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Related Concept Videos

Observational Learning01:12

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning because...
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
Purposive Learning01:22

Purposive Learning

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 bonus...
Steps in the Modeling Process01:14

Steps in the Modeling Process

Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

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...
Associative Learning01:27

Associative Learning

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...

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Related Experiment Videos

Using Generative AI in Learning and Students' Innovative Behavior: A Dual-Path Examination Based on the UTAUT Model.

Lingyi Huang1, Wenhao Luo1

  • 1School of Economics and Management, North China University of Technology, No. 5 Jinyuanzhuang Road, Shijingshan District, Beijing 100144, China.

Behavioral Sciences (Basel, Switzerland)
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

Generative artificial intelligence (GAI) use boosts college students' learning expectancies and innovative behaviors. However, a growth mindset can lessen GAI's indirect impact on innovation, suggesting nuanced effects.

Keywords:
effort expectancygrowth mindsetinnovative behaviorperformance expectancyuse of GAI

Related Experiment Videos

Area of Science:

  • Educational Technology
  • Artificial Intelligence in Education
  • Learning Sciences

Background:

  • Generative artificial intelligence (GAI) is rapidly evolving, significantly impacting higher education.
  • Understanding GAI's influence on student learning behaviors is crucial for pedagogical advancement.
  • The Unified Theory of Acceptance and Use of Technology (UTAUT) provides a framework for analyzing technology adoption.

Purpose of the Study:

  • To investigate the impact of Generative Artificial Intelligence (GAI) usage on college students' innovative learning behaviors.
  • To examine the mediating roles of effort expectancy and performance expectancy in the GAI-learning relationship.
  • To explore the moderating effect of a growth mindset on the pathway from GAI usage to innovative behavior.

Main Methods:

  • A quantitative study involving 430 Chinese college students across various academic disciplines.
  • Latent structural equation modeling (SEM) was employed to analyze the proposed moderated mediation model.
  • Data collection focused on GAI usage, effort expectancy, performance expectancy, growth mindset, and innovative learning behaviors.

Main Results:

  • GAI usage positively influences both effort expectancy and performance expectancy among college students.
  • Both expectancies significantly foster students' innovative learning behaviors.
  • Performance expectancy mediates the relationship between GAI use and innovative behavior, but this indirect effect is weakened by a growth mindset.

Conclusions:

  • GAI tools can enhance student learning by increasing perceived effort and performance expectations, leading to greater innovation.
  • A growth mindset, while generally beneficial, may moderate the positive indirect effects of GAI on innovative behavior.
  • Findings offer insights for educators and institutions on leveraging GAI effectively while considering student mindsets.