TY - JOUR
T1 - Dear admission committee. . .
T2 - Which moves in application essays predict student master grades?
AU - Boer, Timon de
AU - Van Rijnsoever, Frank
AU - Bresser, Hans de
N1 - Publisher Copyright:
© 2024 de Boer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2024/6
Y1 - 2024/6
N2 - Application essays are a commonly used admission instrument for students entering higher education. The quality of the essay is usually scored, but this score is often subjective and has poor interrater reliability due to the unstructured format of the essays. This results in mixed findings on the validity of application essays as an admission instrument. We propose a more objective method of using application essays, using Latent Dirichlet Allocation (LDA), a text mining method, to distinguish seven moves occurring in application essays written by students who apply to a master degree program. We use the probability that these moves occur in the essay to predict study success in the master. Thereby we answer the following research question: What is the effect of discussing different moves in students’ application essays on the student grades in a master program? From the seven different moves (functional unit of text) we distinguished, five of which have a significant effect on student grades. The moves we labeled as ‘master specific’ and ‘interest to learn’ have a positive effect on student grades, and the moves we labeled as ‘research skills’, ‘societal impact’ and ‘city and university’ have a negative effect. Our interpretation of this finding is that topics related to intrinsic motivation and specific knowledge, as opposed to generic knowledge, are positively related with study success. We thereby demonstrate that application essays can be a valid predictor of study success. This contributes to justifying their use as admission instruments.
AB - Application essays are a commonly used admission instrument for students entering higher education. The quality of the essay is usually scored, but this score is often subjective and has poor interrater reliability due to the unstructured format of the essays. This results in mixed findings on the validity of application essays as an admission instrument. We propose a more objective method of using application essays, using Latent Dirichlet Allocation (LDA), a text mining method, to distinguish seven moves occurring in application essays written by students who apply to a master degree program. We use the probability that these moves occur in the essay to predict study success in the master. Thereby we answer the following research question: What is the effect of discussing different moves in students’ application essays on the student grades in a master program? From the seven different moves (functional unit of text) we distinguished, five of which have a significant effect on student grades. The moves we labeled as ‘master specific’ and ‘interest to learn’ have a positive effect on student grades, and the moves we labeled as ‘research skills’, ‘societal impact’ and ‘city and university’ have a negative effect. Our interpretation of this finding is that topics related to intrinsic motivation and specific knowledge, as opposed to generic knowledge, are positively related with study success. We thereby demonstrate that application essays can be a valid predictor of study success. This contributes to justifying their use as admission instruments.
UR - http://www.scopus.com/inward/record.url?scp=85197189393&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0304394
DO - 10.1371/journal.pone.0304394
M3 - Article
C2 - 38941298
AN - SCOPUS:85197189393
SN - 1932-6203
VL - 19
JO - PLoS One
JF - PLoS One
IS - 6
M1 - e0304394
ER -