1. Introduction A. point: decompose "knowledge communication system" B. jargon knowledge communication systems tutoring sys student knowledge/expertise in some domain CAI - computer aided instruction presents a curriculum static pre-stored presentation ITS - about the same as KCS models an active expert contains knowledge to be communicated can apply knowlege within domain C. characteristics of intelligence knowledgable able to learn able to adapt able to apply knowledge able to reason about "symbols" D. components domain knowledge student model pedagogical knowledge interface E. evaluation of article purposely not specified the learning and/or underlying pedagogical theory the domain/topic/curriculum content the target student population population characteristic (novice, expert, ...) the target setting (classroom, lab, industry, etc.) implied to be classroom? several possibilties described the pedagogical goals (if any) of the system describe typical interaction scenario 2. Domain knowledge: the object of communication A. The functions of expert module generate solutions to problems generate (multiple) solution paths explicit standard of evaluation - direct knowledge comparison B. Aspects of communicability domain knowledge related to pedagogy relations between knowledge items relative acquisition difficulty of knowledge items explanation rationales = goals + causes explanation = analogy or taxonomy transparency - can student observe expert's internal functions? psychological plausibility - does expert reason like human? particular viewpoint biased by knowledge representation language choice of atomic primitives expert & student should share or understand viewpoints good teachers adapt to compensate for differences 3. Student model: the recipient of communication A. difficult to model student hard for people to understand each other limited communication channel between human & computer perfect model not required for reasonable pedagogical decisions B. information observe student behavior interpret ("understand") actions reconstruct student knowledge from interpretations directly compare student knowledge to expert knowledge high resolution comparison allows finely directed tutoring sources of incorrect or suboptimal behavior incomplete knowledge incorrect versions of knowledge model can specify incorrect knowledge, accompanied by remedial actions explanatory information C. representation expert's knowledge "language" often insufficient for student must accomodate incorrect knowledge construct both expert & student languages from primitives neutral primitives language does not specify correctness can't account for all observed errors in advance error primitives observe & catalog errors first use cataloged errors as language primitives limits language can use experience of experts to build catalogs executability/runnability student model contains all pertinent information includes information outside of domain of expert execute model to predict particular student's behavior D. the diagnostic model: accounting for data diagnosis reconstruct student's goal structure model student's knowledge automated theory formation - find theory to fit data automatic programming - program to implement behavior "direction" of analysis top-down - observe methods used to achieve goals bottom-up - observe single steps driving force behind analysis model - modify model to fit data change data - model constructed from data primitives problems model size requires huge searches uncertainty observable behavior is "tip of the iceberg" >1 misconception can cause several outputs incorrect correct "noise" limitations of modelling language students are inconsistent students' behavior changes as they learn type of information available for diagnosis passive - only observe behavior and infer active - direct interaction to resolve uncertainties affects choice of next exercise, etc. inferential - student does not directly aid diagnosis interactive - student is asked to resolve uncertainties people can't always explain themselves adequately correctly limited by natural language understanding 4. Pedagogical knowledge: the skill of communication A. didactic process embedded & distributed in system or distinct module interaction of specialized rules principles subsequently interpreted into decisions increases chance of use in several domains descisions made by reference to student model & domain knowledge global decisions: sequence of lessons local decisions: intervention when - let student search vs. interrupt what guidance explanations remediation Pegagogy more difficult than subjects applied to B. degrees of control - fixed or adaptive strict monitoring - system reacts to student but keeps control mixed initatiative - student & system share control coaching - student controls 5. Interface: the form of communication A. importance interface affects understandabilty of topic interface affects student's acceptance of system interface capabilities may drive whole system B. student should have accurate perception of system's capabilities C. natural language text understanding text generation voice recognition? voice generation? D. graphics 6. Summary & conclusion boundaries between components are indistinct hard-coded design vs. system flexibility