This design-based research takes advantage of advanced technologies to support teachers to rapidly respond to evidence about student ideas generated in their classrooms. Leveraging advances in natural language processing methods, the Teacher Action Planner (TAP) analyzes students’ written explanations embedded in web-based inquiry projects to provide teachers with a report on student progress in developing the three-dimensional understanding called for by the Next Generation Science Standards. Based on the pattern in student scores, the TAP recommends research-based ways for teachers to customize instruction. This study examines how ten middle school teachers in 4 schools used the analysis of student ideas and suggestions for instructional customization presented in the TAP. This paper reports on how well their implemented customizations addressed student learning needs. It concludes with a discussion of the implications of the findings for redesign of the TAP.
Improving Teacher Noticing of Students’ Science Ideas with a Dashboard
We explore how a Teacher Action Planner (TAP) that synthesizes student ideas impacts teacher noticing. The TAP uses Natural Language Processing (NLP) to detect student ideas in written explanations. We compared teacher noticing while using the TAP to noticing when reviewing student explanations. The TAP helped teachers deepen their analysis of student ideas. We did not see any impact on immediate instructional practice. We propose redesigns to the TAP to better connect noticing to instruction.
- Editors:
- de Vries, E.; Hod, Y.; Ahn, J.
- Award ID(s):
- 1813713
- Publication Date:
- NSF-PAR ID:
- 10286919
- Journal Name:
- Computersupported collaborative learning
- ISSN:
- 1573-4552
- Sponsoring Org:
- National Science Foundation
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