Abstract
In the age of the Internet and communication technology, changes in Technology Enhanced Learning (TEL) and Lifelong Learning Styles (LLS) are becoming a part of education and everyday life. The objectives of this paper were to develop a mobile application and provide perspectives for Learning Strategies (LS) and Learning Achievement (LA) in lifelong learning at the high school level in Maha Sarakham Province, Thailand. This research focused on the identification of the initial steps required to build academic achievement. Data collection was divided into two parts, comprised of (1) data sets for model analysis and application development from 668 students at Phadungnaree School in Maha Sarakham, and (2) data sets for application testing and level of satisfaction collected from 23 IT specialists and 72 general users at Rajabhat Mahasarakham University, Thailand. The research methodology consisted of five principal steps including (1) data collection, (2) model analysis, (3) model performance, (4) mobile application development, and (5) application implementation. The results from the model analysis showed that the research models displayed high accuracy equal to 94.51%. When developed as an association rule, the model could predict with increased accuracy equal to 98.35%. At the same time, the level of satisfaction for the developed applications was also high, equal to 4.61. Therefore, it could be concluded that this application is appropriate and reasonable for recommendation to interested parties in the future.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Nuankaew, P., Temdee, P.: Determining of compatible different attributes for online mentoring model. In: 2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace Electronic Systems (VITAE), pp. 1–5 (2014)
Nuankaew, P., Temdee, P.: Of online community: identifying mentor and mentee with compatible different attributes and decision tree. In: 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), pp. 1–6 (2015)
Pupara, K., Nuankaew, W., Nuankaew, P.: An institution recommender system based on student context and educational institution in a mobile environment. In: 2016 International Computer Science and Engineering Conference (ICSEC), pp. 1–6 (2016)
Wood, J., Campbell, M., Wood, K., Jensen, D.: Enhancing the teaching of machine design by creating a basic hands-on environment with mechanical ‘breadboards’. Int. J. Mech. Eng. Educ. 33(1), 1–25 (2005)
Silk, E.M., Higashi, R., Schunn, C.D.: Resources for robot competition success: assessing math use in grade-school-level engineering design. In: American Society for Engineering Education (2011)
Nuankaew, P., Temdee, P.: Online mentoring model by using compatible different attributes. Wirel. Pers. Commun. 85(2), 565–584 (2015)
Winne, P.H.: How software technologies can improve research on learning and bolster school reform. Educ. Psychol. 41(1), 5–17 (2006)
Winne, P.H., Jamieson-Noel, D.: Self-regulating studying by objectives for learning: students’ reports compared to a model. Contemp. Educ. Psychol. 28(3), 259–276 (2003)
Wood, S.: Generation Z as consumers: trends and innovation, pp. 1–3. Institute for Emerging Issues: NC State University (2013)
United Nations General Assembly: Transforming Our World: The 2030 Agenda for Sustainable Development. Resolution adopted by the General Assembly on 25 September 2015, New York, United Nations (2015). http://www.un.org/ga/search/view_doc.asp
Office of the National Education Commission, Office of the Prime Minister: National Education Act B.E. 2542 (1999). Office of the National Education Commission, Thailand (1999)
Acknowledgements
The authors and research project were supported financially and with resources by Rajabhat Mahasarakham University and the University of Phayao. The authors would like to thank the researchers, participants, and technicians for their efforts toward the completion of this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Nuankaew, P., Nuankaew, W., Phanniphong, K., Bussaman, S. (2018). Mobile Applications for the Prediction of Learning Outcomes for Learning Strategies and Learning Achievement in Lifelong Learning. In: Auer, M., Guralnick, D., Simonics, I. (eds) Teaching and Learning in a Digital World. ICL 2017. Advances in Intelligent Systems and Computing, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-319-73204-6_45
Download citation
DOI: https://doi.org/10.1007/978-3-319-73204-6_45
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73203-9
Online ISBN: 978-3-319-73204-6
eBook Packages: EngineeringEngineering (R0)