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CSE 497: Intelligent Tutoring Systems
Professor Glenn D. Blank, Fall 2007
Office: 328 Packard Lab, 3:10-4pm and by appointment, 610-758-4867

Course description:
An intelligent tutoring system (ITS) provides individualized computer-based instruction to students. These systems emerged from application of artificial intelligence techniques to the computer aided instruction (CAI) systems. The difference is that an ITS usually compares the student's work with expert solutions or strategies, models the student's probably knowledge of a domain, and provides coaching or advice, taking into account what the student's knowledge state, preferred learning style, etc.

In this course, students will test drive several successfully deployed ITSs, learn ideas from artificial intelligence and cognitive psychology that are needed to build these systems, review and discuss fundamental papers in the field, construct small prototypes using two state of the art authoring tools, and analyze, design and develop a prototype ITS for a practical tutoring problem.

Goals and requirements:

Textbook: Beverly Woolf, Building Intelligent Tutors, manuscript available via Blackboard, and selected readings, below.

Syllabus and assignments (see selected readings and assignments below):
Aug 30, Introduction to intelligent tutoring systems; DesignFirst-ITS demo; project possibilities
Sep 6, CAI vs. ITS discussion; psychology of learning; Cognitive Algebra demo and CTAT
Sep 13, Rosh Hashana, no class
Sep 20, Domain and expert knowledge; think-aloud protocols; AnimalWatch demo
Sep 27, Constraint-based modeling; SQL-tutor demo;
Oct 4, More on student models: open learning models, emotions; Wayang Outpost demo;
Oct 11, Andes and Andes Physics demo; ASPIRE tutor due
Oct 18, Student modeling with Bayesian networks; Java problets demo;
Oct 25,Tutoring knowledge;
project requirements analysis due
Nov 1, Sally Moritz's Solution Generator and Expert Evaluation; Communication knowledge--pedagogical animated agents
Nov 8, Metacognition, inquiry and collaboration; Rashi demo
Nov 15, Communication knowledge--Natural language processing; Autotutor demo; project design due
Nov 22, Thanksgiving break
Nov 29, Web-based tutors; ELM-ART demo; Learning styles in a pedagogical advisor (Shahida Parvez)
Dec 6, Evaluation and Future of tutors and student project prototype presentations
Dec 19, Final projects due (no final exam)

Selected Readings:

Intelligent tutoring systems on the web:
· AnimalWatch (screen shots and downloadable zip file) teaches math concepts by investigating animals
· SQL-Tutor Constraint-based tutoring system for learning database Structured Query Language (login as glenn blank)
· Wayang Outpost (screen shots and Flash-based web site) helps students prepare for math SATs
· Andes physics tutor provides step-by-step feedback and hints on physics homework problems
· StatTutor facilitates understanding of statistical ideas and analysis (CMU)
· Java Programming Problets exercise understanding of Java concepts
· ELM-ART (Episodic Learner Model Lisp Tutor)
· Rashi inquiry-based tutors for supporting or refuting hypotheses (watch the intro Flash movie first)
· Professor Blank has AnimalWatch and Autotutor on CDROM

Conventional e-learning (CAI) on the web:
· E-learning and customer loyalty article claims: "Customer education can be a vital tool for both acquiring and retaining customers."
· Mrs. Glosser’s Math goodies
· Interactive patient (medicine) lessons
·'s demo, introducing Java
· w3schools courses (including HTML, Javascript, XML, SQL, etc.)
· Webmonkey e-learning lessons (including JavaScript, HTML, etc.)
· Quia teaches facts about state capitols drill and practice by matching.
· Mathdork for Algebra I teaches concepts with animation in these lessons. teaches procedures on various technical tools and concepts.
· Lesson on computer networks, from The Universal Computer with Flash animation, text, sound, and interactivity (login as gdb0 0bdg)

Homework assignments:
#1, due Thursday, 9/6, 10am: Write 1-2 page paper comparing an Intelligent Tutoring System and a Computer Aided Instructional (or e-learning) system (select one from the above lists). Compare and contrast interesting pedagogical features, pros and cons. Upload your paper to Blackboard (assignments, #1, attach file).

#2, due Wednesday, 9/19, 1pm : Using CTAT, create an example-tracing tutor that provides pedagogical feedback to students learning how to subtract fractions. To make it interesting, the problem should deal with carrying across multiple columns. Upload your behavior recorded file (a file with extension “. brd ” inside of the “Problem Organizer” folder) to to Blackboard (assignments, #2, attach file).

#3, due Thursday, 9/27, 10am: Think Aloud Protocol Analysis for Tic-Tac-Toe (TTT). See Blackboard for details after September 20.

#4, due Thursday, 10/11, 10am: Using the ASPIRE authoring tool, create a constraint-based tool for subtracting two fractions. See Blackboard for details after September 27.