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Contrasting the learning effectiveness of augmented reality with conventional tours of museums
Interactive Computing Project ( January 2017- May 2017)

For our course, Topics in Interactive Computing CS 666 at LUMS, I along with two fellow researchers developed an Augmented Reality application for the National Museum of Science and Technology. The project went through all phases of user research, design, development and testing. Consequently, our project yielded great insight on the role of AR in Education and the research paper is in process of publishing
With not much attention being paid in museum development in Pakistan, they are losing their charm and annual visitors. There is a long due need to improve this situation using contemporary technologies. Audio and Video guides along with Augmented Reality and Virtual Reality have been incorporated in many museums all across the globe; yet in Pakistan there was a lot of room for the integration of technology. This problem statement helped us design our study.
An inimical relationship is traditionally seen existing between education at museums and technology, with conventional instructional approaches usually characterized by a commentator guiding students in field learning. Unfortunately, in this passive learning approach the factor of experiential self-learning is minimized. Therefore, there is a need for precise and effective guidance providing rich self-learning experience in museums, specifically, science museums. Based on Kolb’s experiential learning theory, our study develops AR based learning smartphone application, implemented in a science museum.

We created a bilingual application that detects the artefact at the museum and augments information on the screen (Due to dull lighting we also placed QR codes for the artefacts that were not detected by our application). We incorporated gamification of collecting points to make our application more engaging. In the field experiment, 30 middle school students divided into two groups, participated in a learning activity using different learning techniques and media. These students were first given a pre-test in order to form uniform groups of equal calibre. Quantitative results indicate that, in comparison to the conventional tours of museums characterized by a commentator, AR based learning app showed improved learning outcomes among learners. In post-activity interviews, students expressed that they found the system more interesting and helpful to their learning in school. The use of contemporary technologies increases student’s willingness to learn more about the artefacts.

Group A were the group of students with the AR application and group B was the control

Group Group A pre test Group A post test
Mean 7.8000 4.4000
SD 2.2000 2.0600
SEM 0.5680 0.5319
N 15 15
P value and statistical significance
The two-tailed P value equals 0.0002
By conventional criteria, this difference is considered to be extremely statistically significant.

Confidence interval
The mean of Group A pre test minus Group A post test equals 3.4000
95% confidence interval of this difference: From 1.8060 to 4.9940

Intermediate values used in calculations
t = 4.3691
df = 28
standard error of difference = 0.778

Group B Results

Group Group A pre test Group A post test
Mean7.87006.9300
SD2.33002.6700
SEM0.60160.6894
N1515
P value and statistical significance
The two-tailed P value equals 0.3131

By conventional criteria, the difference is considered to be not statistically significant.


Confidence interval

The mean of Group B pre test minus Group B post test equals 0.9400

95% confidence interval of this difference: From -0.9342 to 2.8142


Intermediate values used in calculations

t = 1.0273

df = 28

standard error of difference = 0.915

Conclusion

The results of our T-test support our hypothesis that augmented reality positively correlates to the learning efficiency in museum settings. The value between group A’s pre and post test is statistically significant while group B’s not. This suggests that the students significantly made less number of mistakes after using our application. As we have previously established that the mean knowledge of both the groups were the same at the time of pre-test, we later saw statistically significant result in terms of the difference between the post tests of both the groups. The values for each are stated above

Furthermore, interesting conclusion and discussions stemmed out of the results we gathered. Research and documents along with supporting videos can be made available to you on request.

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