1
Ubiquitous Learning
環境中的測驗與評量
國立臺南大學 黃國禎
數位學習科技系 教授
資訊教育研究所 所長／理工學院 院長
gjhwang@mail.nutn.edu.tw
Agenda
Introduction to ubiquitous computing
Intelligent tutoring and adaptive learning
How ubiquitous computing benefits learning?
Minimal Requirements for building a
context-aware u-learning environment?
When should context-aware u-learning be
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Evolution of Learning Environments
In-class learning
Real world
Computer-Aided Learning (CAL)
Computer world
Web-based Learning (WBL)
Cyberspace
Mobile Learning (M-Learning)
Cyberspace + any where access
Ubiquitous Learning (U-Learning)
Cyberspace +
any where access +
real world
Introduction to
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From Designer View
Physical integration
a ubiquitous computing system involves
some integration between
computing
nodes
and the
physical world
.
Spontaneous interoperation
Communicating components can change
both identity and functionality over time as
its circumstances change
From User View
Computing with Natural Interfaces
Context Aware Computing
Automated Capture and Access to Live
Experience
Everyday Computing
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Computing with Natural Interfaces
Context Aware
Computing
minimal set of necessary
context:
Who : User and other people in the
environment.
When : User activity relative changes in time.
Where : The physical location of the user.
What : Interpretations of user activity.
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Automated Capture and Access to
Live Experiences
Not only trying to remember the important pieces
of information
Tools to support automated capture and access
to live experiences
Remove the burden of doing something humans
are not good at (i.e., recording) so that they can
focus attention on activities they are good at (i.e.,
indicating relationships, summarizing, and
Mobile devices & sensors
Wireless communications
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Everyday Computing
Support the informal and unstructured activities of
our everyday lives.
Providing continuous interaction moves computing
Evolution from M to U is going on
Note: E/M/U-Computing is not specially
designed for educational purpose
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Intelligent Tutoring &
Adaptive Learning
Categories of Relevant
Technologies
Intelligent Tutoring System (ITS)
technologies
Curriculum sequencing
Problem solving support
Adaptive hypermedia technologies
Adaptive navigation support
Adaptive presentation
Web-inspired technologies
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Curriculum Sequencing
Also referred to as Instructional Planning
Technology
Helps the student to find an "optimal path"
through the learning material
Two levels of sequencing
High-level sequencing or knowledge sequencing
determines next learning subgoal: next concept, set of
concepts, topic, or lesson to be taught
Low-level sequencing or task sequencing
determines next learning task (problem, example, test) within
current subgoal
E/M to U: Plan curriculum sequencing and guide
students to learn in the real world
Problem Solving Support (1)
Main duty and main value of ITS
technology
Three technologies
Intelligent analysis of student solutions
Interactive problem solving support
Example-based problem solving support
E/M to U: Problems solving scenery moves from
virtual world to real world
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Problem Solving Support (2)
Intelligent analysis of student solutions
deals with students' final answers
decide whether the solution is correct or not
find out what exactly is wrong or incomplete
identify which missing or incorrect knowledge
may be responsible for the error (knowledge
diagnosis)
provide student with extensive error feedback
and update the student model (eg: PROUST
[Johnson, 1986])
E/M to U: Problems solving scenery moves from
virtual world to real world
Problem Solving Support (3)
Interactive problem solving support
provide intelligent help on each step of problem
solving Instead of waiting for the final solution
The levels of help vary from signaling about a wrong
step, to giving a hint, to executing the next step for the
student
The systems (often referred to as interactive tutors)
can watch the actions of the student, understand
them, and use this understanding to provide help and
to update the student model. (eg: LISP-TUTOR
[Anderson, 1985])
E/M to U: Problems solving scenery moves from
virtual world to real world
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Problem Solving Support (4)
Example-based problem solving support
helping students to solve new problems by
suggesting them relevant successful problem solving
cases from their earlier experience (eg: ELM-PE
[Weber, 1996], ELM-ART [Brusilovsky, 1996] and
ELM-ART-II [Weber, 1999])
E/M to U: Problems solving scenery moves from
virtual world to real world
Adaptive Navigation Support
Support the student in hyperspace orientation
and navigation by changing the appearance of
visible links
Has more options than traditional sequencing: it
can guide the students both directly and
indirectly
Three most popular ways
direct guidance
adaptive link annotation
adaptive link hiding
E/M to U: Will the behaviors of the student in the
real world affect the adaptation of the hypermedia?
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Adaptive Presentation
Adapt the content of a hypermedia page to the
user's goals, knowledge and other information
stored in the user model
Pages are not static, but adaptively generated or
assembled from pieces for each user
For example, expert users receive more detailed
and deep information, while novices receive
more additional explanation
E/M to U: Will the behaviors of the student in the real
world affect the presentation of the hypermedia pages?
Student Model Matching
adaptive collaboration support
use system's knowledge about different
students to form a matching group for
different kinds of collaboration
intelligent class monitoring
identify the students who have learning
records essentially different from those of
their peers
to find students who need special attention
E/M to U: Do the behaviors of the student in the real
world provide useful information?
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Introduction to
How u-computing technologies
benefit learning activities?
A u-computing environment is able to sense
personal behaviors in the real world
It is able to provide more information to
support adaptive
learning
It is able to
guide
the learner
in the real world
It is able to
judge
the learner’
s behaviors
in the real world
is correct
It is able to
more actively provide
necessary information
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Four steps of providing u-learning
system services
Setting instructional requirements for each of the
learner’
s learning actions
Detecting the learner's behaviors
Comparing the requirements with the
corresponding learning behaviors
Characteristics of a U-Learning
Environment
Context aware : the learner’
s situation or the situation of
the real-world environment in which the learner is
located can be sensed.
Actively provides personalized supports the right place,
and at the right time, based on the personal and
environmental situations of the learner in the real world
as well as the profile and learning
Learning anywhere and anytime; that is, the learner is
allowed to learn without being interrupted while moving
Be able to adapt the subject contents to meet the
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U-learning vs M-learning
System can record
the real world
information
of the learner.
Learning portfolio records the
on-line behaviors
of the
learner.
System
can
more actively
provide
personalized information or
services to the learners based on
real world context
Learners
need to actively
access the system via wireless
networks.
In addition to access the on-line
database, it is able to
sense
the
learner’
s situation
in the real world
.
understands the learner’
s
situation by accessing the
on-line database
.
U-Learning
M-Learning
More parameters are available in a
u-learning environment
Personal situation in the real world:
learner’
s location, time
of arrival, temperature
, heartbeat, blood pressure, etc.
Environmental situation : the sensor’
s ID and location, the
temperature, humidity, air ingredients, and other parameters of
the environment around the sensor
Feedback from the sensor : the sensed values of the target,
e.g.
PH value of water
.
Personal data in the database :
learner’
s profile and learning
portfolio
, such as the predefined schedule, starting time of a
learning activity, the longest and shortest acceptable time
period, place, learning sequences.
Environmental data in the database :
equipment in the lab,
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Example 1: Arrange the students to
Learn in the real world with on-line
guidance
U-learning system:
Now we are going to learn to
identify the TYPE of a plant. Can you see the plant in front of you?
Your Ans: Yes.
U-learning system: Can you identify the type of the
plant.
> Your Ans : No.
> U-learning system: What is the color of the plant?
> Your Ans : Green.
> U-learning system: Is the plant one trunk?
>Your Ans : No.
YES NO
OK
Example 2: Evaluate the students by
asking them to identify real world
objects
U-learning system:
Now we are going to evaluate
your knowledge concerning the TYPE of plants. The time limit of the first test item is 15 minutes. Are
you ready?
Your Ans: Yes.
U-learning system: Find all of the plants with
“Herb”type in the campus by clicking the
“Confirm”bottom of your learning device while you are in front of the plants.
．．．．．．．．．．．．
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Example 3: Conduct Real world
observations with online information
supports
U-learning system:
Now we are going to learn to
recognize the plants in the campus via identifying their features. Can you see the plant in front of you? Your Ans: Yes.
U-learning system: Do you know the name of this
plant?
> Your Ans : No.
> U-learning system: Connect to the plant database, which will help you in recognizing the plant. When you are ready to answer this question, click the “Ready”bottom.
………..
Example 4: Conduct Cooperative
problem solving in the real world
with on-line assistance
U-learning system:
John, now you are in the
northern-west area of the campus. You can see the locations of your team members on the screen of the learning device. There is a communication window in the up-right corner of the screen that allows you to communicate with them. What you need to do is to complete the map of the campus by locating each building and avenue in the correct position.
(John walking………..)
U-learning system: The location has been occupied
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Characteristics of ideal u-learning
Context aware: At least the location of the
student and the environmental parameters of
that location can be sensed.
Active support: The system is able to actively
provide personalized guidance for each student.
Learning in real world: Real world learning and
assessment are enabled with on-line supports.
Seamlessly learning: The u-learning system can
provide continuous supports without being
Minimal Requirements for building a
context-aware u-learning environment?
A set of readers (or sensors) that sense the
situation (at least location) of the learner (e.g.,
RFID readers)
A set of tags that can be used to identify each
learner
A server that can access the user’
s situation
from the readers
A mobile device that can display the messages
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When should context-aware
u-learning be applied?
Do the learners need supports from the system?
Do we need personalized instructions?
Do the instructions or supports need to be given
actively?
Do the learners need to move from places to
places during the learning process?
Do the learners need to learn in the real world?
Does the context (e.g. location or environmental
temperature) of the learner affect the learning
process?
Three levels of U-Learning
Provide individualized guidance in real world
learning
For naive learners
Provide adaptive supports in real world learning
For learners with different backgrounds and
experiences
Provide hints or necessary reminding in real
world learning
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Case Study on Training Single-Crystal
X-ray Diffraction Researchers
Single-Crystal X-ray Diffraction is the most
effective method for
analyzing 3D structure of
compound materials
The researchers need to
move from places to
places
to operate different equipment
It is time-consuming to train a new researcher
(usually 1-2 years)
The operations could be dangerous, and hence
the learner requires full-time guidance during the
training process
Microscope products –examining, selecting, crystal mounting leaner Indexing, data collecting Centering and aligning the sample Single Crystal X-ray Diffractometer
Instructing Data transmitting
Data transmitting PC Data processing & Structure determination PC (1) (2) (3) Location: 2nd floor, R 203 Location: 1st floor, R 126 Expert System Ubiquitous learning environment Give advice or hints based on the context Context of learner RFID Temperature meter
Is U-learning equal to “
context-aware
ubiquitous learning”
?
The criteria of building a fully functional
u-learning environment is still undefined.
The e-learning system can
more actively
provide
more adaptive
supports according to the
learner’
s context in the real world
.
The real-world observation and problem-solving
abilities can be trained and evaluated in such a
context-aware environment.
Training for operations of a complex procedure
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