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A 10-week, energy literacy curriculum unit for 6th grade students. Students will study energy use and transfer in their own school buildings. They will explore how Earth systems supply renewable and nonrenewable energy, and how these energy sources are transformed and transferred from Earth systems to a school building to meet its daily energy requirements.

A 10-week, energy literacy curriculum unit for 6th grade students. Students will study energy use and transfer in their own school buildings. They will explore how Earth systems supply renewable and nonrenewable energy, and how these energy sources are transformed and transferred from Earth systems to a school building to meet its daily energy requirements.

This report takes stock of what we currently know as well as what we need to know to make classroom assessment maximally beneficial for the teaching and learning of STEM subject matter in K–12 classrooms.

Artificial Intelligence (AI) is prevalent in nearly every aspect of our lives. However, recent studies have found a significant amount of confusion and misunderstanding surrounding AI. To develop effective educational programs in the field of AI, it is vital to examine and understand learners' pre- and misconceptions as well as myths about AI. This study examined a corpus of 591 studies.

This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.

When integrated into online curriculum modules for students, educative curriculum materials (ECMs) can enhance teachers’ enactment of these modules. This study investigated (1) the use of digitally enhanced ECMs built into an online plate tectonics curriculum module by teachers with different backgrounds and teaching experience, (2) the relationship between teachers’ use of ECMs and student learning gains, and (3) teacher reflections on the value of the ECMs they used.

This webinar provided early career data science education researchers with information on the state of the field; tools, curricula, and other resources for researchers; and insight into funding opportunities and proposal development. Participants explore topics, research interests, and problems of practice in more depth in breakout rooms with session leaders.

Although prior research has highlighted the significance of representations for mathematical learning, there is still a lack of research on how students use multimodal external representations (MERs) to solve mathematical tasks in digital game-based learning (DGBL) environments. This exploratory study was to examine the salient patterns problem solvers demonstrated using MERs when they engaged in a single-player, three-dimensional architecture game that requires the acquisition and application of math knowledge and thinking in game-based context problem solving.

Digital game-based math learning environments (math DGBLE) are promising platforms that provide students with opportunities to master conceptual understanding and cultivate mathematical thinking, on which the contemporary mathematics education places an emphasis. Literature on learning support in digital game-based learning (DGBL) rarely investigate learners' support-use behaviors and interaction patterns in relation to math learning. We addressed this research gap in this exploratory mixed-methods study. We designed and developed a packet of learning supports (i.e., Task Planner and Math Story) in a math DGBLE.

Adopting a pretest–posttest experimental design with repeated measures, this study examined the effects of three types of game-based learning supports in the form of modeling on knowledge development that contributed to successful math problem solving and students’ perceived game flow.