The Colleague AI platform introduces a groundbreaking Rubric Generation function designed to streamline how educators create and use rubrics for instructional and assessment purposes. This feature uses artificial intelligence (AI) to produce standards-based rubrics tailored to course content for formative and summative evaluations. By automating…

This article examines the professional knowledge required for mathematics teachers to effectively use generative artificial intelligence (GenAI) in planning high-quality, ambitious mathematics lessons. While GenAI tools like ChatGPT offer promise for automating parts of lesson planning, their utility in supporting ambitious instruction is limited…

We describe here lessons learned in designing an early algebra curriculum to measure early algebra's impact on children's algebra readiness for middle grades. The curriculum was developed to supplement regular mathematics instruction in Grades K-5. Lessons learned centered around the importance of several key factors, including using conceptual…

Lower division engineering courses are important yet hard to teach as many students find these highly abstracted material hard to comprehend. Recent studies have suggested that flipped classroom teaching has potential to improve the teaching and learning of lower division engineering courses. While some educators are optimistic about the potential…

This paper responds to a 2016 systematic literature review of the research on learning games by Ke (2016). The review paper unpacked the idea of intrinsic integration in learning games, analyzing important emergent themes. The key ideas and the value of this review are discussed in the context of the recent shift to virtual instruction. The…

Many studies investigating inquiry learning in science domains have appeared over the years. Throughout this period, inquiry learning has been regularly criticized by scholars who favor direct instruction over inquiry learning. In this vein, Zhang, Kirschner, Cobern, and Sweller (2022) recently asserted that direct instruction is overall superior…

In this paper, we propose a computational approach to model the Zone of Proximal Development (ZPD) using predicted probabilities of correctness and engaging students in reflective dialogue. To that end, we employ a predictive model that uses a linear function of a variety of parameters, including difficulty and student knowledge and we analyze the…

In this paper, we propose a computational approach to modeling the Zone of Proximal Development of students who learn using a natural language tutoring system for physics. We employ a student model that predicts students' performance based on their prior knowledge and their activity when using a dialogue tutor to practice with conceptual,…

This Innovative Practice Category Work In Progress paper presents an application of machine learning and data mining to student performance data in an undergraduate electrical engineering program. We are developing an analytical approach to enhance retention in the program especially among underrepresented groups. Our approach will provide…

"INSPIRE" is an Investing in Innovation (i3) development grant funded by the Office of Innovation and Improvement, U.S. Department of Education. "INSPIRE" provides an innovative integrated K-12 STEM pipeline approach focused on STEM course content and instructional redesign. The INSPIRE model was implemented in Cabarrus County…