Immersive AR Comparison

At our institution as I am certain yours, discussions continue to evolve around keeping up with AI in teaching and learning (TL). This week, I would like to share a recent article that addresses factors supporting TL in a similar genre of the emerging tech of augmented reality (AR). The article entitled, “Design, development and validation of an educational methodology using immersive augmented reality (AR) for STEAM education” was written by Delgado-Rodriguez et al. (2023).

The main objective of the study was the design and validation of an educational methodological model based on the use of immersive technological resources (Augmented Reality – AR) to improve learning processes in science subjects. The process was developed based on three main quantitative studies: an exploratory study, a study of performance divided into three case studies, and an attitudinal study. This research provides empirical evidence that allows validation of the methodological model developed to explain key concepts and to improve the level of motivation and acceptance of AR technology by students. The proposed model can induce improvements in educational processes when used with an immersive AR resource. It also demonstrates that teachers require specific training.

Five hundred (500) students and sixteen (16) teachers were selected through probabilistic, random, and multi-stage sampling. Cronbach’s Alfa procedure was used to determine the internal consistency index. Alfa values of 0.685 and 0.681 were obtained for the data collection instruments, respectively.

Educause Horizon Reports analyze technologies that will have a significant impact on teaching and learning processes (Brown et al., 2020) have emphasized the potential of immersive tech, in particular AR and Virtual Reality (VR). The use of AR has been found to be more suitable for teachers than VR (Alalwan et al., 2020). AR entails the superposition of digital information (images, audio, videos, 3D models) in a register that is displayed in the existing surroundings (Garzón & Acevedo, 2019). The combination of real-world elements with virtual information is performed in real time and allows interaction of all senses (Azuma et al., 2001). AR’s interactive digital content makes learning more significant and improves academic performance (Cai, Chiang, 2017).

Independent variables examined included Condition of Students with Special Educational Needs, Type of School, School’s Geographic Location, Habitual Use of Non-Immersive Tech and Habitual Use of AR and VR, Habitual Use of Evaluation Systems Adapted to New Tech. The three factor scores obtained were used as dependent variables: Level of Motivation, Degree of Acceptance of the Tech and Degree of Acceptance of an Adapted Digital Evaluation System. To compare quantitative data with more than two groups, a fully randomized one-way ANOVA parametric test was used, obtaining the following results:

• The Age of Students has a statistically significant impact on the level of acceptance of an adapted evaluation system (p = .05). Students aged 16 or more have higher scores. Thus, students aged 16 or more present a greater degree of acceptance of adapted evaluation systems than others.

• The condition of Students with Special Educational Needs has a statistically negative impact on the Degree of Acceptance of AR (p < .05). A post hoc analysis revealed that this group of students have higher scores in the statistic F corresponding to the factor Degree of Acceptance of Tech.

• The School’s Geographic Location has a statistically significant impact on the Degree of Acceptance of the Tech and the Degree of Acceptance of an Adapted Digital Evaluation System, respectively: F (5.154) = 3.39, p < .05. An analysis reveals that the students of schools located in towns of more than 10,000 obtain higher mean scores.

• The Habitual Use of Ed Resources based on AR tech has a statistically significant impact on the Degree of Acceptance of an Adapted Digital Evaluation System (p < .05). A post hoc analysis reveals that the students who use AR resources obtain a higher score than the other students in statistic F corresponding to the factor Degree of Acceptance of an Adapted Digital Evaluation System. It is possible to conclude that students who use AR resources in class have a greater degree of acceptance of adapted evaluation systems.

References

Delgado-Rodriguez, S., Carrascal-Dominguez, S. & Garcia-Fandino, R. (2023). Design, development and validation of an educational methodology using immersive augmented reality for STEAM education. Journal of New Approaches in Educational Research, 12(1) 19-39. Doi: http://dx.doi.org/10.7821/naer.2023.1.1250.