Fig 1.
AR consists of two major types: Marker-based AR systems and markerless AR systems. Marker-based AR systems utilize fiducial markers or graphics to activate digital output and display virtual content. On the other hand, markerless AR systems are more common and typically employ optical-mechanical, ultrasonic, magnetic, or inertial sensors to recognize objects, patterns, shapes, and locations.
Fig 2.
QR code functionality description.
In QR codes, the reader can detect the position of the code by using the three squares in the corners.
Fig 3.
ASSURE model as described by Heinich et al.
[90]. In the ASSURE model, six steps are described by a letter, each of which describes a primary task for making informed decisions about educational technology.
Fig 4.
Experimental and control groups were created using a quasi-experimental design. The experimental group utilized AR codes to teach fundamental boxing defensive techniques, while the control group was taught using a program based on the coach’s command style. A pre-post-test design was employed for both groups.
Fig 5.
The estimated sample size according to desired effect size.
A priori power analysis was conducted using G*Power version 3.1.9.7 software. As a result, the minimum sample size needed for this effect size is N = 52 (n1 = n2 = 26).
Table 1.
The fundamental defensive skills included in the proposed program.
Fig 6.
A collection of screenshots of defensive skills from 3D movies.
Fig 7.
Boxers using AR technology as an example.
Table 2.
Control and experimental groups’ descriptive statistics (n1 = n2 = 30).
Table 3.
Comparison of control and experimental samples using T-tests for the pre-measurements (n1 = n2 = 30).
Table 4.
Comparison of control and experimental groups using a t-test in the post-measurements (n1 = n2 = 30).
Fig 8.
Comparison of defensive skill scores between experimental and control groups.
The experimental group outperformed the control group in post-measurements of fundamental boxing defensive techniques.