Skip to content
Free planNo credit card requiredStart writing

article · Journal of Special Education Technology · 2000

The Effect of Icon Prediction on College Students' Recall of Icon Codes

Ann R. Beck, James R. Thompson, Sandra L. Clay

Cited by 2Abstract and details only

Abstract

The influence of icon prediction and length of icon sequence on college students' recall of 24 ironically encoded messages was investigated. Findings indicated that using an icon prediction feature resulted in increased recall. The length of the icon sequence also had a significant effect on recall. Three-icon sequences were more easily recalled than two-icon sequences.

Cite this paper

APA 7

Beck, A. R., Thompson, J. R., & Clay, S. L. (2000). The Effect of Icon Prediction on College Students' Recall of Icon Codes. Journal of Special Education Technology, 15(3), 17–23. https://doi.org/10.1177/016264340001500302

MLA 9

Beck, Ann R., et al. “The Effect of Icon Prediction on College Students' Recall of Icon Codes.” Journal of Special Education Technology, vol. 15, no. 3, 2000, pp. 17–23, https://doi.org/10.1177/016264340001500302.

Chicago

Beck, Ann R., James R. Thompson, and Sandra L. Clay. 2000. “The Effect of Icon Prediction on College Students' Recall of Icon Codes.” Journal of Special Education Technology 15 (3): 17–23. https://doi.org/10.1177/016264340001500302.

Harvard

Beck, A.R., Thompson, J.R. and Clay, S.L. (2000) ‘The Effect of Icon Prediction on College Students' Recall of Icon Codes’, Journal of Special Education Technology, 15(3), pp. 17–23. Available at: https://doi.org/10.1177/016264340001500302.

BibTeX
@article{beck2000effect,
  title = {{The Effect of Icon Prediction on College Students' Recall of Icon Codes}},
  author = {Beck, Ann R. and Thompson, James R. and Clay, Sandra L.},
  journal = {Journal of Special Education Technology},
  volume = {15},
  number = {3},
  pages = {17--23},
  year = {2000},
  doi = {10.1177/016264340001500302}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.