Include your existing worksheet containing subject material and fill-in questions. Registered instructors can make changes to the model , monitor student’s in class progress and assess student submissions - worksheet responses and model changes.

Computational thinking, like critical thinking, is necessary across all subjects, not just STEM courses. Key concepts as decomposition, data abstraction, pattern recognition are subtly included in each exercise. The focus of the lesson remains the subject material, with the discussion and study embellished by the computational thinking model. Students go beyond just using the model - they analyze its steps and algorithm, while making marginal changes.

Interactive, thought-provoking exercises help maintain student interest and encourage further study. Students interact directly with the exercise through worksheet questions and model modification in an environment comfortable to them.

The CTforAll website provides videos on the use of the platform and walk-through of sample exercises. Registered instructors can send exercise material and or request a chat (limited availability) before the class to review the proposed approach.

The AI exercises show the student the algorithmic concepts used by AI tools to provide results. These algorithms include Neural Networks and Convolution for image recognition, large language models for generative text tools like ChatGPT, and statistical models for machine learning. All exercises focus on how the AI model is trained and or used to provide a probabilistic result. The exercises do not teach how or when to use existing AI tools but rather show the key underlying foundations of the AI tool. This understanding enables the student to see the potential benefits of various AI strategies and also recognizing the drawbacks. Publicly available training sets and open source software (TensorFlow) provide the AI power in these exercises. In some instances, the training data can be directly within the AI dataset. For example, hidden layers of the neural network can be changed directly by the student, along with Large Language Model databanks. These AI knowledge bases are very small comparable to industry tools, but do demonstrate the type of data maintained in popular AI software.

The Social Studies exercises extend the study of people and places to encourage the student to think more deeply and be more curious about these subjects. What was the daily schedule of Elizabeth Eckford in Little Rock, what type of bus route was Rosa Parks using, and what conclusions can be reached through analyzing social data patterns. This platform provides an interactive process of students developing possible answers to these questions based on their own vision and analysis. Students create products and ponder the subject much more broadly. The teacher’s existing worksheets (including their embedded questions) can be part of the exercise to be completed by the student. Each exercise is unique, but emanates from a few basic templates that can be used to develop other lesson activities during the year.

Animation of physical relationships, displaying data patterns and performing advanced statistical analysis are all components of exercises in the Science subject area. Students can alter animated orbits, change carbon decay rate factors, alter population mutation patterns, and code physics equations directly. The exercises clearly show the formulas and equations used in science problems and allow the student to modify parameters, inputs and key variables. Instructors can use their existing worksheets, and associate their lesson with a pseudo code model that animates the concepts. Students continue the lesson by changing key factors of the model to notice the impact of the modification. Visual verification of scientific concepts as well as simulation model results bring an exciting perspective to the topics.

This set of exercises can be used throughout a Computer Principles course. The exercises provide animations for common algorithms, which are widely available. However, CTforAll goes well beyond running animated algorithms. Students are enabled to make alterations to the algorithm, watch variables change during execution progress, and correct planned deficiencies in the provided algorithm. Topics include sorting algorithms, performing recursion, transcription, compression, the binary numbering system, and data structures. Several examples of these exercises can be viewed in the link below. CTforAll provides an excellent blend of algorithm study with coding for students in the Computer Principles course.

The Math set of exercises enable students to study plotting algorithms, application of common financial formulas and the invoking of trigonometric functions. Several exercises have a game / quiz approach where equations or coordinates are displayed, and the student must provide possible coefficients and quadrants. The visualization is highly interactive and enhances student perception and enjoyment learning about the mathematical concept. Instructors can make small modifications to the exercises for additional challenges. The graph-based exercises focus the student's attention on key elements of the system including intercepts, scales and axis ranges. Results of formulas are also represented with bar graphs or pie charts.

Fine art includes music, art generation, and exercises about famous artists – painters, dancers. The related models can generate the art and then allow the student to alter the model and create new artwork. Subjects include painter styles, gradient generation, and music compositions. Additionally famous artists can be profiled and simulations of their work included in the model. The CTforAll approach blends the creativity of the art and music world, with the rigid yet versatile world of technology. Students can change the model’s art generation steps, not just feed some input parameters to a static software tool.

Text analysis by technology has been growing steadily, especially with the advent of AI. The Language Arts exercises enable students to see how this technology can help do Language Arts tasks (e.g. motif analysis, alternative ending generation) and understand the logic behind the technology. Students can use this technology to generate their own random story or make an interactive map that pop-up information boxes at key milestone locations. The exercise demonstrates how the computer can read a whole play and delineate key patterns of conversation or word usage. The exercises offer an opportunity to study literature in a unique and technological based manner.

The CTforAll platform supports a number of common games for the students to study and enhance. Each game is ready to be played but also contains a set of possible enhancements or additional features for the students to include. For example, the chess game does highlight all allowable squares to move for a piece, however (by design),it does not include verifying if the king is in check, the casting maneuver, or En Passant rules. The student can study the architecture of the game and make these improvements. These exercises enable the student to learn about state management where an abstraction of the board is in data structure and then rendering to the screen. Some games have extensive event handling capabilities, non-trivial scoring rules and can be enhanced to incorporate advanced algorithms such as backtracking.