As part of a larger study of how problem-solving, communication, and teamwork are integrated into STEM education, we examined how industrial work experience impacts faculty teaching practices around those same competencies. We conducted semi-structured individual interviews with 92 educators in four broad fields, including energy, healthcare, computing, and advanced manufacturing. Educators' industrial experience ranged from no prior experience to a decade or more of industrial experience, which largely depends on STEM field. This paper will report findings from preliminary analysis with six educator interviews in energy and advanced manufacturing. Industry work experience greatly influenced educators' perceptions of the competencies as well as teaching strategies. Instructors with rich industry experience often include more descriptive examples of industrial applications when defining those skills, use industrial-specific tasks to inspire the design of classroom activities, and utilize their industry work experience to help formulate course structure.

Problem-solving is emphasized in introductory physics courses to equip students with tools that hopefully transfer to their future lives and careers. The EMPOWER project interviewed undergraduate STEM majors from computing, manufacturing, nursing, energy, and physics about their perspectives on problem-solving. Sixty-nine student focus groups were conducted, totaling 239 students. All students emphasized the importance of problem-solving in their discipline of study, but no single practice of problem-solving was applicable for all students. Most problem-solving perspectives were unique to each discipline (e.g., perseverance was emphasized in physics, empathy in nursing), while some perspectives were emphasized across several STEM fields (e.g., teamwork). Transferable problem-solving practices were often used alongside specialized practices to handle the unique challenges of each discipline. Findings suggest shifting away from framing problem-solving as a solitary transferable skill and toward framing problem-solving as an integrated set of context-dependent practices.

Math modeling is an iterative process where students use their observations and reasoning abilities to create and refine predictions or explanations about a single referent system (e.g., a lab apparatus). However, modeling may be complicated by the presence of multiple problem representations in an activity (e.g., both a word problem and a video demo), in which case students have multiple referents to consider. To study students' modeling behavior in these situations, we conducted think-aloud interviews with pairs of students around a kinematics activity. While creating process maps of students' modeling, we found that tracking students' system focus was critical to interpreting their reasoning and decisions. The model referent is no longer seen as a static object; instead, it is a dynamic object that changes in response to both structured prompts and spontaneous events. This concept gives rise to practical insights into activity design and implementation.