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Related Concept Videos

Observational Learning01:12

Observational Learning

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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...
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Associative Learning01:27

Associative Learning

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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.
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Purposive Learning01:22

Purposive Learning

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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...
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Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
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Cognitive Learning01:21

Cognitive Learning

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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.
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Introduction to Learning01:18

Introduction to Learning

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Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
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Updated: Aug 29, 2025

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Video Question Answering With Prior Knowledge and Object-Sensitive Learning.

Pengpeng Zeng, Haonan Zhang, Lianli Gao

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    |September 9, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces Prior Knowledge and Object-sensitive Learning (PKOL) to improve Video Question Answering (VideoQA). PKOL enhances models by integrating external knowledge and focusing on object details for better video understanding.

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    Area of Science:

    • Artificial Intelligence
    • Computer Vision
    • Natural Language Processing

    Background:

    • Video Question Answering (VideoQA) is a rapidly advancing field focusing on understanding spatial-temporal video content based on linguistic queries.
    • Current attention-based methods face challenges in effectively locating relevant visual and linguistic information within videos.
    • Existing approaches often underutilize crucial prior knowledge and structured object-level visual information.

    Purpose of the Study:

    • To enhance Video Question Answering (VideoQA) performance by addressing limitations in current attention mechanisms.
    • To explore the impact of incorporating prior knowledge and learning object-sensitive representations for improved reasoning.
    • To develop a novel framework that leverages both external knowledge and detailed visual object information.

    Main Methods:

    • Proposing a Prior Knowledge Exploring (PKE) module to retrieve and integrate relevant external knowledge into question features.
    • Introducing an Object-sensitive Representation Learning (ORL) module to generate features by fusing object-level, frame-level, and clip-level visual information.
    • Developing the Prior Knowledge and Object-sensitive Learning (PKOL) framework combining PKE and ORL modules.

    Main Results:

    • Consistent performance improvements were observed across three benchmark datasets: MSVD-QA, MSRVTT-QA, and TGIF-QA.
    • The proposed PKOL framework achieved state-of-the-art results on these competitive VideoQA benchmarks.
    • The integration of prior knowledge and object-sensitive features significantly boosted the model's ability to answer video-related questions.

    Conclusions:

    • Prior knowledge and object-sensitive representations are critical for advancing VideoQA.
    • The PKOL framework effectively addresses key limitations in existing VideoQA models.
    • The developed approach demonstrates a promising direction for future research in multimodal understanding and reasoning.