Related Experiment Video
Updated: Sep 8, 2025
06:37
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
4.1K
Generative AI without guardrails can harm learning: Evidence from high school mathematics
Hamsa Bastani1,2, Osbert Bastani3, Alp Sungu1
1Department of Operations, Information, and Decisions, Wharton School, University of Pennsylvania, Philadelphia, PA 19104.
Summary
Generative AI tools can boost performance but may harm learning if used as a crutch. Safeguarded AI tutors mitigate negative educational outcomes, preserving long-term skill development.
Area of Science:
- Artificial Intelligence
- Educational Technology
- Cognitive Science
Background:
- Generative AI (Artificial Intelligence) shows potential for enhancing productivity.
- Understanding its impact on skill acquisition and learning is crucial for long-term productivity.
- Generative AI's fallibility necessitates user oversight, highlighting the importance of effective learning strategies.
Purpose of the Study:
- To investigate how generative AI tutors affect learning in high school mathematics.
- To compare the impact of a standard generative AI interface versus one with learning safeguards.
- To assess the long-term educational outcomes of generative AI tool usage.
Main Methods:
- A field experiment involving nearly one thousand high school math students.
- Deployment of two generative AI tutors: a standard ChatGPT interface (GPT Base) and a safeguarded version (GPT Tutor).
- Analysis of student performance and learning outcomes with and without generative AI access, and after access removal.
Main Results:
- Generative AI access significantly improved student performance (48% for GPT Base, 127% for GPT Tutor).
- Removing generative AI access led to worse performance than never having access (17% reduction for GPT Base).
- Safeguards in GPT Tutor largely mitigated negative learning effects, preventing students from using AI as a crutch.
Conclusions:
- Unfettered generative AI access can negatively impact educational outcomes and skill learning.
- Careful design of generative AI tools, incorporating learning safeguards, is essential for positive educational impact.
- Decision-makers must consider AI design to ensure skill preservation and long-term productivity.
More Related Videos
Related Concept Videos
01:16Non-equilibrium in the Cell
4.8K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.8K
01:10Gauss's Law: Problem-Solving
2.1K
Gauss's law helps determine electric fields even though the law is not directly about electric fields but electric flux. In situations with certain symmetries (spherical, cylindrical, or planar) in the charge distribution, the electric field can be deduced based on the knowledge of the electric flux. In these systems, we can find a Gaussian surface S over which the electric field has a constant magnitude. Furthermore, suppose the electric field is parallel (or antiparallel) to the area...
2.1K
02:09Stereotype Threat and Self-fulfilling Prophecies
38.7K
When we hold a stereotype about a person, we have expectations that he or she will fulfill that stereotype. A self-fulfilling prophecy is an expectation held by a person that alters his or her behavior in a way that tends to make it true. When we hold stereotypes about a person, we tend to treat the person according to our expectations. This treatment can influence the person to act according to our stereotypic expectations, thus confirming our stereotypic beliefs. Research by Rosenthal and...
38.7K
01:21Cognitive Learning
513
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
513
01:22Purposive Learning
203
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
203
01:27Associative Learning
566
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Classical conditioning, also known...
566