Introduction
The PE process has been claimed as an important pedagogical tool for student development in schools. There were various innovations developed by teachers such as sophisticated, modern, and accessible technology (Bores-García et al., 2024; Marín-Suelves et al., 2023). Some technologies that have been reported to be used during PE teaching are augmented reality, virtual reality (Pérez-Muñoz et al., 2024), and including SA (Gil-Espinosa et al., 2022; Soliman et al., 2022; Vega-Ramírez et al., 2020; Zulkifli & Danis, 2022). The increasing popularity of technology-based PE teaching is solely due to the positive benefits that can be obtained, for example previous studies have reported that technology has been proven to be a stimulus to stimulate improvements in technical performance aspects (Tannoubi et al., 2023), and mental (Novetra et al., 2025). Other studies have shown that technology in the form of video technology is effective in improving low motivation to be higher than before (Basri et al., 2024). Based on current literature, it confirms that involving the use of augmented reality-based technology in PE teaching can produce several positive benefits, for example, it can increase grit and satisfaction (Paramitha et al., 2024). Rusmanto et al. (2023) also reported that sports engagement experienced positive changes after participating in PE teaching by integrating virtual reality technology. Previous studies showed that implementing SA technology during PE is an effective method to improve several aspects such as physical activity (Zhang et al., 2022), quality of life, and motivation (Gür et al., 2020). At the same time, the trend of PE teaching showed the involvement of a curriculum, teaching style (Fernández-Vázquez et al., 2024), or teaching model. The highest development in the teaching models was due to its role in helping teachers in delivering subject matter to students (Arufe-Giráldez et al., 2023). In the last few decades, TT was the main choice by teachers in the PE curriculum. From a critical perspective, the need to experiment with new teaching was needed, to encourage better learning (Portillo et al., 2023). DTM is one of the teaching models that are popular, and has been applied in various fields of education including PE classes (Blegur & Hardiansyah, 2024). Conceptually, DTM is a teaching model that provides various types of learning activities to fulfill different needs of students (Colquitt et al., 2017). Several previous studies claimed that DTM provided positive benefits, such as increased interest, self-confidence, and academic achievement among students (Eysink et al., 2017). In addition, DTM has also been claimed by several teachers as a very important teaching practice and needs to be integrated into learning, although the facts show that teachers around the world have difficulty differentiating teaching that is tailored to the characteristics, and needs of students (Pozas et al., 2023). This study focuses on the application of SA during DTM, so that it can later present a learning experience that begins with analyzing the movements demonstrated in the animation in SA and then carrying out various learning activities, for example 5 vs 5 in a real game situation (Akbaruddin et al., 2025). Although the number of studies on SA technology, and DTM in PE showed improvement, and had been widely studied internationally, data showed that research integrated SA with DTM during PE was limited, and the impact on increasing study engagement (SE), and games performance (GP) among students was unobvious.
Conceptually, SE is interpreted as a student’s willingness to participate in learning activities during PE classes (Guo et al., 2023). According to the literature, SE reflects students’ behavior in several ways such as vigor, dedication, and absorption (De Francisco et al., 2020; Singh et al., 2022). Basically, vigor describes the behavior of students who are enthusiastic, willing to try, and actively involved in all learning activities in PE. The dedication shows the behavior of students who devote themselves fully to continuing to learn (Mahardhika et al., 2024). Meanwhile, absorption is a behavior that reflects the state of students who are more concentrated, and enjoy all learning activities in PE classes (Miao et al., 2024). In recent years, researchers have claimed that SE is considered an important aspect for students to succeed (Simón-Chico et al., 2023), and achieve high academic achievement (Hastie et al., 2022). Meanwhile, a previous study revealed that low SE was the main factor that caused students to be lazy, often play truant from school, and eventually drop out of school (Benito Mundet et al., 2021). In addition, low SE levels directly affect the intensity of sports training in PE classes (Miao et al., 2024).
In the long PE process, students wish to achieve the ultimate goal which is optimal GP development. GP means the ability of students to display high tactical-technical performance in competing in several types of team sports (Ortiz et al., 2023). In the literature, football is team sport taught in PE class sessions, and in order to achieve satisfactory learning outcomes in football course, students are required to have higher GP. Basically, the GP aspect is closely related to students’ abilities in using a base, adjust, decision-making (Manninen et al., 2024), skill execution (Farias et al., 2018), support, cover, and guard/mark which are needed in game-based sports in PE sessions (Pan et al., 2023). According to Memmert & Harvey (2008), base is the ability of students to take basic positions when defending or attacking, this includes an understanding of proper placement to support team strategy, adjust can be interpreted as the ability of students to adjust movement positions, and change strategies in game situations, decision-making is the ability of students to be able to make the right decisions in game situations while skill execution is related to the ability of students to perform technical performance such as shooting, passing, dribbling successfully. Likewise support which shows how well students support their teammates when they are in control of the ball, while cover is the ability to provide protection, and additional assistance to friends during defensive situations, guard/mark explains the ability of students to guard/mark opponents who are in control of the ball or not. A recent study reported an important fact, a high GP has a greater potential to achieve academic achievement in PE class (Bergkamp et al., 2020). In addition, according to Morales-Belando et al. (2018), a student or team who has a higher GP is able to attack and defend, so in the end has a greater chance of scoring points and winning the game.
Although there have been previous studies on SA and DTM separately, this model differs from previous studies. For example, several studies have involved the use of technology from smartphones (Al-Amri et al., 2023; Gil-Espinosa et al., 2022; Gür et al., 2020), virtual reality (Fernández-Vázquez et al., 2024), but none of the studies that focused on these technologies integrated DTM sessions with soccer material in PE classes. Thus to the best of our knowledge this is the first study involving SA during DTM with soccer material during PE class to improve SE and GP.
Therefore, our current study, has the main objective to investigate the effects of SA-integrated DTM on SE, and GP among male and female students in PE classes. The hypothesis is described as follows:
Hypothesis 1 (H1): Male, and female students who follow SA instruction integrated in DTM will show higher SE scores than TT.
Hypothesis 2 (H2): Male, and female students who receive TT will have lower GP scores than the SA group integrated in DTM.
Methods
Recruitment, Participants And Randomisation
We used G*power 3.1 software analysis to determine the minimum sample requirement in this research. For the analysis, the effect size was 0.40, the significance level was 0.05, and the statistical power was 0.60 (1 – β). The sample size (participants) in each group was determined to be 24 students. Therefore, to overcome the possibility of design effects, and a dropout rate of 20%, it was planned to involve at least 40 students in each group.
Based on the G*Power analysis above, the participants in this study were 80 students who were in the first year of junior high school with details of 40 males, and 40 females from two junior high schools in Karawang City, West Java (Indonesia). The reason to involve first-year junior high school students was because students in the second, and third years were participating in many championship events at national or international levels. The steps to recruit participants were carried out by: contacting (via WhatsApp) related parties such as students, teachers, principals, and parents. They were given information about the procedures, benefits, risks, and objectives of this study. The research team selected the students by using the following inclusion criteria: (i) 100% attendance rate, (ii) voluntarily agree to be involved as participants, (iii) do not have experienced any injuries in the last 1 month, and (iv) have access to a smartphone (students were familiar with and owned smartphone apps, but students’ previous experience with smartphone apps was not assessed). While the exclusion criteria covered: (i) participation in championship events at national or international levels, (ii) medical problems or chronic illnesses, and (iii) without permission from parents. Based on the inclusion and exclusion criteria, 60 participants were selected, and 20 were excluded. 60 students were selected to be randomized using the online random assignment tool method (https://www.randomizer.org/) into the experimental group, namely SA-integrated DTM (n = 30; male = 15; female = 15), and the control group, namely TT (n = 30; male = 15; female = 15). In addition, information on participant characteristics is described in Table 1. Before the study began, the researcher obtained an approval form the junior high school ethics committee (registration number: 376-10-2024). In addition, a consent letter was signed by the students, and their parents. This study strictly followed the guidelines of the latest Declaration of Helsinki (2024).
Table 1
Characteristics of the participant.
| TEACHING | SEX | N (f) | AGE (years) | HEIGHT (cm) | WEIGHT (kg) | BMI (kg/m2) |
|---|---|---|---|---|---|---|
| SA-integrated DTM | Male | 15 | 12.4 ± 0.507 | 141 ± 4.08 | 39.1 ± 3.11 | 21.9 ± 1.22 |
| Female | 15 | 12.3 ± 0.488 | 138 ± 2.80 | 35.3 ± 1.53 | 21.6 ± 1.18 | |
| TT | Male | 15 | 12.5 ± 0.516 | 139 ± 3.51 | 37.3 ± 2.87 | 21.9 ± 1.03 |
| Female | 15 | 12.6 ± 0.507 | 138 ± 3.20 | 36.1 ± 2.90 | 21.3 ± 1.05 |
[i] Note: BMI: Body mass index; DTM: Differentiated teaching model; SA: Smartphones app; TT: Traditional teaching.
Measurements
SE. This study adopted The Utrecht Work Engagement Scale-Student (UWES-S) from previous studies (Mahardhika et al., 2024; Miao et al., 2024). This instrument had 17 question items from three dimensions: (i) vigor with 6 question items, for example, “When participating sports in PE class I feel very enthusiastic”, (ii) dedication with 5 question items, for example, “I am always committed to studying hard in achieving goals”, and (iii) absorption dimensions with 6 question items, for example, “I always concentrate, and enjoy sports lessons in PE class”. UWES-S was answered using a Likert scale from 1 (strongly disagree) to 5 (strongly agree). A high UWES-S score indicated higher student learning engagement. In this study, the intra-class correlation coefficient (ICC) of each dimension was reported as 0.874, 0.820, and 0.845. In addition, UWES-S has been validated in advance into an Indonesian language version.
GP. Based on previous studies, the Game Performance Assessment Instrument (GPAI) has been proven valid for use in assessing GP levels in PE classes (Mahardhika et al., 2024; Pan et al., 2023). However, in this study, GPAI was modified into the Game Performance Assessment Instrument Digital (GPAID). GPAID consists of eight main assessment indicators in GP, namely: (i) base, (ii) adjust, (iii) decision-making, (iv) skill execution, (v) support, (vi) cover, and (vii) guard/mark (Memmert & Harvey, 2008). In order to assess the eight GP indicators, participants were required to compete for 10 minutes, and recorded by a Full HD camera, JVC Quad-Proof R GZ-R315BEU (JVC, Tokyo, Japan) fixed on a tripod in the middle of the field at a height of 5 m, to ensure a view from above that was focused on the game. Scoring was calculated through the total number of eight GP indicators, for example, if skill execution was conducted correctly/efficiently, the score would be 1. On the contrary, if it was conducted incorrectly/inefficiently, the score would be 0. The scores were added up and used as the final data for statistical analysis purposes. In this study, the intra-class correlation coefficient (ICC) was tested with each being base (0.862), adjust (0.870), decision-making (0.890), skill execution (0.836), support (0.784), cover (0.756), and guard/mark (0.858). In addition, GPAID has been validated in advance in the Indonesian language version.
Procedures
This 9-week experimental study with pre- mid-, and post-test design was conducted from October-November 2024 on a sports schedule (e.g., football) in PE class at 08:00–10:00 am every Monday, Wednesday, and Friday (3 sessions/week) at one of the junior high schools located in Karawang City, West Java (Indonesia), which was agreed as the study location. In the first week, participants conducted a pre-test, namely filled in the SG, and measured the GP. The pre-test activities were closely supervised by the research team, and three experts to assist in analyzing the GP recordings. These experts had skills in sports coaching, and had a Dr degree. In the second week, all participants carried out the intervention program, namely SA-integrated DTM, and TT until the fifth week, while in the sixth week it was scheduled carry out the mid-test (SE, GP), then in the seventh week was continued by implementing the intervention program until the eighth week. In the last week, all participants carried out post-test activities, namely filled in SG, and measured GP. The experimental design of the study is presented in Figure 1.
Figure 1
Experimental design of study.
Intervention Program
The teacher who performed the intervention program in the SA-integrated DTM group was an expert, with ten years of experience in teaching PE. The teacher in the TT group has taught PE in junior high schools. The SA-integrated DTM, and TT intervention programs were implemented in three phases, namely: (i) pre-class, (ii) during-class, and (iii) after-class. The SA-integrated DTM program was initiated by giving instruction to participants in the DTM group to watch, and analyze each technical performance for 10 minutes in a football game which was found in the small side game smartphone application. Then, chose a learning activity that they were interested in, and carried out on that day for 50 minutes (see Table 2). At the same time, the control group performed TT, which depend on explanations, and demonstrations regarding technical performance carried out by the teacher. Thus, the TT process in the control group did not involve SA.
Table 2
The teaching program of SA-integrated DTM, and TT for 9 weeks.
| SA-INTEGRATED DTM | TT | ||||||
|---|---|---|---|---|---|---|---|
| WEEKS | DURATION (MIN) | APPS USED | CURRICULUM | ACTIVITY | DURATION (MIN) | CURRICULUM | ACTIVITY |
| 1 | 90 | Pre-Test: student engagement and game performance | |||||
| 2–3 | Course materials: Football | Course materials: Football | |||||
| 10 | Pre-class | Warm-up | 10 | Pre-class | Warm-up | ||
| 60 | Small side game | During-class | Before the learning activity begins, students analyze the basic techniques of football in small side game apps. Learning activity 1: Practice shooting, dribbling and passing in groups (5 people in one group). Learning activity 2: Attacking the goal/defending the goal in a 5 vs 5 game situation (with goalkeeper). Learning activity 3: Full game. | 60 | During-class |
| |
| 10 | After-class | Cool-down | 10 | After-class | Cool-down | ||
| 4–5 | 10 | Pre-class | Warm-up | 10 | Pre-class | Warm-up | |
| 60 | Small side game | During-class | Before the learning activity begins, students analyze the basic techniques of football in small side game apps. Learning activity 1: Practice dribbling, passing, and shooting in groups (5 people in one group). Learning activity 2: Attacking/defending in a 5 vs 5 game situation. Learning activity 3: Real game situations 5 vs 5. | 60 | During-class |
| |
| 10 | After-class | Cool-down | 10 | After-class | Cool-down | ||
| 6 | Mid-Test: student engagement and game performance | ||||||
| 7–8 | 10 | Pre-class | Warm-up | 10 | Pre-class | Warm-up | |
| 60 | Small side game | During-class | Before the learning activity begins, students analyze the basic techniques of football in small side game apps. Learning activity 1: Practice dribbling, passing, and shooting in groups (5 people in one group). Learning activity 2: Keep the ball in one’s own side/attacking the goal/defending the goal. Learning activity 3: Real game situations. | 60 | During-class |
| |
| 10 | After-class | Cool-down | 10 | After-class | Cool-down | ||
| 9 | 90 | Post-Test: student engagement and game performance | |||||
Statistical analysis
The SE and GP measurement data were analyzed with Jamovi v.2.3.2 statistical software (The Jamovi project, Sidney, Australia), and p < 0.05 was determined to indicate the level of statistical significance. The SE, and GP measurement steps are explained as follows. First, researchers calculated descriptive statistics presented in mean ± standard deviation. Second, the normality of the data was tested through Shapiro-Wilk’s, and the results showed a normal distribution (p > 0.05). Third, ICC to determine the reliability value of the dependent variables (SE, GP). Fourth, the test score formula – pre-test score/pre-test score x 100 + post-test score – mid-test score/mid-test score x 100/2, to indicate the delta percentage value (Δ%). Fifth, considering the data was normal, we conducted a parametric approach with 2-Way RM ANOVA to test the main effect of time (pre- vs mid- vs post-test), the main effect of teaching (SA-integrated DTM vs TT), and interaction (time [pre- vs mid- vs post-test] vs teaching [SA-integrated DTM vs TT]) on SE and GP. The Bonferroni post hoc test was used to determine pairwise differences. The effect size was calculated using partial eta-squared (η2p): 0.01, 0.06, and above 0.14.
Results
Effect of SA-integrated DTM and TT on SE
The results of the 2-Way RM-ANOVA analysis (see Table 3) show that there are significant main effects of time (F = 196.6; p < .001; ƞ2p = 0.871), teaching (F = 128.9; p < .001; ƞ2p = 0.816), and interaction (F = 15.2; p < .001; ƞ2p = 0.344) on the vigor aspect. At the same time, there are significant main effects of time (F = 274.2; p < .001; ƞ2p = 0.904), teaching (F = 133.0; p < .001; ƞ2p = 0.821), and interaction (F = 67.6; p < .001; ƞ2p = 0.700) on dedication aspect. Finally, a similar result is found on the absorption aspect, that there is significant main effect of time (F = 464.6; p < .001; ƞ2p 0.941), teaching (F = 127.4; p < .001; ƞ2p = 0.815), and interaction (F = 52.1; p < .001; ƞ2p = 0.642).
Table 3
Effects of teaching (SA-integrated DTM vs TT) on SE.
| Variables measured | Teaching | Sex (N) | Pre-Test | Mid-Test | Post-Test | 95% CI | Δ (%) | 2-Way RM ANOVA | ||
|---|---|---|---|---|---|---|---|---|---|---|
| WITHIN SUBJECTS EFFECTS | ||||||||||
| TIME | TEACHING | TIME VS TEACHING | ||||||||
| Vigor (points) | SA-integrated DTM | Male (15) | 14.7 ± 1.91 | 21.6 ± 1.50 | 24.8 ± 2.40 | –7.95 to –5.78 | +30.88 | F = 196.6 p < .001* η2p = 0.871 | F = 128.9 p < .001* η2p = 0.816 | F = 15.2 p < .001* η2p = 0.344 |
| Female (15) | 15.3 ± 1.39 | 17.9 ± 1.67 | 22.4 ± 1.68 | –3.86 to –1.47 | +21.07 | |||||
| TT | Male (15) | 12.5 ± 1.55 | 15.5 ± 1.19 | 19.3 ± 2.53 | –3.84 to –2.16 | +24.26 | ||||
| Female (15) | 13.5 ± 1.41 | 15.1 ± 1.13 | 19.5 ± 0.990 | –2.18 to –1.02 | +20.50 | |||||
| Dedication (points) | SA-integrated DTM | Male (15) | 13.5 ± 1.36 | 22.0 ± 1.46 | 26.4 ± 1.68 | –9.63 to –7.30 | +40.48 | F = 274.2 p < .001* η2p = 0.904 | F = 133.0 p < .001* η2p = 0.821 | F = 67.6 p < .001* η2p = 0.700 |
| Female (15) | 14.4 ± 1.12 | 18.5 ± 1.73 | 24.7 ± 1.95 | –5.18 to –2.95 | +30.99 | |||||
| TT | Male (15) | 13.9 ± 1.03 | 16.6 ± 1.35 | 19.4 ± 2.16 | –3.35 to –1.98 | +18.15 | ||||
| Female (15) | 14.5 ± 1.30 | 16.7 ± 1.29 | 18.9 ± 2.05 | –3.04 to –1.36 | +14.17 | |||||
| Absorption (points) | SA-integrated DTM | Male (15) | 15.6 ± 1.35 | 22.3 ± 1.58 | 27.6 ± 1.59 | –8.13 to –5.21 | +33.36 | F = 464.6 p < .001* η2p = 0.941 | F = 127.4 p < .001* η2p = 0.815 | F = 52.1 p < .001* η2p = 0.642 |
| Female (15) | 15.7 ± 1.53 | 19.7 ± 1.18 | 25.9 ± 1.98 | –4.83 to –3.03 | +28.47 | |||||
| TT | Male (15) | 15.9 ± 1.10 | 18.4 ± 1.12 | 21.8 ± 1.42 | –3.12 to –1.81 | +17.10 | ||||
| Female (15) | 15.8 ± 1.08 | 18.6 ± 1.59 | 21.4 ± 1.92 | –3.64 to –1.96 | +16.39 | |||||
[i] Note: DTM: Differentiated teaching model; SA: Smartphone Apps; TT: Traditional teaching; CI: Confident interval; Δ (%): Delta percentage. Significance level at *p < 0.001.
Bonferroni post hoc (see Figure 2) shows significant differences in pre-, mid- and post-test between groups (p < 0.001), but the magnitude of change is greater in the SA integrated DTM group such as in vigor (95% CI: male = –7.95 to –5.78, female = –3.86 to –1.47; Δ (%): male = +30.88, female = +21.07), dedication (95% CI: male = –9.63 to –7.30, female = –5.18 to –2.95; Δ (%): male = +40.48, female = +30.99), and absorption (95% CI: male = –8.13 to –5.21, female = –4.83 to –3.03; Δ (%): male = +33.36, female = +28.47) compare to TT in vigor (95% CI: male = –3.84 to –2.16, female = –2.18 to –1.02; Δ (%): male = +24.26, female = +20.50), dedication (95% CI: male = –3.35 to –1.98, female = –3.04 to –1.36; Δ (%): male = +18.15, female = +14.17), and absorption (95% CI: male = –3.12 to –1.81, female = –3.64 to –1.96; Δ (%): male = +17.10, female = +16.39) (see Table 3).
Figure 2
Percentage change of SE ([A] Vigor, [B] Dedication, [C] Absorption). *Significant differences between pre-, mid-, and post-test in SA-integrated DTM. #Significant differences between pre-, mid-, and post-test in TT.
Effect of SA-integrated DTM and TT on GP
The results of the 2-Way RM-ANOVA analysis (see Table 4) show that there are significant main effects of time (F = 355.17; p < .001; ƞ2p = 0.925), teaching (F = 30.45; p < .001; ƞ2p = 0.512), and interaction (F = 9.53; p < .001; ƞ2p = 0.247) on the base aspect. At the same time, there were significant main effects of time (F = 274.52; p < .001; ƞ2p = 0.904), teaching (F = 31.53; p < .001; ƞ2p = 0.521), and interaction (F = 4.86; p = 0.016; ƞ2p = 0.144) on adjust aspect. There was an effect of time (F = 386.9; p < .001; ƞ2p = 0.933), teaching (F = 73.2; p < .001 ƞ2p = 0.723), and interaction (F = 21.3; p < .001; ƞ2p = 0.432) on decision-making aspect. On skill execution aspect, has an effect of time (F = 443.8; p < .001; ƞ2p = 0.939), teaching (F = 21.6; p < .001; ƞ2p = 0.426), and interaction (F = 36.9; p < .001; ƞ2p = 0.560). Support aspect shows an effect of time (F = 342.2; p < .001; ƞ2p = 0.922), teaching (F = 95.2; p < .001; ƞ2p = 0.767), and interaction (F = 16.0; p < .001; ƞ2p = 0.356). Then, the cover aspect shows that there is an effect of time (F = 224.78; p < .001; ƞ2p = 0.886), teaching (F = 5.33; p = 0.028; ƞ2p = 0.155), and interaction (F = 6.84; p = 0.002; ƞ2p = 0.191). Finally, the similar results in the guard/mark aspect, show the effects of time (F = 475.1; p < .001; ƞ2p = 0.942), teaching (F = 28.6; p < .001; ƞ2p = 0.496), and interaction (F = 36.6; p < .001; ƞ2p = 0.558).
Table 4
Effects of teaching (SA-integrated DTM vs TT) on GP.
| VARIABLESMEASURED | TEACHING | SEX (N) | PRE-TEST | MID-TEST | POST-TEST | 95% CI | Δ (%) | 2-WAY RM ANOVA | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| WITHIN SUBJECTS EFFECTS | |||||||||||
| TIME | TEACHING | TIME VS TEACHING | BONFERRONI POST HOC (PRE-, MID-, POST-TEST) | ||||||||
| Base (points) | SA-integrated DTM | Male (15) | 7.47 ± 0.743 | 9.00 ± 1.00 | 12.4 ± 1.64 | –1.82 to –1.25 | +29.13 | F = 355.17 p < .001* η2p = 0.925 | F = 30.45 p < .001* η2p = 0.512 | F = 9.53 p < .001* η2p = 0.247 | SA-DTM vs CG (p < 0.001) |
| Female (15) | 6.87 ± 0.74 | 8.67 ± 0.72 | 11.0 ± 1.60 | –2.23 to –1.37 | +26.54 | ||||||
| TT | Male (15) | 6.07 ± 1.03 | 7.73 ± 0.884 | 9.40 ± 1.06 | –2.16 to –1.17 | +24.48 | |||||
| Female (15) | 6.47 ± 0.834 | 8.13 ± 0.834 | 10.1 ± 1.16 | –2.20 to –1.10 | +24.94 | ||||||
| Adjust (points) | SA-integrated DTM | Male (15) | 6.40 ± 0.828 | 7.73 ± 0.704 | 9.27 ± 0.884 | –1.73 to –0.933 | +20.35 | F = 274.52 p < .001* η2p = 0.904 | F = 31.53 p < .001* η2p = 0.521 | F = 4.86 p = 0.016* η2p = 0.144 | SA-DTM vs CG (p < 0.001) |
| Female (15) | 6.07 ± 0.704 | 7.67 ± 0.816 | 9.93 ± 1.10 | –1.60 to 0.190 | +27.91 | ||||||
| TT | Male (15) | 6.87 ± 0.640 | 8.33 ± 0.617 | 10.8 ± 1.26 | –1.88 to –1.06 | +25.45 | |||||
| Female (15) | 6.47 ± 0.640 | 8.13 ± 0.990 | 10.6 ± 1.45 | –2.28 to –1.05 | +28.02 | ||||||
| Decision-making (points) | SA-integrated DTM | Male (15) | 5.73 ± 0.884 | 9.27 ± 1.10 | 12.9 ± 1.73 | –4.25 to –2.81 | +50.47 | F = 386.9 p < .001* η2p = 0.933 | F = 73.2 p < .001* η2p = 0.723 | F = 21.3 p < .001* η2p = 0.432 | SA-DTM vs CG (p < 0.001) |
| Female (15) | 7.00 ± 0.926 | 9.67 ± 1.29 | 13.2 ± 1.86 | –3.21 to –2.13 | +37.32 | ||||||
| TT | Male (15) | 5.27 ± 0.799 | 7.73 ± 0.799 | 9.93 ± 1.39 | –3.02 to –1.92 | +37.57 | |||||
| Female (15) | 6.14 ± 0.949 | 8.14 ± 0.770 | 10.5 ± 1.16 | –2.51 to –1.49 | +30.78 | ||||||
| Skill execution (points) | SA-integrated DTM | Male (15) | 4.47 ± 0.743 | 7.53 ± 0.834 | 12.3 ± 2.19 | –3.60 to –2.53 | +65.90 | F = 443.8 p < .001* η2p = 0.939 | F = 21.6 p < .001* η2p = 0.426 | F = 36.9 p < .001* η2p = 0.560 | SA-DTM vs CG (p < 0.001) |
| Female (15) | 5.13 ± 0.834 | 8.47 ± 0.743 | 12.2 ± 2.11 | –3.87 to –2.79 | +54.57 | ||||||
| TT | Male (15) | 5.47 ± 0.834 | 6.73 ± 0.594 | 9.07 ± 0.884 | –1.76 to –0.777 | +28.90 | |||||
| Female (15) | 5.60 ± 0.632 | 7.47 ± 0.915 | 10.4 ± 1.35 | –2.37 to –1.36 | +36.31 | ||||||
| Support(points) | SA-integrated DTM | Male (15) | 9.07 ± 1.28 | 12.3 ± 1.53 | 15.7 ± 1.45 | –4.04 to –2.36 | +31.63 | F = 342.2 p < .001* η2p = 0.922 | F = 95.2 p < .001* η2p = 0.767 | F = 16.0 p < .001* η2p = 0.356 | SA-DTM vs CG (p < 0.001) |
| Female (15) | 10.4 ± 1.55 | 13.8 ± 1.47 | 15.9 ± 1.30 | –4.28 to –2.52 | +23.95 | ||||||
| TT | Male (15) | 7.80 ± 1.08 | 9.53 ± 1.77 | 11.5 ± 1.55 | –2.66 to –0.810 | +21.49 | |||||
| Female (15) | 7.83 ± 1.09 | 9.53 ± 1.36 | 12.1 ± 1.44 | –2.12 to –1.34 | +24.34 | ||||||
| Cover(points) | SA-integrated DTM | Male (15) | 7.81 ± 0.834 | 10.1 ± 1.12 | 12.0 ± 1.10 | –3.13 to –1.53 | +24.07 | F = 224.78 p < .001* η2p = 0.886 | F = 5.33 p = 0.028* η2p = 0.155 | F = 6.84 p = 0.002* η2p = 0.191 | SA-DTM vs CG (p < 0.001) |
| Female (15) | 7.47 ± 0.990 | 9.13 ± 1.36 | 11.7 ± 1.80 | –2.16 to –1.17 | +25.19 | ||||||
| TT | Male (15) | 7.81 ± 0.834 | 9.56 ± 0.892 | 11.0 ± 1.03 | –2.47 to –1.13 | +18.00 | |||||
| Female (15) | 7.73 ± 1.03 | 9.00 ± 1.13 | 10.9 ± 1.46 | –1.88 to –0.658 | +18.77 | ||||||
| Guard/mark(points) | SA-integrated DTM | Male (15) | 8.60 ± 1.12 | 9.80 ± 1.01 | 14.1 ± 1.64 | –1.43 to –0.971 | +28.92 | F = 475.1 p < .001* η2p = 0.942 | F = 28.6 p < .001* η2p = 0.496 | F = 36.6 p < .001* η2p = 0.558 | SA-DTM vs CG (p < 0.001) |
| Female (15) | 9.20 ± 1.21 | 10.6 ± 1.24 | 14.0 ± 1.73 | –1.40 to 0.163 | +23.65 | ||||||
| TT | Male (15) | 7.60 ± 1.40 | 8.80 ± 1.26 | 11.2 ± 1.26 | –1.43 to –0.971 | +21.53 | |||||
| Female (15) | 7.93 ± 1.16 | 9.33 ± 1.29 | 11.5 ± 1.25 | –1.75 to –1.05 | +20.46 | ||||||
[i] Note: DTM: Differentiated teaching model; SA: Smartphone Apps; TT: Traditional teaching; CI: Confident interval; Δ (%): Delta percentage. Significance level at *p < 0.001.
Bonferroni post hoc (see Table 4) shows significant differences in pre-, mid-, and post-test between groups (respectively, p < 0.001), but the magnitude of change is greater in the SA-integrated DTM group such as in the aspects of base (95% CI: male = –1.82 to –1.25, female = –2.23 to –1.37; Δ: male = +29.13, female = +26.54), adjust (95% CI: male = 1.73 to –0.933, female = –1.60 to 0.190; Δ: male = +20.35, female = +27.91), decision-making (95% CI: male = –4.25 to –2.81, female = –3.21 to –2.13; Δ: male = +50.47, female = +37.32), skill execution (95% CI: male = –2.82 to –1.25, female = –2.23 to –1.37; Δ: male = +29.13, female = +26.54), and skill execution (95% CI: male = –2.82 to –2.25, female = –2.23 to –1.37; Δ: male = +29.13, female = +26.54). CI: male = –3.60 to-2.53, female = –3.87 to –2.79; Δ: male = +54.57, female = +28.90), support (95% CI: male = –4.04 to –2.36, female = 4.28 to –2.52; Δ: male = +31.63, female = +23.95), cover (95% CI: male = –3.13 to –1.53, female = –2.16 to –1.17; Δ: male = +24.07, female = +25.19), guard/mark (95% CI: male = –1.43 to –0.971, female = –1.40 to 0.163; Δ: male = +28.92, female = +23.65) compared to TT as in base (95% CI: male = –2.16 to –1.17, female = –2.20 to –1.10; Δ: male = +24.48, female = +24.94), decision-making (95% CI: male = –3.02 to –1.92, female = –2.51 to –1.49; Δ: male = +37.57, female = +30.78), execution skills (95% CI: male = –1.76 to –0.777, female = –2.37 to –1.36; Δ: male = +28.90, female = +36.31), support (95% CI: male = –2.66 to –0.810, female = –2.12 to –1.34; Δ: male = +21.49, female = +24.34), cover (95% CI: male = –2.47 to –1.13, female = –1.88 to –0.658; Δ: male = +18.00, female = +18.77), and guard/mark (95% CI: male = –1.43 to –0.971, female = –1.75 to –1.05; Δ: male = +21.53, female = +20.46), but in adjusted (95% CI: male = –1.88 to –1.06, female = –2.28 to –1.05; Δ: male = +25.45, female = +28.02) shows that TT is greater than SA integrated DTM.
Discussion
The main objective of this study was to investigate the effects of SA-integrated with DTM on SE, and GP among male and female students in PE class. The results of the current study showed that the SA program integrated with DTM for 9 weeks was proven effective in improving SE, and GP.
The first finding in this study confirms the first hypothesis proposed, which stated that male and female students who follow SA-integrated with the DTM program will show higher SE scores than TT. This program adopted a new form of teaching that involved sophisticated and modern technology in the form of SA (small-side game smartphone application) integrated with DTM in PE class. Basically, combining SA-integrated DTM, it presented new, fun, innovative learning, and provided more opportunities for students to learn knowledge and skills during PE sessions. In addition, SA-integrated with DTM facilitated students to learn the subject matter anytime, anywhere, for example at the pre-class, during-class, or after-class stages (Langelaan et al., 2024). This result is supported by several previous studies, which involved SA during teaching in PE classes could help teachers to provide more meaningful learning experience (Gil-Espinosa et al., 2022), and facilitate students how to learn movement tasks, and ultimately achieve high learning outcomes compared to TT (Maněnová et al., 2022; Vega-Ramírez et al., 2020). In addition, Yang & Koenigstorfer (2021), reported the results of their study, which implemented fitness-based SA could be positively related to the intention to be physically active. The program offered by SA-integrated into DTM presented a variety of game-based learning media, so that students were able to choose the learning activities they were interested in at that time (Blegur & Hardiansyah, 2024), and this was a key factor that influenced SE (Cui et al., 2024). According to several previous studies, the implementation of a game-based teaching model was an effective pedagogical tool to create a fun learning climate, and help students be more motivated to learn actively (Gaspar et al., 2021; Pan et al., 2023). This finding is consistent with a previous study that reported that DTM was a reliable teaching method to improving academic achievement, and self-efficacy among students is higher (Salar & Turgut, 2021). Another study confirmed that teaching sessions with DTM allowed students to participate more in active learning activities, so the DTM model showed better learning outcomes than TT (Taş & Minaz, 2024). Varga & Révész (2023), emphasized that high learning motivation among students was influenced by mobile or smartphone application technology. Considering that SE among both male and female students increased significantly, it can be said that our study confirms this finding.
The second finding in this study also confirms the second hypothesis proposed, namely that male and female students who receive TT will have lower GP scores than the SA-integrated DTM group. This is because the combination of SA with the DTM program required students to initially observe the football material through a small side game smartphone application technology for 10 minutes, then continue with learning activities 1, 2, and 3 (see Table 2) which have game-based teaching characteristics (e.g., 5 vs 5 game situations). This learning climate, promoted students to get different movement learning experiences with TT, so that GP abilities increased after the intervention program was completed. This result is also supported by previous studies, the popularity of technology-based PE teaching increased significantly (Sargent & Calderón, 2022; Zulkifli & Danis, 2022), and it was used by teachers as an effort to improve important aspects of students, such as physical performance (Cui et al., 2024), fundamental motor skills (Webster et al., 2020), to the level of physical activity (Al-Amri et al., 2023). In our study, male and female students between the two groups experienced an increase in their GP after undergoing a 9-week intervention program, but the DTM integrated SA group achieved a much higher value than the TT, therefore the SA-integrated DTM model is a best choice with a relatively short learning time. On the other hand, Lin et al. (2023) reported similar results, the motor skill aspect of the experimental group which used technology-based teaching was able to outperform the control group (TT) significantly. Improving the GP aspect among students is one of the important PE goals, and it is the main focus of teachers, but the achievement of optimal learning outcomes will be greatly influenced by the implementation of a curriculum, and the teaching model during teaching sessions in PE classes. From this perspective, we designed a DTM integration SA model adjusted to the natural conditions of PE teaching in Indonesia, for example selecting applications (small side games) which are easy to access and use, choosing game-based learning activities that are indeed popular with students. This was also stated by Portillo et al. (2023), that the game-based teaching approach in PE was the best choice for teachers to optimize the learning process.
Finally, the results of this study indicate an increase in SE, and GP is higher in male students compared to female students, based on our observations, this is due to several factors: for example, male students are more active, enthusiastic and have higher involvement compared to female students in the learning process. In addition, other factors are environmental conditions, where in Indonesia football material is more preferred by male students than female students. This is in line with previous studies, where an increase in interest, study habits and student fitness was found to be higher in male students compared to female students (Akbaruddin et al., 2025).
Practical implications
Adding SA technology during DTM teaching with soccer material in PE class can provide a new and interesting learning experience for students. In addition, involving SA during DTM can help teachers explain the subject matter to students. However, technology is not intended to replace the role of a teacher, but to provide more opportunities for students to explore various ways and reasoning to carry out skills effectively (Zulkifli & Danis, 2022). Thus, in our current study, involving the use of SA during DTM can result in higher SE and GP achievements than before. From these findings, we hope that SA integrated into DTM teaching can continue to be applied by teachers in PE teaching in the future to produce optimal learning outcomes.
Strengths, limitations and future directions of the Research
In summary, the SA-integrated DTM program enabled PE class teaching sessions to be more meaningful, interesting, understandable and enjoyable for both males, and females. Although the findings of this study showed effectiveness in both genders, overall a large effect size was found in males. The main strengths of our current study are: (i) the SA-integrated DTM program was designed to provide diverse teaching, and rich movement experiences for both male and female students, (ii) the program was specifically created for subject matter that has team game characteristics (football). However, this study has several limitations such as: (i) SA used only one application, namely small side game smartphone, (ii) small side game smartphone application was specifically used for football, (iii) the sample size (participants) was small, and only involved the first year students in two junior high schools in Karawang City (Indonesia). The small number of participants hindered the generalization of results to other students, (iv) this trial had a short intervention period without follow-up, (v) students’ previous experiences with smartphone applications were not assessed and may have influenced engagement in the research. Therefore, future research is recommended to address the limitations of this study which include: (i) recommending future research that includes more diverse populations and samples, (ii) conducting a preliminary assessment of students’ experiences in using smartphone applications, (iii) designing and implementing SA-integrated DTM programs for other types of team sports such as handball, basketball, volleyball, futsal.
Conclusions
Based on the study results, this study confirms that the SA-integrated DTM program in 9-week was showed significantly positive effects on SE and GP among both male and female students than TT program. The findings of this study contribute to the development of research for the SA-based teaching models in PE classes. In addition, the findings of this study provide important information for PE teachers to implement the integrated SA with DTM program continuously in PE classes as an effort to maintain and foster SE and GP levels in the future. However, the knowledge of teachers and students in using SA during DTM is a determining factor for students’ success in improving SE and GP optimally. SA is not intended to replace the role of a teacher, but to optimize DTM when applied by teachers, so that it can provide a much more perfect and meaningful learning experience for students.
Data Accessibility Statement
All data supporting the findings of this study are available from the corresponding author on reasonable request.
Acknowledgements
The research team would like to thank the students who participated in this research, and those who assisted in data collection.
Competing Interests
The authors have no competing interests to declare.
Author Contributions
ETR, RA, KP, RS, MIAR and ES contributed to the concept and writing of the introduction; ETR, AT, AS, FK and ES contributed methods related to recruitment, participants, randomization, measurements, procedures; ETR, AT, AS, FK and ES contributed to designing the intervention program and statistical analyzes sections; ETR, RA, KP, RS, MIAR contributed to data collection; AT, AS, FK and ES contributed results sections; ETR, AT, AS, FK and ES contributed discussion and conclusion sections; AT, FK and ES contributed to revision and editing. All authors approved the final results of this article.