The utilization of junior high school mathematics national examination data: A conceptual error diagnosis

The goal of the research is to gain insights into the characteristics of the items in the mathematics national examination, the attributes on which the items were formulated and the result of a conceptual error diagnosis of the mathematics materials based on the result of the junior high school mathematics national examination. This is quantitative descriptive research. The data were collected from 3,079 grade-nine students of junior high schools who took the National Examination in the academic year of 2015/2016. The sample was established randomly based on the package code of the examination which is P0C5520 with 574 students as the examinees. Documentation method was applied in collecting the data. The result of the research shows that – upon the implementation of the classical test theory – there are 16 items in ‘difficult’ category, 24 in ‘intermediate’ category, and no items in ‘easy’ category. Furthermore, upon the implementation of the item response theory, the result shows that 28 items are in ‘good’ category and 12 items are in ‘poor’ category. In addition, there are 50 attributes on which the Junior High School Mathematics National Examination test (package P0C520) is formulated. Four attributes are content attributes and the rest (46) are process skill attributes. The result of the diagnosis shows that there are 11 types of errors made by the students when trying to complete the content items. Most of the errors are conceptual errors related to the geometric materials especially in the sub-materials of polyhedron, triangles, and quadrangles

The range of TOEFL scores predicted by TOEP

The Indonesian Testing Service Centre (ITSC) has developed an online standardized test called TOEP (Test of English Proficiency) as a fresh alternative for measuring the test takers’ listening and reading proficiency. To ensure its quality, the TOEP scores need to be validated against the scores obtained from another established standardized test, in this case the ITP-TOEFL. This study aimed at finding out to what extent the range of scores which are measured by TOEP can predict the scores obtained from ITP-TOEFL. A quantitative approach was applied in this study, focusing on the analysis of scores obtained by 1,048 people taking TOEP in 2016, 2017, and 2019 and 383 testees had taken both TOEP and ITP-TOEFL. A regression analysis was conducted to establish the prediction equation of TOEP to ITP-TOEFL. The range of scores of proficiency measured through TOEP was estimated using the advanced item response theory, especially the information function value. The results of analysis show that TOEP can predict test takers’ English proficiency in the range of minimum 310 and maximum 656.34 at the ITP-TOEFL scales. It can be concluded that TOEP has a good predictive validity to ITP-TOEFL

Diagnosis Kesalahan Konsep Materi Matematika SMP Berdasarkan Hasil Ujian Nasional di Kota Baubau.

Penelitian ini bertujuan untuk mengungkapkan: (1) karakteristik butir soal ujian nasional matematika SMP tahun 2015/2016 di Kota Baubau, (2) diagnosis kesalahan konsep materi matematika berdasarkan hasil ujian nasional matematika SMP tahun 2015/2016 di Kota Baubau, (3) penyebab utama kesalahan konsep siswa berdasarkan hasil ujian nasional matematika SMP tahun 2015/2016 di Kota Baubau. Penelitian ini merupakan penelitian deskriptif kuantitatif. Sumber data penelitian ini adalah lembar jawaban siswa dan lembar soal Ujian Nasional. Populasi dalam penelitian adalah siswa SMP di Kota Baubau sebanyak 3.079 siswa dari 30 sekolah yang terdiri dari 20 sekolah berstatus negeri dan 10 sekolah berstatus Swasta. Sampel dipilih secara random berdasarkan kode paket soal yang dikerjakan yaitu P0C5520 dengan jumlah peserta ujian sebanyak 574. Pengumpulan data dilakukan dengan menggunakan metode dokumentasi. Instrumen penelitian divalidasi berdasarkan pertimbangan ahli. Data hasil penelitian yang berupa lembar soal dianalisis menggunakan analisis konten, sedangkan data yang berupa respon jawaban siswa dianalisis menggunakan program TAP versi 14.7.4 dan program R dengan CDM (Cognitive Diagnostic Models). Hasil penelitian menunjukkan bahwa: (1) berdasarkan pendekatan toeri tes klasik ditemukan 16 butir soal tergolong sulit, 24 butir soal tergolong sedang dan tidak ada butir yang tergolong mudah, sedangkan berdasarkan pendekatan teori respon butir ditemukan 28 butir dengan kategori baik dan 12 butir dengan kategori tidak baik; (2) ada 11 jenis kesalahan yang dilakukan siswa dalam menyelesaikan butir soal, namun jenis kesalahan yang paling banyak dilakukan adalah kesalahan konsep pada materi geometri; (3) berdasarkan hasil analisis dengan model DINA ditemukan ada 10 penyebab utama kesalahan konsep siswa, namun penyebab utama dengan persentase tertinggi terletak pada materi aljabar, yaitu tidak memahami konsep pemetaan dari dua himpunan (A20) dan kemiringan (gradien) garis (A23), sedangkan penyebab utama dengan persentase terendah terletak pada materi geometri, yaitu tidak memahami konsep besar pelurus sudut (A27)

The utilization of junior high school mathematics national examination data: A conceptual error diagnosis

The goal of the research is to gain insights into the characteristics of the items in the mathematics national examination, the attributes on which the items were formulated and the result of a conceptual error diagnosis of the mathematics materials based on the result of the junior high school mathematics national examination. This is quantitative descriptive research. The data were collected from 3,079 grade-nine students of junior high schools who took the National Examination in the academic year of 2015/2016. The sample was established randomly based on the package code of the examination which is P0C5520 with 574 students as the examinees. Documentation method was applied in collecting the data. The result of the research shows that – upon the implementation of the classical test theory – there are 16 items in ‘difficult’ category, 24 in ‘intermediate’ category, and no items in ‘easy’ category. Furthermore, upon the implementation of the item response theory, the result shows that 28 items are in ‘good’ category and 12 items are in ‘poor’ category. In addition, there are 50 attributes on which the Junior High School Mathematics National Examination test (package P0C520) is formulated. Four attributes are content attributes and the rest (46) are process skill attributes. The result of the diagnosis shows that there are 11 types of errors made by the students when trying to complete the content items. Most of the errors are conceptual errors related to the geometric materials especially in the sub-materials of polyhedron, triangles, and quadrangles

Why is the mastery of key competencies in mathematics for Indonesian students low? : Re-analysis of PISA 2012

This study aims to determine the level of mastery of the key competency attributes of Indonesian students in mathematics. This study was approached quantitatively by adopting approach retrofitting (posthoc analysis). The data sources for this study were Indonesian students aged 15 years who took part in PISA 2012, as many as 5,622 students. The data of this research are ex post facto data obtained by documentation technique, as for what will be documented in the form of response data from Indonesian students based on the results of PISA 2012 and PISA 2012 instruments (item release PISA2012). The data analysis technique used is descriptive statistics using the DINA package R application. The results of this study indicate that Indonesian students are low in mastering the key competency attributes of mathematics related to mathematical operation (MO) and data analysis (DA); high in the mastery of key mathematical competency attributes related to mathematical abstraction (MA), logical reasoning (LR), mathematical modeling (MM), and intuitive imagination (II)

Prediction model of teacher candidate student graduation status: Decision Tree C4.5, Naive Bayes, and k-NN

This study aims to determine the prediction model of the graduation status of prospective teacher students at IAIN Bone in terms of attributes, accuracy levels, and differences in the level of accuracy produced in the attributes of decision tree C4.5, Naïve Bayes, and k-NN data mining algorithms. This research uses a quantitative approach by adopting the Data Mining method. This research was conducted at IAIN Bone. The data collection process in this study used documentation techniques in the form of data on alumni of the Tarbiyah Faculty of IAIN Bone. The data analysis used was a descriptive analysis using decision tree C4.5, Naive Bayes, and k-NN data mining algorithms assisted by the RapidMiner application.  The results of this study show that (1) model prediction of the graduation status of prospective teacher students in IAIN Bone in terms of attributes generated in the Decision Tree C4.5 and Naïve Bayes data mining algorithms  consist of gender, age, Semester 1 IP, Semester 2 IP, Semester 3 IP, Semester 4 IP, and GPA, while the attributes produced in   k-NN data mining algorithm  consists of gender, regional origin, number of siblings, age, IP Semester 1, IP Semester 2, IP Semester 3, IP Semester 4, and GPA; (2) model prediction of graduation status of iain bone teacher candidate students in terms of the accuracy rate generated in the Decision Tree C4.5 data mining algorithm  of 93.90%, Naïve Bayes by 90.24%, and k-NN of 92.07%; and (3) there was no significant difference between the accuracy rate produced by decision tree's data mining algorithm.  C4.5 and Naïve Bayes (p-value = 1.00); Decision Tree C4.5 and k-NN (p-value = 1.00); as well as Naïve Bayes and k-NN (p-value = 1.00) in predicting the graduation status of iain bone teacher candidate students