1 Granular Approach to Adaptivity in Problem-based Learning Environment Sally He, Kinshuk, Hong Hong Massey University Palmerston North, New Zealand Ashok Patel De 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 Prototype A problem base module is introduced in the architecture of the web-based intelligent educational systems. Inference Engine Knowledge BaseProblem BaseStudent Model Communication Module Client User 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 Base  Problems content  Problems’ attributes  Assessment Criteria Knowledge Base  Content of Domain or subject: such as section, concepts, examples Student Model  Student profile  Student learning state  Others Web Server  Communicate with Client  Bridge between client and application server Application Server  Analyse student’s performance  Deduct the next step of learning  Interact with Database to get suitable information for student Client (Client Tier) Web Browser  User 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.