Analyzing Student Work to Inform Math Instruction is a blended online and face-to-face course for adult education instructors at all levels (novice, intermediate, and advanced) who are looking to improve their ability to analyze and make use of student work in mathematics. In this course, we will look at both student videos and student written work, with a stronger emphasis on the latter. Participants are encouraged to collect and bring examples of student work from their own classes to the face-to-face session.
This professional development activity/course is designed for:
- All teachers involved in adult numeracy instruction. Instructors at all levels of math comfort are encouraged to enroll.
In this blended course, you will improve your ability to give productive feedback and make instructional decisions based on what students are generating in class.
This course involves one online module (September 20–28) and one half-day, face-to-face session (September 29, 8:30 a.m.–12:30 p.m.). The online module runs for one week and should take approximately 3 hours to complete. Participation in the online module involves reading assigned materials, participating in an online discussion, and preparing an analysis to bring to the face-to-face session.There will be an optional online community of practice for two weeks after the face-to-face session.
You do not need to currently teach a math class to fully participate in this course.
To receive a certificate of completion, participants must complete the online module and attend the face-to-face-session. Participation in the community of practice is optional.
For more information, please contact Sherry Soares (email@example.com).
Upon completion of this professional development activity/course, you will be able to:
- Identify mathematical knowledge for teaching, and practices that can deepen it
- Use the DEN (Describe-Evaluate-Next Steps) process to structure your use of student work as formative assessment
- Provide constructive written feedback on student work
- Make instructional decisions based on class sets of student work