1 stephanie e. august, ph.d. allison neyer matthew j. shields james vales department of electrical...

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Stephanie E. August, Ph.D. Allison Neyer Matthew J. Shields James Vales Department of Electrical Engineering and Computer Science

saugust@lmu.edu

Michele Hammers, Ph.D.Department of Communication Studies

Loyola Marymount University, Los Angeles

* This material is based upon work supported by the National Science Foundation under Grants No. 093510 and 0942454. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

Co-opting Games and Social Media for

Education*

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The Challenges

• The NSF Cyberlearning initiative calls for engineering educators to respond to the compelling need for improved competitiveness in engineering-related fields

• The challenge: to attract – multi-talented individuals – who are interested in the study and practice of

engineering – in socially-aware and collaborative contexts

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Fun and Games

• The Virtual Engineering Sciences Learning Lab (VESLL) and the Teaching Artificial Intelligence as a Lab Science (TAILS) project – introduce a social element to the learning

experience – incorporate activities that provide the satisfaction

of accomplishment we often associate with game playing

– provide structured labs with exercises that can be completed before students leave the classroom to build a sense of accomplishment and confidence

VESLL

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• Interactive learning environment • Located on an “island” in Second Life• Built around a functional laboratory designed to

introduce students to engineering concepts through visualization and collaborative problem solving

• Assessment activities integrated into the in-world experience

• Imagine: a virtual version of a science museum • e.g., Exploratorium (San Francisco) or Pacific Science

Center (Seattle)• the opportunity to delve into engineering concepts

and maintain a sense of excitement about the experience

VESLL Overview

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Standard HexWindow

Toggles carry for tile increments/decrements

Returns current displayed value in base 10 in chat

Base of displayed number

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Standard HexWindowDisplays current base in floating text

When clicked, brings up dialog to offer choice of bases to switch between

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Welcome to the Crossword Puzzle Tutorial Guide!

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Crossword puzzle clues: AcrossAcross 1) FAF5B9698 - 2789BCA = ? (hex) 2) FACAEC - E = ? (hex) 3) D7B - CCC = ? (hex with a leading zero)4) 10C24 - FF77 = ? (hex)5) ACE + 7 + F418 = ? (hex)6) C0D0 + E = ? (hex)7) BAAC + 32 = ? (hex)

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Crossword puzzle clues: Down

Down 1) FB2 - 5 = ? (hex)2) FAEE - 20 = ? (hex)3) AD + 52 = ? (hex with a leading zero)4) BC + E = ? (hex) 5) FA31 + AD = ? (hex)6) 5F7 + 8009 + ED = ? (hex)7) 1F - 10 = ? (hex with a leading zero)8) C14 - 7 = ? (hex)9) 90E0 + 1C0D = ? (hex)

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Crossword Puzzle Solution

AND, OR, XOR Logic Gates

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Inverter and Circuit Components

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Flip Flop Display

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S/HE Café

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Scientist/Engineer Engineer

1. Grace Hopper Gracehopper Jules

2. Elijah McCoy Elijahmccoy Bizet

3. Alexander Graham Bell Alexanderbell Button

4. Henry Bessemer Henrybessemer Artful

5. Barbara McClintock Barbaramcclintock Adagio

6. Marie Curie Mariecurie Curteau

7. Jack Kilby Jackkilby Ixtar

8. Yuan Cheng Fung Yuanfung Bakerly

9. Hertha Ayrton Ayrtonherth Aubin

10.Martin Cooper Martincooper Copperfield

Avatars Famous Scientists and Engineers

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Preliminary Workshop Results

• 12 students, Intro to Computer Science (for non-majors)• Characteristics:

– Use email, PowerPoint, Blackboard– but not voice/video chat, teleconferencing,

photosharing sites, immersive platforms; don’t do web page development

• Feedback:– Related to course content– Helped student understand course content– Made course material more interesting

Teaching Artificial Intelligence as a Lab Science

TAILS

TAILS

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Tell a story about each AI Algorithm

• To be fully literate, students must be able to view software systems at many levels of abstraction

(Rasala, 1997; Crews, 1998; Lethbridge, 2000; Pour, 2000)

• Present algorithms in the context of– software engineering best practices– other computer science coursework – guided exercises that can be completing during class

period– the software “store”

• For CS undergrads and Systems Engineering MS students

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Components of TAILS Lab Experiments

1.The Idea: Explain what the program segment does without describing how it is implemented.

2.Applications: Real world applications

3.Sample Input/Process/Output: annotated trace of the program in execution (con-ops, black-box testing)

4. Implementation-independent Design Description: functional perspective, top-down manner

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Components of TAILS Lab Experiments

5. Implementation-specific “HINT” File(s): Partial implementation with HINTs that guide the user in implementing the remainder of the code

6.Test Suite and Driver(s): One driver for each implementation-specific HINT file with relevant data in the test suite

7.Experiments: Implementation-independent set of test data and expected results, plus ideas for enhancements and extensions

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Components of TAILS Lab Experiments

8.Source Code: The ending of the tale -- solutions to the exercise in the HINT files, more extensive implementations readily available from other sources.

9.Complexity Analysis: Complements the work done in a data structures or algorithms class; reveals the different ways to measure complexity

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9-Men’s Morris: Minimax Search

TAILS Learning Outcomes: Skills

Category Outcome Objective Assessment

Skills Students will demonstrate the ability to solve problems collaboratively

Student will demonstrate collaboration and teamwork skills

Students will work in pairs to complete the lab activities, then:• Complete a teamwork attitude questionnaire• Write a team process log to record perceptions about collaboration

TAILS Learning Outcomes: Concepts

Category Outcome Objective Assessment

Concepts Students will demonstrate knowledge of artificial intelligence concepts

Students will demonstrate recall and general understanding of AI concepts

• Answer exam questions• Complete pre- and post-tests• Explain and write software code • Draw a concept map (Angelo and Cross 1993, pp.197-202)

Students will demonstrate a deep understanding of course concepts

• Contrast multiple concepts Based on (Angelo and Cross 1993, p.168)• Define and give one example of a course concept (Angelo and Cross 1993, p.38)

Students will demonstrate knowledge of software engineering practices

Students will demonstrate proficiency in software engineering practices at background-appropriate (grade- and major-appropriate) level

• Specify requirements for a software program • Complete a domain-level design for a software program• Design an algorithm at an implementation-specific level• Reverse engineer software for an algorithm

TAILS Learning Outcomes: Communication

Category Outcome Objective Assessment

Communication

Students will be able to describe course concepts at multiple levels of abstraction

Students will be able to describe course concepts clearly and without technical jargon

•Write an elevator statement geared toward the student's grandmother to describe the concept (Angelo and Cross 1993, pp.183-187)

Students will be able to describe course concepts for a classmate or technical manager

•Write an algorithm in pseudocode to describe the concept for a technical manager

TAILS Learning Outcomes: Application and Research

Category Outcome Objective AssessmentApplication

Students will be able to identify applications of AI concepts

Students will be able to identify real world applications for AI concepts beyond those provided in course materials

•Complete application cards (Angelo and Cross 1993, pp.236-239)

Research Students will demonstrate curiosity about course material

Students will demonstrate the ability to extend course concepts

•Describe one new experiment that can be used in conjunction with each algorithm studied; explain the objective of the experiment and why this is a worthwhile objective

•Describe one enhancement to the algorithm studied and explain why the enhancement is worthwhile

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Future Work

• VESLL– Augment environment (e.g. activities,

biographies, salary info)– Add adventure-based collaborative problem-

solving– Develop automated docents to guide visitors– Provide a more reactive/reflexive environment

• TAILS– Plans to complete two “modules” for each of the

next 3 years– Merge with VESLL?

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Coming back to AI and Fun...

• VESLL and TAILS – Provide socially oriented activities (games requiring

teamwork and collaboration)– Facilitate the transformation between the macro- and

micro-level views of algorithms• Practical issue - platform migration

– Understand problem well enough to design at domain level, then migrate to specific platforms

– Provide a sustainable and sustained development environment

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Seeking VESLL Workshop Participants

• Student workshop (10 students)– 10 August 2010– Loyola Marymount University, Los Angeles– Stipend $ paid!

• Student and faculty workshop (10 students + 3 faculty)– Summer 2011– Loyola Marymount University, Los Angeles– Stipends for students $ and faculty $$$$!

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ReferencesAngelo, Thomas A. and Cross, K. Patricia. Classroom Assessment Techniques; A

Handbook for College Teachers. 2nd edition. San Francisco: Jossey-Bass, 1993.August, Stephanie E.

CCLI: Enhancing Expertise, Sociability and Literacy through Teaching Artificial Intelligence as a Lab Science. NSF Grant no.0942454, 2010

August, Stephanie E. and Hammers, Michele L. IEECI: Encouraging Diversity in Engineering through a Virtual Engineering Sciences Learning Lab. NSF Proposal no.0935100, 2009

Crews, Thad R. Emphasizing design in the computer science curriculum. Proceedings, 1998 Conference Frontiers in Education Conference, Tempe AZ, 1998. http://fie- conference.org/fie98/papers/crews.pdf (last accessed 21 May 2009).

Lethbridge, Timothy C. What knowledge is important to a software professional? Computer, May 2000, 44-50.

Pour, Gilda; Griss, Martin L.; and Lutz, Michael. The push to make software engineering respectable. Computer, May 2000, 35-43.

Rasala, R. Design issues in computer science education. SIGCSE Bulletin, 25:4, December 1997, 4-7.

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Stephanie E. August

saugust@lmu.edu

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Thank you!

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• To complete the conversion, try using the panels to count up/down in binary or hexadecimal

• Exercises (complete what you can in the allotted time)• convert decimal 10 to binary• convert decimal 10 to hexadecimal• convert binary 1011 to decimal• convert binary 1011 to hexadecimal• convert hexadecimal C to decimal• add 5 (binary 101) to 7 (binary 111)• subtract 4 (hex 4) from hexadecimal 1E21

• Jot your answers down on the “Problems” workshop before looking up/retrieving the answers.

Number System Exercises