Educational Technology

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.

The present study focuses on examining transitions in elementary pre-service teachers (PSTs)’ understanding of, and skills in, leading argumentation-focused discussions in mathematics during participation in a sequence of three different practice-based activities, collectively referred to as the Online Practice Suite (OPS).

Slides from a pre-conference workshop at the 2021 National Association for Research in Science Teaching Annual Meeting, Orlando, FL.

In this study, our team developed and is studying the use of an Online Practice Suite (OPS) composed of a coordinated and scaffolded collection of three practice-based online simulations designed to support the development of preservice teachers' (PSTs’) abilities, skills, beliefs, and understanding around one ambitious teaching practice within mathematics and science: facilitating discussions that engage students in argumentation.

This position paper advocates supporting computer science (CS) teacher professional learning by supplementing existing curriculum-specific teacher professional development (PD) with standards-aligned PD that focuses on teachers' conceptual understanding of CS standards and ability to adapt instruction based on student understanding of concepts underlying the CS standards. We share concrete examples of how to design standards-aligned educative resources and instructionally supportive tools that promote teachers' understanding of CS standards and common student challenges and develop teachers' formative assessment literacy, all essential components of CS pedagogical content knowledge.

Narrative as a game design feature constantly yields mixed results for learning in the literature. The purpose of this exploratory mixed-methods case study was to examine design heuristics and implications governing the role of narratives in a digital game-based learning (DGBL) environment for math problem solving.