Stavovi učitelja i studenata prema korištenju igrifikacije u nastavi
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Introduction
Children begin to use digital technologies at a very early age: two-year-old toddlers regularly watch films and videos and listen to music on tablet computers (Ólafsson et al, 2014). Children's Internet use is generally over 85% for the age group beginning at six, rising to around 95% for older children (14 and older). One study finds that even 40% of 3 to 6-year-olds use the Internet at least once a week, predominantly with a tablet device (Ólafsson et al, 2014).
Today's children use digital devices, such as tablets, smartphones and computers, from an early age. Radesky et al. (2020) report research results on the sample of 346 parents and guardians of children aged 3 to 5 years where children were using tablets and smartphones to access applications such as YouTube, YouTube Kids, Internet browser, Quick Search Box or Siri, and streaming video services. 121 children (35%) had their own devices, and their average daily usage was 115 minutes (SD 115.1; range 0.20–632.5).
It is important to prepare children and young people to use information and communication technology safely and responsibly. In the era when Artificial Intelligence (AI) is having a growing influence on people’s everyday lives, it is important to acquire knowledge and skills to learn and work with the newest digital technologies and to be prepared for the future. This set of knowledge and skills is known as digital literacy.
“Digital literacy is the set of knowledge, skills, attitudes and values that enable children to confidently and autonomously play, learn, socialize, prepare for work and participate in civic action in digital environments. Children should be able to use and understand technology, to search for and manage information, communicate, collaborate, create and share content, build knowledge and solve problems safely, critically and ethically, in a way that is appropriate for their age, local language and local culture” (Nascimbeni & Vosloo (UNICEF), (2019), p. 32).
In the European Union, digital literacy is defined through digital competence. “Digital competence involves the confident, critical and responsible use of, and engagement with, digital technologies for learning, at work, and for participation in society. It includes information and data literacy, communication and collaboration, media literacy, digital content creation (including programming), safety (including digital well-being and competences related to cybersecurity), intellectual property related questions, problem solving and critical thinking” (European Union, 2019, p. 10).
Digital competence is one of the key competences for lifelong learning (European Union, 2019, p. 5): Literacy competence, Multilingual competence, Mathematical competence and competence in science, technology and engineering, Digital competence, Personal, social and learning to learn competence, Citizenship competence, Entrepreneurship competence, Cultural awareness and expression competence.
More than one in five young people fail to reach a basic level of digital skills across the European Union (European Commission, 2020b). Providing schooling in computing equips young people with a solid comprehension of the digital realm. Initiating students into computing early on and employing inventive and engaging teaching methods across both formal and informal settings, aids in building problem-solving, creativity, and teamwork skills. Furthermore, it nurtures enthusiasm for STEM fields and potential careers, simultaneously addressing gender stereotypes. Endeavours to enhance computing education's quality and inclusivity can significantly influence the enrolment of female students in IT-related higher education programs and subsequently their participation in digital professions across various economic sectors (European Commission, 2020a).
The Digital Education Action Plan (2021-2027) has two strategic priorities (European Commission, 2020b):
- to foster a high-performing digital education ecosystem, and
- to enhance digital skills and competences for the digital age.
The latter includes the following activities:
- support the provision of basic digital skills and competences from an early age:
- digital literacy, including management of information overload and recognising disinformation
- computing (informatics or computer science) education
- good knowledge and understanding of data-intensive technologies, such as AI
- boost advanced digital skills: enhancing the number of digital specialists and girls and women in digital studies and careers.
One of the Action Plan activities is to encourage female participation in STEM. Female students generally perform better than male students in the Programme for International Student Assessment (PISA) and International Computer and Information Literacy Study (ICILS) international skills tests. However, only one in three STEM graduates is a woman (European Commission, 2020a).
Digital literacy and communication include knowing the possibilities of hardware and software solutions and developing cooperation and communication skills in an online environment. Knowledge of the possibilities of current technology and computer programs is a prerequisite for their proper selection and effective and innovative application in various fields. It is necessary to develop digital literacy from an early age and throughout schooling so that students are prepared for life and work in a digital society (Ministry of Science and Education, 2018).
According to the same source, after the first year of studying the subject Informatics in the field of Digital Literacy and Communication, the students should acquire the following learning outcomes:
- C.1.1 with the support of the teacher student uses the proposed programs and digital educational content and
- C.1.2 with the support of the teacher student creates simple digital content with very simple actions.
Digital literacy is essential to learn, work and succeed in today’s digital society and it is important to prepare children and young people to use information and communication technology safely and responsibly from an early age.
Methodology
Aims
The research aims to explore the digital literacy of first grade primary school students and possible differences by gender and by place of residence (urban or rural).
Hypotheses
H1: There is no statistically significant difference in the self-assessed digital literacy of first grade primary school students by gender.
It is expected that the respondents will self-assess their digital literacy equally regardless of their gender (female and male). Female students generally perform better than male students in the Programme for International Student Assessment (PISA) and International Computer and Information Literacy Study (ICILS) international skills tests. However, only one in three STEM graduates is a woman (European Commission, 2020). The research results can show whether there are differences in the digital literacy of female and male students already at this early age.
H2: There is no statistically significant difference in the self-assessed digital literacy of first grade primary school students by their place of residence.
It is expected that the respondents will self-assess their digital literacy equally regardless of their place of residence (rural and urban). There is a possibility that the availability of optional subjects of informatics in urban and rural schools is not the same and that Internet connectivity in schools and at home is not the same in rural and urban areas. These two factors, the availability of optional subjects of informatics and Internet connectivity, can influence the students’ digital literacy.
H3: More than 80% of students use the Internet.
From an early age, children are exposed to the Internet through information and communication technology such as smartphones, tablets, laptops and desktop computers and know how to use it to search the Internet. It is expected that more than 80% of students use the Internet.
Sample
The research sample consists of 104 first grade primary school students from four primary schools and two primary district schools (district school in Croatian: područna škola) from northwestern Croatia in the spring of 2023. There are 48 female (46.2%) and 56 male (53.8%) students in the sample. There are 53 students (51.0%) from urban places of residence and 51 students (49.0%) from rural places of residence. There are 98 students (94.2%) who attend the optional subject of informatics in the first grade, and 6 students do not attend (5.8%) (Table 1).
Table 1
Respondents’ demographic data
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Instruments
Since the respondents were aged six and seven, the data gathering method used was a simple questionnaire containing eleven items written on paper (Table 2).
Table 2
Questionnaire items with answer options
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The first two items dealt with students’ gender and the place of residence. The other nine items were statements concerning attending the optional subject of informatics, having the computer at home, asking parents or guardians for permission to use computers, knowledge of recognizing the computer parts, knowledge of the use of computer hardware and software to perform simple tasks such as turning on or off computers, writing and editing texts, make drawings, searching the Internet, and understanding and applying rules of conduct on the Internet. The students could answer if they agree or disagree with the statement with simple dichotomous options: yes or no.
The statements were chosen according to the curriculum of the optional subject Informatics and its learning outcomes in the first grade of primary school in Croatia (Ministry of Science and Education, 2018). The items of the questionnaire were adapted to the target group.
Procedure
The survey was implemented using the guidelines of the Ethical Code of Research with Children (National Ethics Committee for Research with Children, 2020).
The survey took place in two counties of northwestern Croatia from March to May 2023. The respondents were students of four primary schools, of which two are in urban and the other two in rural areas. The first author of this paper provided assistance and explanations to the respondents when they were filling out the questionnaire.
The chi-squared test is used to explore the statistically significant differences between students according to their gender and their place of residence (urban and rural).
The statistical software GNU PSPP 1.4.1 was used in the data processing.
Results
Table 3 shows the statements and the number of respondents’ responses (whether they agree with a specific statement or not). There is a total number of responses and there are responses by gender. In the next columns are the results of chi-squared tests (χ2, df, p).
Table 3.
Number of students’ responses by item and gender
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Most of the respondents (98 out of 104, 94.2%) attend the optional subject of informatics in the first grade and there is no statistically significant difference by gender (χ2= 0.38, df=1, p=0.538).
Most of the respondents (91 out of 104, 87.5%) have a computer at home and there is no statistically significant difference by gender (χ2= 0.80, df=1, p=0.372).
Most of the respondents (73 out of 104, 70.2%) always ask parents or guardians for permission to use a computer and there is a statistically significant difference by gender (χ2= 4.27, df=1, p=0.039). There are more female respondents (81.3%) than male respondents (60.7%) who ask their parents or guardians for permission to use the computer.
Most of the respondents (92 out of 104, 88.5%) know how to turn on and off computers and there is no statistically significant difference by gender (χ2= 0.00, df=1, p=1.000).
Most of the respondents (93 out of 104, 89.4%) know the names of the computer parts and there is a statistically significant difference by gender (χ2= 5.23, df=1, p=0.022). There are more female respondents (97.9%) than male respondents (81.1%) who know the names of computer parts.
Most of the respondents (91 out of 104, 87,5%) know how to write a text using a computer and there is no statistically significant difference by gender (χ2= 0.09, df=1, p=0.766).
Most of the respondents (98 out of 104, 94.2%) know how to make a drawing using a computer and there is no statistically significant difference by gender (χ2= 1.15, df=1, p=0.284).
Most of the respondents (98 out of 104, 94.2%) know how to search the Internet (Google, YouTube) and there is no statistically significant difference by gender (χ2= 0.05, df=1, p=0.820).
Most of the respondents (95 out of 104, 91.3%) understand and apply the rules of conduct on the Internet and there is no statistically significant difference by gender (χ2= 0.00, df=1, p=1.000).
Table 4 shows the statements and the number of respondents’ responses (if they agree with a specific statement or not) by the place of residence. In the next columns are the results of chi-squared tests (χ2, df, p).
Table 4.
Number of students’ responses by item and the place of residence
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When the place of residence is considered then there is no statistically significant difference between rural and urban respondents except in the item “I know how to search the Internet” where there is a statistically significant difference (χ2= 4.63, df=1, p=0.031). There are more urban respondents (100.0%) than rural respondents (88.2%) who know how to search the Internet (Google, YouTube).
The research results show that most of the respondents (over 87.5%) self-assess themselves as having acquired the required learning outcomes specified in the informatics curriculum for the first grade in the field of Digital Literacy and Communication: 88.5% know how to turn on/off computers, 89.4% know the names of the computer parts, 87.5% know how to write a text using a computer, 94.2% know how to make a drawing using a computer, 94.2% know how to use the Internet, and 91.3% understand and apply the rules of conduct on the Internet. 87.5% have computers at home and 92.3% of the respondents attended the optional subject of informatics.
Discussion
Confirmation of the hypotheses
H1 states that there is no statistically significant difference in the self-assessed digital literacy of first grade primary school students by gender (female and male).
There is no statistically significant difference in the following items that contribute to the digital literacy of first grade primary school students:
- I know how to turn on/off the computer
- I know how to write a text using a computer
- I know how to make a drawing using a computer
- I know how to search the Internet (Google, YouTube)
- I understand and apply rules of conduct on the Internet.
A statistically significant difference is observed only in the item “I know the names of the computer parts” where there are more female respondents (97.9%) than male respondents (81.1%) who know the names of computer parts (χ2= 5.23, df=1, p=0.022).
The hypothesis H1 is confirmed.
H2 states that there is no significant difference in the self-assessed digital literacy of first grade primary school students by their place of residence (rural and urban areas).
There is no statistically significant difference in the following items that contribute to the digital literacy of primary school first-grade students:
- I know how to turn on/off the computer
- I know the names of the computer parts
- I know how to write a text using a computer
- I know how to make a drawing using a computer
- I understand and apply rules of conduct on the Internet.
A statistically significant difference is observed only in the item “I know how to search the Internet (Google, YouTube)” where there are more urban respondents (100.0%) than rural respondents (88.2%) who know how to search the Internet (χ2= 4.63, df=1, p=0.031).
The hypothesis H2 is confirmed.
H3 states that more than 80% of students use the Internet.
98 out of 104 (94.2%) respondents self-assess themselves as they know how to search the Internet. The hypothesis H3 is confirmed.
The research in this paper uses respondents’ self-assessed data related to their digital competence. The respondents’ age is six or seven so there is a possibility that they do not understand the questionnaire statements and/or cannot self-assess their knowledge. However, they could get guidance and help from a researcher who was present when they filled out the questionnaire. The questionnaire items were very simple and dichotomous.
It is difficult to get valid overviews of skills through questionnaires. The main reason for this is that respondents tend to overestimate themselves, especially when it comes to technical skills (Ala-Mutka, 2011).
García-Vandewalle et al. (2021) warn that evaluating subjectivity may have limitations. The respondents’ subjectivity regarding their level of knowledge is one of the main issues with self-assessment. However, self-assessment is still a valid tool for ascertaining how students perceive their learning and enables the detection of their strengths and weaknesses.
Godaert et al. (2022) analysed 14 studies concerning the assessment of students’ digital competences in primary school. The studies used various scoring systems: three were dichotomous (1=correct; 0=incorrect), four were 5-point Likert scale, one was a 7-point Likert scale, one scoring rubric (0-2 point, 0-5 points), four combined, and one not mentioned. At least five of them were using self-reported data collection. The age of the target population in the studies was mostly in the range of 9 to 13. Only one study, Jun et al (2014), included the first grade of primary school respondents of age 6.
Merritt et al. (2005) report that there were differences in respondents’ self-reported and actual digital literacy. They asked 55 students to self-report their computer literacy and later they were tested in their digital literacy. Research results show that there is a statistically significant difference between self-reported (N=55, M=2.164, SD=0.788) and actual tested (N=55, M=1.873, SD=0.610) levels of digital literacy.
Porat et al. (2018) report on digital literacy research results on 280 junior-high-school students where they compared their perceived digital literacy competencies and their actual performance in relevant digital tasks. Participants expressed high confidence in their digital literacy and overestimated their actual tested competence.
However, Tzafilkou et al (2022) developed and validated students’ digital competence scale based on self-reported data.
Asil et al (2014) used the 5-point Likert scale to collect data on measuring computer attitudes of young students in three separate factors: perceived ease of use, affect towards computers and perceived usefulness.
Hernández-Marín (2024) concludes that attitude scales have been consolidated as valuable elements in educational evaluation, allowing participants' perceptions of their learning to be satisfactorily captured. Self-assessment turns out to be an exceptionally effective method for measuring attitudes. However, to gain more perspective, complete and accurate learning, it is necessary to complement the attitude scales with other methods.
In their three-year longitudinal study, Lazonder et al (2020) followed the digital literacy progress of 151 fifth and sixth graders in their skills to collect, create, transform, and safely use digital information. They report that the children made the most progress in their ability to collect information. However, their capacity for generating information showed the smallest enhancement. “Development of most skills was moderately related, and it was independent of gender, grade level, migration background, and improvements in reading comprehension and maths. Children's socioeconomic status was weakly associated with the ability to collect and safely use information, but not with the other two digital literacy skills” (Lazonder et al, 2020, p. 1).
There are not many research results in the literature which deal with the digital literacy of first grade primary school students. However, the research results of first grade primary school students' self-evaluation agree with the results of Lazonder et al (2020) in the part which states that digital literacy skills are independent of gender.
Conclusion
Most of the respondents (over 87.5%) self-assess themselves as having acquired the required learning outcomes specified in the informatics curriculum for the first grade in the field of Digital Literacy and Communication.
There are no statistically significant differences in digital literacy of first grade primary school students by their gender or by their place of residence. The statistically significant differences were observed only in two items that contribute to digital literacy: more female respondents know the names of computer parts and more respondents coming from urban places of residence know how to search the Internet.
From an early age, students are using the Internet and there is a need to educate them to use it safely and responsibly. It is important to include and continue to teach the subject of informatics (computer science) in the initial grades of elementary school not only as an optional but as a compulsory subject.
It is important to continue to develop the digital literacy of students at an early age so that they can use information and communication technology safely and responsibly and that they are ready for new technologies and new occupations. The goal is also to achieve the equal representation of female and male students in university STEM study programs. The study presented in this paper shows that, at this early age, there are still no statistically significant differences in respondents’ self-assessed digital literacy by gender. However, there is a need to encourage female students in STEM subjects, such as informatics/computer science, to achieve the goal of equal representation of female and male graduates in the STEM fields.
Limitations of the research
The collected data is respondents’ knowledge self-assessment. The authors are aware that the respondents could overestimate their assessment, especially at their current age of six or seven. Actual testing of students’ knowledge would probably get more precise data.
The sample size is 104 and the representativeness of the results is limited.
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Competing interests
Statement on the first publication of the research results
The results of the research presented in this paper have not been published before.
References
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Odgoj danas za sutra: Premošćivanje jaza između učionice i realnosti 3. međunarodna znanstvena i umjetnička konferencija Učiteljskoga fakulteta Sveučilišta u Zagrebu Suvremene teme u odgoju i obrazovanju – STOO4 u suradnji s Hrvatskom akademijom znanosti i umjetnosti
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Katarina ŠiranovićFaculty of education, University of Zagreb, Croatia nhutinski1996@gmail.com |
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| Broj rada: 1 |
Kategorija: Izvorni znanstveni rad |
Sažetak
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Igrifikacija se odnosi na primjenu elemenata igre u kontekstu koji nije namijenjen za igru, s ciljem poticanja motivacije i angažmana pojedinca te boljeg razumijevanja sadržaja. Cilj ovog istraživanja |
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elementi igre; implementacija; kvantitativno istraživanje; pozitivan stav; upoznatost |
Uvod
Od početka 2000-tih godina igrifikacija je postupno postala sve popularnija. Javila se u različitim sektorima poput zdravstvenog, sporta, marketinga pa tako i u području obrazovanja. Termin igrifikacija osmislio je Nick Pelling oko 2002. godine, a definira se kao korištenje elemenata igre u neigrajućem kontekstu (Deterding i sur., 2011). Može se definirati i kao proces specifičnog načina razmišljanja karakterističnog za igranje igara (engl. game-thinking) i mehanike igranja igara s ciljem motiviranja pojedinca za rješavanje nekog problema (Zichermann i Cunningham, 2011). Igrifikacija se često poistovjećuje s učenjem temeljenom na igranju igara (engl. game-based learning), ali navedena dva koncepta nisu ista. Učenje temeljeno na igranju igara koristi igru kao dio procesa učenja, odnosno kao izvor novih znanja, dok igrifikacija preoblikuje proces učenja u igru korištenjem njezinih elemenata (Al-Azawi i sur., 2016). Elementi igre različito se karakteriziraju u literaturi. Najčešće korišteni elementi igre su bodovi, izazovi, značke, ljestvice poredaka i priče (Majuri i ostali, 2018). Do sličnih rezultata došli su i Durin i sur. (2019) analizom provedenih istraživanja navodeći nagrade, povratne informacije, izazove, razine, bodove, avatare, zadatke, vremensko ograničenje, ljestvice poredaka, trake napretka i značke kao najčešće korištene elemente igara. Konceptualni okvir MDA, koji je jedan od najpoznatijih, definira elemente igre kroz njihovu pripadnost jednoj od triju kategorija: mehanika, dinamika i estetika (Zichermann i Cunningham, 2011). Pri tome, mehanika igre opisuje pojedine komponente igre, dinamika opisuje ponašanje za vrijeme izvođenja mehanika, dok estetika obuhvaća poželjne emocionalne reakcije igrača tijekom igranja (Hunicke i sur., 2004). Dobro promišljena implementacija elemenata igrifikacije može poboljšati intrinzičnu motivaciju zadovoljavanjem urođene psihološke potrebe pojedinca za autonomijom, kompetitivnosti i povezanosti (Fuchs i sur., 2014). O navedenim psihološkim potrebama govori teorija samoodređenja (Ryan i Deci, 2000a). Elementi igre koji doprinose zadovoljenju potrebe za kompetitivnosti su bodovi, ljestvice poredaka, značke i drugi koji daju povratnu informaciju pojedincu o njegovom napretku kroz određeni period (Sailer i sur., 2017), dok se zadovoljenje potrebe za autonomijom očituje u mogućnosti donošenja odluka i odabira idućih koraka (Ryan i Deci, 2000b). Uloga elemenata igrifikacije može se promatrati i kroz teoriju zanesenosti koja se odnosi na postojanje optimalnog stanja koje se javlja kada je pojedinac duboko uronjen i angažiran u aktivnost te istu rado izvršava (Csikszentmihalyi, 2014). Da bi se javilo stanje zanesenosti kod pojedinca, aktivnost u kojoj isti sudjeluje treba biti izazovna, ostvariva te pojedinac u njoj treba uživati (Csikszentmihalyi i sur., 2014). Analiza rezultata prethodnih istraživanja o učincima implementacije igrifikacije pokazala je da većina ispitanika pokazuje pozitivan stav prema igrifikaciji u obrazovanju i to u vidu poboljšavanja stava učenika prema učenju, povećanja motivacije učenika (Banfield i Wilkerson, 2014; Cunha i sur., 2018; Treiblmaier i Putz, 2020) i angažiranosti te razumijevanja nastavnog sadržaja (Durin i sur., 2019). Učenici su na nastavi matematike obogaćenoj elementima igrifikacije rješavali više zadataka te su dulje zadržavali fokus na istima (Jagušt i sur., 2017; Türkmen i Soybaş, 2019). Istraživanja su pokazala da korištenje igrifikacije u nastavi stvara poticajno okruženje za učenje (Arkün Kocadere i Çağlar, 2015) te da ima pozitivan i značajan učinak na ishode učenja učenika u formalnom obrazovnom okruženju (Huang i sur., 2020). Bez obzira na prednosti potvrđene brojnim istraživanjima o učincima igrifikacije u nastavi na zadovoljstvo, motivaciju, uspjeh i angažiranost učenika, istraživanja pokazuju da namjera implementacije igrifikacije ovisi o stavovima učitelja prema istoj (Avidov-Ungar i Eshet-Alkalai, 2011; Scherer i sur., 2019). Istraživanja potvrđuju kako su učitelji koji imaju pozitivan stav prema igrifikaciji skloniji korištenju iste u nastavi u budućnosti (Asiri, 2019). Osim stava, crte ličnosti poput otvorenosti prema novim iskustvima i samoučinkovitosti povezane su s razvojem pozitivnog stava prema igrifikaciji (Cramariuc i sur., 2022 ). Kako bi igrifikacija u nastavi bila učinkovita, učitelji moraju imati znanja o njoj, ali je važan i njihov stav prema istoj (Bicen i sur., 2022). Budući učitelji procjenjuju kako nemaju dovoljno teorijskog i praktičnog znanja o načinu implementacije igrifikacije u nastavu u budućnosti (Guerrero Puerta, 2024). Također, istraživanja pokazuju kako ni učitelji zapravo ne poznaju koncept igrifikacije (Brooks i sur., 2019; Mårell-Olsson, 2022). Nedostatak znanja o konceptu igrifikacije dovodi do njezinog uvođenja u nastavni proces bez određenih kriterija ili bez konfiguracije koja ima određenu svrhu (Navarro Mateos i sur., 2021).
Bez obzira na porast interesa prema igrifikaciji u obrazovanju, i dalje nedostaju istraživanja koja istražuju stav učitelja prema igrifikaciji i implementaciji iste u obrazovanje budućih učitelja (Guerrero Puerta, 2024). S obzirom na brojne prednosti koje se očituju u primjeni igrifikacije u nastavi, namjera je ovog istraživanja ispitati stavove učitelja i studenata četvrte i pete godine učiteljskog studija prema igrifikaciji, njihovu upoznatost sa samim konceptom, iskustva u korištenju iste i namjeru njezinog budućeg korištenja te istu povezati sa karakteristikama ličnosti. Na temelju pregleda dosadašnjih istraživanja, pokazano je da učitelji i studenti nemaju dovoljno znanja o igrifikaciji, što znači da postoji potreba za edukacijom istih tijekom studijskog obrazovanja prije implementacije igrifikacije u nastavni proces, stoga se važnost ovog istraživanja očituje u utvrđivanju navedene potrebe s ciljem utjecanja na stvaranje kurikuluma ili smjernica kako navedeni pedagoški pristup implementirati u obuku koju provode obrazovne institucije.
Metodologija istraživanja
Cilj istraživanja
Cilj ovog istraživanja bio je ispitati upoznatost učitelja i studenata Učiteljskog studija s konceptom igrifikacije, njihove stavove prema korištenju igrifikacije u nastavi te utvrditi postoji li povezanost između namjere budućeg korištenja igrifikacije s njihovim stavovima i karakteristikama pojedinih crta ličnosti.
Istraživačka pitanja
Na temelju pregledane literature i postavljenog cilja istraživanja postavljeni su sljedeći problemi istraživanja:
- Ispitati upoznatost učitelja razredne nastave i studenata učiteljskog studija s konceptom igrifikacije.
- Ispitati razliku između stavova učitelja razredne nastave i studenata učiteljskog studija prema implementaciji igrifikacije u nastavu.
- Ispitati razliku između namjere korištenja igrifikacije u budućnosti između učitelja razredne nastave i studenata učiteljskog studija s obzirom na njihov stav prema igrifikaciji i njihove crte ličnosti.
Hipoteze
H2: Ne postoji statistički značajna razlika između učitelja razredne nastave i studenata učiteljskog studija u stavovima prema igrifikaciji u nastavi.
H3: Pozitivan stav prema igrifikaciji i otvorenost prema novim iskustvima statistički su značajni prediktori korištenja igrifikacije u budućnosti.
Sudionici
U istraživanju je sudjelovalo ukupno 220 ispitanika. Od ukupnog broja ispitanika, njih 109 bili su studenti 4. i 5. godine koji pohađaju Učiteljski fakultet u Zagrebu, dok su preostali dio ispitanika činili učitelji razredne nastave koji su zaposleni na području Zagreba. Raspodjela ispitanika prema spolu bila je 210 žena (95,5%) i 10 muškaraca (4,5%).
Postupak i instrumenti
Ispitanici su zamoljeni da ispune anketni upitnik putem Google Forms obrasca koji im je poslan mailom. Prikupljeni podaci analizirani su statističkim softverskim paketom SPSS. Za dobivanje podataka korišten je anketni upitnik Attitude towards the use of gamification in education (InnoRenew CoE, Izola, Slovenia i sur., 2022) za provjeru stavova učitelja i studenata prema igrifikaciji i skraćeni Big Five Inventory (BFI-S) (Lang i sur., 2011) za mjerenje pet glavnih dimenzija ljudske osobnosti. Na početku su prikupljeni opći podaci o ispitanicima (spol, dob, godine staža, vrsta obrazovanja).
Attitude towards the use of gamification in education (InnoRenew CoE, Izola, Slovenia i sur., 2022). Upitnik se sastoji od 32 čestice kojima se mjeri stav prema igrifikaciji. Čestice su zadržane prema originalnom upitniku. Slaganje sa svakom tvrdnjom sudionici su izražavali na skali Likertovog tipa od 5 stupnjeva od 1 (uopće se ne odnosi na mene) do 5 (u potpunosti se odnosi na mene). Čestice su formulirane tako da obuhvaćaju kognitivne aspekte (npr. Uz pomoć igrifikacije u nastavi učenici bi bolje razumjeli sadržaj poučavanja), afektivne aspekte (npr. Zabrinut sam da bi igrifikacija u nastavi potaknula učenički nemir) i one vezane uz namjenu budućeg korištenja (npr. Koristio bih igrifikaciju u nastavi kako bi sadržaj poučavanja bio zanimljiviji učenicima). Inverzno je formulirano 17 čestica s ciljem provjere odgovora ispitanika. Za provjeru faktorske strukture provedena je eksploratorna faktorska analiza metodom glavnih komponenti s Varimax rotacijom (KMO = ,915; Bartlettov test sferičnosti p < ,001) koja je rezultirala s dva faktora koji objašnjavaju 74,37% ukupne varijance. Prvi faktor, koji je nazvan pozitivan stav prema igrifikaciji, objašnjava 27,39% varijance i sastoji se od ukupno 15 čestica. Drugi faktor, koji je nazvan negativan stav prema igrifikaciji, objašnjava 46,98% varijance i sastoji se od ukupno 17 čestica.
Big Five Inventory (BFI-S) (Lang i sur., 2011). Za potrebe istraživanja korišten je skraćena verzija navedenog upitnika. Upitnik se sastoji od 15 čestica kojima je obuhvaćeno pet dimenzija ličnosti: neuroticizam, ugodnost, esktraverzija, savjesnost i otvorenost prema iskustvu. Slaganje sa svakom tvrdnjom ispitanici su izražavali na skali Likertovog tipa od 5 stupnjeva od 1 (uopće se ne odnosi na mene) do 5 (u potpunosti se odnosi na mene).
Na kraju upitnika dano je pitanje otvorenog tipa u kojem su ispitanici mogli dati komentare ili izraziti vlastita iskustva vezana uz korištenje igrifikacije u nastavi.
Rezultati
Prva istraživačka hipoteza, koja predviđa da ne postoji statistički značajna razlika u upoznatosti ispitanika konceptom igrifikacije, ispitana je t-testom. Uočava se da postoji razlika u upoznatosti učitelja razredne nastave i studenata s konceptom igrifikacije, ali je ona mala (M/SD (učitelji) = 3,97/1,084; M/SD (studenti) = 3,48/1,077). Rezultati Leveneova testa o jednakosti varijanci ukazuje na to da su one homogene (F = 1,778; p = ,184). Rezultati prikazani u Tablici 1 prikazuju da je t-test značajan (t = 3,397, p = ,001) te se nul-hipoteza može odbaciti i zaključiti da postoji statistička značajnost u upoznatosti s konceptom igrifikacije, s time da su učitelji bolje upoznati s konceptom igrifikacije nego studenti. Uz provedeni t-test ispitano je i postojanje korelacija između subjektivno procijenjene upoznatosti ispitanika i točne definicije igrifikacije prema literaturi te netočne definicije iste. Pearsonov koeficijent korelacije pokazao je pozitivnu korelaciju srednje jakosti između tvrdnje Upoznat/a sam s konceptom igrifikacije i Korištenje igrifikacije odnosi se na korištenje elemenata igara u nastavi, npr. bodovi, ljestvice poredaka, nagrade i sl. (rs = ,523, p<,001) te negativnu korelaciju između tvrdnje Upoznat/a sam s konceptom igrifikacije i Korištenje igrifikacije u nastavi odnosi se na korištenje igara u nastavi ili na učenje kroz igru (rs = ,-015, p = ,828). Dodatno je izračunat i Cohenov d kojim se izračunava veličina učinka provedenog testa i on iznosi 0,46 što vodi do zaključka da se radi o srednjoj veličini učinka. Drugim riječi:ima, provedeni t-test je ukazao na statistički značajnu razliku, a veličina učinka potvrđene razlike srednje je veličine.
Tablica 1
Razlike u upoznatosti učitelja i studenata s konceptom igrifikacije
|
|
grupa |
N |
M |
SD |
t-test |
p |
|
Upoznatost s konceptom igrifikacije |
učitelji razredne nastave |
109 |
3,97 |
1,084 |
3,397 |
,001 |
|
studenti |
111 |
3,48 |
1,077 |
Drugom hipotezom pretpostavljeno je da ne postoji statistički značajna razlika između učitelja i studenata Učiteljskog studija u stavovima prema igrifikaciji u nastavi. Navedena hipoteza testirana je t-testom. Uočava se da postoji mala razlika u pozitivnom stavu između učitelja razredne nastave i studenata prema igrifikaciji (M/SD (učitelji) = 3,86/0,73; M/SD (studenti) = 4,07/0,56) te izrazito mala razlika u negativnom stavu između učitelja razredne nastave i studenata prema igrifikaciji (M/SD (učitelji) = 2,11/0,49; M/SD (studenti) = 2,08/0,52). Rezultati Leveneova testa o jednakosti varijanci ukazuje na to da su one homogene (F = 2,770/,005; p = ,097/,943). Rezultati prikazani u Tablici 3. prikazuju da je t-test značajan, odnosno, da postoji statistički značajna razlika između učitelja razredne nastave i studenata Učiteljskog studija u njihovom pozitivnom stavu prema igrifikaciji te da oni imaju statistički značajno niži prosječan pozitivan stav prema igrifikaciji u nastavi u usporedbi sa studentima. Rezultati t-testa pokazuju da nema statistički značajne razlike između učitelja razredne nastave i studenata u njihovom negativnom stavu prema igrifikaciji.
Tablica 2
Razlike između pozitivnog i negativnog stava učitelja i studenata prema konceptu igrifikacije
|
|
grupa |
N |
M |
SD |
t-test |
p |
|
Pozitivan stav prema igrifikaciji |
učitelji razredne nastave |
109 |
3,86 |
,73 |
-2.322 |
,021 |
|
studenti |
111 |
4,07 |
,56 |
|||
|
Negativan stav prema igrifikaciji |
učitelji razredne nastave |
109 |
2,12 |
,49 |
,596 |
,552 |
|
studenti |
111 |
2,08 |
,52 |
|
|
U svrhu analize prediktorske vrijednosti faktora koji utječu na namjeru budućeg korištenja igrifikacije u nastavi i provjere postavljene treće hipoteze, provedena je hijerarhijska regresijska analiza u tri koraka. U prvom koraku uvrštena je vrsta zanimanja (student/ica, učitelj/ica). U drugom koraku je na navedenu varijablu dodano pet crta ličnosti (ekstraverzija, neuroticizam, ugodnost, savjesnost, otvorenost). U trećem koraku dodana je varijabla stav prema igrifikaciji (pozitivan stav, negativan stav). Teorijska pretpostavka za ovakav slijed varijabli jest ukazivanje da određene crte ličnosti imaju utjecaj na buduće korištenje igrifikacije u nastavi (Camadan i ostali, 2018; Denden i ostali, 2018) te da je pozitivan stav prema igrifikaciji značajan prediktor budućeg korištenja iste u nastavi (Asiri, 2019; Turan i ostali, 2022).
Pokazalo se kako zanimanje, kao Model 1, nema značajnu prediktivnu vrijednost objašnjenja namjere korištenja igrifikacije u budućnosti te objašnjava samo 0,4% namjere. U drugom koraku analize (Model 2) uvršteni su faktori koji objašnjavaju pet crta ličnosti te se od njih samo ugodnost pokazala značajnom. U drugom koraku povisio se postotak objašnjenja varijance namjere korištenja igrifikacije u budućnosti na 10,7%. U trećem koraku regresijske analize (Model 3) uz varijable zanimanje i pet crta ličnosti, uvrštena je i varijabla stav prema igrifikaciji (pozitivan stav, negativan stav). U posljednjem, trećem koraku, dodavanjem pozitivnog i negativnog stava kao varijable, ugodnost prestaje biti statistički značajan prediktor, dok je namjeru budućeg korištenja igrifikacije značajno predviđa samo stav, i to pozitivni stavovi pozitivno koreliraju, dok negativni stavovi negativno koreliraju te taj model objašnjava ukupno 30,1% varijance namjere korištenja igrifikacije u budućnosti.
Tablica 3
Hijerarhijska regresijska analiza za namjeru korištenja igrifikacije u budućnosti
|
Model |
Faktori |
b |
β |
t |
p |
|
1 |
zanimanje |
-,122 |
-,063 |
-,908 |
,365 |
|
F (modela) = ,463, p (modela) = ,630, R = ,067, R² = ,004, ΔR² = ,004 |
|||||
|
2 |
zanimanje |
-,106 |
-,055 |
-,781 |
,436 |
|
ekstraverzija |
,091 |
,069 |
,919 |
,359 |
|
|
neuroticizam |
-,013 |
-,010 |
-,146 |
,884 |
|
|
ugodnost |
,289 |
,182 |
2,,191 |
,018 |
|
|
savjesnost |
,147 |
,096 |
1,291 |
,198 |
|
|
otvorenost |
,143 |
,107 |
1,426 |
,155 |
|
|
F (modela) = 3,451, p (modela) = ,002, R = ,327, R² = ,107, ΔR² = ,102 |
|||||
|
3 |
zanimanje |
-,211 |
-,109 |
-1,722 |
,087 |
|
ekstraverzija |
,037 |
,028 |
,423 |
,672 |
|
|
neuroticizam |
,006 |
,005 |
,072 |
,942 |
|
|
ugodnost |
,191 |
,120 |
1,755 |
,081 |
|
|
savjesnost |
,095 |
,062 |
,934 |
,351 |
|
|
otvorenost |
,070 |
,053 |
,785 |
,434 |
|
|
pozitivan stav prema igrifikaciji |
,391 |
,258 |
3,599 |
,000 |
|
|
negativan stav prema igrifikaciji |
-.530 |
-,279 |
-4,059 |
,000 |
|
|
F (modela) = 9,578, p (modela) = ,000, R = ,549, R² = ,301, ΔR² = ,194 |
|||||
Devetnaest ispitanika odgovorilo je na otvoreno pitanje u kojem ih se pozivalo da podijele svoje komentare, iskustva ili zabrinutosti vezane uz korištenje igrifikacije u nastavi. Jedan je komentar bio djelomično pozitivan, npr. vremenski je zahtjevno pripremiti takve aktivnosti, ali se isplati uložiti to vrijeme u svrhu poticanja na učenje, bolje razumijevanje sadržaja i motivaciju učenika, jedan je komentar neutralan, npr. smatram da samo ne bi trebalo pretjerati s količinom, dok su preostali komentari, točnije njih sedamnaest, pozitivni, npr. itekako bi igrifikacija trebala više koristiti u nastavi jer djeca promišljaju i nesvjesno razvijaju socijalne vještine i stječu znanje ili djeci se to jako sviđa, zadovoljni su, zaigrani i željni pobjede koja im je veliki motivator. Troje ispitanika izrazilo je želju za edukacijom vezanom uz korištenje igrifikacije u nastavi, npr. zanima me kvalitetnija primjena igrifikacije u nastavi, voljela bih da postoji edukacija za učitelje o igrifikaciji ili voljela bih da ponudite opcije za nas koji minimalno koristimo tehnologiju u nastavi; kako napraviti opciju igrifikacije na ploči ili plakatu.
Rasprava i zaključak
Ovim istraživanjem željela se ispitati upoznatost učitelja razredne nastave i studenata učiteljskog studija s konceptom igrifikacije, njihovi stavovi prema korištenju igrifikacije u nastavi te utvrditi postoji li povezanost između namjere budućeg korištenja igrifikacije s njihovim stavovima i karakteristikama pojedinih crta ličnosti.
Za razliku od rezultata prethodnih istraživanja (E. Brooks i sur., 2019; Guerrero Puerta, 2024; Mårell-Olsson, 2022; Toda i sur., 2020; Yaşar i sur., 2020), rezultati ovog istraživanja pokazali su kako su postoji statistički značajna razlika između učitelja razredne nastave i studenata učiteljskog studija u njihovoj upoznatosti s konceptom igrifikacije, s time da su učitelji bolje upoznati s konceptom igrifikacije od studenata.
U skladu s prethodnim istraživanjima (Asiri, 2019; Martí-Parreño i sur., 2016; Sáez-López i sur., 2022), rezultati provedenog istraživanja pokazuju kako učitelji i studenti imaju pozitivan stav prema igrifikaciji. Druga hipoteza djelomično je potvrđena jer je istraživanjem utvrđeno da postoji statistički značajna razlika između učitelja razredne nastave i studenata Učiteljskog studija u njihovom pozitivnom stavu prema igrifikaciji te da učitelji imaju statistički značajno niži prosječan pozitivan stav prema igrifikaciji u nastavi u usporedbi sa studentima. Također, pokazano je kako nema statistički značajne razlike između učitelja razredne nastave i studenata u njihovom negativnom stavu prema igrifikaciji.
Kao što i prethodna istraživanja pokazuju (Asiri, 2019; Turan i sur., 2022), pozitivan stav prema igrifikaciji statistički je značajni prediktor korištenja igrifikacije u budućnosti. Navedeno je dobiveno i u rezultatima ovoga istraživanja čime se djelomično potvrđuje posljednja hipoteza istraživanja, jer za razliku od prethodnih istraživanja (Cramariuc i sur., 2022), otvorenost prema novim iskustvima nije se pokazala kao statistički značajan prediktor za buduće korištenje igrifikacije u nastavi.
Postoje neka ograničenja istraživanja koja onemogućuju generalizaciju dobivenih rezultata na cijelu populaciju. Glavno ograničenje je odabrani prigodni uzorak. Vjerojatnije je da će u istraživanju radije sudjelovati oni koji imaju pozitivniji stav prema igrifikaciji. S obzirom na to da se 30% varijance (R² = ,301) u namjeri budućeg korištenja igrifikacije u nastavi može objasniti posjedovanjem pozitivnog stava prema igrifikacija, ostalih 70% neobjašnjene varijance naglašava da postoje još neke varijable koje utječu na namjeru korištenja iste te one zahtijevaju daljnje istraživanje. Buduća istraživanja mogla bi prevladati ove nedostatke korištenjem drugačijeg uzorkovanja ispitanika poput korištenja slučajnih uzoraka. Mogu se koristiti i kvalitativne metode u istraživanju s ciljem dobivanja dubljeg uvida u stavove učitelja, poput fokus grupa ili dubinskih intervjua. U budućim istraživanja mogla bi se istražiti razlika u stavovima učitelja razredne nastave prema igrifikaciji između trenutačnih korisnika i onih koji ju ne koriste. Također, buduća istraživanja mogla bi obuhvatiti učitelje i studente učiteljskih studija iz cijele Hrvatske s ciljem pružanja sveobuhvatnijeg uvida u percepciju igrifikacije u hrvatskom obrazovnom sustavu.
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Teaching (Today for) Tomorrow: Bridging the Gap between the Classroom and Reality 3rd International Scientific and Art Conference |
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Teachers' and Students' Attitudes Towards the Use of Gamification in Teaching
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Abstract |
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Gamification refers to the use of game elements in environments that are not necessarily intended for play, with the aim of enhancing individual motivation and engagement as well as facilitating a deeper understanding of specific content. The aim of this study was to examine the familiarity of the teachers and students from the Faculty of Teacher Education with the concept of gamification, their attitudes towards its use in teaching, and to determine whether there is a correlation between the interaction to use gamification in the future and their attitudes and certain personality traits. The study included 111 primary school teachers employed in the city of Zagreb and 109 fourth-and fifth-year students from the Faculty of Teacher Education in Zagreb. A questionnaire on attitudes towards gamification, consisting of 32 statements, and a shortened version of the Big ive personality traits inventory, composed of 15 items, were used. Respondents evaluated their agreement with each statement on a five-point Likert scale. The results show that teachers are more familiar with the concept of gamification than students, but both groups share a positive attitude towards its application in teaching. Teachers have a statistically significantly lower average positive attitude towards gamification in teaching compared to students. Furthermore, the results indicate that a positive attitude towards gamification is the only statistically significant predictor to future use in teaching. Future research could explore the difference in attitudes towards gamification among current users and non-users of gamification in primary education. Additionally, future research could include teachers and students from teacher education programs across Croatia with the aim of providing a more comprehensive understanding of the application and perception of gamification within the Croatian educational system. |
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