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Computer-Supported Learning Environments

Andy Carleacarle@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 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)

Solo tasksInaccessibletasks

ZPD

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 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 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 Logo’s 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 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 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 overlays

PowerPoint 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:1.Students are given a multi-choice question2.They write down an individual answer3.The class “votes” their answer4.Students discuss in small groups, then

answer again.5.Another vote is taken6.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

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 student’s 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 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 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