Transcript Computer-Supported Learning Environments Andy Carle [email protected] CS 260 – Fall 2006 11/7/2015 Outline  Review of learning principles  Design Patterns for Education * The Pedagogical Patterns Project *

Computer-Supported
Learning Environments
Andy Carle
[email protected]
CS 260 – Fall 2006
11/7/2015
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Outline
 Review of learning principles
 Design Patterns for Education
* The Pedagogical Patterns Project
* PACT
 Constructionist Learning Systems:
*
*
*
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Microworlds
Group Learning Systems
Peer Instruction Systems
Integrated Learning Environments
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Building Understanding
 Learning is a process of building new
knowledge using existing knowledge.
 Knowledge is not acquired in the abstract,
but constructed out of existing materials.
 Like any other human process, HCI
researchers/practitioners seek to
mediate learning via technology.
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Constructivism
 Piaget: Learners construct new knowledge
from their experiences via cycles of
accommodation and assimilation
 Accommodation: The process of reframing
one’s mental representation of the world to
be in line with new experiences
 Assimilation: Internalizing new experiences
that fit the model one has already developed
 Constructivism is not a pedagogy
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Constructionism
 A pedagogy designed to explicitly facilitate
the learning methods suggested by
constructivism
 Developed by Seymour Papert and colleagues
at MIT in the 1960s
 Explicitly claims that the construction of
external artifacts is critical to the building
of internal models
* Works even better with social artifacts
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Scaffolding
 Refers to the process of shaping the
learner’s experience while learning, by
creating a “scaffold” to guide their actions.
 Generally, the teacher begins by doing most
or all of the task.
 The task is repeated, with the learner
doing more and more of it.
 Eventually, the learner does the entire task
themselves – the scaffold is removed.
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Scaffolding and ZPD
 Scaffolding produces a steady progression
through the learner’s ZPD (Zone of Proximal
Development)
ZPD
Inaccessible
Solo tasks
tasks
Scaffolded learning
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Design Patterns
 An abstraction of a commonly recurring design
problem and its contextualized solution
* Designed to inform users working in different contexts
 Originated by Christopher Alexander in the study
of architectural design problems
* “Each pattern describes a problem which occurs over and over
again in our environment, and then describes the core of the
solution to that problem, in such a way that you can use this
solution a million times over, without ever doing it the same way
twice” - Alexander
 A process by which ordinary people can capture the
essence of a design decision by seeing how experts
think about common problems in the domain
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Alexander, Ishikawa, & Silverstein, 1977.
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The Pedagogical Patterns Project
 Goals
* Recreate the success of design patterns in architecture and
software engineering in the space of pedagogical theory
* Identify and disseminate context-neutral abstractions of best
practices for teaching
* Encourage instantiation of these patterns in diverse situations
 Early work by Sharp, Manns, Prieto, and McLaughlin focused on
teaching object-oriented programming concepts
* Subsequent work by Joe Bergin extended the focus to general CS
education
 Pattern Format:
* Description of the problem
* Forces governing the application of the pattern
* Description of the solution
* Advice on implementing the solution
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Sharp et al., 2000. http://www.pedagogicalpatterns.org/
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A Pedagogical Pattern: Early Warning
 You teach a course in which ideas build upon one another and students will
be lost if they do not understand early material
 Your students may not realize that they are falling behind or that they
have misconceptions, but you are in a better position to recognize it.
Students may waste time and effort if they have fallen behind or have
misunderstood, but time is short. If your students fall behind or miss
early material it will be difficult for them to catch up and succeed.
 Therefore, give them early warning when you see that they are not coping
with the amount of work, or they have misunderstood some topic. Advice
is best if it points a path to success, not just pointing out the roadblock.
The earlier you give the advice, the better chance for success in the
student. This can take many forms. If your course has special pitfalls for
the student, you can publish these on your course FAQ.
 It helps if you give frequent short exams and quickly return the marked
papers. Some universities require exams in every course every Friday, for
example.
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from: Bergin et al., Feedback Patterns
http://www.pedagogicalpatterns.org/current/feedback.pdf
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Problems in Practice
 Pedagogical patterns have a tendency to be
too abstract to be useful.
* Difficult to apply to a new context
 Pattern-informed environments rarely reveal
clues about the underlying patterns to the
untrained observer
 Collaboration between content experts and
pedagogical specialists is rare
* Individuals that can fill both roles are even more scarce.
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Pattern Annotated Course Tool
 Research project intended to bridge the gap
between pedagogical patterns in theory and
in practice
 Visual editor in which expert course
designers can create representations of
their own courses, complete with references
to pedagogical patterns
 Novice instructors can see patterns
instantiated in a context that they can
relate to directly
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Learning Theory in PACT (1/2)
 Make Thinking Visible
* Enable virtual navigation for exploring complex
(physical) systems
* Model scientific thinking
* Provide knowledge representation tools
 Help Students Learn From Each Other
* Encourage learners to learn from others
* Scaffold the process of generating explanations
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Learning Theory in PACT (2/2)
 Promote Autonomous Life Long Learning
* Encourage reflection
* Engage learners as critics
 Make Theory Accessible
* Connect to personally relevant examples
* Provide students with templates to help reasoning
* Reduce complexity to help learners recognize salient
information
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Demo
 PACT is available for download from
http://www.cs.berkeley.edu/~acarle/PACT/
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Constructionist Learning Systems
 Microworlds
* Logo, Microworlds, Boxer
 Group Learning Systems
* TVI, DTVI, Livenotes
 Peer Instruction Systems
* Flashcards, PRS
 Integrated Learning Environments
* WISE, UC-WISE
 Inquiry Based Systems
* Thinker Tools, Inquiry Island
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Microworlds
 Give students a sandbox in which they can explore
and test their mental models
 Provide far more functionality than would be
obviously useful to beginners
* Usually with no explicit scaffolding to keep them away from
advanced features
 Microworlds encourage less structured
exploration by learners.
 The learner’s discoveries should be driven
more by their own goals, leading to better
learning.
 The structure of the Microworld should
ensure that they make the right inferences.
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Patterns
 Built-In-Failure
 Test Tube
 Try it Yourself
 Larger than Life
 Real World Experience
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Logo
 The Logo project began in 1967 at MIT.
 Seymour Papert had studied with Piaget in Geneva. He arrived
at MIT in the mid-60s.
 Logo often involved control of a physical robot called a turtle.
 The turtle was equipped with a
pen that turned it into a simple
plotter – ideal for drawing math.
shapes or seeing the trace of a
simulation.
 Original turtle (Irving) could go
forwards, backwards, left, right,
and could ring a bell.
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Logo
 Early deployments of Logo in the 1970s happened in
NYC and Dallas.
 In 1980, Papert published “Mindstorms” outlining a
constructionist curriculum that leveraged Logo.
 Logo for Lego began in the
mid-1980s under Mitch
Resnick at MIT.
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Logo
 The “Microworlds” programming environment was
created by Logo’s founders in 1993. It made better
use of GUI features in Macs and PCs than Logo.
 In 1998, Lego introduced
Mindstorms which had
a Logo programming
language with a visual
“brick-based” interface.
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Logo
 Logo was widely deployed in schools in the 1990s.
 Logo is primarily a programming environment, and
assignments need to be programmed in Logo.
 Unfortunately, curricula were not always carefully
planned, nor were teachers well-prepared to use
the new technology.
 This led to a reaction against Logo from some
educators in the US. It remains very strong
overseas (e.g. England, South America).
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Uses of Logo
 Logo is designed to create “Microworlds” that
students can explore.
 The Microworld allows exploration and is “safe,”
like a sandbox.
 Children “discover” new
principles by exploring a
Microworld.
 e.g. they may repeat some
physics experiments to learn
one of Newton’s laws.
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Boxer
 Boxer is a system developed at Berkeley by Andy
diSessa (one of the creators of Logo).
 Boxer uses geometry
(nested boxes) to
represent nested
procedure calls.
 It has a faster learning
curve in most cases
than pure Logo.
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Strengths of Logo
Very versatile.
Can create animations and simulations quickly.
Avoids irrelevant detail.
Tries to create “experiences” for students (from
simulations).
 Provides immediate feedback – students can change
parameters and see the results right away.
 Representations are rather abstract – which helps
knowledge transfer.
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Weaknesses of Logo
 Someone else has to program the simulations etc –
their design may make the “principle” hard to
discover. Usability becomes an issue.
 The “experience” with Logo/Mindstorms is not real-
world, which can weaken motivation and learning.
 The “discovery” model de-emphasizes the role of
peers and teachers.
 It does not address meta-cognition.
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Group Learning Systems
 Students tend to synthesize material more
thoroughly when they feel that they are
creating a social artifact
 Strong mental associations are constructed
between abstract course contents and
concrete concepts, such as other people or a
particular conversation
 Patterns:
* Invisible Teacher
* Groups Work
* Study Groups
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TVI
 TVI (Tutored Video Instruction) was invented by
James Gibbons, a Stanford EE Prof, in 1972.
 Students view a recorded lecture in small groups
(5-7) with a Tutor.
They can pause, replay,
and talk over the video.
 The method works with
a live student group, but
also with a distributed
group, as per the figure
at right.
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DTVI
 Sun Microsystems conducted a large study of
distributed TVI in 1999.
 More than 1100 students participated.
 The study showed
significant improvements
in learning for TVI
students, compared to
students in the live
lecture (about 0.3 sdev).
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DTVI
 The DTVI study produced a wealth of interesting
results:
 Active participation was high (more than 50% of
students participated in > 50% of discussions).
 Amount of discussion in the group correlated with
outcomes (exam scores).
 Salience of discussion did not significantly
correlate with outcome (any conversation is
helpful??).
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Livenotes
 TVI requires a small-group environment (small
tutoring rooms).
 Livenotes attempts to recreate the small-group
experience in a large lecture classroom.
 Students work in small virtual groups, sharing a
common workspace with wireless Tablet-PCs.
 The workspace overlays
PowerPoint lecture slides,
so that note-taking and
conversation are
integrated.
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Livenotes Interface
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Livenotes Findings
 The dialog between students happens
spontaneously in graduate courses – where student
discussion is common anyway.
 It was much less common in undergraduate courses.
 Students have different models of the lecture –
something to be “captured” vs. some that is
collaboratively created.
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Livenotes Findings
 But what was very common in undergraduate
transcripts was student “dialog” with the
PowerPoint slides:
 Students often
add their own
bullets.
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Peer Instruction Systems
 Peer instruction (Mazur) is a pattern that
encourages all these steps:
1. Students are given a multi-choice question
2. They write down an individual answer
3. The class “votes” their answer
4. Students discuss in small groups, then
answer again.
5. Another vote is taken
6. The instructor explains the right answer.
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Patterns and Purpose
 Invisible Teacher
* Other students are able to recognize misconceptions in an
individual that an instructor may not be able to anticipate
 Active Student
* Students that know they will need to prove their
understanding to a peer tend to engage in the learning
process more actively
 Own Words and Early Warning
* Students often under-appreciate the basic concepts of a
course while focusing on the details of particular methods.
By having students address non-trivial questions in their
own words with their fellow students one can expose this
underlying lack of understanding.
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Flashcards
 Inexpensive
and easy
 Difficult
to process
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Personal Response System
 Completely
anonymous response
 Ensures near 100%
participation
 Allows recording of
input, confidence
levels, and instant
summary of answers
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Inquiry-Based Systems
 A development of Piaget based on similarities
between child learning and the scientific method.
 In this approach, learners construct explicit
theories of how things behave, and then test them
through experiment.
 The “ThinkerTools” system (White 1993) realized
this approach for “force and motion” studies.
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Inquiry cycles
 Inquiry-based learning
makes student’s metacognitive strategy
explicit.
 It also treats learning as
a kind of scientific
research.
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Inquiry cycles
 Question: a new problem for the
learner
 Hypothesis: Learner proposes a
solution or a way to understand
the problem better
 Investigate: Learner figures a
way to try out the hypothesis
(often an experiment)
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Inquiry cycles
 Analyze: understand the
results of the investigation.
 Model: Construct a model or
principle for what’s going on.
 Evaluate: Evaluate the
model, the hypothesis,
everything that came before.
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ThinkerTools
 The tools include simulation (for doing
experiments) and analysis, for interpreting the
results.
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ThinkerTools
 Students can modify the “laws of motion” in the
system to see the results (e.g. F=a/m instead of
ma).
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Agents: Inquiry Island
 An evolution of the
ThinkerTools project.
 Inquiry Island includes a
notebook, which structures
students inquiry, and
personified (software agent)
advisers.
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Inquiry Island
 Task advisers:
* Hypothesizer, investigator
 General purpose advisers:
* Inventor, collaborator, planner
 System development advisers:
* Modifier, Improver
 Inquiry Island allows students
to extend the inquiry scaffold
using the last set of agents.
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Integrated Learning Environments
 Web-Based Inquiry Science Environment
(WISE)
* UC Berkeley TELS group
* Middle School ~ High School science classes
 UC-WISE
* TELS group + CS Division
* UC Berkeley & Merced lower division CS courses
 Sakai
* Multiple institutions
* Called bSpace in the UC system
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“The WISE Way”
 Simple authoring environment to encourage
iteration and experimentation by the
teacher
 Inquiry-driven learning environment in which
students learn about a topic while constantly
having their understanding checked
 A gateway to peer instruction, group
learning, and various microworlds
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UC-WISE Goals
 to provide technology and curricula for
laboratory-based higher education courses
that incorporate online facilities for
collaboration, inquiry learning, and
assessment, and to investigate the most
effective ways of integrating this
technology into our courses
 to allow instructors to customize courses,
prototype new course elements, and collect
review comments from experienced course
developers.
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UC-WISE Features
 Learning Management System
* Cohesive collection of lessons, tasks, assignments,
assessments, and related info
 Collaborative Tools
* Brainstorms, discussion forums, collaborative reviews
 Inquiry-Based Tools
* Web-Scheme, Eclipse exercises, Web-Java
 Meta-Cognitive Tools
* Quick quizzes, “extra brain,” peer assessment
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Results
 Early Warning patterns are easily
instantiated using quizzes and
brainstorms in UC-WISE
* These activities have become the key to
successful UC-WISE courses
 Real time feedback affords TVI-like
intervention by the lab TA
 The courses are viewed as very timeintensive, but worthwhile
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