Representation of Industry in Introductory Biology Textbooks: A Missed Opportunity to Advance STEM Learning

Abstract

The majority of students who enroll in undergraduate biology courses will eventually be employed in non-STEM (science, technology, engineering, and mathematics) business occupations. This work explores how representations of industry in undergraduate biology textbooks could impact STEM learning for these students and their ability to apply this learning in their chosen work. We used text analysis to identify passages with references to industry in 29 textbooks. Each passage was categorized for relevance to health or environment, for implied positive or negative connotations, and for descriptions of synergy or conflict between science and industry. We found few passages describing applications of STEM learning in non-STEM business occupations and a paucity of content to support context-based learning for students aiming at business careers. A significant number of passages embodied negative connotations regarding industry. Notable passages highlighted irregular or fraudulent business practices or included simplistic caricatures of business practice. We discuss how the representation of industry in these textbooks may impact student engagement, context-based learning, the ability of students to critically apply STEM learning in industry or business occupations, and heuristics that guide intuitive perceptions about the intersection between science and industry.

Reflecting or ruminating: listening to the regrets of life science leaders

“…A decision was made to stay close to the data and forgo use of NVivo or similar programs. Firsthand experience with NVivo in a large, mixed-methods study led the author to conclude that manual analysis can code with more nuance than software (Simon et al , 2018). Seeing connotative significance in the subtext of a narrative and recognizing layered meanings and in-group references cannot yet be programmed via computer.…”

Recruiting for Resilience

“…Thus, use of qualitative data analysis computer software programs was not helpful in discovering salient themes. Furthermore, the author's prior experience with NVivo in a large, mixed-methods study reinforced a practice of staying close to the data and the nuances available through manual analysis instead of software coding (Simon, et al, 2018). Computer programs cannot yet recognize connotative significance in narrative subtexts, layered meanings, and in-group references.…”

An Investigation of How Environmental Science Textbooks Link Human Environmental Impact to Ecology and Daily Life

“…Environmental Impact was not coded as present in case studies that only described the effects of human actions on people. For example, the relationship between education and poverty in the developing world was coded as Human Action, but not as Environmental Impact (a similar approach was used in Simon et al. , 2018 ).…”