Sen Yan

about me

I’m currently a Ph.D candidate of Information Systems in the Division of Organizational Leadership and Information Analytics, Leeds School of Business, University of Colorado Boulder. Prior joining my Ph.D program, I received my Bachelor from Shanghai University of Finance and Economics.

My research interests lie across many topics including the Cybersecurity, Psychometric Methodology Development, Natural Language Processing, and Multimodal Learning. Feel free to contact me via my email: sen.yan@colorado.edu.

“If I take death into my life, acknowledge it, and face it squarely, I will free myself from the anxiety of death and the pettiness of life - and only then will I be free to become myself.” – Martin Heidegger

education

University of Colorado Boulder, Boulder, CO, USA.

Ph.D Student of Information Systems, 2021 - Present
Shanghai University of Finance and Economics, Shanghai, China.

Bachelor of Finance Management, 2017 - 2021

teaching experiences

BAIM3200/MKGT3201 - Business Analytics University of Colorado Boulder, Spring 2022

news

Jun 01, 2020	Our paper *Toward an Information Systems Ontology* has been accepted by DESRIST2022

selected publications

ICIS 2024

Integrating LLMs and Psychometrics: Global Construct Validity

Kai Larsen, Sen Yan, and Lukyanenko Roman

In Proceedings of the International Conference on Information Systems 2024, Bangkok, Thailand, Dec 2024

Abs PDF

The psychometric approach in IS offers a foundational framework for a broad spectrum of research endeavors, which typically rely on construct validation to confirm that a series of indicators accurately measures the intended construct. However, a longstanding issue with construct validity, unaddressed since its introduction by Cronbach and Meehl in 1955, is that it is evaluated using study-specific response data without comparison to constructs outside the study. This oversight (or, rather, incapability) has significant implications. We introduce a large language model combined with principal components analysis (PCA) and develop the Validity Lodestar application. This approach lays the groundwork for developing more accurate and reliable theoretical models, marking a significant leap forward in the IS discipline’s methodological capabilities, making IS the first psychometric discipline with the capability to properly evaluate construct validity.