Large Language Models for Career Readiness Prediction

Chenwei Cui; Amro Abdalla; Derry Wijaya; Scott Solberg; Sarah Adel Bargal

doi:10.1007/978-3-031-64315-6_26

Large Language Models for Career Readiness Prediction

Chenwei Cui, Amro Abdalla, Derry Wijaya, Scott Solberg, Sarah Adel Bargal

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

1 Citation (Scopus)

Abstract

Large Language Models (LLMs) have recently achieved state-of-the-art performance on many benchmark Natural Language Processing (NLP) tasks. In this work, we are introducing a novel application, career readiness prediction, in the area of NLP for education. We analyze a dataset of student narratives and explore how reliably different LLMs classify them using Marcia’s (1980) identity statuses. We explore the capabilities and limitations of LLMs on this new task and find that there is good potential for automated career readiness evaluation, and for improved survey design that enables larger-scale data collection.

Original language	English
Title of host publication	25th International Conference, AIED 2024 Recife, Brazil, July 8–12, 2024 Proceedings, Part I
Editors	Andrew M. Olney, Irene-Angelica Chounta, Zitao Liu, Olga C. Santos, Ig Ibert Bittencourt
Place of Publication	Cham Switzerland
Publisher	Springer
Pages	304-311
Number of pages	8
ISBN (Electronic)	9783031643156
ISBN (Print)	9783031643149
DOIs	https://doi.org/10.1007/978-3-031-64315-6_26
Publication status	Published - 2024
Externally published	Yes
Event	International Conference on Artificial Intelligence in Education 2024 - Recife, Brazil Duration: 8 Jul 2024 → 12 Jul 2024 Conference number: 25th https://link.springer.com/book/10.1007/978-3-031-64299-9 (Proceedings) https://aied2024.cesar.school/ (Website)

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	2150
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	International Conference on Artificial Intelligence in Education 2024
Abbreviated title	AIED 2024
Country/Territory	Brazil
City	Recife
Period	8/07/24 → 12/07/24
Internet address	https://link.springer.com/book/10.1007/978-3-031-64299-9 (Proceedings) https://aied2024.cesar.school/ (Website)

Keywords

Career Readiness Prediction
Classification
GPT
Large Language Models
Natural Language Processing

Access to Document

10.1007/978-3-031-64315-6_26

Cite this

Cui, C., Abdalla, A., Wijaya, D., Solberg, S., & Bargal, S. A. (2024). Large Language Models for Career Readiness Prediction. In A. M. Olney, I.-A. Chounta, Z. Liu, O. C. Santos, & I. I. Bittencourt (Eds.), 25th International Conference, AIED 2024 Recife, Brazil, July 8–12, 2024 Proceedings, Part I (pp. 304-311). (Communications in Computer and Information Science; Vol. 2150). Springer. https://doi.org/10.1007/978-3-031-64315-6_26

Cui, Chenwei ; Abdalla, Amro ; Wijaya, Derry et al. / Large Language Models for Career Readiness Prediction. 25th International Conference, AIED 2024 Recife, Brazil, July 8–12, 2024 Proceedings, Part I. editor / Andrew M. Olney ; Irene-Angelica Chounta ; Zitao Liu ; Olga C. Santos ; Ig Ibert Bittencourt. Cham Switzerland : Springer, 2024. pp. 304-311 (Communications in Computer and Information Science).

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abstract = "Large Language Models (LLMs) have recently achieved state-of-the-art performance on many benchmark Natural Language Processing (NLP) tasks. In this work, we are introducing a novel application, career readiness prediction, in the area of NLP for education. We analyze a dataset of student narratives and explore how reliably different LLMs classify them using Marcia{\textquoteright}s (1980) identity statuses. We explore the capabilities and limitations of LLMs on this new task and find that there is good potential for automated career readiness evaluation, and for improved survey design that enables larger-scale data collection.",

keywords = "Career Readiness Prediction, Classification, GPT, Large Language Models, Natural Language Processing",

author = "Chenwei Cui and Amro Abdalla and Derry Wijaya and Scott Solberg and Bargal, \{Sarah Adel\}",

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Cui, C, Abdalla, A, Wijaya, D, Solberg, S & Bargal, SA 2024, Large Language Models for Career Readiness Prediction. in AM Olney, I-A Chounta, Z Liu, OC Santos & II Bittencourt (eds), 25th International Conference, AIED 2024 Recife, Brazil, July 8–12, 2024 Proceedings, Part I. Communications in Computer and Information Science, vol. 2150, Springer, Cham Switzerland, pp. 304-311, International Conference on Artificial Intelligence in Education 2024, Recife, Brazil, 8/07/24. https://doi.org/10.1007/978-3-031-64315-6_26

Large Language Models for Career Readiness Prediction. / Cui, Chenwei; Abdalla, Amro; Wijaya, Derry et al.
25th International Conference, AIED 2024 Recife, Brazil, July 8–12, 2024 Proceedings, Part I. ed. / Andrew M. Olney; Irene-Angelica Chounta; Zitao Liu; Olga C. Santos; Ig Ibert Bittencourt. Cham Switzerland: Springer, 2024. p. 304-311 (Communications in Computer and Information Science; Vol. 2150).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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Cui C, Abdalla A, Wijaya D, Solberg S, Bargal SA. Large Language Models for Career Readiness Prediction. In Olney AM, Chounta IA, Liu Z, Santos OC, Bittencourt II, editors, 25th International Conference, AIED 2024 Recife, Brazil, July 8–12, 2024 Proceedings, Part I. Cham Switzerland: Springer. 2024. p. 304-311. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-64315-6_26