TRENDS IN TECHNOLOGY BASED LEARNING : TOWARDS TRULY INTELLIGENT TUTORING SYSTEMS

TRENDS IN TECHNOLOGY BASED LEARNING: TOWARDS TRULY

INTELLIGENT TUTORING SYSTEMS

Janis Grundspenkis

Riga Technical UniversityFaculty of Computer Science and

Information TechnologyDepartment of Systems Theory and Design

E-mail: [email protected]

AGENDA TRADITIONAL vs. TECHNOLOGY

BASED LEARNING VIRTUAL LEARNING: DIFFERENT

TERMS AND VIEWS E-LEARNING M-LEARNING

INTELLIGENT TUTORING SYSTEMS HYBRID SYSTEMS FOR LEARNING CONCLUSIONS

TRADITIONAL LEARNING (1)

FACE-TO-FACE (“TALK AND CHALK”)

“+” Explanation Communication

• Between the teacher and students• Among students

Adaptation to individual students (in case of small number of students)

TRADITIONAL LEARNING (2)

FACE-TO-FACE (“TALK AND CHALK”)

“-” Different teaching quality depending on

teacher (pace dependent) Strict schedule (time and place

dependent) Weak adaptation to individual students

(in case of large number of students)

VIRTUAL LEARNING: DIFFERENT TERMS AND VIEWS* (1)

* Anohina A. Clarification of the Terminology Used in the Field of Virtual Learning. In: Scientific Proceeding of Riga Technical University, 5th Series, Computer Science, Applied Computer Systems, Vol. 17, RTU Publishing, Riga, 2003, pp. 94-102.

Basic term Connective Educational concept

Computer

AidedAssisted

AugmentedBased

ExtendedManagedMediatedMonitoredRelated

Supported

EducationInstructionLearningTeachingTraining



Basic term Educational concept

Distance





Internet based





Online





Technology based





Web based


VIRTUAL LEARNING: DIFFERENT TERMS AND VIEWS (7)

RELATIONSHIPS OF TERMS

ComputerBased

Technology BasedDistance

Online

InternetBased

WebBased

E-LEARNING (1) “+”

Teaching and self-paced learning of anyone, at anytime, anywhere

Substantial cost savings due to elimination of travel expenses

Just-in-time access to timely information Modularity of presentation (facilitates

different construction of learning events)

E-LEARNING (2) “+”

Improved collaboration and interactivity among students

Content can be updated and delivered in real-time

Higher retention of content through personalized learning

Online training is less intimidating than instructor-led courses

E-LEARNING (3)

“-” Learning materials cost quite a lot more

than textbooks Requires more time, dedication, and

time management skills Weak motivation (absence of teacher) Lack of real time communication Weak support from the e-learning

environment

M-LEARNING

Mobile devices open the possibility of collaborative and independent learningCellular phonesSmart phonesPersonal digital assistants (PDA)

INTELLIGENT TUTORING SYSTEMS (1)

AIM To provide sophisticated

instructions on one-to-one basis adapting the learning process to the strength, weaknesses and the level of knowledge and skills of each particular learner

INTELLIGENT TUTORING SYSTEMS (2)TASKS Monitoring of actions of the learner in

the learning environment Appropriate responding to them Assessment of learner’s knowledge Choice and presentation of learning

material Presentation of feedback and help Adaptation of teaching strategy

INTELLIGENT TUTORING SYSTEMS (3) Incorporation of a new concept Web

semantics thanks to the development of “more expressive” mark-up languages and mainly to the use of ontologies

Convergence of Artificial Intelligence and Learning Environments

Convergence of Knowledge Management Systems and Multi-Agent Systems

AGENT BASED INTELLIGENT TUTORING SYSTEMS* (1)STRUCTURE Expert module (the domain knowledge concerns

objects and their relationships taught by the system) Tutoring module (holds teaching strategies and

instructions needed to implement the learning process)

Student diagnosis module (infers the student model for each individual)

Communication module (responsible for the interaction between the system and the learner)

* Grundspenkis J. and Anohina A. Agents in Intelligent Tutoring Systems: State of the Art. In: Scientific Proceedings of Riga Technical University, 5th Series, Computer Science, Applied Computer Systems, Vol. 22, RTU Publishing, Riga, 2005, pp. 110-120.

AGENT BASED INTELLIGENT TUTORING SYSTEMS* (2) Agents comprising the student diagnosis module of

intelligent tutoring system


AGENT BASED INTELLIGENT TUTORING SYSTEMS* (3) Agents comprising the tutoring module of intelligent

tutoring system


AGENT BASED INTELLIGENT TUTORING SYSTEMS* (4) Agents comprising the expert module of intelligent

tutoring system


AGENT BASED INTELLIGENT TUTORING SYSTEMS* (5)

A set of agents comprising the architecture of an intelligent tutoring system (gray boxes are managing agent in a given component)


ANIMATED PEDAGOGICAL AGENTS Animated pedagogical agents emulate

aspects of dialogue between the teacher and the learner

Roles of animated pedagogical agents Agent as an expert (it is similar to human expert

and exhibits mastery of extensive knowledge and performs better than the average within a domain

Agent as a motivator (it suggests its own ideas and encourages the learner)

Agent as a mentor (it incorporates characteristics of both the expert and the motivator

HYBRID COURSES (1) Hybrid courses offer a blend of in-class

teaching and online learning and is an attempt to combine the best elements of traditional face-to-face teaching with the best aspects of distance education

Hybrid courses combine traditional lecture, seminar or lab sections with online and other technology based learning

HYBRID COURSES (2) A significant part of the course

learning is online, and as a result, the amount of classroom seat-time is reduced

Hybrid courses encourage active, independent study and reduce the amount of time students spend in the classroom

HYBRID COURSES (3) Students spend more time working

individually and collaboratively on assignments, projects, and activities

Students who successfully complete hybrid courses are typically self-motivated learners who possess a working knowledge of computers and the Internet

HYBRID COURSES (4) Faculty spend less time lecturing

and more time reviewing and evaluating student work and guiding and interacting with students

Allow students much more flexible scheduling, while maintaining the face-to-face contact with the teacher

HYBRID COURSES (5) “+”

More learning, understanding, and retention

More interaction and discussion•Students are more engaged

More student and learning centered•Less listening and more active learning•Students are more accountable for own

learning

HYBRID COURSES (6) “+”

Teachers can document & examine student work more thoroughly online than face-to-face

Faculty can teach in new ways•Accomplish new learning goals and

objectives•More hands on student involvement with

learning•Provides opportunities to learn in different

ways

HYBRID COURSES (7) “-”

Involves an extensive course redesign Difficult to define optimal proportion

between traditional face-to-face teaching and online learning

Difficult to select which topics include in traditional face-to-face teaching and which topics left for online learning

RESOURCES FOR HYBRID COURSES UWM Hybrid Course Web Site

http://www.uwm.edu/Dept/LTC/hybrid.html

UWM Student Hybrid Course Web Site http://www.uwm.edu/Dept/LTC/hybridcourses.html

Teaching With Technology Today – Hybrid issue http://www.uwsa.edu/ttt/browse/hybrid.htm

CONCLUSIONS A lot of work has been done in technology

based learning but many problems still exist New technologies offer new opportunities

and new challenges Intelligent tutoring systems and animated

pedagogical agents provide more adaptive support for learning

Hybrid courses offer a good balance between traditional face-to-face teaching and distance learning

TRENDS IN TECHNOLOGY BASED LEARNING : TOWARDS TRULY INTELLIGENT TUTORING SYSTEMS

Documents

learningvirtual learning

field of virtual learning

applied computer systems

different terms

rtu publishing

facetoface talk

individual students

place dependentweak