Monday, January 2, 2017
Petrosino and Mann (2017): "Data Modeling for Pre-Service Teachers and Everyone Else"- Journal of College Science Teaching
30-Dec-2016
Dear Dr. Petrosino:
Your manuscript entitled "Data Modeling for Pre-Service Teachers and Everyone Else" has been successfully submitted online and is presently being given full consideration for publication in the Journal of College Science Teaching.
Your manuscript ID is xxx-Oct-Jxxx-F-1101.xx.
Please mention the above manuscript ID in all future correspondence or when calling the office for questions. If there are any changes in your street address or e-mail address, please log in to Manuscript Central and edit your user information as appropriate.
You can also view the status of your manuscript at any time by checking your Author Center.
Thank you for submitting your manuscript to the Journal of College Science Teaching.
Sincerely,
Journal of College Science Teaching Editorial Office
Summary of Paper: This research was aimed at developing teacher thinking about data modeling. Data modeling is a description of the way data is organized. In the past, teachers were expected to teach science from the ideas of science–as-reasoning and science-as-conceptual-change however with the introduction of NGSS, teachers now need to incorporate science-as-practice. NGSS integrates eight practices of science, which students are to use from kindergarten onward. These practices are asking questions, developing and using models, designing and conducting investigations, using data, using computational thinking, constructing explanations, using argument from evidence and obtaining, evaluating and communicating information. All of these practices are part of the curriculum the preservice teachers enacted during this research. Future teachers need to have opportunities to use these practices. Without a solid understanding about how to gather data, and the variability of data it is not possible to correctly interpret data or correctly use arguments supported by data. These skills are needed by all K-16 students including preservice teacher educators. Statistics are ubiquitous and we all need to understand what the data mean. We have also used this same curriculum with science and engineering majors to help them better understand data modeling. Our position is that data modeling is a process that all K-16 students need to understand.
Dear Dr. Petrosino:
Your manuscript entitled "Data Modeling for Pre-Service Teachers and Everyone Else" has been successfully submitted online and is presently being given full consideration for publication in the Journal of College Science Teaching.
Your manuscript ID is xxx-Oct-Jxxx-F-1101.xx.
Please mention the above manuscript ID in all future correspondence or when calling the office for questions. If there are any changes in your street address or e-mail address, please log in to Manuscript Central and edit your user information as appropriate.
You can also view the status of your manuscript at any time by checking your Author Center.
Thank you for submitting your manuscript to the Journal of College Science Teaching.
Sincerely,
Journal of College Science Teaching Editorial Office
Summary of Paper: This research was aimed at developing teacher thinking about data modeling. Data modeling is a description of the way data is organized. In the past, teachers were expected to teach science from the ideas of science–as-reasoning and science-as-conceptual-change however with the introduction of NGSS, teachers now need to incorporate science-as-practice. NGSS integrates eight practices of science, which students are to use from kindergarten onward. These practices are asking questions, developing and using models, designing and conducting investigations, using data, using computational thinking, constructing explanations, using argument from evidence and obtaining, evaluating and communicating information. All of these practices are part of the curriculum the preservice teachers enacted during this research. Future teachers need to have opportunities to use these practices. Without a solid understanding about how to gather data, and the variability of data it is not possible to correctly interpret data or correctly use arguments supported by data. These skills are needed by all K-16 students including preservice teacher educators. Statistics are ubiquitous and we all need to understand what the data mean. We have also used this same curriculum with science and engineering majors to help them better understand data modeling. Our position is that data modeling is a process that all K-16 students need to understand.