This document describes Bloom's Taxonomy, an educational framework for classifying learning objectives into levels of complexity and cognitive process. The taxonomy includes knowledge, comprehension, application, analysis, synthesis, and evaluation. The author interprets how these levels can be applied to mathematics education, providing example questions for each level targeting introductory calculus students. Questions become more complex through the levels, moving from knowledge-based questions testing terms and methods to evaluation questions requiring judgment on what information to use in word problems.
THEORETICAL/CONCEPTUALFRAMEWORK
FRAMEWORK
- defined by the dictionary, is a skeletal or structural framework.
THEORETICAL
- means relating to or having the characteristics of theory.
THEORETICAL FRAMEWORK
- refers to the “set of interrelated constructs (concepts), definitions and propositions that presents a systematic view of phenomena by specifying relations among variables”.
KERLINGER THEORY (1973)
Theoretical framework indicates all the constructs (concepts), definitions and propositions that relate to a research problem.
A conceptual framework is an analytical tool with several variations and contexts. It is used to make conceptual distinctions and organize ideas.
THREE (3) STYLES
STYLE NO. 1
Theoretical framework is presented in the first or introductory chapter (JOURNALISTIC STYLE).
STYLE NO. 2
It is another style and popularly found in other theses and dissertations.
STYLE NO. 3
The third style of presenting the theoretical framework is that which introduces it at about the end of chapter 2.
Semantics-based Graph Approach to Complex Question-AnsweringJinho Choi
This paper suggests an architectural approach of representing knowledge graph for complex question-answering. There are four kinds of entity relations added to our knowledge graph: syntactic dependencies, semantic role labels, named entities, and coreference links, which can be effectively applied to answer complex questions. As a proof of concept, we demon- strate how our knowledge graph can be used to solve complex questions such as arithmetics. Our experiment shows a promising result on solving arithmetic questions, achieving the 3-folds cross-validation score of 71.75%.
Dr. Dorene Balmer PhD (Columbia University) is an expert on Qualitative Research methods and speaks through this webinar on Qualitative Methods, particularly through her own study on Resident Education.
This presentation discusses about content analysis, its use, Types, Advantages, Issues of Reliability & Validity, Problems, Quantitative content analysis, coding, Qualitative content analysis, Creative synthesis, Data reduction and Constant comparison.,
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
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THEORETICAL/CONCEPTUALFRAMEWORK
FRAMEWORK
- defined by the dictionary, is a skeletal or structural framework.
THEORETICAL
- means relating to or having the characteristics of theory.
THEORETICAL FRAMEWORK
- refers to the “set of interrelated constructs (concepts), definitions and propositions that presents a systematic view of phenomena by specifying relations among variables”.
KERLINGER THEORY (1973)
Theoretical framework indicates all the constructs (concepts), definitions and propositions that relate to a research problem.
A conceptual framework is an analytical tool with several variations and contexts. It is used to make conceptual distinctions and organize ideas.
THREE (3) STYLES
STYLE NO. 1
Theoretical framework is presented in the first or introductory chapter (JOURNALISTIC STYLE).
STYLE NO. 2
It is another style and popularly found in other theses and dissertations.
STYLE NO. 3
The third style of presenting the theoretical framework is that which introduces it at about the end of chapter 2.
Semantics-based Graph Approach to Complex Question-AnsweringJinho Choi
This paper suggests an architectural approach of representing knowledge graph for complex question-answering. There are four kinds of entity relations added to our knowledge graph: syntactic dependencies, semantic role labels, named entities, and coreference links, which can be effectively applied to answer complex questions. As a proof of concept, we demon- strate how our knowledge graph can be used to solve complex questions such as arithmetics. Our experiment shows a promising result on solving arithmetic questions, achieving the 3-folds cross-validation score of 71.75%.
Dr. Dorene Balmer PhD (Columbia University) is an expert on Qualitative Research methods and speaks through this webinar on Qualitative Methods, particularly through her own study on Resident Education.
This presentation discusses about content analysis, its use, Types, Advantages, Issues of Reliability & Validity, Problems, Quantitative content analysis, coding, Qualitative content analysis, Creative synthesis, Data reduction and Constant comparison.,
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
(Prefer mailing. Call in emergency )
This interactive session addresses the question “How do the Common Core State Standards affect college faculty and administrators?” The presenters provide an overview of the Common Core State Standards in Literacy, Mathematics, and the Next Generation Science Standards. A panel of teachers share from their experience using these standards in their classrooms. The session supports a rich discussion with participants regarding implications for community colleges in terms of student placement, teaching practices, and articulation with high schools.
Presented at the Statewide Collaboration of Early & Middle Colleges & Dual Enrollment Programs on Friday, January 31, 2014
http://extranet.cccco.edu/Divisions/AcademicAffairs/CurriculumandInstructionUnit/MiddleCollegeHighSchool/DualEnrollmentSummit.aspx
Presenters:
Dr. Erin Craig, Principal, NOVA Academy Early College High School, Santa Ana, CA
Dr. April Moore, Principal, JFK Middle College High School, Norco, CA
Sarah Calloway, Teacher, NOVA Academy Early College High School, Santa Ana, CA
Suena Chang, Teacher, JFK Middle College High School, Norco, CA
Katy McGillivary, Teacher, NOVA Academy Early College High School, Santa Ana, CA
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
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This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Nutraceutical market, scope and growth: Herbal drug technology
Blooms taxonomy
1. Bloom’s Taxonomy Interpreted for Mathematics
Lindsey Shorser
This document contains a description of Bloom’s Taxonomy, a educational
tool developed by Benjamin S. Bloom (1913-1999) that ranks the relative cogni-
tive complexity of various educational objectives. This taxonomy is often used
as an aid when create test questions and assignments. Following the description,
you will find Lindsey Shorser’s interpretation of Bloom’s Taxonomy in the con-
text of mathematical understanding with examples drawn from undergraduate
level topics.
Bloom’s Taxonomy of Cognitive Skills:
• Knowledge - retention of terminology, facts, conventions, methodologies,
structures, principles, etc.
• Comprehension - grasping of meaning, translation, extrapolation, inter-
pretation of facts, making comparisons, etc.
• Application - problem solving, usage of information in a new way
• Analysis - making inferences and supporting them with evidence, identi-
fication of patterns
• Synthesis - derivation of abstract relations, prediction, generalization, cre-
ation of new ideas
• Evaluation - judgement of validity, usage of a set of criteria to make con-
clusions, discrimination
Questions that encourage each of these skills often begin with:
• Knowledge: List, define, describe, show, name, what, when, etc.
• Comprehension: Summarize, compare and contrast, estimate, discuss, etc.
• Application: Apply, calculate, complete, show, solve, modify, etc.
• Analysis: Separate, arrange, classify, explain, etc.
• Synthesis: Integrate, modify, substitute, design, create, What if..., formu-
late, generalize, prepare, etc.
• Evaluation: Assess, rank, test, explain, discriminate, support, etc.
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2. This taxonomy can be used to invent test or assignment questions. Here is an
interpretation of each cognitive skill in a mathematical context. The example
questions are aimed for introductory level, single-variable calculus students, but
could be modified to apply to other courses.
Knowledge: Questions include ”State the definition”, ”State the theorem”,
or ”Use the specified method.”
E.g., Take the derivative of the following rational function using quotient rule.
Comprehension: Questions ask the student to use definitions or methods
to calculate something.
E.g., Find the slope of the tangent line to the following function at a given point.
Application: Questions which require the usage of more than one defini-
tion, theorem, and/or algorithm.
E.g., Find the derivative of the following implicitly defined function. (This
question could be used to test logarithmic differentiation as well, for instance)
Analysis: Questions require the student to identify the appropriate theo-
rem and use it to arrive at the given conclusion or classification. Alternatively,
these questions can provide a scenario and ask the student to generate a certain
type of conclusion.
E.g., Let f(x) be a fourth-degree polynomial. How many roots can f(x) have?
Explain.
Synthesis: Questions are similar to Analysis questions, but the conclusion
to be reached by the student is an algorithm for solving the given question.
This also includes questions which ask the student to develop their own classi-
fication system
E.g., optimization word problems where student generates the function to be
differentiated.
Evaluation: Questions are similar to Synthesis questions, except the stu-
dent is required to make judgements about which information should be used.
E.g., related rate word problem where student decides which formulae are to be
used and which of the given numbers are constants or instantaneous values.
Source: www.coun.uvic.ca/learning/exams/blooms-taxonomy.hrml
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