SECTION – C
Answer the following questions in 50 words each. 10 x 3 = 30 marks
9. Levels-of-processing model
The Levels-of-Processing Model, proposed by Craik and Lockhart, suggests that memory retention depends on the depth of cognitive processing. Shallow processing involves focusing on superficial details like appearance or sound, leading to weaker memory. Deep processing, such as semantic analysis, involves meaningful connections, enhancing retention. For example, remembering a word is more effective when understanding its meaning and context rather than memorizing its shape or sound. This model emphasizes that memory strength is a byproduct of how information is encoded. Deep processing encourages active engagement, making it a critical framework for learning and teaching strategies.
10. Hebb’s Law
Hebb’s Law, formulated by Donald Hebb, is summarized as "neurons that fire together, wire together." It explains how repeated activation of neurons strengthens synaptic connections, forming the basis for learning and memory. When two neurons are repeatedly activated in synchronization, their connection becomes more robust, making future communication between them more efficient. This principle underlies long-term potentiation, a neural mechanism for learning and memory formation. Hebb’s Law is foundational in neuroscience, explaining processes like habit formation and neural plasticity. It has applications in artificial intelligence, particularly in developing neural networks that mimic human learning processes.
11. Role of hippocampus in memory
The hippocampus, located in the brain’s medial temporal lobe, plays a crucial role in memory formation, organization, and consolidation. It is essential for declarative memory, which includes facts and events, and helps transfer short-term memories into long-term storage. The hippocampus is also involved in spatial memory, enabling navigation and recognition of environments. Damage to the hippocampus can result in amnesia, particularly the inability to form new memories (anterograde amnesia). Additionally, it is implicated in memory retrieval and integration, making it a central structure for understanding how humans encode, store, and recall information.
12. Bloom’s taxonomy of cognitive domain
Bloom’s Taxonomy is a hierarchical framework for categorizing cognitive skills in six levels: remembering, understanding, applying, analyzing, evaluating, and creating. Developed by Benjamin Bloom, it guides educators in designing learning objectives and assessments. Lower-order skills (remembering and understanding) involve basic knowledge retention, while higher-order skills (analyzing, evaluating, creating) foster critical thinking and creativity. For example, a student might first recall a fact (remembering), explain it (understanding), and later apply it in real-world scenarios (applying). This taxonomy is widely used in education to ensure balanced cognitive development and to encourage students to achieve higher-order thinking.
13. Principles of the information processing
The information processing model compares human cognition to a computer system, emphasizing stages like encoding, storage, and retrieval. Key principles include attention, perception, and working memory, which serve as gateways for encoding information. Long-term memory stores processed information for future use. Retrieval is influenced by cues and memory strength. Processing is either automatic (e.g., recognizing a face) or effortful (e.g., solving a problem). Effective problem-solving depends on attention, minimizing cognitive overload, and organizing information meaningfully. The model emphasizes the importance of both environmental factors and individual cognitive strategies in learning and memory retention.
14. Well-defined and Ill-defined problems
Well-defined problems have clear goals, constraints, and solutions, such as mathematical equations or puzzles. These problems are structured and allow algorithmic solutions. Ill-defined problems lack clarity in goals, constraints, or solutions, requiring creativity and flexible thinking. Examples include ethical dilemmas or societal issues like poverty. Solving ill-defined problems often involves heuristic strategies, critical thinking, and iterative refinement. While well-defined problems are easier to approach systematically, ill-defined problems challenge individuals to navigate ambiguity and develop innovative solutions. Both types are integral to cognitive research, highlighting the diversity of human problem-solving abilities.
15. Relationship between creativity and intelligence
Creativity and intelligence are related yet distinct cognitive constructs. Intelligence involves reasoning, problem-solving, and analytical thinking, often measured through IQ tests. Creativity emphasizes divergent thinking, generating novel and original ideas. While a certain level of intelligence is necessary for creative thinking, high intelligence doesn’t guarantee creativity. Theories like the threshold hypothesis suggest creativity requires average or above-average intelligence but operates independently beyond that threshold. Creative individuals use intelligence to analyze problems and creativity to propose unique solutions. This relationship underscores the complementary roles of logical reasoning and imaginative thinking in innovation and problem-solving.
16. Benefits of multilingualism
Multilingualism enhances cognitive flexibility, executive function, and memory. Bilingual individuals often excel in problem-solving and multitasking due to improved attention control. It delays cognitive decline, reducing the risk of dementia in older adults. Multilingualism also fosters cultural awareness, promoting empathy and global understanding. Professionally, it provides competitive advantages in diverse job markets. Additionally, switching between languages enhances brain plasticity, benefiting overall mental health. Children raised in multilingual environments develop stronger linguistic and cognitive skills. Beyond practical benefits, multilingualism enriches personal connections and broadens perspectives, making it an invaluable skill in a globalized world.
17. Phonemes and morphemes
Phonemes and morphemes are fundamental language units. Phonemes are the smallest sound units in a language (e.g., /p/, /b/) and form the building blocks of words. Morphemes are the smallest meaningful units, including root words, prefixes, and suffixes (e.g., "un-", "happy"). While phonemes focus on sound, morphemes add meaning. For example, "unhappiness" consists of three morphemes ("un-", "happy," "-ness") and multiple phonemes. Together, they enable the construction and understanding of language. Phonemes facilitate pronunciation and differentiation of words, while morphemes aid in conveying meaning and grammatical structure, making both essential for language development and communication.
18. Problem space hypothesis
The problem space hypothesis, proposed by Newell and Simon, explains problem-solving as navigating through a mental "problem space." This space consists of the initial state, goal state, and possible intermediate states. Solvers use strategies like algorithms (systematic) or heuristics (shortcuts) to move through this space. The hypothesis highlights the importance of clear problem representation, as a well-defined space improves efficiency. For example, solving a maze involves visualizing pathways (intermediate states) to reach the exit (goal state). It emphasizes that effective problem-solving relies on exploring potential solutions systematically while balancing efficiency and creativity.
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