Projects per year
The current study builds upon a previous study, which examined the degree to which the lexicalproperties of students’ essays could predict their vocabulary scores. We expand on this previousresearch by incorporating new natural language processing indices related to both the surface- anddiscourse-levels of students’ essays. Additionally, we investigate the degree to which these NLPindices can be used to account for variance in students’ reading comprehension skills. We calculatedlinguistic essay features using our framework, ReaderBench, which is an automated text analysis toolsthat calculates indices related to linguistic and rhetorical features of text. University students (n = 108)produced timed (25 minutes), argumentative essays, which were then analyzed by ReaderBench.Additionally, they completed the Gates-MacGinitie Vocabulary and Reading Comprehension tests.The results of this study indicated that two indices were able to account for 32.4% of the variance invocabulary scores and 31.6% of the variance in reading comprehension scores. Follow-up analysesrevealed that these models further improved when only considering essays that contained multipleparagraph (R2 values = .61 and .49, respectively). Overall, the results of the current study suggest thatnatural language processing techniques can help to inform models of individual differences amongstudent writers.
|Title of host publication||EDULEARN16 Proceedings|
|Subtitle of host publication||8th International Conference on Education and New Learning Technologies|
|Editors||L. Gómez Chova, A. López Martínez, I. Candel Torres|
|Publication status||Published - 2016|
|Event||EDULearn16: 8th International Conference on Education and New Learning Technologies - Barcelona, Spain|
Duration: 4 Jul 2016 → 6 Jul 2016
|Period||4/07/16 → 6/07/16|
- writing skills
- automated writing evaluation
- comprehension prediction
- vocabulary measures
- natural language processing
FingerprintDive into the research topics of 'MODELING INDIVIDUAL DIFFERENCES AMONG WRITERS USING READERBENCH'. Together they form a unique fingerprint.
- 1 Finished
Rage: Realising an Applied Gaming Eco-system
Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.
1/02/15 → 31/07/19