The final two presentations of the CARMA Webcast Lecture Series for fall 2019 will occur on Friday, November 4, beginning at 12:00 CT. These two lectures will focus on Big Data and will be delivered by Dr. Sang Eun Woo of Purdue University (Big Data Concepts) and Dr. Fred Oswald of Rice University (Big Data Analysis). These lectures will add to the set of five previous lectures on Big Data (see a list of these lectures at the end of the Update).
The goal of Dr. Woo’s lecture on Big Data Concepts is to provide a broad overview of conceptual issues related to big data. First, she will discuss big data as a ‘phenomenon’ from etymological, ontological, and epistemological angles. After that she will briefly go over how big data has been and/or can be applied to various workplace HR solutions, highlighting a few promising directions (i.e., big data ‘applications’). Then, she will devote the rest of the talk to discussing big data as ‘research method’ within the field of psychological/organizational sciences. She will emphasize the need for greater openness toward data-driven (inductive and abductive) modes of science while cautioning against premature claims of causality and measurement validity. Some tangible examples will be provided to elaborate on these two points. Lastly, she will conclude with a brief discussion of different perspectives on theory and causation that may shape future dialogues around big data science within our field.
Dr. Woo is an Associate Professor in the Department of Psychological Sciences at Purdue University. She received her PhD degree in industrial and organizational psychology from University of Illinois at Urbana-Champaign with a minor in quantitative psychology. Sang has extensive experience in conducting research in the area of psychological measurement in both public and private sectors. Her focal expertise lies in developing and validating techniques for assessing personality and individual differences for various organizational and educational purposes (e.g., selection, diagnosis, training/development, and retention), as well as in clarifying the theoretical underpinnings and implications of such techniques. Sang recently guest-edited a special issue on inductive approaches to organizational science for Human Resource Management Review (2017). She is currently serving on the editorial board for Organizational Research Methods, Journal of Applied Psychology, Journal of Management, Journal of Business and Psychology, and Human Resource Management Review. Sang is also serving on the APA Committee on Psychological Tests and Assessment (2019-2021).
The second lecture of the day by Dr. Oswald (1:15 CT) will walk the audience through two predictive analytic techniques using big data (lasso regression and random forests). Although there are hundreds of these techniques at this point, these examples sufficiently emphasize how (a) robust prediction is a primary goal and (b) the interpretability or explainability of this prediction varies, depending on the technique used. The presentation concludes by emphasizing several key scientific, legal, and ethical considerations in this arena.
Dr. Fred Oswald is a Professor in the Department of Psychological Sciences at Rice University. His research, grants, publications with graduate students involve the development of psychological measures, personnel selection and college admissions, and many quantitative methods
that include today’s topic of big data and machine learning. Fred has held a number of leadership roles related to quantitative methods that are editorial (e.g., current Associate Editor at Psychological Methods as well as Advances in Methods and Practices in Psychological Science) and professional (e.g., Chair of the APA Committee on Psychological Tests and Assessment, 2018-19; panelist for Statistical and Research Methodology grants for IES at the US Department of Education). Learn more at https://workforce.rice.edu
Previous CARMA Webcast Lectures on Big Data topics include:
Statistical Analysis with Big Data, Dr. Fred Oswald
Ramp Up Big Data Research and Teaching with R, Dr. Jeff Stanton
Creating Datasets with Social Media, Dr. Richard Landers
Text Mining, Dr. Scott Tonidandel
Modern Prediction Methods, Dr. Dan Putka
Recordings of these Big Data lectures and all CARMA Webcast Lectures are available for free on-demand viewing in the CARMA Video Library by faculty and students from CARMA’s Institutional Premium and Basic Membership Programs. Over 125 universities world-wide are CARMA Members for 2019-2020, and the Video Library contains over 160 recorded lectures from previous CARMA Webcast Programs.
For more information on CARMA and its programs and events visit the CARMA website https://carmattu.com/