Future-proofing I-O psychology: The need for updated graduate curriculum

Abstract

Comments on an article by Patrick Hyland (see record 2023-54807-014). Hyland provides a model for reflection and reflexivity to prevent industrial-organizational (I-O) psychology research from growing stale. Authors focus is to expand upon Hyland's model by first reflecting on the recent sociohistorical forces that have shaped I-O psychology and then by proactively future-proofing their field through graduate education focused on transparency, software accessibility, and multidisciplinary collaboration. Recent history has seen an upsurge of unprecedented macro events such as COVID-19, nationwide racial division, political unrest, and mental health crisis;these events make authors aware of blind spots within our societal, scientific, and economical systems. Such events force us as a field to be reactive and adaptive by transitioning from old methods to new and developing methods (e.g., work shifting from in-person to online). However, as humans, authors tend to cling to what is familiar and comfortable, and likewise, their field has often chosen to remain comfortable. Authors believe that the proclivity to resist change results in an overreliance on outdated practices and to combat this, authors suggest a grassroots approach to transformation by focusing on future-proofing graduate coursework. In line with the Society of Industrial Organizational Psychology's (SIOP) strategic goals, authors envision a future that equips future generations of researchers and practitioners with the skills and knowledge to be lifelong learners, so they are prepared for ever-changing challenges. Authors suggest updating the I-O graduate course curriculum by (a) implementing open science practices throughout courses, (b) embracing the latest open-source coding technologies (e.g., R and Python), and (c) advancing inferential inclusivity by teaching Bayesian statistics in addition to traditional methods. This three-pronged approach addresses the need for transparency, software accessibility, and multidisciplinary research to prepare graduate students to theorize, plan appropriate study design, thoughtfully consider necessary analyses, interpret meaningful results, and share those results in a clear and far-reaching manner. Researchers can then prepare for (rather than react to) unprecedented macro events, clarifying our collective identity and future-proofing the field with an updated skill set to overcome obstacles. (PsycInfo Database Record (c) 2023 APA, all rights reserved)