Algebra

Algebra LearnLab course description

The Algebra LearnLab course is described here.

The Algebra LearnLab course involves teaching high school Algebra I using the textbook and tutoring system of Carnegie Learning. The curriculum combines software-based, individualized computer lessons with collaborative, real-world problem-solving activities. Students spend about 40% of their class time using the software, and the balance of their time engaged in classroom problem-solving activities. Three Pittsburgh-area high schools are currently participating as PSLC Algebra LearnLab sites, offering a diverse student population, and additional high schools around the country are anticipated for future participation.

See a list of course topics below.

Algebra & Geometry LearnLab Course Committee

The Math Course Committee meets monthly and is led by Albert Corbett (corbett@andrew.cmu.edu).

Teachers (and perhaps researchers) can find answers to questions on the FAQ for teachers.

Algebra Learnlab Studies

• Improving skill at solving equations through better encoding of algebraic concepts (Booth, Siegler, Koedinger & Rittle-Johnson)
• Handwriting Algebra Tutor (Anthony, Yang & Koedinger)
  • Lab study proof-of-concept for handwriting vs typing input for learning algebra equation-solving (completed)
  • Effect of adding simple worked examples to problem-solving in algebra learning (completed, analysis in progress)
  • In vivo comparison of Cognitive Tutor Algebra using handwriting vs typing input (in progress)
• Collaborative Extensions to the Cognitive Tutor Algebra: Scripted Collaborative Problem Solving (Rummel, Diziol, McLaren, & Spada)
• Collaborative Extensions to the Cognitive Tutor Algebra: A Peer Tutoring Addition (Walker, McLaren, Koedinger, & Rummel)
• Robust Learning in Culturally and Personally Relevant Algebra Problem Scenarios (DiBiano, Petrosino, Greeno, & Sherman)
• Improving student affect through adding game elements to mathematics LearnLabs (Baker, Aleven)

These studies are also organized within research clusters that address common issues across a variety of academic content domains: Coordinative Learning, Interactive Communication, and Refinement and Fluency.

Algebra I topics

• Organizing Single Variable Data
• Simplifying Linear Expressions
• Finding Linear Equations from Graphs
• Solving Linear Equations and Inequalities
• Standard Form
• Slope Intercept Form
• Mathematical Modeling
• Linear Expressions and Equations
• Quadratic Expressions and Equations
• Solving Systems of Linear Equations Algebraically and Graphically
• Solving and Graphing Equations Involving Absolute Values
• Problem Solving using Proportional Reasoning
• Analyzing Data and Making Predictions
• Powers and Exponents