THE IMPLEMENTATION OF PERFORMANCE ASSESSMENT IN SUB MATERIAL STRING WAVE REFLECTION USING GUIDED INQUIRY LEARNING MODEL TO TRAIN SCIENCE PROCESS SKILLS

This research reported the work on the implementation of performance assessment (PS) in sub material string wave reflection in senior high school using guided inquiry learning model. The aims were to train student’s science process skills and to collect the student’s response on the learning activities. The examined science process skills are as follows: how the students to formulate an experimental question, to determine the experimental goal, to formulate hypotheses, to determine the experimental variables, to administrate the data and analyzing it and to draw conclusion. The research was designed to be one group pre-test post-test. The teaching learning materials were validated before being used. The student’s activities on the class and their science process skills were recorded by video before being evaluated. The research data were analyzed by learning device analysis, implementation learning analysis, pre-test and post-test analysis, interview analysis and student response analysis. The change of students science process skills were analyzed by t-paired test. The results showed that: (1) the students’s science process skills improved. For the example, the students can formulate that experiment questions. (2) The question of “what the difference between the reflected string wave at the tight and the loose strings?”, (3) the students responses to the learning activities were also very good. The students felt happy, they were more active, more motivated to learn, braver to express their opinions and they felt that their science process skills were trained. Keywords: Performance Assessment, Guided Inquiry Learning Model, Science Process Skills, String Wave Reflection

Intelligent strategies for mobile robotics in laboratory automation

In this thesis a new intelligent framework is presented for the mobile robots in laboratory automation, which includes: a new multi-floor indoor navigation method is presented and an intelligent multi-floor path planning is proposed; a new signal filtering method is presented for the robots to forecast their indoor coordinates; a new human feature based strategy is proposed for the robot-human smart collision avoidance; a new robot power forecasting method is proposed to decide a distributed transportation task; a new blind approach is presented for the arm manipulations for the robots