Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 31, 02 April 2024


Open Access | Article

Design and implementation of English vocabulary orthographical revision application based on Matlab

Qi Cao * 1
1 Jilin University

* Author to whom correspondence should be addressed.

Advances in Humanities Research, Vol. 31, 336-345
Published 02 April 2024. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Qi Cao. Design and implementation of English vocabulary orthographical revision application based on Matlab. TNS (2024) Vol. 31: 336-345. DOI: 10.54254/2753-8818/31/20241089.

Abstract

Apropos of English learning, vocabulary learning is one of the most essential parts. Thanks to modern technology, recent years has witnessed scads of vocabulary learning apps springing in the app market which include greatly comprehensive functions. However, among those popular apps, some universal handicaps still exist in the design of the review section, for example, the absence of the freedom for the users to classify the cognitive or priority grade of vocabulary and the low effect of some reviewing methods that could not satisfy the need of the language learners to fully master the orthography of words. This paper aims at contriving an app serving as a supplementary part of English vocabulary learning in order to remedy those inadequacies of mainstream applications or other self-learning methods. In this paper, literature study, graphology, and mathematical modelling are involved. Based on Matlab GUI/App Designer, this paper presents a new method to review English words in which users could customize their lexicon, as well as define the priority of each word and practice spelling of vocabulary on an hourly-based system instead of a daily-based one that most of the existing online platforms adopted. Through creating a discrete probability density function for each word, this app could forward a random word in the glossary for users to practice orthography, obeying the probability density distribution that has a mathematical relationship with familiarity and priority of the words as well as the time factor (Ebbinghaus forgetting curve). Thus, users could thoroughly grasp the orthography of target words.

Keywords

Vocabulary learning, forgetting curve, mathematic model

References

1. Wilkins D A 1972 Linguistics in Language Teaching (Massachusetts: MIT Press)

2. Beijing Afan Technology Co., LTD 2016 China post-00s Internet Learning Behaviour Report. R/OL.

3. Peng W 2021 Application of Ebbinghaus Forgetting Curve in English Vocabulary Teaching in Secondary vocational schools. Proc. Symp. on innovation in Science and Education (01), 184-5

4. Wang G 2011 A study of conceptual and operational models of second language vocabulary knowledge China. J. Foreign Language Education (01), 51-6

5. Dunlosky J, Rawson K A, Marsh E J, Nathan M J and Willingham D T 2013 Improving students' learning with effective learning techniques: promising directions from cognitive and educational psychology. J. Psychol. Sci. Public Interest 14(1), 4-58

6. Roediger H L and Karpicke J D 2006 Test-enhanced learning: taking memory tests improves long-term retention. J. Psychol. Sci. 17(3), 249–55

7. Rowland C A 2014 The effect of testing versus restudy on retention: a meta-analytic review of the testing effect. J. Psychol. Bull. 140(6), 1432–63

8. Bjork R A and Kroll J F 2015 Desirable difficulties in vocabulary learning. Am. J. Psychol. 128(2), 241–52

9. Ebbinghaus H 1913 Memory: A contribution to experimental psychology (New York: Teachers College Press)

10. Cai L, Xiong W and Sun X 2016 Adaptive vocabulary memorization model based on forgetting curve. J. Microcomputer Applications (05), 16-9

11. Donkin C and Nosofsky R M 2012 A power-law model of psychological memory strength in short- and long-term recognition. J. Psychological science 23(6), 625–34

12. Settles B and Meeder B 2016 A trainable spaced repetition model for language learning. Proceedings of the 54th annual meeting of the association for computational linguistics (01), 1848-58

13. Mei X 2007 Association and second language vocabulary acquisition. D. (Shanghai: Shanghai International Studies University)

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
ISBN (Print)
978-1-83558-317-3
ISBN (Online)
978-1-83558-318-0
Published Date
02 April 2024
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/31/20241089
Copyright
02 April 2024
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated