Correlation of Stem Students’ Performance in the National Career Assessment Examination and Academic Subjects

Ferrer, Flordeliza P.; Cruz, Roberto J. Dela

doi:10.20319/pijss.2017.s31.532541

Cited by 5 publications

(8 citation statements)

References 2 publications

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“…It means that the SHS administrators should look first on the GPA in Mathematics 10 of the students which should be 85 and above as stated in DepEd Order Number 55 series of 2016. It is supported by the study of Ferrer et. al (2017) that there is significant relationship between GPA in Mathematics 10 and NCAE -Mathematical Ability.…”

Section: Resultssupporting

confidence: 67%

“…It means that the respondents have different level of mathematical ability using NCAE results. On the study of Ferrer et. al, (2017), it was revealed that NCAE Mathematical Ability of STEM students was 88.4 which implies that most of the students who enrolled in STEM strand is inclined in mathematics.…”

Section: Resultsmentioning

confidence: 99%

“…It only implies that most of the students who are enrolled in STEM strand are intelligent and excelled in Mathematics when they were in grade 10. Study of Ferrer et al (2017) showed the performance of STEM students in Mathematics 10 which is 89.6. It indicates that senior high school utilized the DepEd memorandum in accepting STEM students.…”

Section: Resultsmentioning

confidence: 99%

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Mathematical Models in Predicting Retention of STEM Students in Pre-Calculus

Barroso¹

2020

International Journal of Pedagogical Development and Lifelong L

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This study aimed to determine the mathematical models in predicting retention of STEM students in Pre-Calculus. The study utilized a non-experimental research specifically a cross-sectional predictive design. The independent variables in the study are the Grade Point Average (GPA) in Mathematics 10, General Weighted Average (GWA) in grade 10, National Career Assessment Examination (NCAE) -mathematical ability, NCAE -STEM results, gender and family monthly income. The dependent variable is the retention of STEM students in Pre-Calculus. The instruments in the study are Pre-Calculus Retention Test (PRT), interview and documentary analysis. The PRT was validated by five experts and underwent reliability testing with a Cronbach alpha value of 0.524. Percentage, mean, standard deviation, Pearson Product Moment Coefficient of Correlation and Multiple Regression Analysis were applied in the study. The researcher used IBM SPSS version 20 in analyzing the data gathered. The study developed two mathematical models that can predict retention of STEM students in Pre-Calculus. Using the standardized coefficients, the formula in predicting retention of STEM students in Pre-Calculus are y = 0.035x1 + 0.632x2 -31.462 and y = 0.033x1 + 0.599x3 -28.370 where y is PRT scores of the STEM students, x1 is NCAE-Mathematical Ability scores, x2 is GPA in Mathematics 10 and x3 is GWA in grade 10. . It can be gleaned on the mathematical models that the best predictor of the retention of STEM students in Pre-Calculus are GPA in Mathematics 10 and GWA in grade 10.

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Section: Resultssupporting

confidence: 67%

Section: Resultsmentioning

confidence: 99%

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Mathematical Models in Predicting Retention of STEM Students in Pre-Calculus

Barroso¹

2020

International Journal of Pedagogical Development and Lifelong L

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“…In this section, the interesting thing is the relationship between English and Mathematics -Science. In some places, in countries that do not use English as the main language, it shows that the influence of English language skills indirectly has a significant effect on academic achievement in Science and Mathematics of students in Grades 10, 11, and Higher Education at the beginning of the lecture year (Fenoll, 2018;Maskar, 2020;Murray, 2017;P. Ferrer & J. Dela Cruz, 2017;Stoffelsma & Spooren, 2019).…”

Section: Discussionmentioning

confidence: 99%

Clustering Subjects in Lampung Provincial National Examination of Junior High School Through Maximum Spanning Tree

Maskar

Puspaningtyas

2021

AJPM

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AbstrakUjian Nasional yang dilaksanakan setiap tahun di Indonesia telah menghasilkan banyak data, termasuk di Provinsi Lampung. Pada rentang tahun 2015 sampai dengan tahun 2018, telah terkumpul kurang lebih 11 juta data hasil ujian nasional. Data tersebut tentu dapat memberikan banyak informasi untuk perbaikan Pendidikan Indonesia di masa mendatang. Tulisan ini membahas tentang pengelompokan mata pelajaran pada Ujian Nasional SMP di Provinsi Lampung dengan tujuan untuk memetakan hubungan hasil belajar Matematika, IPA, Bahasa Indonesia, dan Bahasa Inggris. Tujuan pengelompokan tersebut sebagai analisa lebih jauh agar perbaikan pendidikan juga dapat mulai masuk pada ranah non-teknis, seperti penjadwalan, penyeusaian waktu belajar di kelas sampai dengan waktu pengerjaan tugas, serta perbaikan pada penentuan mata pelajaran yang menjadi syarat pelajaran lainnya. Analisis klusterisasi dilakukan dengan menggunakan Algoritma Kruskal berdasarkan graf maximum spanning tree (MST) dengan bantuan teknik statistik deskriptif dan inferensial. Data yang digunakan adalah hasil Ujian Nasional di Provinsi Lampung tahun 2017 dan 2018 sebanyak 15876 data. Graf MST ditentukan menggunakan algoritma Kruskal dan koefisien korelasi ditentukan menggunakan nilai koefisien korelasi Pearson. Hasil eksperimen menunjukkan bahwa Matematika, IPA, dan Bahasa Inggris memiliki korelasi yang paling kuat. Mata pelajaran yang paling kuat korelasinya dengan Bahasa Indonesia adalah Bahasa Inggris. Oleh karena itu, pemetaan mata pelajaran dapat disusun menjadi dua kelompok yaitu Matematika-IPA-Bahasa Inggris dan Bahasa Inggris- Bahasa Indonesia- IPA. Hasil tersebut dapat bermanfaat sebagai dasar pengambilan keputusan pada berbagai aspek teknis untuk mengoptimalkan hasil belajar siswa SMP khususnya di Provinsi Lampung. Kata kunci: Klusterisasi, Lampung, Ujian Nasional AbstractNational exams carried out every year in Indonesia have produced a lot of data, including in Lampung Province. In the span of 2015 to 2018, approximately 11 million national exam results have been collected. This data can certainly provide a lot of information for the improvement of Indonesian education. This paper discusses the clustering of subjects on junior high school national exams in Lampung Province with the aim of mapping the relationship of learning outcomes in Mathematics, Sciences, Indonesian, and English. The purpose of the clustering is as a further analysis so that educational improvements can also begin to enter the non-technical realm, such as scheduling, adjusting class and assignment time, and also determine prerequisite subjects. Clustering analysis is performed using an algorithm based on maximum spanning tree (MST) graphs with the help of descriptive and inferential statistical techniques. The data used are the results of national exams in Lampung province in 2017 and 2018 totaling 15.876 data. The MST Graph is determined using Kruskal’s algorithm and the coefficient of correlation is determined using Pearson coefficient of correlation value. The experimental results show that Mathematics, Natural Sciences, and English have the strongest correlation. Subject that has the strongest correlation with Indonesian is English. Therefore, the mapping of subjects can be arranged into two groups namely Mathematics- Sciences- English and English-Indonesian- Sains. These results can be useful as a basis for decision making on various technical aspects to optimize junior high school student learning outcomes, especially in Lampung Province.Keywords: Clusterization, Lampung, National Examination

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“…(2009) The development of students' entrepreneurial and innovative competences results in building an awareness of their own strengths, capabilities and effectiveness of operation as well the ability to identify and exploit market opportunities. Because learning outcomes are often correlated with proper career assessment (Ferrer & Dela Cruz, 2017), it can be assumed that these effects influence graduates' determination and preferences in the selection of further career paths, especially related to the founding In order to obtain the answers to these questions in relation to a selected Polish university, empirical research was conducted for which a report is presented further on in the paper.…”

Section: Introductionmentioning

confidence: 99%