Associationism

Duration: 9 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: संख्या पद्धति / Number System, महत्तम समापवर्तक और लघुत्तम समापवर्त्य / HCF and LCM, Divisibility Rules, प्रतिशत / Percentage, अनुपात और समानुपात / Ratio and Proportion, औसत / Average, लाभ, हानि और बट्टा / Profit, Loss and Discount, समय और कार्य / Time and Work, घन क्षेत्रमिति / Solid Mensuration, साधारण और चक्रवृद्धि ब्याज / Simple and Compound Interest, समय, चाल और दूरी / Time, Speed and Distance, Age Problems, मिश्रण और एलिगेशन / Mixture and Alligation, Algebra, सरलीकरण, घातांक और करणी / Simplification, Indices and Surds, Pipe and Cistern, Trigonometry, Statistics, आँकड़ा निर्वचन / Data Interpretation, Arithmetic, समुच्चय, संबंध, फलन और विविक्त गणित / Sets, Relations, Functions and Discrete Mathematics, संख्या पद्धति और संख्या सिद्धांत / Number Systems and Number Theory, निर्देशांक ज्यामिति, सदिश और त्रिविमीय ज्यामिति / Coordinate Geometry, Vectors and 3D Geometry, बहुपद, समीकरण और सम्मिश्र संख्याएँ / Polynomials, Equations and Complex Numbers
  3. Logical Reasoning: श्रेणी / Series, कूट लेखन एवं कूट वाचन / Coding-Decoding, सादृश्यता एवं वर्गीकरण / Analogy and Classification, रक्त संबंध / Blood Relations, दिशा एवं दूरी / Direction and Distance, क्रम एवं रैंकिंग / Order and Ranking, अशाब्दिक तर्क / Non-Verbal Reasoning, बैठक व्यवस्था एवं पहेलियाँ / Seating Arrangement and Puzzles, Syllogisms, वेन आरेख, न्याय वाक्य एवं असमानता / Venn Diagrams, Syllogism and Inequalities, गणितीय संक्रियाएँ एवं लुप्त संख्या / Mathematical Operations and Missing Numbers, वर्णमाला एवं संख्या परीक्षण / Alphabet and Number Test, कथन आधारित तार्किक विवेचन / Statement-Based Reasoning, Analytical Reasoning (Counting Figures Reasoning), घन, पासा एवं आकृतियों की गिनती / Cubes, Dice and Figure Counting, कैलेंडर एवं घड़ी / Calendar and Clock, Clock
  4. General Knowledge: वैज्ञानिक उपलब्धियाँ और अनुसंधान / Scientific Achievements and Research, Chemistry, Biology, History, Geography, Polity, Indian Economy, समसामयिकी / Current Affairs, Static General Knowledge, राज्य विशेष सामान्य ज्ञान / State-Specific General Knowledge
  5. Art of Teaching: शिक्षण-अधिगम प्रक्रिया एवं कक्षा प्रबंधन / Teaching-Learning Process and Classroom Management, Learners & Learning Process, Factors Affecting Teaching, शिक्षण विधियाँ एवं उपागम / Teaching Methods and Approaches, सूक्ष्म शिक्षण एवं कक्षा संप्रेषण / Microteaching and Classroom Communication, शिक्षण सहायक सामग्री एवं शैक्षिक तकनीकी / Teaching Aids and Educational Technology, आकलन एवं मूल्यांकन / Assessment and Evaluation, शिक्षक: गुण, व्यावसायिक नैतिकता एवं विकास / Teacher: Qualities, Professional Ethics and Development, शैक्षिक नीतियाँ, अधिनियम एवं प्रशासन / Educational Policies, Acts and Administration, पाठ्यचर्या, कला एवं सह-शैक्षिक क्षेत्र / Curriculum, Arts and Co-curricular Areas, निर्देशन एवं परामर्श / Guidance and Counselling, दिव्यांग बच्चों की शिक्षा / Education of Children with Disabilities, Micro-Teaching & Teaching Skills, पाठ योजना / Lesson Planning
  6. Environmental Science: Environment
  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, कंप्यूटर नेटवर्क / 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.

This educational video provides a detailed lecture on Associationism, a psychological theory explaining how ideas and experiences are linked in the mind. The instructor uses a digital slide to outline the core definition and several fundamental laws of association. The lesson progresses from basic principles like Contiguity and Similarity to more complex concepts such as Frequency, Recency, and Partial Activity. Throughout the lecture, the instructor actively engages with the material by writing notes on the screen, underlining key terms, and drawing diagrams to illustrate abstract concepts like priming and proximity. The content is structured to help students understand how mental connections are formed through experience, repetition, and spatial or logical relationships, serving as a comprehensive guide for psychology students.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The lecture begins with a clear definition of Associationism displayed on the screen. The on-screen text states, 'Associationism is a psychological theory that explains how ideas and experiences are linked or associated together in the mind.' The slide further explains that this theory suggests learning and memory are based on principles of association, where connections are formed through experience and repetition. The text explicitly mentions, 'Several laws or principles under associationism describe how these mental associations are formed and influence thought processes.' The instructor introduces the first two laws listed on the slide: the 'Law of Contiguity' and the 'Law of Similarity.' The text explains that the Law of Contiguity states ideas occurring close together in space or time are more likely to be associated, while the Law of Similarity suggests similar ideas are more likely to be linked. This initial segment sets the foundational framework for understanding how mental associations influence thought processes.

  2. 2:00 – 5:00 02:00-05:00

    The instructor elaborates on the first two laws using specific examples provided in the text. She points to the section on the Law of Contiguity, which notes that 'hearing a song may evoke memories of a specific event or location where you first heard it due to their contiguity in time.' She then moves to the Law of Similarity, highlighting the example where 'seeing a basketball might bring to mind thoughts of other sports balls like a soccer ball or a volleyball due to their similarity in appearance and function.' During this explanation, the instructor writes the word 'Autobio' on the screen, likely referring to autobiographical memory as a practical application of these laws. Her gestures and annotations help clarify how these abstract psychological principles manifest in everyday cognitive experiences, bridging the gap between theory and personal memory.

  3. 5:00 – 8:48 05:00-08:48

    The slide updates to display laws 3 through 7, expanding the scope of the lecture. The instructor focuses on the 'Law of Frequency,' underlining the text and writing 'Memory and practice' next to it to emphasize that repeated pairing strengthens associations. She then discusses the 'Law of Partial Activity,' explaining that recalling part of an experience can lead to the activation of related ideas, a phenomenon known as priming. To illustrate this, she draws a diagram involving geometric shapes on the screen, specifically a triangle inside a circle with an arrow. Finally, she addresses the 'Law of Proximity,' writing 'Proximity -> closeness / space' to define the concept. The text explains that ideas close in space or logical sequence are more likely to be associated, such as related information presented together being more easily remembered. This section deepens the student's understanding of the mechanisms behind memory and association, covering a wide range of associative principles.

The video effectively structures a complex psychological theory into digestible components. By moving from the definition of Associationism to specific laws like Contiguity, Similarity, and Frequency, the instructor builds a comprehensive understanding of mental associations. The use of visual aids, such as the slide text and handwritten notes like 'Autobio' and 'Memory and practice,' reinforces key concepts. The progression from simple examples (songs, balls) to more nuanced ideas (priming, partial activity) ensures a logical flow of information, making the material accessible for revision and exam preparation. The instructor's active engagement with the slide, through underlining and drawing, models how to interact with study materials effectively.

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