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.
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.
Explaining phenomena associated with a system involves describing a system’s structure and articulating the process through which the system’s structure changes over time. This paper defines geo-sequential reasoning in the context of plate tectonics and uses it to analyse how students explain the geological processes that occur along convergent boundaries as part of the plate tectonics system. This study was part of design-based research on an online Plate tectonics module that included simulation-based modelling developed for secondary school students.
Explaining phenomena associated with a system involves describing a system’s structure and articulating the process through which the system’s structure changes over time. This paper defines geo-sequential reasoning in the context of plate tectonics and uses it to analyse how students explain the geological processes that occur along convergent boundaries as part of the plate tectonics system.
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.
Zhai, X. (2023). ChatGPT for Next Generation Science Learning | XRDS: Crossroads, 29(3), 42-46. https://doi.org/10.1145/3589649
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.
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.
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.
Science learning is an important part of the K-12 educational experience, as well as in the lives of students. This study considered students’ science learning as they engaged in the instruction of scientific issues with social relevance. With classroom environments radically changing during the COVID-19 pandemic, our study adapted to teachers and students as they were forced to change from more traditional, in-person instructional settings to virtual, online instruction settings.
Science learning is an important part of the K-12 educational experience, as well as in the lives of students. This study considered students’ science learning as they engaged in the instruction of scientific issues with social relevance. With classroom environments radically changing during the COVID-19 pandemic, our study adapted to teachers and students as they were forced to change from more traditional, in-person instructional settings to virtual, online instruction settings.
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings. We illustrate the characteristics and value of integrative analysis within an empirical study of student learning in 9th-grade biology.
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings.
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings. We illustrate the characteristics and value of integrative analysis within an empirical study of student learning in 9th-grade biology.
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings.
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings. We illustrate the characteristics and value of integrative analysis within an empirical study of student learning in 9th-grade biology.
Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings.
