ComputerSupported Learning Environments

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Computer-Supported Learning Environments

• Andy Carle
• acarle_at_cs.berkeley.edu
• CS 260 Fall 2006

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Outline

• Review of learning principles
• Design Patterns for Education
• The Pedagogical Patterns Project
• PACT
• Constructionist Learning Systems
• 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 ones
  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 learners
  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 learners ZPD (Zone of Proximal Development)

ZPD
Inaccessibletasks
Solo 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

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

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.

from Bergin et al., Feedback Patternshttp//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 learners 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 apen that turned it
  into a simpleplotter ideal for drawing
  math.shapes or seeing the trace of asimulation.
  
• 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 Logos founders in 1993. It made
  better use of GUI features in Macs and PCs than
  Logo.
• In 1998, Lego introducedMindstorms 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 Newtons 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 witha live student group,
  butalso with a distributedgroup, as per the
  figureat 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 improvementsin
  learning for TVIstudents, compared tostudents
  in the livelecture (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 overlaysPowerPoint lecture
  slides,so that note-taking andconversation 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 oftenadd their ownbullets.

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Peer Instruction Systems

• Peer instruction (Mazur) is a pattern that
  encourages all these steps
• Students are given a multi-choice question
• They write down an individual answer
• The class votes their answer
• Students discuss in small groups, then answer
  again.
• Another vote is taken
• 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

• Inexpensiveand easy
• Difficultto 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 students
  meta-cognitive 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 whats
  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. Fa/m instead of
  ma).

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Agents Inquiry Island

• An evolution of the ThinkerTools project.
• Inquiry Island includes anotebook, which
  structuresstudents 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 studentsto extend the
  inquiry scaffoldusing 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 time-intensive,
  but worthwhile