Learning Theories

Duration: 23 min

This video lesson is available to enrolled students.

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Inside: a video lesson and guided study material.

Module outline

  1. About the course: About the Course
  2. Mathematical Aptitude / गणितीय अभिक्षमता: Number System / संख्या पद्धति, HCF and LCM / महत्तम समापवर्तक और लघुत्तम समापवर्त्य, Divisibility Rules / विभाज्यता के नियम, Percentage / प्रतिशत, Ratio and Proportion / अनुपात और समानुपात, Average / औसत, Profit, Loss and Discount / लाभ, हानि और बट्टा, Time and Work / समय और कार्य, Solid Mensuration / घन क्षेत्रमिति, Simple and Compound Interest / साधारण और चक्रवृद्धि ब्याज, Time, Speed and Distance / समय, चाल और दूरी, Age Problems / आयु संबंधी प्रश्न, Mixture and Alligation / मिश्रण और एलिगेशन, Algebra / बीजगणित, Simplification, Indices and Surds / सरलीकरण, घातांक और करणी, Pipe and Cistern / नल और टंकी, Trigonometry / त्रिकोणमिति, Statistics / सांख्यिकी, Data Interpretation / आँकड़ा निर्वचन, Arithmetic / अंकगणित, Sets, Relations, Functions and Discrete Mathematics / समुच्चय, संबंध, फलन और विविक्त गणित, Number Systems and Number Theory / संख्या पद्धति और संख्या सिद्धांत, Coordinate Geometry, Vectors and 3D Geometry / निर्देशांक ज्यामिति, सदिश और त्रिविमीय ज्यामिति, Polynomials, Equations and Complex Numbers / बहुपद, समीकरण और सम्मिश्र संख्याएँ
  3. Logical Reasoning / तार्किक तर्कशक्ति: Series / श्रेणी, Coding-Decoding / कूट लेखन एवं कूट वाचन, Analogy and Classification / सादृश्यता एवं वर्गीकरण, Blood Relations / रक्त संबंध, Direction and Distance / दिशा एवं दूरी, Order and Ranking / क्रम एवं रैंकिंग, Non-Verbal Reasoning / अशाब्दिक तर्क, Seating Arrangement and Puzzles / बैठक व्यवस्था एवं पहेलियाँ, Syllogisms / न्यायवाक्य, Venn Diagrams, Syllogism and Inequalities / वेन आरेख, न्याय वाक्य एवं असमानता, Mathematical Operations and Missing Numbers / गणितीय संक्रियाएँ एवं लुप्त संख्या, Alphabet and Number Test / वर्णमाला एवं संख्या परीक्षण, Statement-Based Reasoning / कथन आधारित तार्किक विवेचन, Analytical Reasoning (Counting Figures Reasoning) / विश्लेषणात्मक तर्क (आकृति गणना तर्क), Cubes, Dice and Figure Counting / घन, पासा एवं आकृतियों की गिनती, Calendar and Clock / कैलेंडर एवं घड़ी, Clock / घड़ी
  4. General Knowledge / सामान्य ज्ञान: Scientific Achievements and Research / वैज्ञानिक उपलब्धियाँ और अनुसंधान, Chemistry / रसायन विज्ञान, Biology / जीव विज्ञान, History / इतिहास, Geography / भूगोल, Polity / राजव्यवस्था, Indian Economy / भारतीय अर्थव्यवस्था, Current Affairs / समसामयिकी, Static General Knowledge / स्थैतिक सामान्य ज्ञान, State-Specific General Knowledge / राज्य विशेष सामान्य ज्ञान
  5. Art of Teaching / शिक्षण कला: Teaching-Learning Process and Classroom Management / शिक्षण-अधिगम प्रक्रिया एवं कक्षा प्रबंधन, Learners & Learning Process / अधिगमकर्ता और अधिगम प्रक्रिया, Factors Affecting Teaching / शिक्षण को प्रभावित करने वाले कारक, Teaching Methods and Approaches / शिक्षण विधियाँ एवं उपागम, Microteaching and Classroom Communication / सूक्ष्म शिक्षण एवं कक्षा संप्रेषण, Teaching Aids and Educational Technology / शिक्षण सहायक सामग्री एवं शैक्षिक तकनीकी, Assessment and Evaluation / आकलन एवं मूल्यांकन, Teacher: Qualities, Professional Ethics and Development / शिक्षक: गुण, व्यावसायिक नैतिकता एवं विकास, Educational Policies, Acts and Administration / शैक्षिक नीतियाँ, अधिनियम एवं प्रशासन, Curriculum, Arts and Co-curricular Areas / पाठ्यचर्या, कला एवं सह-शैक्षिक क्षेत्र, Guidance and Counselling / निर्देशन एवं परामर्श, Education of Children with Disabilities / दिव्यांग बच्चों की शिक्षा, Micro-Teaching & Teaching Skills / सूक्ष्म शिक्षण और शिक्षण कौशल, Lesson Planning / पाठ योजना
  6. Environmental Science / पर्यावरण विज्ञान: Environment / पर्यावरण
  7. Unit 1 | Digital Electronics: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  8. Unit 2 | COA: Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Instr Formats & Modes, Control Unit Design, Register Transfer and Microoperations, Programming the Basic Computer
  9. Unit 3 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  10. Unit 3 | Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  11. Unit 4 | Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Advanced Algorithms
  12. Unit 5 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  13. Unit 6 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Transaction Management, Concurrency Control
  14. Unit 7 | Computer Networks: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer
  15. Unit 8 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  16. Unit 9 | Object Oriented Programming: OOPS with C++
  17. Unit 10 | Web Development: HTML Basics, CSS, JavaScript-Basics, XML, Node.js, Git & Github, PHP
  18. Unit 11 | Theory Of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines
  19. Unit 12 | IoT: Emerging Tech Trends, Cloud Computing, Computer Networks, Internet of Things
  20. Unit 13 | Artificial Intelligence: Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Natural Language Processing, Artificial Neural Networks, Genetic Algorithms
  21. Unit 14 | E-Commerce: Electronic Data Interchange and E-Commerce, Role of Internet and Web Services, Security in Mobile and Wireless Computing, Physical Security and Cryptography Basics, Cyber Safety and Security
  22. Unit 15 | Multimedia: Multimedia
  23. Unit 16 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis, DSA using Python
  24. Full Length Mock Tests — General Paper:
  25. Full Length Mock Tests — Computer Science (Paper II):
  26. Full Length Mock Test – General + Computer Science:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video provides a comprehensive lecture on Learning Theories, specifically focusing on Classical and Operant Conditioning. It begins by categorizing learning into four main types: Classical Conditioning, Operant Conditioning, Learning by Observation, and Cognitive Learning Theory. The instructor then delves into Conditioning Theory, defining it as the association of a stimulus with a response. The first major section covers Classical Conditioning, attributed to Ivan Pavlov, detailing his famous dog experiment where a neutral stimulus (bell) was paired with an unconditioned stimulus (food) to elicit a conditioned response (salivation). The second major section covers Operant Conditioning, introduced by B.F. Skinner, which focuses on how behavior is shaped by consequences like reinforcement and punishment. The lecture concludes by breaking down key concepts such as positive reinforcement, negative reinforcement, punishment, and extinction.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video begins with a presentation slide titled "LEARNING THEORIES" at the top. The screen is divided into four colored quadrants. The top-left quadrant, in a brown box, reads "CLASSICAL CONDITIONING THEORY" with Hindi text below it. The top-right, in a green box, reads "OPERANT CONDITIONING THEORY". The bottom-left, in a lighter green box, reads "LEARNING BY OBSERVATION". The bottom-right, in a blue box, reads "COGNITIVE LEARNING THEORY". The instructor, wearing a red top, stands to the right of the screen. She gestures towards the "Operant Conditioning Theory" box, indicating that this is the primary topic of discussion for the session, while acknowledging the other theories as part of the broader context.

  2. 2:00 – 5:00 02:00-05:00

    The slide transitions to a text-heavy page titled "What Is Conditioning Theory Of Learning?". The English text defines the theory as a form of learning where learning occurs as a result of "associating a condition or stimulus with a particular reaction or response." It further states that human behavior is shaped by habits picked up in response to certain situations. The instructor points to the text with a pen, emphasizing the phrase "associating a condition or stimulus". She explains that there are two main types: "classical conditioning theory and operant conditioning theory," which are highlighted in red text on the slide.

  3. 5:00 – 10:00 05:00-10:00

    The slide changes to "CLASSICAL CONDITIONING THEORY". The first bullet point states it was "Discovered by Russian physiologist Ivan Pavlov" and is a type of "unconscious or automatic learning." The instructor underlines "Ivan Pavlov" and explains his contribution. The slide describes the experiment where Pavlov rang a bell before giving a dog food. It notes that eventually, the "dog started associating the sound of the bell with food." The instructor points to this specific sentence to illustrate the core mechanism of classical conditioning, where a neutral stimulus becomes associated with a meaningful stimulus.

  4. 10:00 – 15:00 10:00-15:00

    The slide continues with "Learning by the classical conditioning theory involves". It defines "Unconditioned Stimulus" as a trigger leading to an automatic response, citing the dog's food as the example. It defines "Neutral Stimulus" as a stimulus that doesn't initially trigger a response, like the sound of a fan. The instructor points to the definition of "Unconditioned Stimulus" and explains that in Pavlov's experiment, the dog's food is the unconditioned stimulus that causes the dog to start salivating. She also points to the "Neutral Stimulus" section, explaining that the bell was initially neutral.

  5. 15:00 – 20:00 15:00-20:00

    The topic shifts to "OPERANT CONDITIONING THEORY". The slide identifies "Renowned Behavioural Psychologist B.F. Skinner" as the main proponent. The text explains that the theory stresses the role of "punishment or reinforcements for increasing or decreasing the probability of the same behaviour to be repeated in the future." The instructor highlights "B.F. Skinner" and explains that this theory is also known as Skinnerian Conditioning. She discusses the assumption that the consequences of a behavior determine the possibility of it being repeated.

  6. 20:00 – 23:07 20:00-23:07

    The final slide lists "Key Concepts". It defines "Reinforcement" as increasing a behavior. It breaks this down into "Positive Reinforcement" (Reward after desired behaviour, add pleasant stimulus) and "Negative Reinforcement" (Removal of unpleasant stimulus after behavior). It also defines "Punishment" as decreasing a behavior by adding an unpleasant stimulus. The instructor underlines "Reward after desired behaviour" and "Removal of unpleasant stimulus after behavior" to clarify the difference between positive and negative reinforcement. She explains that punishment reduces behavior, while extinction occurs if reinforcement is removed.

The lecture progresses from a broad overview of learning theories to a deep dive into two specific behavioral theories. It starts by mapping the landscape of learning (Classical, Operant, Observation, Cognitive) before narrowing down to Conditioning. It then systematically deconstructs Classical Conditioning using Pavlov's experiment to explain stimulus-response associations. Finally, it shifts to Operant Conditioning, using Skinner's framework to explain how consequences (reinforcement and punishment) shape voluntary behavior. This structure moves from general categorization to specific mechanisms of learning.

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