Abstract
A novel method to generate memory aids for general forms of knowledge is presented. Mnemonic phrases are constructed using constraints of phonetic similarity to learning material, grammar, semantics, and factual consistency. The method has been implemented in Python using the CMU Pronouncing Dictionary, the CYC AI knowledge base, and Kneser-Ney 5-gram probabilities built from the large-scale COCA text corpus. Initial tests have produced encouraging output.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Schwartz, B.L.: Memory: Foundations and Applications. 3rd edn. SAGE (2017).
Worthen, J.B. and Hunt, R.R.: Mnemonology: Mnemonics for the 21st Century. Essays in Cognitive Psychology. New York, NY, US. Psychology Press. (2011)
Carney, R. N., & Levin, J. R.: Delayed mnemonic benefits for a combined pegword-keyword strategy, time after time, rhyme after rhyme. Applied Cognitive Psychology, 25, 204-211. (2011).
Seay, S.S.: The Use/Application of Mnemonics As a Pedagogical Tool in Auditing, Academy of Educational Leadership Journal 14 (2). (2010).
Jeyaraman,S., Topkara, U.: Have the cake and eat it too - Infusing usability into text-password based authentication systems. In Proceedings of ACSAC ‘05 Proceedings of the 21st Annual Computer Security Applications Conference. Pages 473 – 482. (2005).
Savva, M., Chang, A.X., Manning, C., Hanrahan, P.: TransPhoner: Automated Mnemonic Keyword Generation. In Proceedings: ACM Conference on Human Factors in Computing Systems. (2014).
Mountstephens, J.: Towards Computer-Generated Mnemonic Phrases: Experiments with Genetic Algorithms and N-Grams. Journal of Engineering and Applied Sciences. Vol 9, Issue 9. (2014).
Mountstephens, J.: Computer-Generated Mnemonics Can Improve Student Memory, Advanced Science Letters, in press.
Bird, S., Klein, E,, Loper, E.: Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. Beijing: O’Reilly. (2009).
Acknowledgements
This work was funded by Universiti Malaysia Sabah under SGPUMS Grant SBK0363-2017.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Mountstephens, J., Wi, J.T.T., Kler, B.K. (2020). Towards Computer-Generated Cue-Target Mnemonics for E-Learning. In: Alfred, R., Lim, Y., Haviluddin, H., On, C. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 603. Springer, Singapore. https://doi.org/10.1007/978-981-15-0058-9_37
Download citation
DOI: https://doi.org/10.1007/978-981-15-0058-9_37
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0057-2
Online ISBN: 978-981-15-0058-9
eBook Packages: EngineeringEngineering (R0)