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Information Architecture of Interactive and Customizable Learning Environments

Information Architecture of Interactive and Customizable Learning Environments. Myeongjin Lee Adviser : Geoffrey Fox NPAC Computer and Information Science Syracuse University. The Learning Environment.

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Information Architecture of Interactive and Customizable Learning Environments

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  1. Information Architecture of Interactive and Customizable Learning Environments Myeongjin Lee Adviser : Geoffrey Fox NPAC Computer and Information Science Syracuse University

  2. The Learning Environment • To design a computerized learning environment is interdisciplinary, spanning such areas as HCI, Cybernetics, Cognitive Psychology, Human factor engineering, and education. • Computer scientist is an architect to design/build the house of learning environment, to encompass required functionalities by a customer (a learner and a teacher)

  3. The Learning Environment • Computer Science Cybernetics HCI Learning Environment Education Cognitive Psychology Human factor engineering Computer Science

  4. Interaction Model (Wegner 1997) • Algorithms vs. Interaction Model • Interactive systems provide history-dependent services over time that can learn from and adapt to experience. • Interaction Machines : Turing machines + input and output actions that support dynamic interaction with an external environment. • Interaction machines to model practical applications!

  5. Learning Software and Batteries • Computerized performance evaluation tools - e.g. to measure motor skills, response time. Limited because they can not be changed dynamically and seldom customizable. • Computerized learning tools - ordering customized software is not easy. User performance may change in different ratio according to each user. • Lack of functionalities in observing user events’ flows.

  6. The System • Cybernetics (the ancestor of Computer Science) : the nature and concepts of a system. • We use their terms to design computerized learning environment (instrumental learning) based on “real learning process” • Requirements of a successful learning is also applied to the case of instrumental learning.

  7. The System

  8. The Control System

  9. Adaptive Control System • The adaptive control system can change the relation between a user and system to achieve a more specific object as time goes on. • The learning system requires a control of user inputs with adaptive ability. • A learning machine is an advanced instance of an adaptive control system.

  10. Teaching Machine • To interact with students in order to teach or aid in their learning • The first teaching machine : S. L. Pressy 1920 • First, it was an automatic test administrator, then “learning” mode was added. • Norman Crowder, and Skinner’s teaching machines • Skinner contended that learning through a programmed environment is more effective. • An adaptive controller can provide flexible model of teaching machine. (above ones are fixed environments)

  11. Discrete Event System • A dynamic system whose state space is a discrete set, where the state transition mechanism is event-driven. • A discrete set • an event-driven state transition mechanism • a stochastic discrete event system : a system with timing information and an uncertainty factor regarding event prediction a learning system!

  12. An Interactive Customizable Information Architecture for a Learning Environment • Internet : Collection of available and extensible (scalable) components and services. • Information architecture to build and design a learning environment on the Internet. • Also to support “exploratory learning” • The adaptive control system is an abstraction of such architecture. • An architecture can be viewed as an interaction model.

  13. Components • Application Server (AS), Server, and Client

  14. Application Server • To render custom interfaces • separation of data presentation from its contents • To get user inputs to process • most of the work is processed at the server side. • AS processes the trapped user events and sends them to a server • To update or custom user environments • registration, customization, or update requests from clients • interfaces or protocol to use pre-existing web-based software

  15. Server • A Content Server. • To communicate with databases • To process data from the AS or from a database • object repository

  16. Client • A user ( the learning environment) • A student or a teacher • Clients generate user events which are tracked and processed at both client and server sides.

  17. Services • Our information architecture provides education services • AS is the middle tier • Content server and database are the back-end • Described here are required services at our information architecture for a learning environment • Properties are the requirement of each service.

  18. http://www.npac.syr.edu/DC“Full Description of Web Flow and Friends for Education and Science portals”

  19. Education Portals • Not one-size-fits-all approach, but customizable objects • Links to other sites/games/softwares can be added/deleted (adaptiveness). • Portal Objects are handled by services of the Information Architecture.

  20. Education Portals Continued • Our content-based analysis can be “required / recommended features” to be good education portals. • “Assume that we are building education portals in terms of Distributed Education Objects” (http://www.npac.syr.edu/DC/) • OSS (Nasdaq:WEBB), WebCT, Blackboard..

  21. Services at the Information Architecture

  22. Event Service • To track and analyze client inputs or events • User events need to be captured at both client and server sides! • User performance at the learning session • System performance may make user perceive information differently. • Basic functions to analyze crude data at the AS reduce workload at Content server.

  23. Data Rendering Service • This service renders different types of data to client’s interface. • Content server or object repository does not have to know the representation of data in the information processing procedure. • The user interface rendered by the AS should have event gathering features to be used by event service.

  24. Administrative Service • Registration of users • Monitoring of user activity • the customization of user environment • software module to include pre-existing application into the learning system

  25. Content Service • Content Service concerns the repository requirement for different performance tests, batteries, or learning application. • The repository needs to be scalable. • To add new required features should be easy to program. • To be modular in terms of functionalities • Performance test or learning application can well be implemented over such information architecture!

  26. Database related service • Connection between the content server and databases

  27. Services and their properties

  28. An example of interaction among components

  29. Conclusion • To transform the Internet into an intelligent learning environment • An AS : customization, rendering data, and tracking user inputs. • Possibly several content servers and the AS architecture provide simple and easy-to-follow 3 tier architecture for interactive learning environment. • The use of XML : easy personalization, presentation of information in richer way.

  30. Smart Desk • A web-based interactive learning environment. • Initially designed by Dr. Warner for a patient who was cognitively disabled from early brain seizure. • Also a hardware environment to explore or develop a user’s physical capability.

  31. Hardware Interface Example 1 • Track ball for a mouse movement. • Graphic Tablet for a mouse movement • Other objects with photo sensors • Designed by Matt Carbone

  32. Hardware Interface Example 2 • Smart Desk Chair designed by Tim Lauring • 8 analog signals from pressure sensors and 12 digital signals from palm mouse.

  33. Features • Customizable • Adaptive • Scalable • User tracking mechanism (event detection)

  34. Customizable • To choose from list of applications (game, learning software, etc), which are classified as level, subjects.. • Tailoring the learning system’s interface and content feature to the cognitive and learning needs and capacities • Java servlets, HTML, Javascript, Oracle, and JDBC

  35. Tracking Examples (Card Game)

  36. Tracking Examples (Word Learning)

  37. Tracking Examples (Mouse Trajectory)

  38. Tracking Examples ( web browser)

  39. Tracking and Adaptiveness • Java Classes • Javascripts : event Object from Javascript • Background Process (e.g. NeatTools by Yuh-Jye Chang) • Adaptiveness : Tracked Information is reflected back to the learning environment.

  40. SD Information Architecture • Registration and Customization process are conceptually handled by AS. • At SD, Servlets play the role as AS in the above processes between user requests and a content server.

  41. User Registration

  42. Customization

  43. Servlets at AS AS Regist.. DB Custom.. . .

  44. Table (User Information) • Create table sd_table{ userid varchar2, ufname varchar2, ulname varchar2, uschool varchar2, usex varchar2, umajor varchar2, unation varchar2, ucomment varchar2, uip varchar2};

  45. Table (Objects’ Information) • Create table object_table{ ID varchar2 name varchar2 image varchar2 url varchar2 a_level varchar2 field varchar2 description varchar2 author_name varchar2 author_contact varchar2};

  46. SD Event Model SD Client Brower User AS CS

  47. Data and Event flow at SD Server user CS client AS CS

  48. Client-side event • Javascript : easily added to the “head” of any html file for “event” detection of keydown, keyup, mouse move, mouse location, event time, double click, etc. (Mix ‘n match!) • With proper browser detection scheme, it will work at both IE and Netscape.

  49. Client-side event Continued • NeatTool : “replay” functionality, using standard MS-windows file type (text file can be parsed for further analysis) • Both needs to send information back to server through web browser or other ways. • Easy and accurate • How user interact with the interface.

  50. Event.ntl file for client side event detection

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