In a national-scale educational assessment system, such as the National Examination, the need for several sets of questions that have the same level of difficulty is very required to avoid cheating by students. Therefore, the objective, which is to make a set of questions with the same level of difficulty automatically, is done in this research. It used a machine learning approach, namely K-Means. To achieve this goal, several following procedures need to be implemented. Firstly, we need to create banks of questions to be assigned to students. Then, we build training data by determining the value of each question based on Bloom's Taxonomy, item characters/types, and other parameters. Then, with utilizing K-Means, several cluster centers are obtained to represent the uniformity of the questions in the cluster members. By using several heuristics criteria defined previously, several sets or packages of questions that have the same characteristics and difficulty levels are obtained. From the experiments conducted, the analysis with descriptive (i.e., mean, standard deviation, and data visualization) and inference (i.e., ANOVA) statistics of results are presented showing that questions of each sets have the same characteristics to ensure the fairness of examinations. Moreover, by using this system, the contents of the questions in the generated set do not need to be the same, the package of questions can be generated automatically quickly, and the level of the difficulties can be measured and guaranteed.
The aims of the research were to find out improving students intelligences trough questioning identification. For this purpose, data were analyzed by the prospective problem posing process. It was a descriptive research with a sample of elementary school. The entire of the research is in grade two. Qualitative data contains students intelligences from students questioning identification. Design of improving students intelligences trough questioning identification were measured by question type, suitability with the material, have an answer or not, a degree of difficulty, level of courage in asking, and why they ask that question. All variables were analyzed using Bloom’s Taxonomy. All students involved in this study have received permission from parents. The participants in this study were students in one of the elementary school in Indonesia. Participants totaled 29 students with an age range of 7-8 years. This research was conducted by researchers from several studies of student intelligence, observation with research instruments in the form of observation sheets, documentary, and video of activity classes. Students questioning identification category with a questioning medium, questioning low, and questioning high. In conclusion, it was concluded that the difficulties questioning skills determined as; lack of experience, lack of the content knowledge, not recognizing the cognitive levels of the students, and difficulties in understand problem texts. The solutions for the teacher which were suggested in the scope of this research were as the following; emphasizing problem-solving and posing studies, in-depth analysis of the curriculum, teaching special teaching methods in details and resorting to resources during problem posing process
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