Automating the Generation of Personalized Parsons Problems with Customizable Contexts and Programming Concepts

Core Concepts

Leveraging large language models to automatically create customizable Parsons problems that align with students' interests and learning needs.

Abstract

The paper introduces PuzzleMakerPy, an educational tool that uses a large language model (GPT-3.5) to generate personalized Parsons problems. Students can customize the context and programming concepts for the generated problems, allowing them to engage with exercises that align with their interests and target their learning needs.
The key highlights and insights from the paper are:

Students had the option to select from a predefined list of 20 contexts or enter their own custom context when generating Parsons problems. The most popular contexts were "Animals", "Music", and "Basketball".

Students could also choose up to 3 programming concepts from a list of 8 options (e.g., loops, variables, strings) to include in the generated problems. The most frequently selected concepts were "Loops" and "Variables".

Feedback from students was generally positive, with the majority agreeing that the ability to customize the context and programming concepts was enjoyable and valuable for their learning. Students found the personalized Parsons problems useful for improving their programming skills and understanding code structure.

Some students suggested that the tool could be improved by incorporating more complex and challenging programming problems, as well as allowing them to provide their own code solutions instead of using the generated ones.

The authors conclude that the ability to personalize Parsons problems through customizable contexts and programming concepts was well-received by students and enhanced their learning experience in the introductory programming course.

Stats

"Customizing the context of a programming question was interesting/enjoyable."
"Customizing programming concepts is valuable for improving my own programming skills."
"Solving customized/personalized drag-and-drop programming questions was useful for my learning."
"Generating unlimited personalized drag-and-drop programming questions was useful for my learning."

Quotes

"It makes the learning process more enjoyable and interesting if the context in which I am trying to solve the problem is something that interests me instead of some random generic problem."
"It's helpful for visualizing and practicing code structure."
"I found it somewhat helpful, it is a nice alternative to study."

Key Insights Distilled From

Automating Personalized Parsons Problems with Customized Contexts and Concepts

by Andre del Ca... at arxiv.org 04-18-2024

https://arxiv.org/pdf/2404.10990.pdf

Deeper Inquiries

How could the tool be further improved to provide more challenging and complex programming problems that better reflect real-world programming tasks?

To enhance the tool's ability to generate more challenging and real-world reflective programming problems, several improvements can be considered:

Introduce Advanced Concepts: Incorporate advanced programming concepts beyond the introductory level, such as recursion, object-oriented programming, and data structures. This will expose students to more complex problem-solving scenarios.

Multiple Solutions: Allow for the generation of problems with multiple correct solutions. Real-world programming often involves various approaches to solving a problem, and this feature would encourage critical thinking and creativity.

Integration of APIs: Enable the tool to interact with external APIs to create problems that involve real data manipulation or integration with external services, mirroring real-world programming tasks.

Scalability and Efficiency Challenges: Include problems that focus on optimizing code efficiency, handling large datasets, or implementing scalable algorithms, reflecting common challenges faced in professional programming environments.

Error Handling and Debugging: Integrate problems that require students to identify and fix bugs, handle exceptions, and debug code effectively, simulating real-world scenarios where debugging skills are crucial.

Project-Based Problems: Develop project-based problems that span multiple concepts and require students to design and implement a complete solution, mimicking the holistic approach needed in real-world programming projects.

By incorporating these enhancements, the tool can provide a more comprehensive and challenging learning experience that better prepares students for real-world programming tasks.

How could the tool be extended to support collaborative learning and peer feedback on the generated Parsons problems?

To facilitate collaborative learning and peer feedback on the generated Parsons problems, the tool can be extended in the following ways:

Peer Review Feature: Implement a peer review system where students can share their generated solutions with peers for feedback and evaluation. Peers can provide comments, suggestions, and corrections to enhance learning through collaboration.

Collaborative Problem Solving: Enable collaborative problem-solving sessions where students can work together in real-time to solve Parsons problems. This feature promotes teamwork, communication, and collective problem-solving skills.

Discussion Forums: Integrate discussion forums within the tool where students can discuss problem-solving strategies, share insights, and ask questions. This fosters a sense of community and allows for knowledge exchange among peers.

Version Control: Incorporate version control functionality to track the evolution of solutions, enabling students to compare different iterations, learn from each other's approaches, and understand the progression of problem-solving techniques.

Group Projects: Introduce group projects that require collaboration on larger programming tasks, encouraging students to work together, delegate responsibilities, and collectively tackle complex problems.

Peer Rating System: Implement a peer rating system where students can evaluate and provide feedback on their peers' solutions based on predefined criteria, promoting accountability and constructive criticism.

By incorporating these collaborative features, the tool can create a more interactive and engaging learning environment that promotes teamwork, communication, and peer learning in programming education.

What other personalization features could be incorporated into the tool to better align with students' individual learning styles and preferences?

To enhance personalization and better align with students' individual learning styles and preferences, the tool can incorporate the following features:

Learning Path Customization: Allow students to create personalized learning paths by selecting specific topics, difficulty levels, and learning objectives tailored to their needs and interests.

Adaptive Difficulty: Implement an adaptive difficulty system that adjusts the complexity of generated problems based on students' performance, ensuring a suitable challenge level for each individual.

Visual Preferences: Provide customization options for the tool's interface, such as themes, color schemes, and layout preferences, to accommodate visual learning preferences and enhance user experience.

Interactive Tutorials: Integrate interactive tutorials and hints that adapt to students' progress and learning pace, offering personalized guidance and support throughout the problem-solving process.

Learning Analytics: Incorporate learning analytics to track students' performance, identify strengths and weaknesses, and offer personalized recommendations for improvement based on individual learning patterns.

Gamification Elements: Introduce gamification elements such as badges, leaderboards, and rewards to motivate students, increase engagement, and cater to different learning preferences, including competitive learners.

Multimodal Learning Resources: Provide diverse learning resources, including text, images, videos, and audio, to accommodate different learning styles and preferences, ensuring a comprehensive and inclusive learning experience.

By integrating these personalization features, the tool can offer a more tailored and adaptive learning environment that caters to the diverse needs and preferences of individual students, enhancing their overall learning outcomes and engagement.