ViSTA Plus

  • NSF-funded project
  • Curriculum will be available in 2016
  • ViSTA Plus study to take place in New Mexico and Oklahoma

Videocases for Science Teaching Analysis Plus (ViSTA Plus) is an NSF-funded project that merges two successful, research-based teacher education programs—BSCS ViSTA and STeLLA—into a multiyear teacher education curriculum that spans a year of preservice preparation and the first year of teaching.

“ViSTA Plus presents a distinctive version of practice-based teacher education,” says Principal Investigator Rebecca Kruse.

ViSTA Plus starts with analysis of other teachers’ videocases during the methods course and moves to collaborative analysis of teachers’ own videocases during their student teaching and first year of teaching. The ViSTA Plus conceptual framework supports teachers in using Student Thinking and Science Content Storyline Lenses to analyze science teaching, and in using a set of teaching strategies that supports use of both of these lenses in their planning and teaching. Through this analysis work, teachers deepen their science content knowledge, develop their ability to analyze teaching and learning, and improve their teaching and their students’ learning.  

“We aim to develop effective beginning teachers—that is, teachers who have a demonstrated positive impact on their students’ learning in science,” says Kruse.

BSCS will launch its study of the ViSTA Plus curriculum at University of New Mexico and Oklahoma State University in Spring 2013 using a quasi-experimental design that compares the impact of the ViSTA Plus program to that of these traditional teacher preparation programs that serve diverse populations, especially Native American, Hispanic, and low-SES (socio-econimic status) students.

The study will conclude in Spring 2015. The tested and revised ViSTA Plus curriculum should be widely available in late 2016. BSCS Senior Science Educator and ViSTA Plus Co-Principal Investigator Kathy Roth has been instrumental in helping develop both BSCS ViSTA and STeLLA.

This material is based upon work supported by the National Science Foundation under Grant No. DRL-1220635. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.