1. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 1 Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques Presenter : Wu, Jia-Hao Authors : G.D. Chen, C.K. Chang, C.Y. Wang CE (2008) 國立雲林科技大學 National Yunlin University of Science and Technology

2. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 22 Outline Motivation Objective Methodology Experiments Conclusion Personal Comments

3. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 3 Motivation The portability and immediate communication properties of mobile devices influence the learning processes.  Like accessing resources, contact with peers, and transferring data. Few researchers have discussed ways of integrating mobile devices with web-based learning systems.  To build a ubiquitous learning environment is difficult.

4. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 4 Objective To create the ubiquitous learning environment, students can learn by a Desktop PC, laptop, PDA or cell phone.  Student can undertake online learning by using any one of these learning devices to interact with the Web-based learning system. Use the SMS (Short Message Service) to transmit the instructions and notifications.

5. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 5 Methodology-System overview

6. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 6 Methodology-Three modules Learning status awareness module  Analyzes students’ online learning performance, such as learning works, test results and self-assessment results, to capture a learner’s knowledge acquisition status. Schedule reminder module  This module enables teachers to manage and adjust the course schedule.  All the adjustments from a teacher are immediately applied to students’ personal schedules in the web learning system. Mentor arrangement module  This module recommends three consulting classmates, called mentors, for question/answer sessions via voice communication  The student can then consults with mentors by phone or meet him for a face- to-face discussion.

7. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 7 Methodology-Concepts-mapping The concept-mapping techniques was applied to the present knowledge structure to guide students in learning. A concept map is a node-link diagram represent a concept using a node and a relationship  For example, “is-a”, “related-to”, “part-of”

8. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 8 Methodology-Student model construction The student model contains the learning status of every concept; the schedule information for every learner, and the learning sequences for their goals.

9. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 9 Methodology-Student model construction (Cont.) In capturing students’ learning status for each concept, all clues are generated by analyzing students’ online learning behaviors and testing the results.

10. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 10 Methodology-Learning status awareness module This module is recommends to students, which concepts they should learn through SMS messages.

11. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 11 Methodology-Schedule reminder module The course schedule and student’s personal online calendar are created on a web server and stored in a database table. For each student, the student model includes a variable storing the up-to-date learning goal, which is the grade(0- 100)

12. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 12 Methodology-Mentor arrangement module This module is designed to support students’ peer mentoring or coaching. After receiving this recommendation, the consulter can discuss this question by phone or face-to-face. The schedule information can indicate who has free time to help peers.

13. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 13 Experiments School  National Central University. Sample  54 student ( 27 experiment group, 27 control group )  Experiment group : use the mobile device.  Control group : use the desktop PC or laptop. Course  Introduction to Computer Science.

14. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 14 Experiments (Cont.)-learning status awareness module In the pretest, the grades of the experiment group were 4.3% higher than those of the control group. The grades of the experiment group outperformed the control group by 12%, 5.3%, 13%, and 9% in four weekly tests. The average improvement in the grades of members of the control group was 6.14, while that of the experiment group was 7.81. 73.4% 79.8% Experiment group : use the mobile device. Control group : use the desktop PC or laptop.

15. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 15 Experiments (Cont.) The result reveal that the system has almost has no effect on those students in the higher subgroup(33%)  However, the reminder system can significantly improve the learning performance of students in the middle and lower subgroups (66%), particularly in the lower subgroup(33%) Experiment group : use the mobile device. Control group : use the desktop PC or laptop.

16. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 16 Experiments-Schedule reminder module Students in the experimental group failed to finish 7.9% of assigned tasks, while students in the control group did not finish 23.8%. Students’ learning goals and their rates of achievement of learning goals in four weekly tests. Average achievement rateAverage learning goals Experiment group50.8%74.35 Control group34.15%70.03 Experiment group : use the mobile device. Control group : use the desktop PC or laptop.

17. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 17 Experiments-mentor arrangement module Two question  Before I discuss with the recommended mentors, do I think they can solve my problem?  After consulting the mentor, has my problem been solved? Experiment group : use the mobile device. Control group : use the desktop PC or laptop.

18. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 18 Conclusion This study developed a ubiquitous learning environment for students to learn by a desktop PC, laptop, PDA and cell phone. The analysis of experimental results and system logs indicate that the testing results, task-accomplished rate and learning -goal-achieved rate can be improved by the support of the ubiquitous learning website.

19. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 19 Comments Advantage  A useful e-learning system.  Something like our project with language center. Drawback  Some experiment didn’t use table to display. Application  E-learning  Ubiquitous learning