, scant research has delved into how these factors affect K-12 teachers’ integration of LADs for CPS assessments in classroom settings. Therefore, in the current study, we implemented a teacher-facing LAD for assessing students’ CPS in K-12 classrooms, and examined the relationships between environmental and personal factors and how they shape K-12 teachers’ behavioural intention and actual usage of the LAD. The current study will extend our theoretical understanding of the P-E fit theory through its application in the context of technology-enhanced CPS assessment. Methodologically, although previous studies on P-E fit have proposed and validated diverse technology integration models, they focused on checking their models’ explanatory power (i.e., \({R}^{2}\) ) and offered limited evidence of the models’ predictive capability and external validity. Thus, whether our proposed model possesses strong out-of-sample predictive power warrants further investigation. Our research findings could shed light on the determinants that either facilitate or hinder teachers’ successful integration of LADs into teaching practices and offer recommendations on how to support teachers in leveraging LADs to foster students’ CPS skills.

2.6 Conceptual model and hypotheses

Based on the P-E fit theory and our literature review as discussed above, this study constructed an integrated conceptual model (see Fig.  1 ), where the hypothesised model relationships are as follows:

The integrated conceptual model

H 1 -H 5 : subjective norms (SN) affect TPACK, self-efficacy (SE), technostress (TS), behavioural intention (BI), and actual behaviour (AB) respectively.

H 6 -H 10 : school support (SS) affects TPACK, self-efficacy (SE), technostress (TS), behavioural intention (BI), and actual behaviour (AB) respectively.

H 11 -H 13 : TPACK affects technostress (TS), behavioural intention (BI), and actual behaviour (AB) respectively.

H 14 -H 16 : self-efficacy (SE) affects technostress (TS), behavioural intention (BI), and actual behaviour (AB) respectively.

H 17 -H 18 : technostress (TS) affects behavioural intention (BI) and actual behaviour (AB) respectively.

H 19 : behavioural intention (BI) affects actual behaviour (AB).

Additionally, we postulate that TPACK and self-efficacy indirectly affect behavioural intention and actual behaviour through technostress. Firstly, it was discovered that teachers’ TPACK abilities lessened their levels of technostress, which subsequently enhanced their intention to utilise educational technologies (Joo et al., 2016 ). Concerning the relationship between SE and technostress, in studies on K-12 and university teachers’ technostress towards online teaching tools, teachers’ self-efficacy reduced their technostress (Chou & Chou, 2021 ). Similarly, Dong et al. ( 2020 ) illustrated that self-efficacy mitigated technostress among K-12 in-service teachers during the integration of ICT into teaching activities. We therefore hypothesise:

H 20 -H 21 : technostress (TS) mediates the relations between TPACK and behavioural intention (BI) and actual behaviour (AB).

H 22 -H 23 : technostress (TS) mediates the relations between self-efficacy (SE) and behavioural intention (BI) and actual behaviour (AB).

We also propose that school support indirectly affects behavioural intention and actual behaviour through TPACK, self-efficacy, and technostress. School support has been identified as a crucial catalyst in motivating teachers to incorporate e-learning into their teaching practices (Atman Uslu & Usluel, 2019 ; Ifinedo & Kankaanranta, 2021 ; Liu et al., 2017 ). Both administrative and collegial support were found to positively influence teachers’ TPACK and computer self-efficacy within K-12 school settings (Dong et al., 2020 ). In the absence of sufficient school support, K-12 teachers are prone to ‘experience resistance and animosity from colleagues’, which could consequently undermine their self-efficacy when applying educational games to their teaching activities (Stieler-Hunt & Jones, 2017 ). Numerous studies also suggest that school support can help teachers alleviate their technostress, which in turn facilitates the integration of emerging technologies into teaching (e.g., Joo et al., 2016 ; Özgür, 2020 ; Chou & Chou, 2021 ). We therefore hypothesise:

H 24 -H 25 : TPACK mediates the relations between school support (SS) and behavioural intention (BI) and actual behaviour (AB).

H 26 -H 27 : self-efficacy (SE) mediates the relations between school support (SS) and behavioural intention (BI) and actual behaviour (AB).

H 28 -H 29 : technostress (TS) mediates the relations between school support (SS) and behavioural intention (BI) and actual behaviour (AB).

Subjective norms have been recognised as a key factor in shaping teachers’ technology usage intention and behaviour (Jeong & Kim, 2017 ; Shin, 2015 ; Wijnen et al., 2021 ). Nevertheless, there is a scarcity of knowledge concerning whether and how teachers’ personal factors mediate the influences of subjective norms on their usage intention and behaviour towards educational technologies. Previous studies (e.g., Kwon et al., 2019 ; Wu et al., 2022 ; Zhang & Chen, 2022 ) demonstrated the significant influences of teachers’ TPACK, self-efficacy, and technostress on their behavioural intention and actual usage towards digital learning technologies. At the same time, subjective norms were found to be highly associated with TPACK, self-efficacy, and technostress (Dong et al., 2020 ; Jang et al., 2021 ; Scherer et al., 2019 ). Hence, we expect that subjective norms have significant indirect effects on behavioural intention and actual behaviours through TPACK, self-efficacy, and technostress, respectively. We therefore hypothesise:

H 30 -H 31 : TPACK mediates the relations between subjective norms (SN) and behavioural intention (BI) and actual behaviour (AB).

H 32 -H 33 : self-efficacy (SE) mediates the relations between subjective norms (SN) and behavioural intention (BI) and actual behaviour (AB).

H 34 -H 35 : technostress (TS) mediates the relations between subjective norms (SN) and behavioural intention (BI) and actual behaviour (AB).

3.1 Overview of the CPS game and the LAD

For facilitating the assessment of young students’ CPS skills, Digital City Fighter ( D-City Fighter ) was developed as part of a larger theme-based research project titled Learning and Assessment for Digital Citizenship. D-City Fighter (see Fig. 2 ) is a mobile online role-playing game focused on CPS with a 3D interface supporting multiple players. Based on the principles of evidence-centred design, three CPS quests have been designed and developed in the game (Tsang et al., 2020 ; Liu et al.,  2024 ). As Fig. 2 shows, one of the quests requires a group of four student-players to locate puzzle pieces scattered throughout the digital city and assemble them within a 15-minute timeframe. Specifically, players are tasked with identifying puzzle pieces whose frames correspond to the colour of the circle at their feet and positioning these pieces correctly in their respective locations within the puzzle area. A hidden clue for completing this puzzle task becomes available to players upon entering the bush. Various tools (i.e., Virtual Joystick, Pickup/Putdown, Emoji, Chat, Scoreboard, Map, and Timer) are incorporated into the graphical user interface to support players’ CPS processes. To assess the players’ CPS skills, measures from their gameplay data (e.g., movement trajectories, clickstreams) were mapped to CPS skills, referencing a well-known framework for teachable CPS skills proposed by Hesse et al. ( 2015 ): participation, perspective taking, task regulation, social regulation, and knowledge building.

The interface of D-City Fighter (Payer E1’s point of view)

CPSLens (see Fig.  3 ) is a teacher-facing mobile LAD designed to analyse and visualise students’ interactions within virtual CPS environments, such as D-City Fighter . It aims to assist teachers in assessing students’ CPS skills and performance. The pipeline for game learning analytics of CPS is depicted in Fig.  4 . Specifically, student-players’ gameplay data are fed into CPSLens , which visualises their CPS skills and processes as well as quest performance and engagement to teachers. Teachers can then use the generated visualisations to evaluate students’ CPS skills and performance. In CPSLens , six visualisation panels are offered: Quest Performance , Player Movement , CPS Performance , Quest Playback , Quest Engagement , and CPS Dynamics . Moreover, CPSLens allows teachers to switch between the visualisation interfaces of different groups and group members.

The interface of CPSLens (Group B and Player B1)

Game learning analytics pipeline adapted from Calvo-Morata et al. ( 2019 )

Students’ CPS skills and processes are visualised via the CPS Performance , CPS Dynamics , Player Movement , and Quest Playback panels. Through the CPS Performance panel, teachers can assess group members’ performance on five CPS skills identified in the literature (Hesse et al., 2015 ), represented by a circular bar chart. Teachers can also visually check the transition patterns among the CPS skills, depicted by nodes of varying sizes corresponding to skill performance levels. When clicking specific skill bars, such as participation (yellow) and task regulation (pink) (See Fig. 3 ), teachers will be presented with multiple black-and-white bars. Each of these black-and-white bars indicates the proportion of the selected skill performed by one player (black part) relative to the corresponding skill performance of the entire group at a given time point on the x-axis of the CPS Dynamics panel. The CPS Dynamics panel displays a stacked bar chart with coordinates; the x-axis represents time points (in minutes), and the y-axis signifies one group member’s performance scores on the CPS skills, providing teachers with insights into dynamic changes in individual CPS skills over time. The Player Movement panel visualises different group members’ movement trajectories within the digital city. The city’s geography is divided into quest zones containing quest-related elements (e.g., puzzle pieces) and non-quest zones without relevant problem-solving information. This feature enables teachers to track and monitor different group members’ task progress. For instance, teachers can leverage this visualisation panel to identify difficulties that group members encounter as well as unintended events (e.g., ‘gaming the system’, off-quest behaviours) in the CPS process by comparing their actual movement trajectories with the expected ones. Finally, the Quest Playback panel allows teachers to review the video recording of each group member’s CPS process individually.

The Quest Performance and Quest Engagement panels visualise the performance and engagement of the CPS quests, respectively. Teachers can use the Quest Performance panel to examine the quest scores at both individual and group levels, as well as check the remaining and expended time during group members engaging with the quests. The quest scores are computed using performance metrics derived from students’ gameplay data, such as the duration of quest completion and the count of incorrect attempts. Additionally, the Quest Engagement panel showcases the level of engagement of each group member, evaluated through the group member’s interactions with teammates, in-game support tools, quest elements, and both quest and non-quest zones. A higher level of engagement correlates with darker shades of the square colour. Quest Engagement is represented as coordinates, with each point on the x-axis marking a time point (in minutes) and each label (e.g., B1-B4 in Group B) on the y-axis representing a group member. Quest Engagement informs teachers about different group members’ temporal changes in engagement levels in the entire CPS process.

The use of CPSLens offers interactive, near real-time visualisations of students’ strengths or weaknesses regarding particular CPS skills. Such feedback can not only support teachers to foster students’ CPS skills in an adaptive and personalised way but also help teachers improve their design and implementation of collaborative learning activities, such as building an appropriate group composition referring to CPS assessment results from CPSLens .

3.2 Participants and procedure

A total of 300 in-service teachers from ten K-12 schools in China participated in this study. Among the participants, 59.3% were female, with an overall average age of 40.40 ( SD  = 7.05). Table  1 shows their demographic details. None of the participating teachers had experience implementing LADs or educational games in their classrooms. Before data collection, informed consent was obtained from the participating teachers, principals, students, and their parents. The researchers emphasized to the participating teachers that they had the freedom to withdraw from the study at any time without any consequences.

Initially, the research team disseminated multimedia materials for the teachers to acquire knowledge about technology-enhanced CPS assessments, LADs, and their pedagogical affordances. Then, considering teachers’ lack of experience in implementing LADs, the researchers conducted a full-day onsite training session in each school to familiarise the teachers with the operations of D-City Fighter and CPSLens . This comprehensive training, guided by the researchers, included a live demonstration of D-City Fighter and CPSLens , followed by a hands-on trial allowing teachers to gain practical experience with these technology applications. Upon completion, the participating teachers were invited to integrate D-City Fighter and CPSLens into their teaching and implement them within classroom environments in the subsequent semester. Inherently functioning as a domain-general competence (Graesser et al., 2017 ; Greiff et al., 2014 ), CPS has been widely applied across various disciplines (e.g., mathematics, computer science) (Baucal et al., 2023 ; Tian & Zheng, 2023 ) and different active learning approaches (e.g., project-based learning, problem-based learning) (Song , 2018 ; Saleh et al., 2022 ). In this study, as shown in Table 1 , the participating teachers implemented the CPS game and the LAD in STEM (e.g., technology, mathematics) and non-STEM (e.g., language) subjects.

Throughout the implementation of D-City Fighter and CPSLens , researchers provided remote assistance via a social media group whenever participants encountered and reported technical difficulties. Excluding these sporadic cases of troubleshooting, all the participants received similar amounts of support from the researchers. One semester after the implementation (approximately four months), we distributed questionnaires to elicit teachers’ perceptions of constructs corresponding to environmental and personal factors (as detailed in the next section), as well as the behavioural intentions and actual use of CPSLens . Log files from CPSLens showed that the teachers, on average, accessed CPSLens 4.63 times, spending approximately 10.13 min during each interaction.

3.3 Measures

We measured subjective norms (SN), self-efficacy (SE), and behavioural intention (BI) using 12 items with a 7-point Likert scale (1 =  strongly disagree ; 7 =  strongly agree ). The items were adapted from Admiraal et al. ( 2017 ) and Teo and van Schaik ( 2009 ). Cronbach’s alpha for SN (five items), SE (four items), and BI (three items) ranged from 0.838 to 0.902.

Technological pedagogical content knowledge (TPACK), school support (SS), and technostress (TS) were measured using 11 items with the same 7-point Likert scale used above. The items were adapted from the highly cited literature (Archambault & Crippen, 2009 ; Ayyagari et al., 2011 ; Chou & Chou, 2021 ; Lam et al., 2010 ; Schmidt et al., 2009 ). Cronbach’s alpha for TPACK (four items), SS (four items), and TS (three items) ranged from 0.784 to 0.907.

We assessed actual behaviour (AB) using five items adapted from Davis et al. ( 1989 ), Schildkamp et al. ( 2017 ), and Siyam ( 2019 ). These five 7-point Likert-type items included the teachers’ frequency of utilising the LAD over the one-semester period (from 1 =  not at all to 7 =  more than 10 times ), their duration per LAD usage (from 1 =  less than five minutes to 7 =  more than half an hour ), and three other items measuring the extent to which the teachers used LAD for instructional purposes (from 1 =  never to 7 =  always ). Cronbach’s alpha for AB was 0.838.

3.4 Data Analysis

All data analyses were performed using R 4.3.2 and SmartPLS 4.0.7.8. For examining the relationships between personal and environmental factors and how they influenced teachers’ behavioural intention and actual usage of the LAD, we evaluated the proposed model (see Fig. 1 ) through partial least squares structural equation modelling (PLS-SEM). The PLS-SEM algorithm combines principal component analysis with ordinary least squares regressions to estimate model structures. Compared with covariance-based SEM commonly adopted in studying technology acceptance and adoption, PLS-SEM offers several advantages, including accommodating non-normal data distributions, achieving sufficient statistical power with small sample sizes, and managing complex models with multiple latent and observed variables and their interrelationships. PLS-SEM is particularly exceptional at assessing a model’s out-of-sample predictive power. These strengths align well with our study’s characteristics, such as the non-normality of our data (see item descriptive statistics in Appendix Table 4 ), complex model relationships within a relatively small sample size, and the requirement to assess the model’s predictive capacity. Despite this study’s small sample size, it still meets the minimum sample size as calculated by G*power 3.1.9.4 (Faul et al., 2009 ). With population effect size, power level, and significance level \(\alpha\) set to 0.15, 0.95, and 0.01 respectively, G*power suggests that 189 is the minimum sample size required for our model estimation.

Adopting a two-stage process as delineated by Anderson and Gerbing ( 1988 ), the PLS-SEM analysis comprised assessments of the measurement model and structural model. In the measurement model, we checked indicator reliability (indicator loading \(\ge\) 0.708 and statistically significant), internal consistency reliability (0.70 \(\le\) Cronbach’s alpha and composite reliability (CR) \(\le\) 0.95), convergent validity (average variance extracted (AVE) \(\ge\) 0.50), and discriminant validity (the heterotrait-monotrait ratio of correlations (HTMT) \(<\) 0.85; Square root of AVE for a construct higher than its correlation with other constructs). In the structural model, we examined the statistical significance of path coefficients, collinearity (variance inflation factor (VIF) \(<\) 3.3), and effect size of path coefficients and model explanatory power (i.e., \({R}^{2}\) ), ranging from weak (0 \(\le\) x \(\le\) 0.10), modest (0.10 \(<\) x \(\le\) 0.30), moderate (0.30 \(<\) x \(\le\) 0.50) to strong (x \(>\) 0.50). These assessment criteria are from Hair et al.’s ( 2021 ) guidelines for PLS-SEM model evaluation.

Following the recommended procedures in Shmueli et al. ( 2019 ), this study assessed the out-of-sample predictive power of the proposed model. Initially, a holdout sample-based procedure was executed involving three-fold cross-validation and 20 repetitions to derive training and holdout samples. Next, out-of-sample prediction metrics for the model indicators were computed and compared with the linear regression model (LM) benchmark. According to Shmueli et al. ( 2019 ), a PLS model’s Q predict 2 larger than zero and prediction errors (e.g., root-mean-squared error) lower than the LM benchmark indicate the sufficient predictive power of the model. Because Shmueli et al. ( 2019 ) emphasise that the assessment of a PLS model’s prediction performance should concentrate on its key endogenous constructs, our analysis primarily targeted the BI and AB constructs within the model. For mediation analyses, the multiple mediation effects were analysed with reference to the procedure in Zhao et al. ( 2010 ).

4.1 Assessing the measurement model

The results from the measurement model assessment can be found in Appendix Table 4 . All indicator loadings proved statistically significant, with all but two items (AB4 = 0.560; AB5 = 0.560) surpassing the threshold of 0.708. These two items were retained due to their role in measuring the frequency and duration of LAD use—crucial for the content validity of the measurement—and the fact that the CR and AVE of the construct (i.e., AB) exceeded recommended thresholds (Hair et al., 2021 ). The CR of all constructs ranged from 0.869 to 0.931, larger than the cut-off value of 0.70, and Cronbach’s alpha ranging from 0.784 to 0.907—considered ‘satisfactory to good’ according to Hair et al. ( 2021 ). Convergent validity was achieved, as denoted by AVE (ranging between 0.598 and 0.795) exceeding 0.50 (see Appendix Table 4 ). The discriminant validity of the measurement model was acceptable, with HTMT below 0.85 and the square root of each construct’s AVE greater than its correlations with other constructs within the model (see Table 2 ).

4.2 Assessing the structural model and mediation effects

Appendix Table 5 and Fig.  5 showcase the results of the hypothesis testing. The structural model did not have the problem of collinearity, as the VIF values ranged from 1.109 to 2.274, not exceeding the threshold of 3.3. TPACK (𝛽 = 0.596, CI [0.496; 0.681], strong effect size) and SE (𝛽 = 0.494, CI [0.389; 0.587], moderate effect size) were positively predicted by SN, supporting H 1 and H 2 . While SS was a positive predictor of SE (𝛽 = 0.270, CI [0.159; 0.370]), it occurred to be a negative predictor of TS (𝛽 = -0.291, CI [-0.413; -0.143]), with both paths bearing modest effect sizes and accepting H 7 and H 8 . SN (𝛽 = 0.346, CI [0.217; 0.473]) and SE (𝛽 = 0.366, CI [0.216; 0.499]) positively predicted BI respectively with moderate effect sizes, while TS (𝛽 = -0.093, CI [-0.187; -0.010]) negatively predicted BI with a weak effect size, confirming H 4 , H 15 , and H 17 . SS (𝛽 = 0.087, CI [0.011; 0.167]) and TPACK (𝛽 = 0.162, CI [0.056; 0.275]) were predictive of AB, showing a weak and modest effect size, respectively. Therefore, H 10 and H 13 were established. With a strong effect size, BI was found to be a predictor of AB (𝛽 = 0.524, CI [0.409; 0.636]), supporting H 19

Results of structural model relationships

The model explained 54.5% of the variance for BI and 62.1% for AB, showing that our research model possessed a strong explanatory power (i.e., in-sample predictive power). According to the results of PLSpredict analysis (see Table  3 ), the Q predict 2 values for the BI and AB indicators exceeded zero, and the prediction errors in the PLS model were lower than the LM model, indicating that our model had high out-of-sample predictive power. Appendix Table 5 and Fig.  6 show the results of mediation analyses. TPACK (𝛽 = 0.097, CI [0.034; 0.167]) was a mediator of the relationship between SN and AB, supporting H 31 . SE mediated the relationships between SN and BI (𝛽 = 0.181, CI [0.101; 0.267]) and between SS and BI (𝛽 = 0.099, CI [0.053; 0.162]), confirming H 26 and H 32 .

Statistically significant mediation effects

5 Discussion

The overarching objective of the current study was to formulate and validate a model that elucidates and predicts in-service K-12 teachers’ integration of LADs for assessing students’ CPS skills in an educational game. In particular, this study investigated the postulated relationships among environmental factors (i.e., SN and SS), personal factors (i.e., TPACK, TS, and SE), as well as intention (BI) and behaviour (AB) regarding LAD usage. Beyond a high explanatory power, our model demonstrated a strong out-of-sample predictive power, which provides supporting evidence for its predictive capability and external validity for similar research contexts of exploring teachers’ technology integration. It was found that SN positively predicted TPACK ( SN→TPACK ) and SE ( SN→SE ), which echoes the findings of previous studies, such as Jang et al. ( 2021 ), who examined in-service teachers’ integration of augmented reality and virtual reality techniques into teaching practices in elementary schools in South Korea, and Scherer et al. ( 2019 ), who identified the environmental and personal factors that determine the success of teacher technology integration using meta-analytic SEM. In line with previous studies (e.g., Dong et al., 2020 ; Joo et al., 2016 ), the impacts of SS on SE ( SS→SE ) and TS ( SS→TS ) were supported in the current study, indicating that backing and promotion of technology integration by school administrators could bolster teachers’ confidence and mitigate their technostress during the implementation of new technologies, such as LADs, in classrooms.

Results also showed that SS significantly predicted AB ( SS→AB ), which corroborates Atman Uslu and Usluel’s ( 2019 ) assertion that school support directly affected teachers’ utilisation of ICT in K-12 education. This was further substantiated by Hew and Syed A. Kadir ( 2017 ), who ascertained that school support is a fundamental prerequisite for the implementation of cloud computing and web 2.0 technologies for teaching purposes. Teachers’ SN was found to positively affect their BI ( SN→BI ) to employ the LAD, aligning with Wijnen et al.’s ( 2021 ) findings of systematic review, which highlighted the significance of the social acceptability of e-learning technologies within K-12 educational contexts. With respect to the personal factors, namely TPACK, TS, and SE, we found that SE ( SE→BI ) and TS ( TS→BI ) significantly predicted BI, which resonates with findings from various previous studies (e.g., Chou & Chou, 2021 ; Joo et al., 2018 ; Panisoara et al., 2020 ). To illustrate, Chou and Chou ( 2021 ) underscored the pivotal role of self-efficacy and technostress in shaping K-12 teachers’ intent to persistently employ online teaching technologies, even beyond the COVID-19 pandemic. Apart from SS, our study also identified both TPACK ( TPACK→AB ) and BI ( BI→AB ) as significant predictors of AB. Similar results were obtained in a variety of empirical studies (e.g., Anthony et al., 2021 ; Hsu et al., 2021 ; Zhang & Chen, 2022 ). For instance, Anthony et al. ( 2021 ) pinpointed lecturers’ TPACK and intention to adopt technologies for teaching as key determinants of their actual usage of e-learning systems.

Additionally, this study supported the mediating role of TAPCK in the linkage from SN to AB ( SN→TPACK→AB ). In other words, when teachers were exposed to social pressure (e.g., peers, societal trends) in using LADs, they would more likely incorporate LADs into their teaching with the consideration of their pedagogy and subject matter, which would subsequently lead to their increasing actual usage of LADs. This finding implies the importance of peer influence in teachers’ adoption of emerging educational technologies. The mediation analyses also revealed that SN ( SN→SE→BI ) and SS ( SS→SE→BI ) had indirect effects on BI through SE. That is, teachers experiencing social pressure to use LADs or receiving school support from administrators are more likely to feel confident in actual LAD use within their classrooms, thereby developing stronger intentions towards LAD integration into teaching. Upon reviewing existing literature on technology acceptance and adoption, we discovered numerous studies providing evidence of the direct influences of SN on AB (e.g., see review by Wijnen et al., 2021 ) and also those of SN and SS on BI (e.g., Jeong & Kim, 2017 ; Jung et al., 2019 ; Porter & Graham, 2016 ). However, no studies, to the best of our knowledge, have examined the mediation effects on these relationships.

A plausible explanation for such significant mediation effects could lie in the active environments we created—such as offering training sessions and establishing social media communities—where teachers could learn, discuss, and share ideas on incorporating LAD into their teaching activities, subsequently enhancing their TPACK and confidence in LAD integration. Our findings support the claim of Fishbein and Ajzen ( 2011 ) that actual behaviour is shaped by the confluence of personal competence and environmental support, a pattern particularly evident in our research context. Furthermore, in cultures characterised by collectivist traditions and Confucian values, which emphasise conformity and respect for authority, the decisions teachers make regarding technology integration into classroom settings may be directly or indirectly influenced by environmental factors (Huang et al., 2019 ; Huang & Teo, 2020 ; Teo et al., 2019 ). Specifically, the subjective opinions and tangible support from influential figures around them, such as school leaders, administrators, and colleagues, can play crucial roles (Huang & Teo, 2020 ).

6 Conclusion

To investigate in-service teachers’ integration of a mobile LAD for game-based CPS assessments in K-12 classrooms, the present study constructed and tested an integrated conceptual model based on the person-environment fit theory. This model was validated using PLS-SEM on survey data collected from 300 K to 12 in-service teachers from ten schools in China. It was found that teachers’ subjective norms significantly influenced TPACK and self-efficacy, while school support significantly influenced technostress and self-efficacy. More importantly, our proposed model exhibited both strong in-sample explanatory power and out-of-sample predictive capability. In particular, behavioural intention was predicted by subjective norms, technostress, and self-efficacy, while actual behaviour was predicted by school support, TPACK, and behavioural intention. Our analysis results also highlighted the mediating roles of TPACK and self-efficacy. Specifically, TPACK mediated the impact of subjective norms on actual behaviour, and self-efficacy mediated the impacts of subjective norms and school support on behavioural intention.

Our findings yield theoretical implications for studies concerning teacher integration of advanced learning technologies, empowered by artificial intelligence and big data (e.g., learning analytics tools), into teaching practices. Grounded in the person-environment fit theory, this study advances the theoretical understanding of the factors that determine the extent to which teachers incorporate learning analytics applications into their teaching. Our study also extends the literature on teacher technology integration by uncovering the mediation effects of personal factors on the linkages from environmental factors to technology acceptance and adoption. The methodological implication of this study is underscored by its demonstration of how to assess a model’s predictive capability and external validity through out-of-sample predictive power.

The novelty of this study resides in not only in the implementation of a LAD designed for CPS assessments in authentic classroom settings but also in the investigation of teachers’ acceptance and adoption of such emerging technologies within educational contexts. Given the interactive, interdependent, and temporal features that are inherent in CPS (Swiecki et al., 2020 ), it can be challenging for teachers to measure students’ CPS skills and performance at both individual and group levels during live instruction within physical classrooms. In this study, we introduced a solution leveraging a LAD, which provides teachers with immediate and actionable feedback on individual contributions and group performance. This equips teachers with the ability to implement an evidence-based, data-driven approach to teaching 21st century skills and delivering adaptive learning support. Consequently, teachers’ LAD-empowered teaching may improve student engagement and encourage better learning attainments. Technologically, besides game-based learning, due to the prevalence of CPS skills across educational contexts, our LAD holds the potential to be applied to supporting other active learning approaches (e.g., project-based learning, problem-based learning) across a diversity of STEM and non-STEM disciplines. Our study has also constructed a research model characterised by high explanatory capacity and external validity, which could be generalised to other contexts of educational technology integration. This model illuminates the intricate relationships among environmental factors, personal characteristics, and technology acceptance and adoption. In doing so, it encapsulates multiple critical elements that shape technology integration into teaching practices, which can inform the design, implementation, and evaluation of LADs for CPS assessments.

Our research findings lend themselves to practical recommendations for facilitating teachers’ usage of LADs in their teaching. Firstly, it is advisable for teachers to forge mutually beneficial virtual communities via social media. This would provide a constructive and relaxed atmosphere conducive to dialogues and problem solving, thereby fostering LAD integration into teaching practices. Secondly, schools can launch professional and technological training initiatives, inclusive of workshops, seminars, and certificate programs, with the objective of enhancing teachers’ TPACK, an essential prerequisite for the seamless and sustainable integration of LADs. These professional development programs should also develop teachers’ data literacy knowledge and skills, such as how to interpret data and formulate pedagogical responses (Liu et al., 2023 ; Khulbe & Tammets, 2023 ), particularly through capacity-building and reflective activities (Cui & Zhang, 2022 ). Thirdly, it is suggested that schools provide required software, hardware, and timely assistance both in-person and online under researchers’ support. These endeavours can mitigate teachers’ technostress, build their confidence, and even directly affect their actual utilisation of LAD. Lastly, given the significant mediating roles of TPACK and self-efficacy, school administrators should pay close attention to the needs of teachers displaying inadequate TPACK skills and low confidence in LAD usage. This is particularly applicable to those possessing traditional teaching conceptions (Tsai & Tsai, 2019 ) or limited information and digital literacy (Lim, 2023 ).

This study has several limitations that should be addressed in future research. Firstly, all the participating teachers are from China, which might impact the generalisation of our research findings. Future researchers are encouraged to leverage our proposed model to investigate teachers’ integration of other emerging technologies in other sociocultural contexts. In particular, the cultural norms in different educational systems (e.g., collectivist versus individualist tendencies, respectively in Chinese and Western systems) and the teachers’ cultural beliefs can also be considered influential factors on LAD adoption (Huang et al., 2019 , 2021b ; Teo & Huang, 2019 ). Secondly, although the proposed model has been validated in this study, the exclusive reliance on survey data might limit our understanding of the in-depth reasons behind teachers’ intentions and behaviours regarding LAD integration. Future investigations would benefit from gathering and analysing multimodal data (e.g., interviews and physical signals) to corroborate and enrich our research findings. For instance, qualitative data and methodologies (e.g., document analysis of institutional policies) can reveal the extent to which inter-twined policy-related and institutional factors (e.g., comprehensiveness of infrastructure) would affect LAD integration (Broos et al., 2020 ). Finally, despite the use of PLS-SEM in our study to examine relationships among variables, this variable-centred method may not fully account for the influences of teachers’ individual characteristics (e.g., digital literacy levels) on the actual use of LADs. Person-centred methods (e.g., clustering analysis and finite mixture modelling) could be adopted to further probe how distinct teacher profiles contribute to variability in integrating LADs into classrooms.

Data availability

The raw datasets used in the current study are not publicly available due to ethics requirements, but the anonymized data are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to extend the gratitude to the participating schools, teachers, and students.

This work was supported by the Research Grants Council of the HKSAR Government, #T44-707/16 N, under the Theme Based Research Scheme and Guangdong Planning Office of Philosophy and Social Science, China [Grant No. GD24YJY14].

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