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	<title>Interactive Reasoning Taxonomy Explorer</title>
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	Framework for Complex-Reasoning Taxonomy
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	<h2 class="text-xl font-bold text-slate-800 mb-4 pb-2 border-b border-slate-200">Taxonomy Outline</h2>
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	{"prompt": "In Java, create a `Car` class with private fields for `make` and `model`. Provide public getter and setter methods for these fields to demonstrate encapsulation.", "difficulty": "medium", "taxonomies": ["Conceptual Abstraction", "Procedural Abstraction", "Decomposition Tasks"]},
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	{"prompt": "Write a Python script that uses the `os` module to list all files in the current directory and prints only those with a '.py' extension.", "difficulty": "medium", "taxonomies": ["Intermediate-Level Tasks", "Branching Chain-of-Thought"]},
	{"prompt": "In C++, implement a function that takes a `std::vector<int>` and returns the sum of all its elements without using `std::accumulate`.", "difficulty": "medium", "taxonomies": ["Algorithm Design Tasks", "Iterative Chain-of-Thought"]},
	{"prompt": "Create a Python class `BankAccount` with methods to `deposit`, `withdraw`, and `check_balance`. Ensure the balance cannot go below zero.", "difficulty": "medium", "taxonomies": ["Conceptual Abstraction", "Decomposition Tasks", "Branching Chain-of-Thought"]},
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	{"prompt": "Implement a Python function `find_longest_word(words_list)` that returns the longest word from a list of strings.", "difficulty": "medium", "taxonomies": ["Algorithm Design Tasks", "Iterative Chain-of-Thought"]},
	{"prompt": "Write a Python script to parse a JSON file named `config.json` and extract the value of the `api_key` field.", "difficulty": "medium", "taxonomies": ["Intermediate-Level Tasks", "Structural Pattern Tasks"]},
	{"prompt": "In Java, create an `Animal` abstract class with an abstract method `makeSound()`. Then create `Dog` and `Cat` classes that extend `Animal` and implement the method.", "difficulty": "medium", "taxonomies": ["Conceptual Abstraction", "Deep-Level Tasks"]},
	{"prompt": "Using Python's `re` module, write a regular expression to validate an email address format.", "difficulty": "medium", "taxonomies": ["Pattern Recognition Tasks", "Structural Pattern Tasks"]},
	{"prompt": "Implement the Bubble Sort algorithm in Java to sort an array of integers in ascending order.", "difficulty": "hard", "taxonomies": ["Algorithm Design Tasks", "Algorithm Analysis Tasks", "Iterative Chain-of-Thought"]},
	{"prompt": "Write a Python decorator `@timer` that calculates and prints the execution time of any function it wraps.", "difficulty": "hard", "taxonomies": ["Meta-Reasoning Tasks", "Procedural Abstraction", "Reflection and Evaluation"]},
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	{"prompt": "Write a Python script using `asyncio` to run two simple coroutines concurrently that each print a message and sleep for a different amount of time.", "difficulty": "hard", "taxonomies": ["High Cognitive Load Tasks", "Algorithmic Thinking Tasks"]},
	{"prompt": "In C++, implement a `LinkedList` class from scratch with methods for `append`, `prepend`, and `delete` nodes.", "difficulty": "hard", "taxonomies": ["Conceptual Abstraction", "Algorithm Design Tasks", "Deep-Level Tasks"]},
	{"prompt": "Write a Python function to perform a binary search on a sorted list of integers to find the index of a target value. Return -1 if the value is not found.", "difficulty": "hard", "taxonomies": ["Algorithm Design Tasks", "Algorithm Analysis Tasks", "Branching Chain-of-Thought"]},
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	{"prompt": "Write a Python script that scrapes all the image URLs from a specific Wikipedia page using `requests` and `BeautifulSoup`.", "difficulty": "hard", "taxonomies": ["Deep-Level Tasks", "Structural Pattern Tasks", "Iterative Chain-of-Thought"]},
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	{"prompt": "Design and implement a multi-threaded web crawler in Java that can fetch and parse multiple web pages concurrently. The system should manage a queue of URLs to visit, handle duplicate URLs, and respect `robots.txt` files. Use a thread pool for efficient resource management.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "High Cognitive Load Tasks", "Algorithm Design Tasks", "Open-Ended Tasks", "Multithreading"]},
	{"prompt": "Implement Dijkstra's shortest path algorithm in C++ for a graph represented by an adjacency matrix. The function should take a source vertex and return the shortest distances to all other vertices. The implementation must use a priority queue for efficiency.", "difficulty": "insanely difficult", "taxonomies": ["Algorithm Design Tasks", "Graph-pattern matching exercises", "Algorithm Analysis Tasks", "Deep-Level Tasks"]},
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	{"prompt": "In Java, implement a generic `Pair` class that can hold two objects of any type.", "difficulty": "hard", "taxonomies": ["Conceptual Abstraction", "Procedural Abstraction"]},
	{"prompt": "Create a Python script that acts as a simple TCP echo server. It should listen on a port, accept a connection, receive data from the client, and send the same data back.", "difficulty": "hard", "taxonomies": ["System Analysis Tasks", "High Cognitive Load Tasks"]},
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	{"prompt": "Write a Python script that connects to a public API (e.g., a weather API), fetches data for a specific city, and prints a formatted summary of the current weather conditions.", "difficulty": "hard", "taxonomies": ["System Analysis Tasks", "Data Analysis Reasoning"]},
	{"prompt": "Implement a basic version of the A* search algorithm in Python to find the shortest path in a 2D grid with obstacles.", "difficulty": "insanely difficult", "taxonomies": ["Algorithm Design Tasks", "Graph-pattern matching exercises", "High Cognitive Load Tasks", "Strategy Selection Tasks"]},
	{"prompt": "In Java, write a program that uses `java.nio` channels and buffers to efficiently copy a large file from one location to another.", "difficulty": "hard", "taxonomies": ["System Analysis Tasks", "Deep-Level Tasks"]},
	{"prompt": "Develop a C++ program that uses multiple threads to parallelize the calculation of the sum of elements in a very large array. Ensure the solution is thread-safe when accumulating the final result.", "difficulty": "hard", "taxonomies": ["Multithreading", "High Cognitive Load Tasks", "Decomposition Tasks", "Algorithm Design Tasks"]},
	{"prompt": "Write a Python metaclass that enforces a specific coding standard on any class that uses it, such as ensuring all public methods have docstrings.", "difficulty": "insanely difficult", "taxonomies": ["Meta-Reasoning Tasks", "Conceptual Abstraction", "Reflection and Evaluation", "Open-Ended Tasks"]},
	{"prompt": "In Java, implement a custom annotation `@Loggable` that, when applied to a method, uses Aspect-Oriented Programming (AOP with AspectJ or Spring AOP) to log method entry, exit, and execution time.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Meta-Reasoning Tasks", "Procedural Abstraction", "Deep-Level Tasks"]},
	{"prompt": "Create a C++ program that implements a simple expression evaluator for arithmetic expressions involving `+`, `-`, `*`, `/`, and parentheses. The program should take an infix expression as a string and calculate the result using the Shunting-yard algorithm and a stack-based evaluation.", "difficulty": "insanely difficult", "taxonomies": ["Algorithm Design Tasks", "Logical and Formal Reasoning", "Decomposition Tasks", "Long-Form Reasoning"]},
	{"prompt": "Write a Python script that uses the `ctypes` library to call a function from a shared library (`.dll` or `.so`) written in C. The C function should perform a complex calculation, and the Python script should handle passing data to it and retrieving the result.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Deep-Level Tasks", "Learning Transfer Tasks"]},
	{"prompt": "In Java, build a simple object-relational mapping (ORM) framework from scratch. It should be able to map a POJO (Plain Old Java Object) to a database table, handle basic CRUD operations using JDBC, and use annotations to define table and column mappings.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Open-Ended Tasks", "Conceptual Abstraction", "Decomposition Tasks", "Long-Form Reasoning"]},
	{"prompt": "Write a C++ program that uses template metaprogramming to compute the factorial of a number at compile time.", "difficulty": "insanely difficult", "taxonomies": ["Meta-Reasoning Tasks", "Mathematical Reasoning", "Deep-Level Tasks", "Logical and Formal Reasoning"]},
	{"prompt": "Implement a distributed locking service using Redis in Python. The service should provide `acquire` and `release` methods and handle lock timeouts to prevent deadlocks.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Algorithm Design Tasks", "High Cognitive Load Tasks", "Error Correction"]},
	{"prompt": "Write a Python script to train a simple Generative Adversarial Network (GAN) using PyTorch or TensorFlow/Keras on a dataset like MNIST. The script should define both the generator and discriminator networks and include the training loop that alternates between training them.", "difficulty": "insanely difficult", "taxonomies": ["Scientific Reasoning", "Mathematical Reasoning", "Algorithm Design Tasks", "Long-Form Reasoning", "Open-Ended Tasks"]},
	{"prompt": "In Java, create a simple garbage collector for a custom memory management system. It should use a mark-and-sweep algorithm to identify and reclaim unreachable objects from a simulated heap.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Algorithm Design Tasks", "High Cognitive Load Tasks", "Open-Ended Tasks"]},
	{"prompt": "Develop a C++ library for performing matrix operations (addition, multiplication, inversion) using expression templates to avoid creating temporary objects and improve performance.", "difficulty": "insanely difficult", "taxonomies": ["Algorithm Design Tasks", "Mathematical Reasoning", "Algebraic Reasoning", "Deep-Level Tasks", "Meta-Reasoning Tasks"]},
	{"prompt": "Write a Python function to find the median of a list of numbers without sorting the entire list. Implement the median of medians algorithm.", "difficulty": "hard", "taxonomies": ["Algorithm Design Tasks", "Algorithm Analysis Tasks", "Mathematical Reasoning"]},
	{"prompt": "In Java, create a class that represents a playing card and another class for a deck of cards. The deck class should have methods to shuffle and deal cards.", "difficulty": "medium", "taxonomies": ["Conceptual Abstraction", "Decomposition Tasks", "Algorithm Design Tasks"]},
	{"prompt": "In Python, use the `collections.Counter` class to count the frequency of items in a list.", "difficulty": "medium", "taxonomies": ["Data Analysis Reasoning", "Procedural Abstraction"]},
	{"prompt": "Write a Java program that demonstrates method overloading by creating three methods with the same name `printData` but with different parameter types (e.g., `String`, `int`, `double`).", "difficulty": "medium", "taxonomies": ["Conceptual Abstraction", "Procedural Abstraction"]},
	{"prompt": "In C++, create a function that takes a string as input and returns a reversed version of the string.", "difficulty": "medium", "taxonomies": ["Algorithm Design Tasks", "Iterative Chain-of-Thought"]},
	{"prompt": "Write a Python script that defines a simple class and then uses the `__str__` method to provide a user-friendly string representation of its objects.", "difficulty": "medium", "taxonomies": ["Conceptual Abstraction", "Procedural Abstraction"]},
	{"prompt": "In Java, implement the `Comparable` interface in a `Student` class to allow sorting a list of students based on their GPA.", "difficulty": "hard", "taxonomies": ["Conceptual Abstraction", "Algorithm Design Tasks", "Data Analysis Reasoning"]},
	{"prompt": "Write a C++ program that demonstrates the use of `static` members in a class by creating a counter that tracks how many objects of the class have been instantiated.", "difficulty": "hard", "taxonomies": ["Conceptual Abstraction", "Self-Monitoring Tasks"]},
	{"prompt": "In Python, write a function that takes a list of integers and uses a `try-except` block to handle potential `TypeError` if the list contains non-integer values, returning an error message.", "difficulty": "hard", "taxonomies": ["Error Correction", "Self-Monitoring Tasks", "Strategy Adaptation"]},
	{"prompt": "Write a Java program that uses JDBC to connect to a MySQL database, execute a query to select all records from a `products` table, and display the results.", "difficulty": "hard", "taxonomies": ["System Analysis Tasks", "Decomposition Tasks", "Data Analysis Reasoning"]},
	{"prompt": "In C++, implement a simple RAII (Resource Acquisition Is Initialization) wrapper for a file handle (`FILE*`) to ensure the file is automatically closed when the wrapper object goes out of scope.", "difficulty": "hard", "taxonomies": ["Conceptual Abstraction", "Error Correction", "Deep-Level Tasks"]},
	{"prompt": "In Java, create a simple producer-consumer problem solution using `wait()` and `notify()` on a shared buffer object to demonstrate thread communication and synchronization.", "difficulty": "insanely difficult", "taxonomies": ["High Cognitive Load Tasks", "System Analysis Tasks", "Multithreading", "Algorithm Design Tasks"]},
	{"prompt": "Write a C++ program that implements a simple observer design pattern. Create a `Subject` class that maintains a list of `Observer` objects and notifies them whenever its state changes.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Conceptual Abstraction", "Decomposition Tasks", "Pattern Recognition Tasks"]},
	{"prompt": "In Python, implement a breadth-first search (BFS) algorithm to traverse a graph represented by an adjacency list and find the shortest path between two nodes.", "difficulty": "insanely difficult", "taxonomies": ["Algorithm Design Tasks", "Graph-pattern matching exercises", "Algorithm Analysis Tasks"]},
	{"prompt": "Write a Java application that uses the JAX-RS (Jersey) framework to create a RESTful web service with endpoints for CRUD operations on a list of in-memory objects.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Decomposition Tasks", "Algorithmic Thinking Tasks", "Long-Form Reasoning"]},
	{"prompt": "In C++, create a program that uses the `<chrono>` library to benchmark the performance of sorting a large vector using `std::sort` versus your own implementation of bubble sort.", "difficulty": "hard", "taxonomies": ["Reflection and Evaluation", "Solution Evaluation Tasks", "Algorithm Analysis Tasks"]},
	{"prompt": "Write a Python script that uses `BeautifulSoup` and `requests` to scrape a table from an HTML page and convert it into a pandas DataFrame.", "difficulty": "hard", "taxonomies": ["Structural Pattern Tasks", "Data Analysis Reasoning", "Decomposition Tasks"]},
	{"prompt": "In Java, write a program that uses a `ReentrantLock` to protect a critical section of code accessed by multiple threads, demonstrating its use over intrinsic locks.", "difficulty": "hard", "taxonomies": ["High Cognitive Load Tasks", "Multithreading", "System Analysis Tasks"]},
	{"prompt": "Create a Python function that implements a Caesar cipher, taking a string and a shift value as input and returning the encrypted string.", "difficulty": "medium", "taxonomies": ["Algorithm Design Tasks", "Mathematical Reasoning"]},
	{"prompt": "In C++, write a program that dynamically allocates a 2D array of integers, fills it with values, and then properly deallocates the memory.", "difficulty": "medium", "taxonomies": ["Deep-Level Tasks", "Error Correction"]},
	{"prompt": "Write a Java class that has a method that might throw a custom exception, and then call this method within a `try-catch-finally` block.", "difficulty": "medium", "taxonomies": ["Error Correction", "Self-Monitoring Tasks"]},
	{"prompt": "Write a Java program that uses a `BufferedReader` to read a text file more efficiently than a simple `FileReader`.", "difficulty": "medium", "taxonomies": ["System Analysis Tasks", "Intermediate-Level Tasks"]},
	{"prompt": "Write a C++ program that uses `std::vector::erase` to remove a specific element from a vector.", "difficulty": "easy", "taxonomies": ["Surface-Level Tasks"]},
	{"prompt": "In Python, write a one-liner to reverse a string.", "difficulty": "easy", "taxonomies": ["Procedural Abstraction"]},
	{"prompt": "Write a Java program that checks if two strings are anagrams of each other.", "difficulty": "medium", "taxonomies": ["Algorithm Design Tasks", "Data Analysis Reasoning"]},
	{"prompt": "In C++, create a function that takes an integer and returns `true` if it's a prime number and `false` otherwise.", "difficulty": "medium", "taxonomies": ["Algorithm Design Tasks", "Mathematical Reasoning", "Branching Chain-of-Thought"]},
	{"prompt": "Write a Python script that uses the `glob` module to find all files in a directory matching a specific pattern (e.g., `*.txt`).", "difficulty": "medium", "taxonomies": ["Structural Pattern Tasks", "Intermediate-Level Tasks"]},
	{"prompt": "In Java, create a program that demonstrates the use of a `static` block for one-time initialization of a class.", "difficulty": "medium", "taxonomies": ["Conceptual Abstraction", "System Analysis Tasks"]},
	{"prompt": "Write a C++ program that uses `std::transform` and a lambda function to create a new vector containing the squares of the elements of an original vector.", "difficulty": "hard", "taxonomies": ["Procedural Abstraction", "Iterative Chain-of-Thought", "Data Analysis Reasoning"]},
	{"prompt": "In Python, write a class that overloads the addition operator (`__add__`) to allow for the addition of two custom objects.", "difficulty": "hard", "taxonomies": ["Conceptual Abstraction", "Procedural Abstraction", "Deep-Level Tasks"]},
	{"prompt": "Write a Java program that uses a `Semaphore` to limit the number of threads that can access a particular resource simultaneously.", "difficulty": "hard", "taxonomies": ["High Cognitive Load Tasks", "System Analysis Tasks", "Multithreading"]},
	{"prompt": "In C++, implement a function to check if a singly linked list has a cycle.", "difficulty": "hard", "taxonomies": ["Algorithm Design Tasks", "Graph-pattern matching exercises", "Deep-Level Tasks"]},
	{"prompt": "Write a Python script that uses `argparse` to create a command-line interface with sub-commands (e.g., `git push`, `git pull`).", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "Decomposition Tasks", "Long-Form Reasoning"]},
	{"prompt": "In Java, write a program that uses the `java.nio.file` package to watch a directory for changes (creation, deletion, modification of files).", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "High Cognitive Load Tasks", "Event-Driven Programming"]},
	{"prompt": "Write a C++ program that implements a simple futures and promises mechanism from scratch to manage asynchronous operations.", "difficulty": "insanely difficult", "taxonomies": ["System Analysis Tasks", "High Cognitive Load Tasks", "Multithreading", "Algorithm Design Tasks", "Conceptual Abstraction"]},
	{"prompt": "In Python, write a script that uses `scipy.optimize` to find the minimum of a mathematical function.", "difficulty": "hard", "taxonomies": ["Mathematical Reasoning", "Scientific Reasoning", "Algorithmic Thinking Tasks"]},
	{"prompt": "Write a Java program that uses the Builder design pattern to construct a complex `User` object with multiple optional fields.", "difficulty": "hard", "taxonomies": ["Pattern Recognition Tasks", "Conceptual Abstraction", "Decomposition Tasks"]},
	{"prompt": "Write a Python script that uses a `set` to find the elements that are common to two lists.", "difficulty": "medium", "taxonomies": ["Data Analysis Reasoning", "Procedural Abstraction"]},
	{"prompt": "Write a C++ program that uses `dynamic_cast` to safely downcast a base class pointer to a derived class pointer, with a check to ensure the cast is valid.", "difficulty": "hard", "taxonomies": ["Conceptual Abstraction", "Deep-Level Tasks", "Error Correction"]},
	{"prompt": "In Python, create a simple context manager using a generator function and the `@contextmanager` decorator from `contextlib`.", "difficulty": "hard", "taxonomies": ["Procedural Abstraction", "Conceptual Abstraction", "Deep-Level Tasks"]},
	{"prompt": "Write a Java program that uses a `CyclicBarrier` to synchronize a group of threads at a certain point, making them wait until all threads have reached the barrier.", "difficulty": "insanely difficult", "taxonomies": ["High Cognitive Load Tasks", "System Analysis Tasks", "Multithreading", "Algorithm Design Tasks"]},
	{"prompt": "In C++, implement a function that serializes a `std::map<std::string, int>` to a binary file and another function to deserialize it.", "difficulty": "insanely difficult", "taxonomies": ["Algorithm Design Tasks", "System Analysis Tasks", "Structural Pattern Tasks", "Deep-Level Tasks"]},
	{"prompt": "Write a Python script that uses the `async/await` syntax with `asyncio.gather` to run multiple asynchronous operations concurrently and wait for all of them to complete.", "difficulty": "insanely difficult", "taxonomies": ["High Cognitive Load Tasks", "System Analysis Tasks", "Algorithmic Thinking Tasks", "Decomposition Tasks"]},
	{"prompt": "In Java, create a program that uses the `java.lang.instrument` API and a bytecode manipulation library like ASM or ByteBuddy to dynamically add logging to the entry and exit of a specific method in another class at runtime.", "difficulty": "insanely difficult", "taxonomies": ["Meta-Reasoning Tasks", "System Analysis Tasks", "Deep-Level Tasks", "High Cognitive Load Tasks", "Reflection and Evaluation"]}]

	const taxonomyData = {
	"id": "root",
	"name": "Framework for Complex-Reasoning Taxonomy",
	"children": [
	{
	"id": "intro",
	"name": "Introduction",
	"content": "\n <h2 class=\"text-2xl font-bold text-teal-700 mb-4\">A Comprehensive Analysis of Evaluation Datasets</h2>\n <p class=\"mb-4\">This application presents a detailed analysis and compilation of evaluation datasets for the \"Framework for Complex-Reasoning Taxonomy.\" The primary objective is to systematically explore the \"Evaluation Datasets\" for each category by synthesizing empirical findings from cognitive science, education, and artificial intelligence.</p>\n <p class=\"mb-4\">A significant theme that emerges is the parallel and increasingly convergent evolution of datasets for human and artificial intelligence. Historically, assessment has followed two distinct tracks: one rooted in cognitive psychology (e.g., Wason Selection Task) and another driven by Large Language Models (LLMs) using large-scale datasets (e.g., GSM8K). This explorer illuminates the dynamic interplay between these two traditions.</p>\n <div class=\"chart-container my-8\">\n <canvas id=\"datasetChart\"></canvas>\n </div>\n <p class=\"text-sm text-slate-600 text-center\">Chart: High-level overview of the primary dataset categories discussed throughout this report.</p>\n "
	},
	{
	"id": "foundational",
	"name": "1. Foundational Framework",
	"score": null,
	"content": "<p>This section addresses the overarching theoretical models that frame the study of complex reasoning. The datasets here are designed to validate the core tenets of these theories by operationalizing their central constructs.</p>",
	"children": [
	{
	"id": "bloom",
	"name": "Bloom’s Taxonomy Integration",
	"score": 0.95,
	"content": "<p>Mapping reasoning tasks onto Bloom’s six cognitive levels (remember→create), guiding alignment of objectives, activities, and assessments.</p>",
	"datasets": [
	{
	"name": "Revised Bloom’s Taxonomy-aligned performance tasks and rubrics",
	"link": "https://www.coloradocollege.edu/other/assessment/how-to-assess-learning/learning-outcomes/blooms-revised-taxonomy.html"
	}
	]
	},
	{
	"id": "dual_process",
	"name": "Dual-Process Theory",
	"score": 0.9,
	"content": "<p>Distinguishes fast, intuitive (System 1) vs. slow, analytical (System 2) reasoning processes; informs when each process dominates.</p>",
	"datasets": [
	{
	"name": "Cognitive Reflection Test (CRT) for detecting System 1 override; implicit-association tasks assessing interplay",
	"link": "https://www.jstor.org/stable/30033704"
	}
	]
	},
	{
	"id": "metacognitive_framework",
	"name": "Metacognitive Framework",
	"score": 0.88,
	"content": "<p>Meta-Reasoning processes that monitor (feelings of rightness) and control (strategy shifts) ongoing reasoning and problem-solving.</p>",
	"datasets": [
	{
	"name": "Meta-Reasoning paradigms using think-aloud protocols and process-tracing (e.g., Felt-Rightness ratings)",
	"link": "https://dacemirror.sci-hub.se/journal-article/c2286260f7ebbc44e1d06675e66fc87d/ackerman2017.pdf"
	}
	]
	}
	]
	},
	{
	"id": "level1",
	"name": "1.1 Level 1: Cognitive Complexity Dimensions",
	"score": null,
	"content": "<p>This level deconstructs reasoning into its fundamental operational components. Datasets here focus on the intrinsic complexity of the cognitive operations required by a task and the formal type of reasoning being employed.</p>",
	"children": [
	{
	"id": "depth_processing",
	"name": "1.1.1 Depth of Processing",
	"score": null,
	"children": [
	{
	"id": "surface_tasks",
	"name": "Surface-Level Tasks",
	"score": 0.6,
	"content": "<p>Reliance on shallow perceptual or structural analyses (e.g., font, letter shapes) with minimal semantic engagement.</p>",
	"datasets": [
	{
	"name": "Recognition tasks with form-based cues (DOK Level 1)",
	"link": "https://www.structural-learning.com/post/webbs-depth-of-knowledge"
	}
	]
	},
	{
	"id": "intermediate_tasks",
	"name": "Intermediate-Level Tasks",
	"score": 0.7,
	"content": "<p>Incorporates phonemic or moderate semantic processing (e.g., rhyming, basic categorization).</p>",
	"datasets": [
	{
	"name": "Simple application tasks (DOK Level 2)",
	"link": "https://www.structural-learning.com/post/webbs-depth-of-knowledge"
	}
	]
	},
	{
	"id": "deep_tasks",
	"name": "Deep-Level Tasks",
	"score": 0.8,
	"content": "<p>Engages rich semantic elaboration, integration with prior knowledge, and meaning-based encoding.</p>",
	"datasets": [
	{
	"name": "Extended reasoning items (DOK Levels 3–4)",
	"link": "https://www.structural-learning.com/post/webbs-depth-of-knowledge"
	}
	]
	}
	]
	},
	{
	"id": "reasoning_type_classification",
	"name": "1.1.2 Reasoning Type Classification",
	"score": null,
	"children": [
	{
	"id": "deductive_tasks",
	"name": "Deductive Reasoning Tasks",
	"score": 0.85,
	"content": "<p>Deriving specific conclusions from general premises; guarantee of truth if premises valid.</p>",
	"datasets": [
	{
	"name": "Syllogistic reasoning tests and deductive logic puzzles",
	"link": "https://en.wikipedia.org/wiki/Syllogism"
	}
	]
	},
	{
	"id": "inductive_tasks",
	"name": "Inductive Reasoning Tasks",
	"score": 0.8,
	"content": "<p>Generalizing from specific instances; probabilistic support for conclusions.</p>",
	"datasets": [
	{
	"name": "Hypothesis-generation tasks; pattern generalization benchmarks",
	"link": "https://www.sciencedirect.com/topics/psychology/hypothesis-testing"
	}
	]
	},
	{
	"id": "abductive_tasks",
	"name": "Abductive Reasoning Tasks",
	"score": 0.75,
	"content": "<p>Inferring the best explanation for given data; reasoning to the most likely hypothesis.</p>",
	"datasets": [
	{
	"name": "Medical diagnosis simulations; abductive inference drills",
	"link": "https://en.wikipedia.org/wiki/Abductive_reasoning"
	}
	]
	},
	{
	"id": "analogical_tasks",
	"name": "Analogical Reasoning Tasks",
	"score": 0.88,
	"content": "<p>Mapping relational structure from one domain to another, recognizing similarity in relations.</p>",
	"datasets": [
	{
	"name": "Analogical mapping tests (e.g., Raven’s Analogies)",
	"link": "https://en.wikipedia.org/wiki/Raven%27s_Progressive_Matrices"
	}
	]
	}
	]
	}
	]
	},
	{
	"id": "level2",
	"name": "1.2 Level 2: Computational Thinking",
	"score": null,
	"content": "<p>Computational Thinking (CT) is a problem-solving methodology. Its evaluation has evolved from programming-specific tasks to more generalized, cross-curricular assessments.</p>",
	"children": [
	{
	"id": "decomposition_tasks",
	"name": "2.1 Decomposition Tasks",
	"score": 0.83,
	"content": "<p>Breaking complex problems into manageable sub-problems or system components.</p>",
	"datasets": [
	{
	"name": "Programming assignments scored by decomposition quality rubrics",
	"link": "https://sites.udel.edu/ctal/project-based-learning/computational-thinking-rubric/"
	}
	],
	"children": [
	{
	"id": "problem_breaking",
	"name": "Problem Breaking Tasks",
	"score": 0.8,
	"content": "<p>Identifying constituent elements of a problem and formulating subgoals.</p>",
	"datasets": [
	{
	"name": "Code-trace decomposition questions",
	"link": "#"
	}
	]
	},
	{
	"id": "system_analysis",
	"name": "System Analysis Tasks",
	"score": 0.85,
	"content": "<p>Modeling and analyzing interactions within system components.</p>",
	"datasets": [
	{
	"name": "Systems modeling labs with rubric-referenced evaluation",
	"link": "https://ieeexplore.ieee.org/document/10837599/"
	}
	]
	}
	]
	},
	{
	"id": "pattern_recognition_tasks",
	"name": "2.2 Pattern Recognition Tasks",
	"score": 0.82,
	"content": "<p>Identifying meaningful patterns, sequences, or structures in data.</p>",
	"datasets": [
	{
	"name": "Sequence prediction benchmarks (e.g., BerCal CT challenges)",
	"link": "https://sainshumanika.utm.my/index.php/sainshumanika/article/view/1987"
	}
	],
	"children": [
	{
	"id": "sequential_pattern",
	"name": "Sequential Pattern Tasks",
	"score": 0.8,
	"content": "<p>Detecting chronological or ordered patterns.</p>",
	"datasets": [
	{
	"name": "Algorithmic sequence detection quizzes",
	"link": "#"
	}
	]
	},
	{
	"id": "structural_pattern",
	"name": "Structural Pattern Tasks",
	"score": 0.84,
	"content": "<p>Recognizing spatial or relational structures.</p>",
	"datasets": [
	{
	"name": "Graph-pattern matching exercises",
	"link": "#"
	}
	]
	}
	]
	},
	{
	"id": "abstraction_tasks",
	"name": "2.3 Abstraction Tasks",
	"score": 0.86,
	"content": "<p>Formulating high-level representations, generalizing from specifics.</p>",
	"datasets": [
	{
	"name": "Abstraction matrix tasks in CT rubrics",
	"link": "https://sites.udel.edu/ctal/project-based-learning/computational-thinking-rubric/"
	}
	],
	"children": [
	{
	"id": "conceptual_abstraction",
	"name": "Conceptual Abstraction",
	"score": 0.88,
	"content": "<p>Extracting core concepts from complex details.</p>",
	"datasets": [
	{
	"name": "Model-building assessments",
	"link": "#"
	}
	]
	},
	{
	"id": "procedural_abstraction",
	"name": "Procedural Abstraction",
	"score": 0.84,
	"content": "<p>Encapsulating repeated procedures or operations.</p>",
	"datasets": [
	{
	"name": "Function design tasks in coding rubrics",
	"link": "https://sites.udel.edu/ctal/project-based-learning/computational-thinking-rubric/"
	}
	]
	}
	]
	},
	{
	"id": "algorithmic_thinking_tasks",
	"name": "2.4 Algorithmic Thinking Tasks",
	"score": 0.87,
	"content": "<p>Designing and analyzing step-by-step procedures to solve problems.</p>",
	"datasets": [
	{
	"name": "Algorithm design and analysis labs with scoring rubrics",
	"link": "https://sites.udel.edu/ctal/project-based-learning/computational-thinking-rubric/"
	}
	],
	"children": [
	{
	"id": "algorithm_design",
	"name": "Algorithm Design Tasks",
	"score": 0.88,
	"content": "<p>Crafting correct, efficient algorithms for specified problems.</p>",
	"datasets": [
	{
	"name": "Pseudocode/rubric-scored assignments",
	"link": "#"
	}
	]
	},
	{
	"id": "algorithm_analysis",
	"name": "Algorithm Analysis Tasks",
	"score": 0.86,
	"content": "<p>Reasoning about algorithm correctness and complexity.</p>",
	"datasets": [
	{
	"name": "Big-O analysis problems",
	"link": "https://www.bigocheatsheet.com/"
	}
	]
	}
	]
	}
	]
	},
	{
	"id": "level3",
	"name": "1.3 Level 3: Chain-of-Thought Reasoning",
	"score": null,
	"content": "<p>This level addresses datasets specifically designed to evaluate explicit, step-by-step reasoning processes, an area that has evolved rapidly with the advent of Large Language Models (LLMs).</p>",
	"children": [
	{
	"id": "sequential_reasoning_tasks",
	"name": "3.1 Sequential Reasoning Tasks",
	"score": 0.89,
	"content": "<p>Evaluating reasoning as a linear or branching sequence of inferences.</p>",
	"datasets": [
	{
	"name": "Chain-of-Thought benchmarks such as GSM8K-Verification",
	"link": "https://www.emergentmind.com/topics/gsm8k-verification"
	}
	],
	"children": [
	{
	"id": "linear_cot",
	"name": "Linear Chain-of-Thought",
	"score": 0.88,
	"content": "<p>Single-threaded deduction from premises to conclusion.</p>",
	"datasets": [
	{
	"name": "Linear CoT challenges (GSM8K)",
	"link": "https://github.com/openai/grade-school-math"
	}
	]
	},
	{
	"id": "branching_cot",
	"name": "Branching Chain-of-Thought",
	"score": 0.9,
	"content": "<p>Exploring alternative inference paths before selecting final outcome.</p>",
	"datasets": [
	{
	"name": "Multi-path logic puzzles scored on path coverage",
	"link": "#"
	}
	]
	},
	{
	"id": "iterative_cot",
	"name": "Iterative Chain-of-Thought",
	"score": 0.89,
	"content": "<p>Refining reasoning through successive revisions of partial solutions.</p>",
	"datasets": [
	{
	"name": "Self-reflective CoT evaluation protocols",
	"link": "https://www.emergentmind.com/topics/gsm8k-verification"
	}
	]
	}
	]
	},
	{
	"id": "multimodal_reasoning_integration",
	"name": "3.2 Multi-Modal Reasoning Integration",
	"score": 0.85,
	"content": "<p>Combining visual, embodied, and linguistic reasoning modes.</p>",
	"datasets": [
	{
	"name": "Vision-language CoT tasks; embodied simulation benchmarks",
	"link": "https://arxiv.org/abs/2305.05308"
	}
	],
	"children": [
	{
	"id": "visual_cot",
	"name": "Visual Chain-of-Thought",
	"score": 0.86,
	"content": "<p>Integrating visual interpretations into step-by-step reasoning.</p>",
	"datasets": [
	{
	"name": "Visual-CoT datasets (e.g., MME-CoT)",
	"link": "https://arxiv.org/abs/2405.14341"
	}
	]
	},
	{
	"id": "embodied_cot",
	"name": "Embodied Chain-of-Thought",
	"score": 0.84,
	"content": "<p>Simulating physical interactions in reasoning chains.</p>",
	"datasets": [
	{
	"name": "Robotics CoT tasks",
	"link": "#"
	}
	]
	}
	]
	},
	{
	"id": "meta_reasoning_tasks",
	"name": "3.3 Meta-Reasoning Tasks",
	"score": 0.87,
	"content": "<p>Monitoring and controlling one’s own chain-of-thought processes.</p>",
	"datasets": [
	{
	"name": "Meta-Reasoning protocols with feeling-of-rightness ratings",
	"link": "https://dacemirror.sci-hub.se/journal-article/c2286260f7ebbc44e1d06675e66fc87d/ackerman2017.pdf"
	}
	],
	"children": [
	{
	"id": "strategy_selection",
	"name": "Strategy Selection Tasks",
	"score": 0.88,
	"content": "<p>Choosing among alternative reasoning strategies based on task demands.</p>",
	"datasets": [
	{
	"name": "Strategy-selection experiments with process tracing",
	"link": "#"
	}
	]
	},
	{
	"id": "process_monitoring",
	"name": "Process Monitoring Tasks",
	"score": 0.86,
	"content": "<p>Tracking intermediate confidence and detecting errors.</p>",
	"datasets": [
	{
	"name": "Feeling-of-error paradigms",
	"link": "https://dacemirror.sci-hub.se/journal-article/c2286260f7ebbc44e1d06675e66fc87d/ackerman2017.pdf"
	}
	]
	}
	]
	}
	]
	},
	{
	"id": "level4",
	"name": "1.4 Level 4: Domain-Specific Reasoning",
	"score": null,
	"content": "<p>This level addresses reasoning that relies on specialized knowledge and principles from distinct academic or professional domains. Datasets test not only logical processes but also the correct application of domain-specific content.</p>",
	"children": [
	{
	"id": "mathematical_reasoning",
	"name": "4.1 Mathematical Reasoning",
	"score": 0.92,
	"content": "<p>Applying numerical, algebraic, and geometric principles in proofs and problem-solving.</p>",
	"datasets": [
	{
	"name": "Math CoT benchmarks (GSM8K-Verification); standardized math tests (TIMSS)",
	"link": "https://www.emergentmind.com/topics/gsm8k-verification"
	}
	],
	"children": [
	{
	"id": "arithmetic_reasoning",
	"name": "Arithmetic Reasoning",
	"score": 0.9,
	"content": "<p>Multi-step numerical calculations and unit reasoning.</p>",
	"datasets": [
	{
	"name": "GSM8K arithmetic problems",
	"link": "https://github.com/openai/grade-school-math"
	}
	]
	},
	{
	"id": "algebraic_reasoning",
	"name": "Algebraic Reasoning",
	"score": 0.92,
	"content": "<p>Symbolic manipulation and equation solving.</p>",
	"datasets": [
	{
	"name": "Algebraic proof rubrics",
	"link": "#"
	}
	]
	},
	{
	"id": "geometric_reasoning",
	"name": "Geometric Reasoning",
	"score": 0.95,
	"content": "<p>Spatial deduction, proof construction.</p>",
	"datasets": [
	{
	"name": "Geometry proof assessments",
	"link": "#"
	}
	]
	}
	]
	},
	{
	"id": "scientific_reasoning",
	"name": "4.2 Scientific Reasoning",
	"score": 0.89,
	"content": "<p>Designing experiments, analyzing data, inferring causality.</p>",
	"datasets": [
	{
	"name": "Experimental design tasks; PISA science frameworks",
	"link": "https://www.oecd.org/pisa/pisaproducts/pisa-2025-science-framework.pdf"
	}
	],
	"children": [
	{
	"id": "experimental_design",
	"name": "Experimental Design Reasoning",
	"score": 0.88,
	"content": "<p>Formulating hypotheses, controls, and valid protocols.</p>",
	"datasets": [
	{
	"name": "Science inquiry rubrics",
	"link": "#"
	}
	]
	},
	{
	"id": "data_analysis",
	"name": "Data Analysis Reasoning",
	"score": 0.9,
	"content": "<p>Interpreting charts, statistical inference.</p>",
	"datasets": [
	{
	"name": "Data-analysis problem sets",
	"link": "#"
	}
	]
	}
	]
	},
	{
	"id": "logical_formal_reasoning",
	"name": "4.3 Logical and Formal Reasoning",
	"score": 0.85,
	"content": "<p>Applying formal symbolic logic and proof systems.</p>",
	"datasets": [
	{
	"name": "Propositional/predicate logic exams",
	"link": "#"
	}
	],
	"children": [
	{
	"id": "propositional_logic",
	"name": "Propositional Logic Tasks",
	"score": 0.84,
	"content": "<p>Truth-table analysis, logical equivalences.</p>",
	"datasets": [
	{
	"name": "Logic course assessments",
	"link": "#"
	}
	]
	},
	{
	"id": "predicate_logic",
	"name": "Predicate Logic Tasks",
	"score": 0.86,
	"content": "<p>Quantifier manipulation, formal derivations.</p>",
	"datasets": [
	{
	"name": "Predicate calculus assignments",
	"link": "#"
	}
	]
	}
	]
	},
	{
	"id": "commonsense_reasoning",
	"name": "4.4 Commonsense Reasoning",
	"score": 0.8,
	"content": "<p>Everyday causal and situational inference.</p>",
	"datasets": [
	{
	"name": "Winograd Schema Challenge",
	"link": "https://winogrande.allenai.org/"
	}
	],
	"children": [
	{
	"id": "everyday_reasoning",
	"name": "Everyday Reasoning Tasks",
	"score": 0.78,
	"content": "<p>Inferences about routine causal chains.</p>",
	"datasets": [
	{
	"name": "Commonsense QA datasets",
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