Knowledge Organizers of Cell Biology

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Information about Knowledge Organizers of Cell Biology

Published on February 11, 2009

Author: meena74


Knowledge Organizers of Cell Biology Meena Kharatmal & Nagarjuna G. {meena, nagarjun} EPISTEME ­1  December 16, 2004 Homi Bhabha Centre for Science Education (Tata Institute of Fundamental Research) Mumbai, INDIA

Working Hypotheses of Knowledge Organization in  Science Education To understand is to establish relations between concepts ● To educate is to help to organize concepts  ● All learning involves restructuring (conceptual change).  ● Misunderstanding is due to incorrect organization of  ● concepts Goal of teaching is to restructure (reorganize) novice's  ● knowledge structure so as to align with expert's  knowledge structure

Importance of Knowledge Organization in Science Education Understanding of knowledge organization (KO) will help in  ● building a framework for curriculum development To understand the transformation (conceptual change) of  ● novice into an expert Curriculum designed using KO approach follows a principled  ● approach, which is used by the experts in their respective  domains. Incorporating the principled/logical approach is  very essential to transform a novice into an expert (which is  the goal of education)

Knowledge Representation (KR)  A KR is a surrogate: KR acts as a surrogate for representing the physical objects,  ● events, relationships which cannot be stored directly in a computer.  It can be  represented by symbols, and these symbols serve as surrogates for external system.  A  computational model is a surrogate for some real or hypothetical system.   A KR is a set of ontological commitments: An ontology is a study of existence. A  ● KB is determined by its ontology. Every KB is based on some conceptualization.  An  explicit specification of this conceptualization is called an ontology. In ontology, what  one does is articulate the knowledge in terms of concepts, relations, axioms,  instances.    A KR is a fragmentary theory of intelligent reasoning: It serves to support  ● reasoning about things in a domain.   A KR is a medium for efficient computation: It processes knowledge efficiently  ● for problem solving on the available computing equipment.   A KR is a medium of human expression: A good KR language should facilitate  ● communication between the knowledge engineers who understand AI and the  domain experts who understand the application.  Although the knowledge engineer  may write the definition, and rules, the domain experts should be able to read them  Davis, Schrobe, Szolovits (1993); Sowa (2000) and verify whether they represent a realistic theory of the domain.

Different ways of knowledge representation Concept  Map  (Novak) Conceptual Graphs (Peirce, Sowa) Concept  Circle  Diagram  (Wandersee) Semantic  Network  (Fisher)

How does KR help student learn?   A collaborative task occurs on the discussions about the meanings of  ● concepts and the relations between them. The act of creating an organized  structure of ideas on paper or on a computer helps in creating a knowledge  structure in the mind.   KR helps in making the implicit (often fuzzy) knowledge into an explicit  ● and precise knowledge. It incorporates cognitive and metacognitive skills,  thus occurs meaning­making.   KR helps students to make finer discriminations between ideas and helps to  ● organize better. The more one practices the better one becomes at organizing  and relating concepts.   Structural (organized, semantic) knowledge is essential to assimilate, recall  ● and comprehend. Structural knowledge is essential to problem solving.   There exists significant differences between the structural knowledge of  ● novices and experts, and hence for novices a natural part of learning is to  work on their structural knowledge to make it more expert­like. Fisher (1996)

Comparing expert's and novice's knowledge structure Expert Novice Knowledge cohesive, integrated  loose form  structure unambiguous relations  ambiguous relations        parsimony   uneconomical Knowledge    core concepts     periphery                   organization      Approach principled, accurate, deep       superficial Theories abstract, global, consistent, concrete,  fragmentary,     universal, precise  inconsitent,   particular, diffuse Reasoning explicit and articulate implicit and intuitive Brewer, Samarapungawan (1991)

Methodology Classify concepts on the basis of their cognitive function ● Assign valid and authentic semantic relations to the concepts  ● Analysis of the knowledge­base based on the usage of  ● different kinds of semantic relations applied Comparing the novice's knowledge structure with that of an  ● expert's knowledge structure Restructuring (reorganizing) to align the novice's knowledge  ● structure with the expert's knowledge structure Develop a minimal set of relation types for representing the  ● entire domain of biology

3­layer model of GNOWSYS MetaType MTRelation MetaType MetaType layer MetaType MetaType MetaType MetaType MetaType Instance of MetaType Type AT AT layer AT ObjectType ObjectType RelationType AT Instance of Type Token A A layer A Object Object Relation A

Classify concepts on the basis of their cognitive function MetaType Taxonomical concept Structural concept Process concept Relational concept Kingdom TYPE Spatial inclusion Phylum Meronymic inlucsion Class inclusion Class Instance of ObjectType Structure Process Animalia Cell Protein synthesis TYPE Cytoplasm Vertebrata Nucleus Lipid synthesis Mammalia Nuclear envelope Human Diffusion Mitochondria Fish Metabolism Ribosomes by   Instance of ed Object in co Robert Hooke TOKEN

Assign valid and authentic semantic relations to the concepts  Meta Type Relational concept  Class inclusion  Meronymic inclusion   Spatial inclusion  Functional RelationType Ribosomes located on endoplasmic reticulum Vertebrata includes fish, mammal Protein synthesis occurs in cytoplasm Mitochondria, ER, part of cell Amino acids includes alanine, glutamine DNA wound around histones Purines includes adenine, guanine Ribosomes located on ER Nucleus function DNA synthesis Plankton includes phytoplankton, zooplankton Relation Schleiden, Shwann formulated Cell theory

Classify concepts on the basis of their cognitive function cell  small       lipid synthesis nucleus frog osmosis cytoplasm nekton diffusion endoplasmic reticulum plankton metabolism mitochondria ocean my cell protein synthesis size 20nm animalia eukaryotic cell ribosomes mammalia kingdom shark whale phylum 1µ m structure Watson class process Hooke vertebrata attributes objects

Assign valid and authentic semantic relations to the concepts Animalia instance­of kingdom class membership ● Vertebrata instance­of phylum ● class inclusion Vertebrate includes mammalia, fish ● meronymic inclusion Shark instance­of chondrichthyes ● Kingdom subtype­of taxonomical concept spatial inclusion ● Mitochondria  part­of cell ● Ribosomes part­of cell ● Instance­of Robert Hooke instance of human ● subtype­of Nuclear envelop surrounds nucleus ● part­of surrounds

Semantic relations Meronymic inclusion (part­of/consists­of) ● Nucleus, cytoplasm, ER, mitochondria part­of cell – Phosphoric acid, pentose sugar, nitrogenous base part­of nucleotides – Amino acids part­of proteins – Class inclusion (includes /type­of, subclass­of) ● Amino acids includes alanine, glutamine – Purines includes adenine, guanine – Vertebrates includes mammals, fish – Spatial inclusion (surrounded by/surrounds) ● Nucleus surrounded­by nuclear envelope – DNA wound around histones – Ribosomes located on endoplasmic reticulum – Functional (function) ● Smooth ER function lipid synthesis – Golgi apparatus function transport of materials –

Process modelling Object undergoes event ● Object transforms into object ● Event takes place in region ● Event takes place during time ●

Process modelling for prophase Structure Process ● ● Chromatin undergoes condensation; Condensation takes place in nucleus Chromatin Condensation – – Chromatin transforms  into chromosome Chromatin moves towards nuclear envelope Chromosome Reduction Nucleoli reduces in size – – Reduction takes place in nucleoplasm Nuclear envelope undergoes fragmentation Nucleoli Movement – – Fragmentation results in disappearance Spindle formation takes place in cytoplasm Nuclear envelope Fragmentation – – Centrioles undergoes movement Spindle undergoes lengthening Spindle Formation – – Centrioles Chromatin – Condensation Location/Region Effect ● ● Nucleus Nucleus Disappear – – Chromosomes Nucleoplasm Lengthen – –

Concept map on “life in the ocean” Many relation types ● 1st level Hierarchy not ordered 2nd level ● 3rd level Hierarchy not validated ● 4th level Incorrect cross­links ● 5th level Graphical representation  ●      misleading  6th level Not principled ● Martin, Mintzes, Clavijo (IJSE, 2000)

Principled concept map on “life in the ocean”  Consists  Ocean of Includes Living Beings Non­living Beings Habi (Biotic) (Abiotic) t Habita t Animals Plants Produce s Geological Chemical Physical Seagrass Algae Plankton Pleuston Nekton Vertebrates Invertebrates Cnidaria Chlorophyta Fish Mammal Phytoplankton Arthropoda Current Wave Phaeophyta Porifera Wind Zooplankton Rhodophyta Crustal plate Mollusca Inorganic Organic boundaries Agnatha Osteichthyes Carnivora Pinnipeda Holoplankton Chonodrichthyes Cetacea Sirenia Meroplankton Ca Cl Ligands K Na Co3 Mysteceti Odonteceti Constructive Rays Shark Conservative Destructive

Principled concept map on “organic molecules” Consists of Organic molecules Includes Polysaccharides Proteins Lipids Nucleic acids Minimal Set of  RNA Knowledge  DNA Organizers Fatty acids Monosaccharides Amino acids Nucleotides Glycerol Principled Concept Alanine    Map: Glutamine Concepts ➔ Glycine Relation types Phenylalanine Pentose sugar ➔ R H C Relations ➔ Phosphoric acid Nitrogenous bases NH2 COOH Hierarchy ➔ Branching ➔ Cross­links Purines Pyrimidines ➔ Instances ➔ Attributes ➔ Cytosine Metatypes ➔ Adenine Guanine Thymine Uracil

Screenshot of  GNOWSYS

Screenshot of  GNOWSYS Knowledge  Organizers

Screenshot of  GNOWSYS Meronymic Inclusion

Screenshot of  GNOWSYS

Screenshot of  GNOWSYS Relation  Process  Structure

Implications of the reasearch Study the transformation and restructure (reorganize) the  ● novice's knowledge structure with that of an expert's knowledge  structure To develop a knowledge base of biological concepts with valid  ● and authentic semantic relations (can serve as criteria maps for  assessment and scaling) To develop a principled concept mapping approach with scaling  ● and assessment criteria using the knowledge base  Develop a controlled language (small subset of natural  ● language) to express scientific knowledge based on minimal  knowledge organizers (following the concept graphs of Peirce  and Sowa) 

Ausubel, Novak and Hanesian (1978): Cognitive Physchology: A Cognitive View, Holt, Rinehart and Winston, New York ● Brewer and Samarapungavan(1991): Children's Theories vs. Scienctific Theories: Differences in Reasoning or Differences in Knowledge? In  ● Hoffman and Palermo (Eds.), Cognition and the Symbolic Processes: Applied and Ecological Perspectives, pp. 209­232, Erlbaum, NJ. Carey (1986): Conceptual Change and Science Education, American Psychologist, 41(10, pp.1123­1130. ● Castro, Peter and Huber, Michael (2003): Marine Biology, Fourth edition, McGrawHill, USA. ● Fisher, Wandersee and Moody (2000): Mapping Biology Knowledge, Kluwer Academic Publishers, The Netherlands ● Fisher and Kibby (1996): Knowledge Acquisition, Organization and Use in Biology, Springer­Verlag, Germany ● Grabowski (2000): Principles of Anatomy and Physiology, John Wiley and Sons, New York ● International Journal of Science Education: 2000, 2002 ● Journal of Research in Science Teaching: 1990, 1994, 1996, 2000 ● Mader (2000): Inquiry into Life, McGraw Hill, USA ● Mintzes, Wandersee and Novak (1998): Teaching Science for Understanding ­­­ A Human Constructivist View, Academic Press, USA ● Mintzes, Wandersee and Novak (2000): Assessing Science Understanding ­­­ A Human Constructivist View, Academic Press, USA ● Novak, Gowin (1984): Learning How to Learn, Cambridge University Press, UK ● Soper (1997): Biological Science, Cambridge University Press, UK ● Sowa (2000): Knowledge Representation: Logical, Philosophical, and Computational Foundations, Brooks/Cole, USA ● Sowa (1984): Conceptual Structures: Information Processing in Mind and Machine, Addison­Wesley Publishing Company, USA.  ● Stephens and Chen (1995): Principles for Organizing Semantic Relations in Large Knowledge Bases, IEEE. ● Storey (1993): Understanding Semantic Relationships, VLDB, 2, pp.455­488 ● Winston, Chaffin and Hermann (1987): A Taxonomy of Part­Whole Relations, Cognitive Science, 11, pp. 417—444 ●

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