Technology

• Genetics
  

This commentary highlights key themes across the five chapters of this volume, as well as offers specific recommendations concerning future directions for inquiry on the issue of family–school connections. A case is made that in order to advance scientific knowledge of this issue and its application, dialogue is sorely needed that is multidisciplinary, engages mixed methods and emic traditions, and attends to how context shapes family–school connections.

Supporting Secondary Students in Building External Models is a collaborative project with Michigan State University and the Concord Consortium, funded by the National Science Foundation (NSF) to examine how to support secondary school students in constructing and revising models to explain scientific phenomena and design solutions to problems. This article describes the project and research plans.

Damelin, D., & Krajcik, J. (2016). Supporting secondary students in building external models to explain phenomena. @Concord, 20(1), 10-11.

Supporting Secondary Students in Building External Models is a collaborative project with Michigan State University and the Concord Consortium, funded by the National Science Foundation (NSF) to examine how to support secondary school students in constructing and revising models to explain scientific phenomena and design solutions to problems. This article describes the project and research plans.

Damelin, D., & Krajcik, J. (2016). Supporting secondary students in building external models to explain phenomena. @Concord, 20(1), 10-11.

This brief article provides an overview of how to use the SageModeler systems modeling tool with an ocean acidification model as an example.

Damelin, D. (2016). Monday's lesson: Students making models. @Concord, 20(2), 7.

This study investigates student interactions with simulations, and teacher support of those interactions, within naturalistic high school classroom settings. Two lesson sequences were conducted, one in 11 and one in 8 physics class sections, where roughly half the sections used the simulations in a small group format and matched sections used them in a whole class format.

Background Inclusive STEM (traditionally known to stand for “Science, Technology, Engineering, and Math”) high schools are emerging across the country as a mechanism for improving STEM education and getting more and diverse students into STEM majors and careers. However, there is no consensus on what these schools are or should be, making it difficult to both evaluate their effectiveness and scale successful models. We addressed this problem by working with inclusive STEM high school leaders and stakeholders to articulate and understand their intended school models.

In formative assessment, constructed response questions are typically used for scientific argumentation, but students seldom receive timely feedback while answering these questions. The development of natural language processing (NLP) techniques makes it possible for the researchers using an automated scoring engine to provide real-time feedback to students. As is true for any new technology, it is still unclear how automated scoring and feedback may impact learning in scientific  argumentation.

The logic underlying inclusive STEM high schools (ISHSs) posits that requiring all students to take advanced college preparatory STEM courses while providing student-centered, reform-oriented instruction, ample student supports, and real-world STEM experiences and role models will prepare and inspire students admitted on the basis of STEM interest rather than prior achievement for postsecondary STEM. This study tests that logic model by comparing the high school experiences and achievement of students in ISHSs and comparison schools in North Carolina.

Systems are a natural part of our world—from the smallest chemical system to the Earth's climate system. The Framework for K-12 Science Education and the Next Generation Science Standards identify systems and system models as one of the crosscutting concepts, and developing and using models as one of the science and engineering practices. However, students do not naturally engage in systems thinking or in building models to make sense of phenomena, and there are few easily accessible tools designed specifically for students to construct models.