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Context aware mobile learning application development: A systematic literature review

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Abstract

Context Aware Mobile Learning Applications (CAMLA) are an emerging field of research, they provide educational resources tailored to educational needs and particular circumstances of the learner. Despite the increase in the number of applications being developed, there is a lack of study that provides comprehensive knowledge on the development of CAMLA. Motivated by this shortcoming, Systematic Literature Review (SLR) was conducted to establish a body of knowledge that describes the key components of CAMLA that includes; context information extraction and representation, context adaptation and different types of applications developed. SLR was conducted on 24 papers retrieved from seven databases. The results identified different types of context amongst which learner, location and time are the most widely used in the development of CAMLA. The context data is collected using virtual and physical sensors and mostly represented as relational or ontology data. CAMLA provides different types of adaptation where adaptation to learning resource and location are very common. The results are useful to position future research activities to scientifically strengthen this field.

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Authors and Affiliations

  1. Department of Computer Science and Information Systems, Fiji National University, Suva, Fiji

    Bimal Aklesh Kumar

  2. School of Mathematical and Computing Science, University of the South Pacific, Suva, Fiji

    Bibhya Sharma

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  1. Bimal Aklesh Kumar
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  2. Bibhya Sharma
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Correspondence to Bimal Aklesh Kumar.

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Appendix

Appendix

1

Martin, S., Sancristobal, E., Gil, R., Castro, M., & Peire, J. (2008). Mobility through location-based services at university. International Journal of Interactive Mobile Technologies (iJIM), 2(3), 34–40.

2

Hwang, G. J., Yang, T. C., Tsai, C. C., & Yang, S. J. (2009). A context-aware ubiquitous learning environment for conducting complex science experiments. Computers & Education, 53(2), 402–413.

3

Al-Mekhlafi, K., Hu, X., & Zheng, Z. (2009, June). An approach to context-aware mobile Chinese language learning for foreign students. In Mobile Business, 2009. ICMB 2009. Eighth International Conference on (pp. 340–346). IEEE.

4

Gómez, S., Huerva, D., Mejía, C., Baldiris, S., & Fabregat, R. (2009, June). Designing context-aware adaptive units of learning based on IMS-LD standard. In EAEEIE Annual Conference, 2009 (pp. 1–6). IEEE.

5

Martín, E., & Carro, R. M. (2009). Supporting the development of mobile adaptive learning environments: a case study. IEEE Transactions on Learning Technologies, 2(1), 23–36.

6

Nguyen, V. A., Pham, V. C., & Ho, S. D. (2010, November). A context-aware mobile learning adaptive system for supporting foreigner learning English. In Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2010 IEEE RIVF International Conference on (pp. 1–6). IEEE.

7

Chen, C. M., & Li, Y. L. (2010). Personalised context-aware ubiquitous learning system for supporting effective English vocabulary learning. Interactive Learning Environments, 18(4), 341–364.

8

Aziz, Z., Anumba, C. J., & Peña-Mora, F. (2010). Using context-aware wireless technologies to support teaching and learning in built environment. International Journal of Construction Education and Research, 6(1), 18–29.

9

Hashemi, H. S. F., Orooji, F., & Taghiyareh, F. (2012, November). A context-aware mobile learning model for web-based learning environments. In Telecommunications (IST), 2012 Sixth International Symposium on (pp. 924–928). IEEE.

10

Gómez, S., Zervas, P., Sampson, D. G., & Fabregat, R. (2013, July). Supporting context-aware adaptive and personalized mobile learning delivery: evaluation results from the use of UoLm player. In Advanced Learning Technologies (ICALT), 2013 IEEE 13th International Conference on (pp. 354–358). IEEE

11

Gómez, S., Zervas, P., Sampson, D. G., & Fabregat, R. (2014). Context-aware adaptive and personalized mobile learning delivery supported by UoLmP. Journal of King Saud University-Computer and Information Sciences, 26(1), 47–61.

12

Benlamri, R., & Zhang, X. (2014). Context-aware recommender for mobile learners. Human-centric Computing and Information Sciences, 4(1), 12.

13

Hsu, C. K., & Hwang, G. J. (2014). A context-aware ubiquitous learning approach for providing instant learning support in personal computer assembly activities. Interactive Learning Environments, 22(6), 687–703.

14

Abdulkarem, H. F., & Şevkli, A. Z. (2014, October). A Context-aware Mobile Application for Cultural Learning. In Proceedings of the 3rd International Conference on Context-Aware Systems and Applications (pp. 37–41). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).

15

Morales, R., Igler, B., Böhm, S., & Chitchaipoka, P. (2015). Context-aware mobile language learning. Procedia Computer Science, 56, 82–87.

16

Baccari, S., & Neji, M. (2016, December). Design for a context-aware and collaborative mobile learning system. In Computational Intelligence and Computing Research (ICCIC), 2016 IEEE International Conference on (pp. 1–6). IEEE.

17

Chen, C. C., & Lin, P. H. (2016). Development and evaluation of a context-aware ubiquitous learning environment for astronomy education. Interactive Learning Environments, 24(3), 644–661.

18

Zhang, B., Yin, C., David, B., Chalon, R., & Xiong, Z. (2016). A context-aware mobile system for work-based learning. Computer Applications in Engineering Education, 24(2), 263–276.

19

Curum, B., Chellapermal, N., & Khedo, K. K. (2016, November). A Context-Aware Mobile Learning System Using Dynamic Content Adaptation for Personalized Learning. In International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (pp. 305–313). Springer, Cham.

20

Yau, J. Y. K., & Hristova, Z. (2017). Evaluation of an Extendable Context-Aware “Learning Java” App with Personalized User Profiling. Technology, knowledge and learning, 1–16.

21

Curum, B., Gumbheer, C. P., Khedo, K. K., & Cunairun, R. (2017, July). A content-adaptation system for personalized m-learning. In Next Generation Computing Applications (NextComp), 2017 1st International Conference on (pp. 121–128). IEEE.

22

Yao, C. B. (2017). Constructing a user-friendly and smart ubiquitous personalized learning environment by using a context-aware mechanism. IEEE Transactions on Learning Technologies, 10(1), 104–114.

23

Sevkli, A. Z., Motiwalla, L., & Abdulkarem, H. F. (2017). The design and implementation of a context-aware mobile hadith learning system. International Journal of Mobile Learning and Organisation, 11(4), 295–313.

24

Nuzhat, S., Shaikh, T., & Ismail, S. (2018, March). A Context Aware Prototype Application for University Students and Lecturers. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (pp. 155–160). IEEE.

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Kumar, B.A., Sharma, B. Context aware mobile learning application development: A systematic literature review. Educ Inf Technol 25, 2221–2239 (2020). https://doi.org/10.1007/s10639-019-10045-x

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