The document describes the development and validation of a Visualization Tendency Test. It involved three phases: generating and refining test items, exploratory factor analysis, and confirmatory factor analysis. The exploratory factor analysis revealed the test measured five factors of visualization tendency. The confirmatory factor analysis supported the five-factor structure and the test's validity and reliability. The final Visualization Tendency Test consists of 20 items measuring an individual's proclivity in five areas of visualization: generative, space-motor, instrumental, proactive, and representational. Further validation with larger samples is still needed.
National level data metrics framework development in Kouth Korea -Iljr RhaIlju Rha
The research study explores the potential of a national data set for learning analytics in the context of digital textbook usage in secondary education in South Korea
Instructional Contents Delivery through SPAT format in Mobile Environment: ...Ilju Rha
Instructional Contents Delivery through SPAT format in Mobile Environment: Introduction to L.i.B study system.
SPAT represents Still Picture+Audio+Text format digital knowledge unit. The slide was presented for Global Knowledge Alliances.
National level data metrics framework development in Kouth Korea -Iljr RhaIlju Rha
The research study explores the potential of a national data set for learning analytics in the context of digital textbook usage in secondary education in South Korea
Instructional Contents Delivery through SPAT format in Mobile Environment: ...Ilju Rha
Instructional Contents Delivery through SPAT format in Mobile Environment: Introduction to L.i.B study system.
SPAT represents Still Picture+Audio+Text format digital knowledge unit. The slide was presented for Global Knowledge Alliances.
Aparato Cardiovascular Generalidades e Insuficiencia Cardiaca en ImagenologíaNery Josué Perdomo
Muy importante el conocimiento general de este sistema de unas de las principales afecciones como lo es La Insuficiencia Cardiaca, este es un Síndrome de disfunción ventricular, y la incapacidad del corazón como bomba para enfrentar las necesidades del organismo.
Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.
A Small Helping Hand from me to my Engineering collegues and my other friends in need of Object Detection
Aparato Cardiovascular Generalidades e Insuficiencia Cardiaca en ImagenologíaNery Josué Perdomo
Muy importante el conocimiento general de este sistema de unas de las principales afecciones como lo es La Insuficiencia Cardiaca, este es un Síndrome de disfunción ventricular, y la incapacidad del corazón como bomba para enfrentar las necesidades del organismo.
Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.
A Small Helping Hand from me to my Engineering collegues and my other friends in need of Object Detection
Sheet1VARIABLE INFORMATION - POPULATION - 50 WAITERSGENDERMale27Fe.docxbjohn46
Sheet1VARIABLE INFORMATION - POPULATION - 50 WAITERSGENDERMale27Female2350AGE20-301330-402640 more 1150QUALIFICATION1 - Professional152 - Paraprofessional233 - Nonprofessional1250WORSITEOn-Site50Off-site050KNOWLEDGE BEFORE TRAININGwe will use some questions of the questionnaire that is in our research scenario. I dont know how you can use it. Level 1 - weak22Level 2 - medium19Level 3 - advanced950KNOWLEDGE AFTER TRAININGWE MUST DECIDE based on the quantitative analysis Level 1 - weak0Level 2 - medium0Level 3 - advanced0YEARS OF EXPERIENCE1-3 Years93-5 Years215 plus Years2050LEVEL OF CONFIDENCEwe also can use the answers from our questionnaire. Based on their correct answers we can measure their confidence1 to 33 to 66 to 10EXAM - cetificate of knowledgeReceived 38Non received 1250
Sheet1VARIABLE INFORMATION - POPULATION - 50 WAITERSGENDERMale27Female2350AGE20-301330-402640 more 1150QUALIFICATION1 - Professional152 - Paraprofessional233 - Nonprofessional1250WORSITEOn-Site50Off-site050KNOWLEDGE BEFORE TRAININGwe will use some questions of the questionnaire that is in our research scenario. I dont know how you can use it. Level 1 - weak22Level 2 - medium19Level 3 - advanced950KNOWLEDGE AFTER TRAININGWE MUST DECIDE based on the quantitative analysis Level 1 - weak0Level 2 - medium0Level 3 - advanced0YEARS OF EXPERIENCE1-3 Years93-5 Years215 plus Years2050LEVEL OF CONFIDENCEwe also can use the answers from our questionnaire. Based on their correct answers we can measure their confidence1 to 33 to 66 to 10EXAM - cetificate of knowledgeReceived 38Non received 1250
I. A Feedback Model of the Research Process
II. Strategies for Statistical Thinking
The purpose of this section is to provide students basic strategies to practice statistical thinking, in addition to fundamental applications.
Teaching statistical thinking and improving performance involves learning how to resolve a number of ambiguities during the statistical inquiry process that are not found in typical homework problems and exams. Inquiry with ill-structured problems requires a number of skills that need to be developed during the course:
a. “Generating a curiosity about the world that identifies “I wonder problems”;
b. Writing a measurable question that provides insight into these problems;
c. Determining relevant valid and accessible data;
d. Planning and carrying out data collection;
e. Checking, cleaning and organizing data;
f. Recognizing the data's limitations;
g. Analyzing and interpreting data;
h. Articulating findings;
i. Seeking explanations; and,
j. Generating further questions (4)”.
This iterative process often requires revision as new understandings develop and unanticipated problems or opportunities arise. The weekly discussion questions provide an opportunity to develop inquiry skills throughout the course. Inquiry is a well-accepted (but not always implemented) process in other subjects, such as science and social studies, but requires development.
Abstract: This paper presents a new face parts information analyzer, as a promising model for detecting faces and locating the facial features in images. The main objective is to build fully automated human facial measurements systems from images with complex backgrounds. Detection of facial features such as eye, nose, and mouth is an important step for many subsequent facial image analysis tasks. The main study of face detection is detect the portion of part and mention the circle or rectangular of the every portion of body. In this paper face detection is depend upon the face pattern which is match the face from the pattern reorganization. The study present a novel and simple model approach based on a mixture of techniques and algorithms in a shared pool based on viola jones object detection framework algorithm combined with geometric and symmetric information of the face parts from the image in a smart algorithm.Keywords: Face detection, Video frames, Viola-Jones, Skin detection, Skin color classification, Face reorganization, Pattern reorganization. Skin Color.
Title: Face Detection Using Modified Viola Jones Algorithm
Author: Alpika Gupta, Dr. Rajdev Tiwari
International Journal of Recent Research in Mathematics Computer Science and Information Technology
ISSN 2350-1022
Paper Publications
Describing latest research in visual reasoning, in particular visual question answering. Covering both images and videos. Dual-process theories approach. Relational memory.
this's my presentation during 610 class.
idea like how i gonna create that 3D phenomena to explain those concepts
but im not gonna use it anymore ... after so many things had change
Human visual intelligence visualization tendency aace2009
1. Development and Validation of a
Visualization Tendency Test
Ilju Rha, Sowha Park, Hyoseon Choi, Sookkyung Choi
Seoul National University
AACE 2009 e-learn, Vancouver, 28 Octorber, 2009
2. Content
Page 2
Introduction
Research Question
Research Process
Phase I: Generating and Refining Test Items
Phase II: Exploratory Factor Analysis
Phase III: Confirmatory Factor Analysis
Conclusion
3. The impacts of Visualization
Anecdotes
Einstein ….. Speed of light
Kekule ….. Molecular Structure of
Benzene
Faraday .…. Electromagnetic Fields
Feynman….. Feynman Diagrams
There is considerable evidence that much of our everyday
thinking is based on the formation and transformation of
visual images. Moreover, there are many accounts of the role
that visualization plays in the learning and teaching process.
”
“
Introduction
4. Introduction
Visualization refers to a mental process for
explaining, expecting, operating, and creating
objects, processes or events through imagery
formats (Rha, 2007; Stevick, 1986)
Most studies on Visualization have focused on
- effects of visuals on memorization (Pavio, 1986;
Marcus, Cooper, & Sweller, 1996; Harp & Mayer,
1998; Mayer & Moreno, 1998; Vekiri, 2002)
- understanding and idea construction (Gyselink &
Tradieu, 1999)
Page 4
6. Research Interests
Page 6
This study tried
- to define key constructs that are involved in
individuals’ visualization tendency.
- to develop and validate a tool to measure an
individual’s visualization tendency.
8. Phase I: Generating and Refining Test Items
An item pool was generated from two sources
- mundane visualization experiences of ordinary people,
- famous anecdote on visualization of extraordinary people
Page 8
9. Phase I: Generating and Refining Test Items
1. Mundane visualization
1) initially about 600 items were collected by 10
researchers of educational technology
2) 150 items were selected through three assessment
sessions with a team of experts consisting of 10
researchers (1 professor, 5 doctor students, and 4
mastery students)
3) After elimination items below 3 points out of 5, 26
items of visualization tendency from the dimension of
ordinary people’s mundane experiences were left
Page 9
10. Phase I: Generating and Refining Test Items
2. Visualization for extraordinary people
1) Leonardo da Vinci and Albert Einstein had been
recommended by experienced researchers of visuals
2) 49 items were collected from biographies and
documentary films on them
3) eliminating below 3 points out of 5
4) 16 items were remained from the dimension of
extraordinary people’s habitual tendency
Page 10
11. Phase II: Exploratory Factor Analysis
In order to discover what the test tried to measure and
to explore what constructs comprised this test,
1. Survey using the visualization tendency test
2. Exploratory factor analysis
153 undergraduate students taking pre-service teacher
education courses in two universities
49.7% were males, 46.4% females and 3.9% no answer
The analysis revealed that the visualization tendency
comprised of five factors with twenty question items.
Page 11
13. Phase III: Confirmatory Factor Analysis
In order to provide evidence for the validity of the
visualization tendency test,
- Confirmatory factor analysis by using a structural
equation model(SEM)
- AMOS 7.0 statistical program
- 155 undergraduate students taking pre-service teacher
education courses in two universities
- 54.2% were males, 44.5% females and 2.6% no answer
Page 13
14. Phase III: Confirmatory Factor Analysis
The confirmatory factor analysis procedures are based on
the following steps:
1) model specification
2) identification
3) estimation
4) testing fit
5) re-specification
Page 14
17. Phase III: Confirmatory Factor Analysis
Factors
(eigenvalue,
explained
variance)
Item Questions
Generative
Visualization
(4.12, 24.2%)
5 35. I tend to infer related or influencing factors when I
see things.
36. I am good at inventing or devising necessary or
gadgetry things by using imaginative-reasoning.
5. When touching or reaching a certain item with a hand,
I tend to figure the things in images.
38. I tend to associate things with other things that look
similar.
39. When looking at objects, I tend to fill the unseen or
missing parts of them figuring out the whole look.
Space-Motor
Visualization
(3.69, 21.7%)
4 27. When throwing an object, I can easily guess where the
object will reach when.
28. I can envision my movement in the axis of
coordinates.
9. While parking a car, I tend to picture the parking
motion of the car.
13. When playing some sports such as golf, football, and
swimming, I imagine my body movement in my head like
“image training”.
Page 17
18. Phase III: Confirmatory Factor Analysis
Factors
(eigenvalue,
explained variance)
Item Questions
Instrumental
Visualization
(3.67, 21.6%)
4 21. When I would explain a complicated story or a
person’s delicate characters, I can describe them by
pictures.
19. I tend to take notes by using visual languages such
as symbols, marks, diagrams or pictures.
20. When taking a note or learning some contents, I
tend to reorganize them in a figure, a picture or
table.
16. In attempting to figure out complicated matter, I
tend to draw diagrams or pictures.
Proactive
Visualization
(3.55, 18.5%)
4 14. When spending some free time, I tend to frame
and visualize something to myself.
15. I usually imagine my future with clear picture or
images
33. I tend to enjoy visualizing and imaging things and
matters.
8. When choosing some clothes, without trying on
myself I try to figure it out if they go well with me.
Page 18
19. Phase III: Confirmatory Factor Analysis
Factors
(eigenvalue,
explained variance)
Item Questions
Representational
Visualization
(2.40, 14.1%).
3 1. While listening to music or lyrics of a song, I usually
hit upon related scenes or images of the music or
song.
2. While reading a book, I tend to picture scenes to
myself.
3. While listening to a story, I tend to let my
imagination run.
Total 20
Page 19
20. Phase III: Confirmatory Factor Analysis
Page 20
Inventory for the Visualization Tendency Test
- consisting 20 items
- internal consistency of the scale (Cronbach’s Alpha =.796)
23. Conclusion
This visualization tendency test measures individual
learners’ inclination toward transforming information in
various modalities into the visual format
The test has 20 items in five factors for assessing
visualization tendency of individuals
Five factors are 1) Generative Visualization, 2) Space-Motor
Visualization, 3) Instrumental Visualization, 4) Proactive
Visualization, and 5) Representational Visualization
the present study requires further studies with a larger size
of sample, and also its generalization is demanded
conducting a concurrent validity analysis with other tests.
Page 23
24. “Pictures were for the illiterates.”
“Pedagogical and didactic use of visuals”
In the
Past
After
Comenius
Knowledge
Based
Society
“The Potential
instructional power of
human visual
intelligence grew
bigger.”
Conclusion
25. Hyoseon CHOI Page 25
Thank you!
Ilju Rha
Professor, Seoul National University
Korea
iljurha@snu.ac.kr