diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md
new file mode 100644
index 0000000..20209ad
--- /dev/null
+++ b/.github/CONTRIBUTING.md
@@ -0,0 +1,11 @@
+# Contributing Guidelines
+
+Thank you for your interest in contributing!
+
+- All pull requests **must** be opened against the `dev` branch.
+- Ensure your code passes all test workflows:
+    - `mypy` (type checking)
+    - `flake8` (linting)
+    - Unit tests
+
+Pull requests that meet these requirements will be considered for merging.
\ No newline at end of file
diff --git a/.readthedocs.yml b/.readthedocs.yml
new file mode 100644
index 0000000..d786e48
--- /dev/null
+++ b/.readthedocs.yml
@@ -0,0 +1,22 @@
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Set the OS, Python version, and other tools you might need
+build:
+  os: ubuntu-24.04
+  tools:
+    python: "3.13"
+
+# Build documentation in the "docs/" directory with Sphinx
+sphinx:
+   configuration: docs/source/conf.py
+
+python:
+    install:
+    - method: pip
+      path: .
+    - requirements: docs/requirements.txt
+        
\ No newline at end of file
diff --git a/BREAKING_CHANGES.md b/BREAKING_CHANGES.md
deleted file mode 100644
index 42e9f3c..0000000
--- a/BREAKING_CHANGES.md
+++ /dev/null
@@ -1,65 +0,0 @@
-# Breaking Changes in `adaptivetesting`
-
-This document highlights breaking changes and updates in the `adaptivetesting` package, considering its structure, features, and potential impacts on users transitioning between versions.
-
-## 1. Python Version Requirement
-- **Updated Requirement**: Python version `>= 3.11` is now required. Users on Python 3.10 or earlier may experience compatibility issues.
-
-## 2. Package Structure
-- The package is organized into several key modules:
-  - **`adaptivetesting.models`**: Core classes including `AdaptiveTest`, `ItemPool`, and `TestItem`.
-  - **`adaptivetesting.implementations`**: Ready-to-use test implementations like `TestAssembler`.
-  - **`adaptivetesting.math`**: Mathematical functions for IRT, ability estimation, and item selection.
-  - **`adaptivetesting.simulation`**: Simulation framework and result management.
-  - **`adaptivetesting.data`**: Data management utilities for CSV and pickle formats.
-  - **`adaptivetesting.services`**: Abstract interfaces and protocols.
-
-## 3. Key Features
-- **Bayesian Methods**: Built-in support for Bayesian ability estimation with customizable priors.
-- **Flexible Architecture**: Object-oriented design with abstract classes for easy extension.
-- **Item Response Theory**: Full support for 1PL, 2PL, 3PL, and 4PL models.
-- **Multiple Estimators**: 
-  - Maximum Likelihood Estimation (MLE)
-  - Bayesian Modal Estimation (BM)
-  - Expected A Posteriori (EAP)
-- **Item Selection Strategies**: Maximum information criterion and Urry's rule.
-- **Simulation Framework**: Comprehensive tools for CAT simulation and evaluation.
-- **Real-world Application**: Direct transition from simulation to production testing.
-- **Stopping Criteria**: Support for standard error and test length criteria.
-- **Data Management**: Built-in support for CSV and pickle data formats.
-
-## 4. Installation Instructions
-- Install from PyPI using pip:
-  ```bash
-  pip install adaptivetesting
-  ```
-- For the latest development version:
-  ```bash
-  pip install git+https://github.com/condecon/adaptivetesting
-  ```
-
-## 5. Requirements
-- The following dependencies are required:
-  - Python >= 3.11
-  - NumPy >= 2.0.0
-  - Pandas >= 2.2.0
-  - SciPy >= 1.15.0
-  - tqdm >= 4.67.1
-
-## 6. Documentation Updates
-- Full documentation is available in the `docs/` directory:
-  - [API Reference](docs/readme.md)
-  - [Models Module](docs/adaptivetesting.models.md)
-  - [Math Module](docs/adaptivetesting.math.md)
-  - [Implementation Examples](docs/adaptivetesting.implementations.md)
-  - [Simulation Guide](docs/adaptivetesting.simulation.md)
-
-## 7. Testing
-- Comprehensive tests are included. Run them using:
-  ```bash
-  python -m pytest adaptivetesting/tests/
-  ```
-
----
-
-**Action Required**: Users should review these changes and update their environments and workflows accordingly.
diff --git a/CHANGELOG.md b/CHANGELOG.md
new file mode 100644
index 0000000..5c977e3
--- /dev/null
+++ b/CHANGELOG.md
@@ -0,0 +1,4 @@
+# Version 1.1.2
+
+- The `ItemPool` class now correctly honors the `id` field of items. (#30, #31)
+- Examples and the readme file have been updated accordingly.
\ No newline at end of file
diff --git a/README.md b/README.md
index 8b3bffa..85d3f51 100644
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@
 - **Bayesian Methods**: Built-in support for Bayesian ability estimation with customizable priors
 - **Flexible Architecture**: Object-oriented design with abstract classes for easy extension
 - **Item Response Theory**: Full support for 1PL, 2PL, 3PL, and 4PL models
-- **Multiple Estimators**: 
+- **Multiple Estimators**:
   - Maximum Likelihood Estimation (MLE)
   - Bayesian Modal Estimation (BM)
   - Expected A Posteriori (EAP)
@@ -113,25 +113,31 @@ adaptive_test = TestAssembler(
 ### Real-world Testing (Non-simulation) with PsychoPy
 
 ```python
+# setup item pool
+# the item pool is retrieved from the PREVIC
+# https://github.com/manuelbohn/previc/tree/main/saves
+import pandas as pd
+from adaptivetesting.models import ItemPool
 from psychopy import visual, event
 from psychopy.hardware import keyboard
 from adaptivetesting.implementations import TestAssembler
 from adaptivetesting.models import AdaptiveTest, ItemPool, TestItem
 from adaptivetesting.data import CSVContext
-from adaptivetesting.math.estimators import BayesModal, CustomPrior
+from adaptivetesting.math.estimators import ExpectedAPosteriori, CustomPrior
 from adaptivetesting.math.item_selection import maximum_information_criterion
 from scipy.stats import t
 import pandas as pd
 
+previc_item_pool = pd.read_csv("item_pool.csv")
+# add item column
+previc_item_pool["id"] = list(range(1, 90))
+previc_item_pool.head()
 
-# Create item pool from DataFrame
-items_data = pd.DataFrame({
-    "a": [1.32, 1.07, 0.84, 1.19, 0.95],  # discrimination
-    "b": [-0.63, 0.18, -0.84, 0.41, -0.25],  # difficulty
-    "c": [0.17, 0.10, 0.19, 0.15, 0.12],  # guessing
-    "d": [0.87, 0.93, 1.0, 0.89, 0.94]   # upper asymptote
-})
-item_pool = ItemPool.load_from_dataframe(items_data)
+
+item_pool = ItemPool.load_from_list(
+    b=previc_item_pool["Difficulty"],
+    ids=previc_item_pool["id"]
+)
 
 # Create adaptive test
 adaptive_test: AdaptiveTest = TestAssembler(
@@ -161,12 +167,12 @@ win = visual.Window([800, 600],
 # init keyboard
 keyboard.Keyboard()
 
+## FIX THIS
 
 # define function to get user input
 def get_response(item: TestItem) -> int:
-    # get index
-    item_difficulty: float = item.b
-    stimuli: str = [item for item in item_pool.test_items if item["Difficulty"] == item_difficulty][0]["word"]
+    # select corresponding word from item pool data frame
+    stimuli: str = previc_item_pool[previc_item_pool["id"] == item.id]["word"].values[0]
 
     # create text box and display stimulus
     text_box = visual.TextBox2(win=win,
@@ -301,7 +307,8 @@ Full documentation is available in the `docs/` directory:
 The package includes comprehensive tests. Run them using:
 
 ```bash
-python -m pytest adaptivetesting/tests/
+uv sync
+uv run python -m unittest
 ```
 
 ## Contributing
@@ -309,7 +316,7 @@ python -m pytest adaptivetesting/tests/
 We welcome contributions! Please see our [GitHub repository](https://github.com/condecon/adaptivetesting) for:
 
 - Issue tracking
-- Feature requests  
+- Feature requests
 - Pull request guidelines
 - Development setup
 
diff --git a/adaptivetesting/models/__item_pool.py b/adaptivetesting/models/__item_pool.py
index b747160..661ca7c 100644
--- a/adaptivetesting/models/__item_pool.py
+++ b/adaptivetesting/models/__item_pool.py
@@ -37,7 +37,7 @@ def get_item_by_index(self, index: int) -> Tuple[TestItem, int] | TestItem:
             return selected_item, simulated_response
         else:
             return selected_item
-    
+
     def get_item_by_item(self, item: TestItem) -> Tuple[TestItem, int] | TestItem:
         """Returns item and if defined the simulated response.
 
@@ -94,24 +94,27 @@ def load_from_list(
             a: List[float] | None = None,
             c: List[float] | None = None,
             d: List[float] | None = None,
-            simulated_responses: List[int] | None = None) -> "ItemPool":
+            simulated_responses: List[int] | None = None,
+            ids: List[int] | None = None) -> "ItemPool":
         """
         Creates test items from a list of floats.
 
         Args:
             a (List[float]): discrimination parameter
-            
+
             b (List[float]): difficulty parameter
-            
+
             c (List[float]): guessing parameter
-            
+
             d (List[float]): slipping parameter
-            
+
             simulated_responses (List[int]): simulated responses
 
+            ids (List[int]): item IDs
+
         Returns:
             List[TestItem]: item pool
-        
+
         """
         items: List[TestItem] = []
 
@@ -126,19 +129,25 @@ def load_from_list(
                 raise ValueError("Length of a and b has to be the same.")
             for i, discrimination in enumerate(a):
                 items[i].a = discrimination
-        
+
         if c is not None:
             if len(c) != len(b):
                 raise ValueError("Length of c and b has to be the same.")
             for i, guessing in enumerate(c):
                 items[i].c = guessing
-        
+
         if d is not None:
             if len(d) != len(b):
                 raise ValueError("Length of d and b has to be the same.")
             for i, slipping in enumerate(d):
                 items[i].d = slipping
 
+        if ids is not None:
+            if len(ids) != len(b):
+                raise ValueError("Length of ids and b has to be the same.")
+            for i, id_ in enumerate(ids):
+                items[i].id = id_
+
         item_pool = ItemPool(items)
         item_pool.simulated_responses = simulated_responses
 
@@ -146,10 +155,11 @@ def load_from_list(
 
     @staticmethod
     def load_from_dict(source: dict[str, List[float]],
-                       simulated_responses: List[int] | None = None) -> "ItemPool":
+                       simulated_responses: List[int] | None = None,
+                       ids: List[int] | None = None) -> "ItemPool":
         """Creates test items from a dictionary.
         The dictionary has to have the following keys:
-            
+
             - a
             - b
             - c
@@ -158,6 +168,8 @@ def load_from_dict(source: dict[str, List[float]],
 
         Args:
             source (dict[str, List[float]]): item pool dictionary
+            simulated_responses (List[int]): simulated responses
+            ids (List[int]): item IDs
 
         Returns:
             List[TestItem]: item pool
@@ -170,13 +182,13 @@ def load_from_dict(source: dict[str, List[float]],
         # check none
         if a is None:
             raise ValueError("a cannot be None")
-        
+
         if b is None:
             raise ValueError("b cannot be None")
-        
+
         if c is None:
             raise ValueError("c cannot be None")
-        
+
         if d is None:
             raise ValueError("d cannot be None")
 
@@ -184,6 +196,10 @@ def load_from_dict(source: dict[str, List[float]],
         if not (len(a) == len(b) == len(c) == len(d)):
             raise ValueError("All lists in the source dictionary must have the same length")
 
+        if ids is not None:
+            if len(ids) != len(b):
+                raise ValueError("Length of ids and b has to be the same.")
+
         n_items = len(b)
         items: List[TestItem] = []
         for i in range(n_items):
@@ -193,12 +209,15 @@ def load_from_dict(source: dict[str, List[float]],
             item.c = c[i]
             item.d = d[i]
 
+            if ids is not None:
+                item.id = ids[i]
+
             items.append(item)
 
         item_pool = ItemPool(items, simulated_responses)
-        
+
         return item_pool
-    
+
     @staticmethod
     def load_from_dataframe(source: DataFrame) -> "ItemPool":
         """Creates item pool from a pandas DataFrame.
@@ -206,7 +225,7 @@ def load_from_dataframe(source: DataFrame) -> "ItemPool":
         Each column has to contain float values.
         A `simulated_responses` (int values) column can be added to
         the DataFrame to provide simulated responses.
-        
+
 
         Args:
             source (DataFrame): _description_
@@ -218,28 +237,33 @@ def load_from_dataframe(source: DataFrame) -> "ItemPool":
         # check if columns are present
         if "a" not in source.columns:
             raise ValueError("Column 'a' not found.")
-        
+
         if "b" not in source.columns:
             raise ValueError("Column 'b' not found.")
-        
+
         if "c" not in source.columns:
             raise ValueError("Column 'c' not found.")
-        
+
         if "d" not in source.columns:
             raise ValueError("Column 'd' not found.")
-        
+
         # get values
         a: List[float] = source["a"].values.tolist() # type: ignore
         b: List[float] = source["b"].values.tolist() # type: ignore
         c: List[float] = source["c"].values.tolist() # type: ignore
         d: List[float] = source["d"].values.tolist() # type: ignore
 
+        if "ids" in source.columns:
+            ids: List[int] | None = source["ids"].values.tolist() # type: ignore
+        else:
+            ids = None
+
         # create item pool
-        item_pool = ItemPool.load_from_list(a=a, b=b, c=c, d=d)
-    
+        item_pool = ItemPool.load_from_list(a=a, b=b, c=c, d=d, ids=ids)
+
         # check if simulated responses are present
         if "simulated_responses" in source.columns:
             simulated_responses: List[int] = source["simulated_responses"].values.tolist() # type: ignore
             item_pool.simulated_responses = simulated_responses
-        
+
         return item_pool
diff --git a/adaptivetesting/models/__test_item.py b/adaptivetesting/models/__test_item.py
index c4bad75..7203208 100644
--- a/adaptivetesting/models/__test_item.py
+++ b/adaptivetesting/models/__test_item.py
@@ -4,10 +4,11 @@ def __init__(self):
         The format is equal to the implementation in catR.
 
         Properties:
-            - a (float):
-            - b (float): difficulty
-            - c (float):
-            - d (float):
+            - id (int | None): item ID
+            - a (float): discrimination parameter
+            - b (float): difficulty parameter
+            - c (float): guessing parameter
+            - d (float): slipping parameter / upper asymptote
 
         """
         self.id: int | None = None
@@ -15,11 +16,18 @@ def __init__(self):
         self.b: float = float("nan")
         self.c: float = 0
         self.d: float = 1
-    
-    def as_dict(self) -> dict[str, float]:
-        return {
+
+    def as_dict(self, with_id: bool = False) -> dict[str, float | int | None]:
+        """Returns the item as a dictionary"""
+
+        item_dict: dict[str, float | int | None] = {
             "a": self.a,
             "b": self.b,
             "c": self.c,
             "d": self.d
         }
+
+        if with_id and self.id is not None:
+            item_dict["id"] = self.id
+
+        return item_dict
diff --git a/adaptivetesting/tests/test_load_test_items.py b/adaptivetesting/tests/test_load_test_items.py
index 46423ea..91c8fa2 100644
--- a/adaptivetesting/tests/test_load_test_items.py
+++ b/adaptivetesting/tests/test_load_test_items.py
@@ -15,6 +15,18 @@ def __init__(self, methodName="runTest"):
         self.item2.a = 1.9
         self.item2.b = 3
         self.item2.c = 1.9
+
+        self.item1_with_id = TestItem()
+        self.item1_with_id.a = self.item1.a
+        self.item1_with_id.b = self.item1.b
+        self.item1_with_id.c = self.item1.c
+        self.item1_with_id.id = 1
+
+        self.item2_with_id = TestItem()
+        self.item2_with_id.a = self.item2.a
+        self.item2_with_id.b = self.item2.b
+        self.item2_with_id.c = self.item2.c
+        self.item2_with_id.id = 42
 # List
 
 # Dict
@@ -30,6 +42,20 @@ def test_load_test_items_from_dict_success(self):
 
         self.assertEqual([self.item1.as_dict(), self.item2.as_dict()], [i.as_dict() for i in generated.test_items])
 
+    def test_load_test_items_from_dict_with_id_success(self):
+        source_dictionary: dict[str, list[float]] = {
+            "a": [0.9, 1.9],
+            "b": [5, 3],
+            "c": [0.9, 1.9],
+            "d": [1, 1],
+            "id": [1, 42]
+        }
+
+        generated = ItemPool.load_from_dict(source_dictionary)
+
+        self.assertEqual([self.item1_with_id.as_dict(), self.item2_with_id.as_dict()], [i.as_dict()
+                         for i in generated.test_items])
+
     def test_load_test_items_from_dict_error_none(self):
         source_dictionary: dict[str, list[float]] = {
             "a": [0.9, 1.9],
@@ -86,7 +112,45 @@ def test_load_items_from_pandas_success(self):
         )
 
         self.assertEqual([1, 0], generated.simulated_responses)
-        
+
+    def test_load_items_from_pandas_with_ids_success(self):
+        dictionary = {
+            "a": [0.9, 1.9],
+            "b": [5, 3],
+            "c": [0.9, 1.9],
+            "d": [1, 1],
+            "simulated_responses": [1, 0],
+            "ids": [101, 202]
+        }
+        df = pd.DataFrame(dictionary)
+
+        generated = ItemPool.load_from_dataframe(df)
+
+        # check that items are equal
+        self.assertEqual(
+            {
+                "a": 0.9,
+                "b": 5,
+                "c": 0.9,
+                "d": 1,
+                "id": 101
+            },
+            generated.test_items[0].as_dict(with_id=True)
+        )
+
+        self.assertEqual(
+            {
+                "a": 1.9,
+                "b": 3,
+                "c": 1.9,
+                "d": 1,
+                "id": 202
+            },
+            generated.test_items[1].as_dict(with_id=True)
+        )
+
+        self.assertEqual([1, 0], generated.simulated_responses)
+
     def test_load_items_pandas_error_missing_column(self):
         dictionary = {
             "a": [0.9, 1.9],
diff --git a/adaptivetesting/tests/test_test_assembler.py b/adaptivetesting/tests/test_test_assembler.py
index a3bbbe9..4a09d7e 100644
--- a/adaptivetesting/tests/test_test_assembler.py
+++ b/adaptivetesting/tests/test_test_assembler.py
@@ -11,7 +11,7 @@ class DummyTestItem(TestItem):
     def __init__(self, id=0):
         self.id = id
     
-    def as_dict(self):
+    def as_dict(self, with_id: bool = True) -> dict[str, float | int | None]:
         return {"id": self.id}
 
 
diff --git a/docs/requirements.txt b/docs/requirements.txt
new file mode 100644
index 0000000..b6bfecd
Binary files /dev/null and b/docs/requirements.txt differ
diff --git a/docs/source/conf.py b/docs/source/conf.py
index bec2a45..e054868 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -29,7 +29,7 @@
 # -- Options for HTML output -------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
 
-# html_theme = 'sphinx_rtd_theme'
+html_theme = 'sphinx_book_theme'
 html_static_path = ['_static']
 html_css_files = [
     'main.css',
@@ -37,11 +37,13 @@
 html_logo = "_static/logo.svg"
 html_theme_options = {
     "navigation_depth": -1,
-    "display_version": True,
-    "logo_only": True,
+    "repository_url": "https://github.com/condecon/adaptivetesting",
+    "use_issues_button": True
 
 }
 
 
+
+
 def setup(app: Sphinx):
     app.add_css_file("main.css")
diff --git a/examples/testing.py b/examples/testing.py
index 8b5cf40..0bca296 100644
--- a/examples/testing.py
+++ b/examples/testing.py
@@ -1,12 +1,17 @@
 # flake8: noqa
 # setup item pool
+# the item pool is retrieved from the PREVIC
+# https://github.com/manuelbohn/previc/tree/main/saves
 import pandas as pd
 previc_item_pool = pd.read_csv("item_pool.csv")
+# add item column
+previc_item_pool["id"] = list(range(1, 90))
 previc_item_pool.head()
 
 from adaptivetesting.models import ItemPool
 item_pool = ItemPool.load_from_list(
-    b=previc_item_pool["Difficulty"]
+    b=previc_item_pool["Difficulty"],
+    ids=previc_item_pool["id"]
 )
 
 # import psychopy
@@ -51,10 +56,8 @@
 
 # define function to get user input
 def get_response(item: TestItem) -> int:
-    # get index
-    item_difficulty: float = item.b
     # select corresponding word from item pool data frame
-    stimuli: str = previc_item_pool.loc[previc_item_pool["Difficulty"] == item_difficulty, "word"].values[0]
+    stimuli: str = previc_item_pool[previc_item_pool["id"] == item.id]["word"].values[0]
 
     # create text box and display stimulus
     text_box = visual.TextBox2(win=win,
diff --git a/pyproject.toml b/pyproject.toml
index 35518b5..3c9e91a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,16 +1,11 @@
 [project]
 name="adaptivetesting"
 version="1.1.1"
-author="Jonas Engicht"
-author_email="jonas.engicht@uni-jena.de"
 description="adaptivetesting is a Python package that can be used to simulate and evaluate custom CAT scenarios as well as implement them in real-world testing scenarios from a single codebase"
 readme = "README.md"
 authors = [
     { name = "Jonas Engicht", email = "dev@condecon.de" }
 ]
-maintainters = [
-    { name = "Jonas Engicht", email = "dev@condecon.de" }
-]
 requires-python = ">=3.10"
 dependencies = [
     "numpy>=2.0.0",
@@ -33,9 +28,13 @@ dev = [
     "pandas-stubs>=2.2.3.250308",
     "scipy-stubs>=1.15.2.2",
     "snakeviz>=2.2.2",
+    "types-tqdm>=4.67.0.20250516",
+]
+# required to build documentation
+docs = [
     "sphinx>=8.1.3",
+    "sphinx-book-theme>=1.1.3",
     "sphinx-markdown-builder>=0.6.8",
-    "types-tqdm>=4.67.0.20250516",
 ]
 plot = [
     "matplotlib>=3.10.5",
diff --git a/requirements.txt b/requirements.txt
index 4a28fa6..70e075f 100644
Binary files a/requirements.txt and b/requirements.txt differ
diff --git a/uv.lock b/uv.lock
index c3c4a19..2fab80c 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 1
 requires-python = ">=3.10"
 resolution-markers = [
     "python_full_version >= '3.12' and sys_platform == 'darwin'",
@@ -16,9 +16,21 @@ resolution-markers = [
     "python_full_version < '3.11' and sys_platform == 'win32'",
 ]
 
+[[package]]
+name = "accessible-pygments"
+version = "0.0.5"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pygments" },
+]
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