The development of computer systems capable of performing tasks that typically require human intelligence, enabling automated decision-making, learning, and adaptation.

The inappropriate or unethical application of AI technology, leading to harmful consequences or misuse of information.

The process of reviewing and assessing the relevance, accuracy, and quality of AI-generated responses to prompts.

The obligation to take responsibility for the effects and outcomes of AI prompts, ensuring ethical and effective use.

Practical, concrete recommendations designed to facilitate the achievement of specific learning or project outcomes.

Designed experiences or tasks that facilitate learning by doing, supporting the application of concepts in practical settings.

The adjustment of AI prompts or teaching strategies in response to changing conditions, feedback, or new insights.

A planning method that begins with identifying end goals, then devises activities and instruction to achieve those outcomes, ensuring alignment with learning objectives.

Proven strategies and techniques that enhance the effectiveness and ethical use of AI prompts in education.

The presence of systemic or individual prejudices in AI prompts, potentially leading to skewed or unfair outcomes.

This technique involves presenting an initial question followed by a sequence of logical reasoning steps that guide the model toward the final answer. It's akin to mapping out a thought process in natural language, breaking down complex problems into more manageable parts, and sequentially addressing each to arrive at a conclusion.

The degree of difficulty or sophistication inherent in learning materials or tasks, challenging learners to think critically and solve problems.

This strategy involves giving the AI model additional background information or context along with the prompt, enhancing its understanding and the relevance of its responses. Contextual prompting is particularly useful for complex or nuanced questions where the model benefits from a broader understanding of the subject matter.

The ongoing process of learning and professional development, especially in rapidly evolving fields like AI.

A technique where the model is asked to consider or compare different outcomes, perspectives, or scenarios within the same prompt. This approach encourages the AI to analyze distinctions and similarities, aiding in tasks that require evaluation, comparison, or decision-making based on contrasting information.

The degree of complexity and nuance in an AI-enabled conversation, facilitated by strategically crafted prompts.

Essential content and concepts that form the foundation of an educational course or module, critical for understanding the subject.

Prompts designed to encourage imaginative and innovative responses from AI, fostering creativity and novel ideas.

Questions designed to stimulate thought, reflection, and dialogue, promoting deeper understanding and exploration of topics.

The systematic recording of project processes, decisions, and outcomes, serving as a reference and learning tool.

Customized prompts that are tailored to elicit information or responses relevant to a particular field or subject matter.

The evaluation of moral principles and social implications in the crafting and implementation of AI prompts.

Strategies and criteria for assessing the performance and impact of AI responses, ensuring alignment with learning and project goals.

Opportunities or suggestions for extending learning beyond the initial content, encouraging further exploration and discovery.

A professional skilled in coordinating and guiding projects to completion, ensuring objectives are met efficiently.

The principle of impartiality and equity in AI interactions, ensuring unbiased and just responses and outcomes.

A method where the AI is provided with a small set of examples or scenarios alongside the prompt. This approach helps the model understand the context or format of the desired response by illustrating how similar problems or questions were answered previously, effectively using these examples as a guide for generating its own responses.

Utilizes prompts that include specific instructions or guidance on how to approach the response, often directing the AI model to use certain reasoning methods, perspectives, or data sources. This method aims to steer the model's response generation process in a way that aligns with the user's expectations or the requirements of the task.

The practice of making AI interactions accessible and relevant to a diverse range of users, respecting different perspectives and needs.

A technique where prompts are presented in a sequence, with each subsequent prompt building on the response to the previous one. This method encourages the model to develop a more comprehensive and detailed understanding or solution over multiple interactions, allowing for a deeper exploration of topics or more complex problem-solving.

A dynamic prompting approach where the interaction between the user and the AI model is bidirectional, allowing for real-time feedback and adjustment of prompts based on the model's responses. This method fosters a conversational and adaptive exchange, enabling more accurate and personalized outcomes.

A single cycle within an iterative process, focusing on gradual improvement of AI prompts or educational content.

A repetitive cycle of planning, executing, and evaluating, allowing for continual refinement and improvement of prompts or projects.

The continuous process of making incremental improvements to prompts or learning content based on feedback and outcomes.

Statements specifying what learners will know or be able to do as a result of an educational activity, measurable and observable.

Involves crafting prompts that instruct the AI model to reflect on or analyze its own thought process, response strategies, or decision-making criteria. This advanced technique can be used to enhance the model's self-awareness and adjust its responses based on an evaluation of its own reasoning or output patterns.

A structured educational unit designed to convey a specific set of information or skills within a larger curriculum.

Interactive prompts that foster a dialogue between the AI and the user, enhancing engagement and depth of response.

The intended knowledge, skill, or competence gained from an educational activity or learning process.

The safeguarding of personal data and information in interactions with AI, ensuring confidentiality and data protection.

Specific criteria and instructions that outline the expectations and requirements for educational projects, guiding successful completion.

A detailed proposal outlining project goals, timelines, resources, and steps needed to complete tasks effectively and efficiently.

A dynamic classroom approach where students actively explore real-world problems through projects, fostering deeper understanding and application of knowledge.

An input given to an AI to initiate a response, serving as a catalyst for generating specific or desired information.

Similar to incremental prompting, prompt chaining involves linking a series of prompts together, where the output of one serves as the input for the next. This method is useful for complex tasks that require multiple steps to resolve, allowing the model to progressively work through a problem or generate content that evolves based on previous interactions.

The art and science of formulating prompts to achieve specific outcomes, enhancing the effectiveness of AI in teaching and learning.

An individual skilled in creating and refining prompts to optimize interactions with AI systems for educational purposes.

The strategic crafting and optimization of prompts to effectively communicate with AI, aiming for precise and beneficial outcomes.

A set of effectively designed prompts that address a specific challenge or goal, demonstrating understanding and application of AI.

Situations or scenarios that apply theoretical knowledge to practical, everyday contexts, enhancing relevance and understanding.

An overview or summary of course content, aimed at reinforcing key concepts and ensuring comprehension.

A strategic plan outlining the steps and milestones necessary to achieve educational or project goals.

AI-generated content that is ethical, non-harmful, and appropriate for the intended audience and context.

The use of different lengths and types of sentences to make written or spoken language more engaging and readable.

The broader effects of AI technology on social structures, cultural norms, and ethical values.

Detailed instructions provided in a logical sequence to guide learners through a particular task or process.

Building on the concept of breaking down complex problems, Tree of Thought (ToT) prompting further segments the problem-solving process into discrete, independently solved steps or "thoughts." Unlike Chain-of-Thought prompting, ToT does not require solving these steps in a single sequence. Instead, it allows the model to: explore various pathways for each step, assess the efficacy of individual thoughts, revisit and revise with backtracking, and navigate through a vast array of potential steps to discover the most effective solution.

The overall impact and satisfaction of users when interacting with AI systems, focusing on ease of use and quality of responses.

A pre-written outline for a video, detailing the narrative or educational content to be delivered visually and audibly.

This method involves providing the AI with only the essential instruction or question without any previous examples or context. It's a straightforward approach where the prompt can take the form of a direct question or a role for the model to assume, relying on the AI's pre-existing knowledge and capabilities to generate a response.