Improving Student Performance Using Self-Assessment Tests

Testing is the most generic and perhaps most widely used mechanism for student assessment. Most tests are based on the classical test theory, which says that a student's score is the sum of the scores obtained in all questions plus some kind of error. The most relevant is that the student test result depends heavily on the individual's learning preferences or abilities and also on the actual test's format. According to this theory, tests aren't necessarily useful in intelligent educational systems, which require accurately obtaining the student's knowledge state to guide the learning process. Yet the Web has created a new generation of intelligent systems-adaptive hypermedia systems which offer new types of instructional interaction. Educational AHSs adapt the learning process on the basis of the student's learning preferences, knowledge, and availability. One such Web-based tool is Siette (the system of intelligent evaluation using rests), which infers student knowledge using adaptive testing.

Authors

• Eduardo Guzman
• Ricardo Conejo
• Jose-Luis Perez-de-la-Cruz

Keywords

• Automatic testing
• System testing
• Intelligent systems
• Computer science
• Computer languages
• Adaptive systems
• Mobile computing
• Databases
• Timing
• Collaboration
• Student Performance
• Self-assessment Test
• Academic Year
• Version Of Test
• Test Theory
• Final Exam
• Knowledge Of Students
• Classical Test Theory
• Experimental Group
• Distribution Of Variables
• Level Of Knowledge
• Greater Than Or Equal
• Test Session
• Student Level
• Percentage Of Students
• Item Response Theory
• Student Model
• Tutoring Systems
• adaptive testing
• personalized content delivery and generation
• user-modeling techniques
• system evaluation
• adaptive hypermedia