Update README.md

README.md

@@ -1,3 +1,127 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+language:
+  - en
+task_categories:
+  - question-answering
+  - text-generation
+tags:
+  - mathematics
+  - education
+  - word-problems
+pretty_name: Math Problem Generator Dataset
+size_categories:
+  - 100K<n<1M
+---
+
+# Dataset Card for Math Problem Generator
+
+
+### Dataset Summary
+
+This dataset contains 100,000 procedurally generated math word problems covering various mathematical concepts and difficulty levels. The problems were generated using a Java program that creates contextual word problems with solutions and explanations.
+
+### Supported Tasks and Leaderboards
+
+This dataset can be used for:
+- Math word problem solving
+- Educational AI systems
+- Math question generation
+- Automatic explanation generation
+
+### Languages
+
+The dataset is in English.
+
+## Dataset Structure
+
+### Data Instances
+
+Each instance contains:
+- A unique problem ID
+- Problem category/type
+- The word problem text
+- The correct answer
+- A step-by-step explanation
+
+Example:
+Problem ID: abc12345
+Category: fractions addition
+Alice has 3/4 of a pizza and finds another 2/5 of the same pizza. How much pizza does Alice have in total?
+Answer: 23/20
+Explanation: To add fractions, find a common denominator (20). Convert 3/4 to 15/20 and 2/5 to 8/20. Add the numerators: 15 + 8 = 23. The answer is 23/20.
+
+text
+
+### Data Fields
+
+- `id`: Unique problem identifier
+- `operation`: Math category (addition, fractions, algebra, etc.)
+- `problem_text`: The word problem
+- `answer`: The correct answer (format varies by problem type)
+- `explanation`: Step-by-step solution
+
+### Data Splits
+
+The dataset comes as a single file with all 100,000 problems.
+
+## Dataset Creation
+
+### Curation Rationale
+
+This dataset was created to provide a large, diverse set of math word problems for training educational AI systems. The problems cover fundamental math concepts with varying contexts to improve generalization.
+
+### Source Data
+
+The problems are procedurally generated using predefined templates and randomization of:
+- Mathematical operations
+- Subjects/objects
+- Character names
+- Real-world contexts
+
+### Annotations
+
+Each problem includes:
+- Automatically generated correct answer
+- Step-by-step explanation
+- Problem categorization
+
+### Personal and Sensitive Information
+
+The dataset uses common first names and generic objects, containing no real personal information.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+This dataset can help:
+- Develop educational tools for math learning
+- Create AI tutors for students
+- Generate practice problems at scale
+
+### Discussion of Biases
+
+Potential biases include:
+- Western-centric names and contexts
+- Limited to elementary/middle school math levels
+- English language only
+
+### Other Known Limitations
+
+- Problems are generated rather than human-written
+- Limited creative variation in problem structures
+- Explanations follow standardized formats
+
+## Additional Information
+
+### Dataset Curators
+
+C.J. Jones
+
+### Licensing Information
+
+cc-by-nc-4.0
+
+### Citation Information
+
+If you use this dataset, please cite it as: Part of the C.J. Jones synthetic data collection. With link back to this page.