Critical Reasoning for College Readiness: An assessment development project in computational thinking
Mark Wilson, Professor
Education
Applications for Fall 2024 are closed for this project.
Critical Reasoning for College Readiness (CR4CR) is a project that seeks to develop psychometrically sound assessments that can be used by teachers in the classrooms at the high school and early college levels. Our goal is to develop, revise, and validate a suite of assessments, including unique assessment tasks and their underlying models of learning. We focus on the measurement of critical thinking and reasoning skills that are essential for college readiness in the following three domains:
1. problem-solving using mathematics (algebra),
2. data-based decision making (statistics/data science), and
3. computational thinking.
We use an online assessment system called the Berkeley Assessment System Software (BASS for short) to guide the development, refinement, and management of the assessment materials, including constructs, items, scoring guides, and reports. To achieve our goal, we consult the learning sciences literature about how students learn in a domain, develop theoretical models of learning progression and assessment tasks, collect and analyze qualitative and quantitative data.
Role: This listing is for one or more positions in the two strands: a) data-based decision-making and b) computational thinking. Responsibilities include one or more of the following, depending on the undergraduate students’ interests and experiences:
- Co-design assessment tasks following a template/specifications. We welcome applicants who are technology-savvy and creative as we would like to develop innovative tasks that take advantage of technology affordances (e.g., ChatGPT, GeoGebra).
- Score student-written responses following scoring guides/rubrics and contribute to the development/refinement of scoring guides and selected-response version of tasks.
- (Lower priority) Use R/RStudio to analyze student responses and other related data descriptively.
- (Lower priority) Use Python and R/RStudio to develop automated scoring based on machine learning techniques.
- Attend meetings (mostly over Zoom) and work collaboratively with team members.
Qualifications: We are looking for JUNIORS who are interested in assessment design, qualitative and quantitative educational research in Computational Thinking and Statistics. You MUST BE ABLE TO MANAGE the WORKLOAD between YOUR OTHER COURSES and the URAP PROJECT. Training will be provided so no prior experience is necessary, however, background in Data Science/Computer Science, education minor, and teaching experience in DS/CS, math & statistics, are welcome. This position is perfect for those who are interested in cognitive / learning sciences and psychometrics, and want to gain some research and development experiences in the STEM disciplines.
Day-to-day supervisor for this project: Karen Draney, Staff Researcher
Hours: 6-8 hrs
Off-Campus Research Site: We are flexible with off-campus working arrangements; we will conduct most work via Zoom.
Related website: http://bear.soe.berkeley.edu
Education, Cognition & Psychology Social Sciences Digital Humanities and Data Science