Undergraduate

The CADRE Learning Series was designed to provide targeted support for STEM education researchers on topics of DRK-12 needs and interests. The learning series has covered the topics of professional development and case study design. 

The work presented here focuses on student struggles in undergraduate general chemistry laboratory activities, the source of these struggles, and the actions students take to overcome them. Using an activity theoretical lens and multiple domains (cognitive, epistemological, socioemotional, and psychomotor), we developed a domains-of-struggle framework which encompasses how struggles emerge through contradictions within the laboratory activity system.

The tasks described in this chapter are intended to build connections between these real-world dangers of viral spread and some relevant topics from the secondary mathematics curriculum. We also explore a link between mathematical reasoning and media literacy—the ability to discern the commercial, ideological, or political motivations of media and the recognition that receivers negotiate the meaning of messages (Aufderheide, 1993)—so that, just as we know to take safety precautions with regard to an airborne coronavirus, we can also help our students learn to take precautions against the spread of misinformation on social media.

This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the same learning design and adapted it to three different populations, settings, and classroom contexts: at the middle-school, high-school, and pre-service teaching levels.

This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the same learning design and adapted it to three different populations, settings, and classroom contexts: at the middle-school, high-school, and pre-service teaching levels.

This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the same learning design and adapted it to three different populations, settings, and classroom contexts: at the middle-school, high-school, and pre-service teaching levels.

Computer-aided design (CAD) programs are essential to engineering as they allow for better designs through low-cost iterations. While CAD programs are typically taught to undergraduate students as a job skill, such software can also help students learn engineering concepts. A current limitation of CAD programs (even those that are specifically designed for educational purposes) is that they are not capable of providing automated real-time help to students. To encourage CAD programs to build in assistance to students, we used data generated from students using a free, open-source CAD software called Aladdin to demonstrate how student data combined with machine learning techniques can predict how well a particular student will perform in a design task.

Computer-aided design (CAD) programs are essential to engineering as they allow for better designs through low-cost iterations. While CAD programs are typically taught to undergraduate students as a job skill, such software can also help students learn engineering concepts. A current limitation of CAD programs (even those that are specifically designed for educational purposes) is that they are not capable of providing automated real-time help to students. To encourage CAD programs to build in assistance to students, we used data generated from students using a free, open-source CAD software called Aladdin to demonstrate how student data combined with machine learning techniques can predict how well a particular student will perform in a design task.

Computer-aided design (CAD) programs are essential to engineering as they allow for better designs through low-cost iterations. While CAD programs are typically taught to undergraduate students as a job skill, such software can also help students learn engineering concepts. A current limitation of CAD programs (even those that are specifically designed for educational purposes) is that they are not capable of providing automated real-time help to students. To encourage CAD programs to build in assistance to students, we used data generated from students using a free, open-source CAD software called Aladdin to demonstrate how student data combined with machine learning techniques can predict how well a particular student will perform in a design task.