The students already have preconceptions in learning chemical concepts. However, each student's preconception can differ from the actual concept according to the chemists. This is what allows the wrong concept in students or commonly called misconceptions. In this case, if the misconception is not immediately solved it will affect the next learning process. One learning model to reduce misconceptions is ECIRR. This study aims to determine the effectiveness of LKPD which develope in reducing misconceptions in term the shifting students conception of students from misconception to knowing concept. This research uses pre-experiment research method with One group Pretest – Posttest Design model. There are 15 students of class x science from a senior high school in surabaya who are selected based on the results of the students' initial understanding test. The understanding test used is a three-tier test to identify students concepts given as initial concept detection and final concept detection, while students' misconceptions are reduced with the ECIRR learning model. The results of the study obtained a percentage shift from misconception to know concept of 92.31% for the sub concepts of basic chemical law (Gay-lussac), 88.24% for the sub concepts of molar mass and relative molecular mass, 72% for the subconcepts of the number of particles, and 88% for empirical formula sub concepts. So it can be shown that LKPD is very effectively used to reduce students' misconceptions on stoichiometry material.
On the use of feature tracks for dynamic concept detection in video
