1

Granular Approach to Adaptivity in Problem-based

Learning Environment

Sally He, Kinshuk, Hong HongMassey University

Palmerston North, New Zealand

Ashok PatelDe Montfort University

Leicester, United Kingdom

2

Problem-based learning

• An attractive approach to foster critical problem solving and self-directed learning skills.

• Roots in apprenticeship, or learning-by-doing.

• A motivating way to learn because learners are involved in active learning, working with real problems.

• Based on constructivist learning approach.

3

Some facts about constructivism• Knowledge is in the interaction of

humans with the environment.

• Cognitive conflict is the stimulus for learning and determines the organization and nature of what is learned.

• When human beings are in a learning environment, there is some stimulus for learning.

These are the basis of problem-based learning

4

Challenges for PBL

• PBL is difficult to implement.

• Students can get inundated by the fine granularity of the problems.

• They can loose focus of overall aims of the learning process.

• Students can become frustrated by feeling out of control in their study.

5

Student adaptivity technologies can address the

deficiencies of current problem-based learning

environments

6

Student Adaptivity

• Enables the systems to adapt themselves to the goals and tasks of student by monitoring their performance.

• Enables the systems to individualize instruction for students with varied backgrounds, learning styles, individual preferences, and knowledge levels.

7

Towards the Prototype

A web-based prototype is implemented in accounting domain to demonstrate how the student adaptivity can improve the effectiveness and efficiency of the PBL environments.

8

Architecture of the PrototypeA problem base module is introduced in the architecture of the web-based intelligent educational systems.

Inference Engine

Knowledge BaseProblem Base Student Model

Communication Module

ClientUser Interface Module

Internet

Server

9

The Features of the Prototype• Problem base: the system uses a set

of different levels of real world problems.

• Flexible assessment : each problem consists of several parts, and each part is assessed according to its degree of difficulty.

• Student adaptivity: the system adapts according to the student performance.

• Teacher defines the criteria for assessing student’s level.

10

3-tier architecture of the Prototype

Server(Middle Tier)

Backend Database (Backend Tier)

Problem BaseProblems contentProblems’ attributesAssessment Criteria

Knowledge BaseContent of Domain or subject: such as section, concepts, examples

Student ModelStudent profileStudent learning stateOthers

Web ServerCommunicate with ClientBridge between client and application server

Application ServerAnalyse student’s performanceDeduct the next step of learningInteract with Database to get suitable information for student

Client (Client Tier) Web BrowserUser interface

Internet

11

How the System Works

• Student finishes a problem and submits the solutions.

• System analyzes the solutions and decide the student's level against the criteria.

• System recommends the proper next step for the student

12

How the System Works

Say, if the student got less than 60 points in an exercise, then the system infers the student at the beginning level of the defined assessment criteria.

The system in this case will present the student with the related information from introduction and basic concepts to examples.

13

Problem screen

14

Sample feedback screen

15

Conclusion

• The system has successfully introduced the adaptivity into the PBL environment.

• The strategies used in this system can be applied into the pure PBL educational systems or the assessment parts within generic intelligent educational systems to improve their adaptation capability.