Fundamental: A Teacher Professional Development Program in Engineering Research with Entrepreneurship and Industry Experiences
Bibliographic record
Abstract
Abstract Today, technology is pervasive and it is reshaping every aspect of our lived experience. Unfortunately, similar to the vast majority of adults in our society, K-12 students generally lack an understanding of the engineering foundation of the tech-gadgets that have become an integral part of their lifestyles. As technology undergoes accelerating and converging advances, it is paramount that K-12 students receive high quality STEM education so that they have the potential to join the future engineering workforce as contributors to our innovation-driven economy. In recent years, hands-on, problem- and project-based learning has been gathering momentum in K-12 education. Such an approach can benefit students in gaining a greater understanding of subject material and allow teachers to support students of diverse learning styles. Even as hands-on STEM learning aims to incorporate real-world applications, many implementations of learning activities and practices are restricted to the classroom environment and constrained by the scale and resource availability. Teachers and students seldom get opportunities to explore authentic, real-world challenges, primarily due to the lack of teacher knowledge and experiences with modern technologies. These dynamics continue to reinforce students’ misperception that science and math are activities that students do in the classroom, disconnected from the real-world. Thus, to develop a technically literate workforce, educators must not only teach STEM knowledge but also address the students’ question, “Why do I need to know this?” Guided by the internship efficacy research, we posit that through exposure to hands-on engineering and industry experiences, teachers can become better equipped to inform students about how classroom science and math connects to real-world career opportunities. This paper documents activities and outcomes of a teacher professional development (PD) program, which allows participants to have authentic experiences in engineering, technology, entrepreneurship, and industry. An engineering department at a higher education institute hosted nine teachers for a six-weeklong summer PD, beginning with a two-week hands-on, structured learning followed by a four-week collaborative research and periodic industry interaction experiences. During the structured learning, teachers performed numerous hands-on experimental activities to learn and understand scientific and mathematical foundations of mechatronics and robotics. Moreover, through experiential activities, including visit to a technology startup incubator, they learned fundamental concepts of entrepreneurship, such as business model canvas, minimum viable product, intellectual property, raising funding, etc. In the four-week research phase, to experience the process and challenge of conducting engineering research, the teachers worked in teams to collaborate in and contribute to ongoing projects involving graduate researchers, undergraduate and high-school students, and faculty mentors. Moreover, talks from industry professionals, including a two-day workshop by an industry partner, and visits to startup and factory sites provided ample industry exposure, giving teachers a unique opportunity to develop their innovation, entrepreneurship, and networking skills as well as to gain a real-world understanding of engineering workplace and careers. Teachers created lesson plans to share educational, technical, entrepreneurial, and industry aspects of their summer experience, to provide a foundation for college-level education to their students, and better inform their students about engineering career opportunities. Through follow-up sessions over the academic year, teachers continue to receive additional support for implementing authentic, engineering-based lesson plans. The participants made significant contributions to research projects in four engineering labs. Illustrative research includes the design of a wirelessly controlled robot to study marine environments, development of an affordable game-based telerehabilitation solution for stroke victims, etc. Based on pre- and post- technical quizzes conducted during the PD, the teacher’s understanding of scientific and mathematical foundations of the concepts improved from 49% to 64%. Final submission of this paper will provide a detailed overview of PD curriculum, activities, research projects, and teacher outcomes (e.g., technical quiz, self-efficacy, and external evaluation).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".