| Literature DB >> 35225928 |
Chao Gu1, Jiangjie Chen2, Chun Yang2, Wei Wei3, Qianling Jiang2, Liao Jiang4, Qiuhong Wu4, Shu-Yuan Lin5, Yunshuo Yang6.
Abstract
In this paper, we discuss the teaching effects of augmented reality (AR) technology in German instruction. We conducted one prestudy and three formal studies on German learners in China's mainland and Taiwan region. In the formal studies, a total of 120 students participated in the survey, allowing us to compare the differences in interest in learning between AR picture books and traditional picture books. A total of 114 students took part in the survey, which enabled us to compare the contribution of AR picture books to teaching when students' satisfaction and German proficiency were different. To improve satisfaction, 514 students participated in the survey regarding the influence of the interactive narrative design effect and peer learning on satisfaction with using AR picture books. The results suggest that when learning German with AR picture books, satisfaction is the key construct that determines students' learning states.Entities:
Keywords: augmented reality; cooperative learning; media in education; teaching strategies
Year: 2022 PMID: 35225928 PMCID: PMC8884012 DOI: 10.3390/jintelligence10010013
Source DB: PubMed Journal: J Intell ISSN: 2079-3200
Figure 1Spatial mapping of different ontological positions onto an interactive narrative (Koenitz 2018).
Figure 2Classification outcomes of the picture book samples and the selection results of the representative samples.
Satisfaction differences among picture books.
| Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Partial Eta Squared | Observed Power b |
|---|---|---|---|---|---|---|---|
| BBAC-FY | 4.354 a | 1 | 4.354 | 7.776 | 0.006 | 0.055 | 0.791 |
| Intercept | 2200.066 | 1 | 2200.066 | 3929.501 | 0.000 | 0.967 | 1.000 |
| Error | 75.025 | 134 | 0.560 | ||||
| Total | 2279.444 | 136 | |||||
| Corrected total | 79.378 | 135 |
a R2 = 0.055 (Adjusted R2 = 0.048); b Computed using alpha = 0.05.
Figure 3Bilingual AR picture book sample.
Differences between groups in learning interest.
| Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Partial Eta Squared | Observed Power b |
|---|---|---|---|---|---|---|---|
| Traditional -AR | 1.633 a | 1 | 1.633 | 5.470 | 0.021 | 0.044 | 0.640 |
| Intercept | 1220.668 | 1 | 1220.668 | 4087.853 | 0.000 | 0.972 | 1.000 |
| Error | 35.236 | 118 | 0.299 | ||||
| Total | 1257.537 | 120 | |||||
| Corrected Total | 36.869 | 119 |
a R Squared = 0.044 (Adjusted R Squared = 0.036); b Computed using alpha = 0.05.
MANOVA test for satisfaction.
| Dependent Variable | German Proficiency | Satisfaction | Satisfaction | Mean Difference (1–2) | S.E. | Sig. b |
|---|---|---|---|---|---|---|
| LI | 1 | 4.367 | 3.984 | 0.382 * | 0.156 | 0.016 |
| 2 | 3.487 | 2.897 | 0.590 * | 0.163 | 0.000 | |
| CLI | 1 | 4.429 | 4.059 | 0.369 * | 0.165 | 0.027 |
| 2 | 3.406 | 2.652 | 0.753 * | 0.171 | 0.000 | |
| LO | 1 | 4.375 | 3.922 | 0.453 * | 0.208 | 0.032 |
| 2 | 3.660 | 3.192 | 0.468 * | 0.217 | 0.033 |
Based on estimated marginal means: * The mean difference is significant at the 0.05 level; b Adjustment for multiple comparisons: Bonferroni.
MANOVA test for German proficiency.
| Dependent Variable | Satisfaction | German Proficiency | German Proficiency | Mean Difference (1–2) | S.E. | Sig. b |
|---|---|---|---|---|---|---|
| LI | 1 | 4.367 | 3.487 | 0.879 * | 0.163 | 0.000 |
| 2 | 3.984 | 2.897 | 1.087 * | 0.156 | 0.000 | |
| CLI | 1 | 4.429 | 3.406 | 1.023 * | 0.171 | 0.000 |
| 2 | 4.059 | 2.652 | 1.407 * | 0.165 | 0.000 | |
| LO | 1 | 4.375 | 3.660 | 0.715 * | 0.217 | 0.001 |
| 2 | 3.922 | 3.192 | 0.731 * | 0.208 | 0.001 |
Based on estimated marginal means: * The mean difference is significant at the 0.05 level; b Adjustment for multiple comparisons: Bonferroni.
Figure 4Research hypothesis diagram.
Reliability analysis results.
| Item | Corrected Item-Total Correlation | Cronbach’s Alpha If Item Deleted | Cronbach’s Alpha | Item | Corrected Item-Total Correlation | Cronbach’s Alpha If Item Deleted | Cronbach’s Alpha |
|---|---|---|---|---|---|---|---|
| PIN3 | 0.485 | 0.587 | 0.676 | FL4 | 0.483 | 0.530 | 0.653 |
| PIN4 | 0.496 | 0.572 | FL5 | 0.462 | 0.559 | ||
| PIN7 | 0.485 | 0.587 | FL7 | 0.446 | 0.581 | ||
| PN1 | 0.466 | 0.475 | 0.624 | SA1 | 0.493 | 0.554 | 0.668 |
| PN2 | 0.427 | 0.532 | SA2 | 0.481 | 0.570 | ||
| PN3 | 0.405 | 0.563 | SA3 | 0.464 | 0.592 | ||
| PIG1 | 0.450 | 0.531 | 0.636 | ||||
| PIG2 | 0.447 | 0.537 | |||||
| PIG3 | 0.439 | 0.547 |
Results of exploratory factor analysis.
| Construct | KMO | Bartlett’s Sphere Test | Item | Commonality | Factor Loading | Eigenvalue | Total Variation Explained % |
|---|---|---|---|---|---|---|---|
| PIN | 0.665 | 0.000 | PIN3 | 0.603 | 0.776 | 1.821 | 60.710% |
| PIN4 | 0.617 | 0.785 | |||||
| PIN7 | 0.602 | 0.776 | |||||
| PN | 0.641 | 0.000 | PN1 | 0.616 | 0.785 | 1.712 | 57.061% |
| PN2 | 0.564 | 0.751 | |||||
| PN3 | 0.531 | 0.729 | |||||
| PIG | 0.652 | 0.000 | PIG1 | 0.586 | 0.765 | 1.737 | 57.893% |
| PIG2 | 0.581 | 0.762 | |||||
| PIG3 | 0.570 | 0.755 | |||||
| FL | 0.655 | 0.000 | FL4 | 0.616 | 0.785 | 1.773 | 59.086% |
| FL5 | 0.589 | 0.768 | |||||
| FL7 | 0.567 | 0.753 | |||||
| SA | 0.661 | 0.000 | SA1 | 0.618 | 0.786 | 1.803 | 60.088% |
| SA2 | 0.603 | 0.777 | |||||
| SA3 | 0.581 | 0.762 |
Figure 5First-order CFA model.
Adaptation indices of the first-order CFA model.
| Common Indices | χ2 | df | χ2/df | RMSEA | GFI | AGFI | CFI | NFI | SRMR |
|---|---|---|---|---|---|---|---|---|---|
| Judgement criteria | <3 | <0.08 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 | ||
| Value | 81.686 | 80 | 1.021 | 0.006 | 0.979 | 0.969 | 0.999 | 0.962 | 0.024 |
Convergence validity results.
| Item | Factor Loading | t | S.E. | Sig. | CR | AVE |
|---|---|---|---|---|---|---|
| PIN3 | 0.63 | 14.076 | 0.034 | 0.001 | 0.675 | 0.410 |
| PIN4 | 0.64 | 14.338 | 0.034 | 0.002 | ||
| PIN7 | 0.65 | 14.559 | 0.033 | 0.002 | ||
| PN1 | 0.65 | 14.591 | 0.035 | 0.002 | 0.628 | 0.362 |
| PN2 | 0.60 | 13.189 | 0.036 | 0.001 | ||
| PN3 | 0.55 | 11.978 | 0.039 | 0.001 | ||
| PIG1 | 0.59 | 12.698 | 0.039 | 0.001 | 0.636 | 0.368 |
| PIG2 | 0.62 | 13.440 | 0.039 | 0.002 | ||
| PIG3 | 0.61 | 13.238 | 0.037 | 0.001 | ||
| FL4 | 0.63 | 14.155 | 0.037 | 0.001 | 0.652 | 0.385 |
| FL5 | 0.64 | 14.420 | 0.035 | 0.001 | ||
| FL7 | 0.59 | 13.257 | 0.036 | 0.001 | ||
| SA1 | 0.63 | 14.448 | 0.034 | 0.001 | 0.668 | 0.401 |
| SA2 | 0.65 | 14.851 | 0.033 | 0.001 | ||
| SA3 | 0.62 | 14.235 | 0.035 | 0.002 |
Discriminant validity results.
| PIN | PN | PIG | FL | SA | |
|---|---|---|---|---|---|
| PIN | 0.640 | ||||
| PN | 0.549 ** | 0.602 | |||
| PIG | 0.498 ** | 0.539 ** | 0.607 | ||
| FL | 0.523 ** | 0.520 ** | 0.497 ** | 0.620 | |
| SA | 0.553 ** | 0.575 ** | 0.510 ** | 0.617 ** | 0.633 |
* p <, 0.05 ** p < 0.01 The diagonal number is the square root of the factor AVE.
Figure 6Second-order CFA model.
Adaptability of second-order CFA model.
| Common Indices | χ2 | df | χ2/df | RMSEA | GFI | AGFI | CFI | NFI | SRMR |
|---|---|---|---|---|---|---|---|---|---|
| Judgement criteria | <3 | <0.08 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 | ||
| Value | 18.177 | 24 | 0.757 | 0.000 | 0.992 | 0.986 | 1.000 | 0.982 | 0.018 |
Figure 7Structural equation model.
Adaptability of SEM.
| Common Indices | χ2 | df | χ2/df | RMSEA | GFI | AGFI | CFI | NFI | SRMR |
|---|---|---|---|---|---|---|---|---|---|
| Judgement criteria | <3 | <0.08 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 | ||
| Value | 83.610 | 84 | 0.995 | 0.000 | 0.979 | 0.970 | 1.000 | 0.961 | 0.025 |
Direct and indirect effects.
| Path | Direct Effect | Indirect Effect | Total Effect | |||
|---|---|---|---|---|---|---|
| β | B-C Sig. | β | B-C Sig. | β | B-S Sig. | |
| INDE→FL | 0.876 | 0.001 | / | / | 0.876 | 0.001 |
| FL→SA | 0.553 | 0.006 | / | / | 0.553 | 0.006 |
| INDE→SA | 0.436 | 0.095 | 0.484 | 0.005 | 0.920 | 0.001 |
Moderating effect results.
| Group | INDE→SA β | Nested Model Comparisons | ||
|---|---|---|---|---|
| Original Model | Specify PL β = Ilβ Model | CMIN | Sig. | |
| PL | 0.36 | 0.39 | 0.828 | 0.363 |
| IL | 0.83 | 0.41 | ||
Summary of survey results.
| Studies | Content | Variables | Results |
|---|---|---|---|
| Prestudy | Select representative samples with high and low satisfaction. | SA | Select high satisfaction sample (BBAC), and low satisfaction sample (FY). |
| Study 1 | Contrast AR picture books with traditional picture books in German instruction. | LI | Students who used AR picture books had higher interest in learning. |
| Study 2 | Examine how AR picture books contribute to different levels of satisfaction regarding students’ learning. | LI, CLI, LO | AR picture books with higher satisfaction enhanced the learning of German. |
| Examine how AR picture books help students with different levels of German proficiency. | LI, CLI, LO | AR picture books helped students with a higher level of German proficiency. | |
| Study 3 | Examine the variables that may affect students’ satisfaction with AR picture books in the structural equation model. | PIN, PN, PIG, INDE, FL, SA, PL |
PIN, PN, and PIG constitute the second-order variable INDE; INDE directly affects FL; FL directly affects SA; INDE indirectly influences SA through FL mediation; PL does not play a significant moderating role between INDE and SA. |