This study aims to apply the model Principal component Analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hongkong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield levels of multicolinierity which is smaller in comparison with PCA applications using multiple regression. This study used multiple regression test and PCA application to investigate the differences in multicollinearity at yield. From this research, it can be concluded that the use of PCA analysis applications can reduce multicollinearity in variables in doing research.

Teaching with technology is considered a necessity in the U.S. mathematics classroom. However, few studies have established explicit considerations to support technology-enhanced student achievement. The purpose of this study was to characterize the effectiveness of technology in the mathematics classroom by systematically reviewing meta-analytic research. An exhaustive literature search was conducted. After applying a prioi inclusion criteria the pool of 65 initial meta-analyses was reduce to 13 representative studies. Each study was reviewed and characteristics were coded in four categories: (1) sample, (2) measurement, (3) design, and (4) source. An inductive review of the coded studies produced five unique moderators that were the most salient across studies. Overall mean effect sizes were retrieved or calculated from available study data. Hedges g was used as the common effect size metric for comparison across studies.  The Technological Pedagogical Content Knowledge (TPACK) framework was used to interpret the most salient moderators of effects across studies.  Studies were categorized by didactical functionality and technology type. The results suggest that effects vary by didactical functionality from small to medium. The largest variations were observed for the didactical function of developing conceptual understanding.  Implications for research and instructional praxis are provided.

By using multi-level modeling, this study explores the impact of students’ perception of the quality of the teacher-student relationship and family structure on student achievement after controlling for socioeconomic status (SES), school urbanicity, and school control. The data from 750 schools and 17,000 10th grade students were analyzed. Family structure and student’s perception of teacher-student relationship, and SES were student-level; school urbanicity and school control were school-level variables. The findings indicated that students, who had a positive perception about their relationship with their teachers, came from families including two biological parents, and had high SES and high math achievement. Students’ SES and attending public school in urban areas were found to be significantly related to students’ math achievement. The math score for public school students was lower than students from private and Catholic schools. The further research should have a design addressing the impact of these variables in a longitudinal term.

In the current study, the problems posed by pre-service primary school teachers within the context of semi-structured problem formation were analyzed according to their type, cognitive structure, and content knowledge. A total of 134 pre-service primary school teachers attending a state university in Turkey participated in the current study designed in line with the case study design. The pre-service teachers were presented with a table and they were asked to establish a problem suitable for the elementary level using the data given in the table. The data were collected through the established problem statements and written explanations of the participants. The collected data were analyzed by using both content and descriptive analyses. The findings have revealed that the pre-service teachers less preferred real-life problems than routine type of problems and the problems at the level of reasoning than the problems at the levels of knowing and applying. Moreover, nearly half of the pre-service teachers erroneously expressed the grade level for which they established their problem. The results have shown that the pre-service teachers do not adequately use real-life problems and problems at the level of reasoning and that there are deficiencies in their mathematical content knowledge depending on their knowledge of the curriculum.

STEM education is a pedagogical philosophy which aims to draw the interrelationship between science, technology, engineering and mathematics to solve complex problems in real life situations. In order to use STEM education to foster students’ learning, the researchers designed STEM activities for middle school students related to the concept of force and motion in three different approaches: a linear model, a jigsaw learning and a stand-alone engineering design activity. To compare the effectiveness of the three approaches, the researchers analysed students’ reasoning and problem-solving scores gained before and after doing the activities. The result showed students participating in the linear model and in the jigsaw learning significantly outperformed those in the stand-alone engineering design activity. In addition, when comparing conceptual development between those attending the linear model and jigsaw learning, the result showed that the former significantly outperformed the latter. It is therefore suggested that to maximise the effectiveness of STEM activities in promoting conceptual understanding as well as reasoning and problem-solving skills, teachers should adopt the linear model. However, when instructional time is limited, the jigsaw learning can be considered as an alternative approach. The stand-alone engineering design activity although can promote students’ enthusiasm to learn, it may not sufficiently lead to the development of reasoning and problem-solving skills as expected.

Pearson product–moment correlation coefficient between item g and test score X, known as item–test or item–total correlation (Rit), and item–rest correlation (Rir) are two of the most used classical estimators for item discrimination power (IDP). Both Rit and Rir underestimate IDP caused by the mismatch of the scales of the item and the score. Underestimation of IDP may be drastic when the difficulty level of the item is extreme. Based on a simulation, in a binary dataset, a good alternative for Rit and Rir could be the Somers’ D: it reaches the ultimate values +1 and –1, it underestimates IDP remarkably less than Rit and Rir, and, being a robust statistic, it is more stable against the changes in the data structure. Somers’ D has, however, one major disadvantage in a polytomous case: it tends to underestimate the magnitude of the association of item and score more than Rit does when the item scale has four categories or more.

The study's goal was to examine the correlation between the computer programming self-efficacy and computational thinking skills of gifted and talented students. The capacity of the computer programming self-efficacy of gifted and talented students to predict their computational thinking skills were also examined. The relational screening model has been implemented in the research. The participants of the study were composed of 106 secondary school gifted and talented students studying the Individual Ability Recognition Program (IAR) at the Science and Art Center in the city center. Typical case sampling was applied for the student identification of the participants, 46 are female and 60 are male. Gifted and talented students' computational thinking skills were assessed using the "Computational Thinking Skills Scale” and the computer programming self-efficacy was measured by using the "Computer Programming Self-Efficacy Scale". Data were analysed by Pearson correlation analysis and simple linear regression analysis in statistical software SPSS 22. Research results found that there was a positive and high correlation between the computer programming self-efficacy and computational thinking skills. The gifted and talented students' computer programming self-efficacy demonstrated 31.5% of the total variance in computational thinking skills. This finding supports the claim which is present in the literature that self-efficacy in computer programming is the affective aspect of computational thinking skills. To predict computational thinking skills, it may be recommended to build multiple models for cognitive and affective skills of gifted and talented students.

A new index of item discrimination power (IDP), dimension-corrected Somers’ D (D2) is proposed. Somers’ D is one of the superior alternatives for item–total- (Rit) and item–rest correlation (Rir) in reflecting the real IDP with items with scales 0/1 and 0/1/2, that is, up to three categories. D also reaches the extreme value +1 and ‒1 correctly while Rit and Rir cannot reach the ultimate values in the real-life testing settings. However, when the item has four categories or more, Somers’ D underestimates IDP more than Pearson correlation. A simple correction to Somers’ D in the polytomous case seems to lead to be effective in item analysis settings.  In the simulation with real-life items, D2 showed very few cases of obvious underestimation and practically no cases of obvious overestimation. With certain restrictions discussed in the article, D2 seems to be a good alternative for these classic estimators not only with dichotomous items but also with the polytomous ones. In general, the magnitudes of the estimates by D2 are higher than those by Rit, Rir, and polychoric correlation and they seem to be close of those of bi- and polyserial correlation coefficients without out-of-range values.

Although Goodman–Kruskal gamma (G) is used relatively rarely it has promising potential as a coefficient of association in educational settings.  Characteristics of G are studied in three sub-studies related to educational measurement settings. G appears to be unexpectedly appealing as an estimator of association between an item and a score because it strictly indicates the probability to get a correct answer in the test item given the score, and it accurately produces perfect latent association irrespective of distributions, degrees of freedom, number of tied pairs and tied values in the variables, or the difficulty levels in the items. However, it underestimates the association in an obvious manner when the number of categories in the item is more than four. Towards this, a dimension-corrected G (G2) is proposed and its characteristics are studied. Both G and G2 appear to be promising alternatives in measurement modelling settings, G with binary items and G2 with binary, polytomous and mixed datasets.

Response times are one of the important sources that provide information about the performance of individuals during a test process. The main purpose of this study is to show that survival models can be used in educational data. Accordingly, data sets of items measuring literacy, numeracy and problem-solving skills of the countries participating in Round 3 of the Programme for the International Assessment of Adult Competencies were used. Accelerated failure time models have been analyzed for each country and domain.  As a result of the analysis of the models in which various covariates are included as independent variables, and response time for giving correct answers is included as a dependent variable, it was found the associations between the covariates and response time for giving correct answers were concluded to vary from one domain to another or from one country to another. The results obtained from the present study have provided the educational stakeholders and practitioners with valuable information.

What are missing in the U.S. education policy of “college for all” are supporting data and indicators on K-16 education pathways, i.e, how well all students get ready and stay on track from kindergarten through college. This study creates synthetic national longitudinal education database that helps track and support students’ educational pathways by combining two nationally-representative U.S. sample datasets: Early Childhood Longitudinal Study- Kindergarten (ECLS-K; Kindergarten through 8th grade) and National Education Longitudinal Study (NELS; 8th grade through age 25). The merge of these national datasets, linked together via statistical matching and imputation techniques, can help bridge the gap between elementary and secondary/postsecondary education data/research silos. Using this synthetic K-16 education longitudinal database, this study applies machine learning data analytics in search of college readiness early indicators among kindergarten students. It shows the utilities and limitations of linking preexisting national datasets to impute education pathways and assess college readiness. It discusses implications for developing more holistic and equitable educational assessment system in support of K-16 education longitudinal database.

Technical and pedagogical counseling as accompaniment benefits teachers’ development. However, there are information gaps on the specific impact of counseling with a socio-formative approach on both professionalization and the improvement of teaching practice. The objective is to analyze the relationship between these three elements. A cross-sectional study with a quantitative approach was employed. A validated questionnaire was applied to a representative sample of 212 teachers. The information analysis was carried out through statistics: descriptive, correlational, and linear regression, whose level of significance was: <.01-. 05. Teachers consider that technical and pedagogical counseling from socio-formation fosters the development of an ethical life project, promotes problem solving in their educational practice, collaborative work, metacognition, and entrepreneurship (92.78 ± 14.3). The correlational analysis showed a significant relationship between socio-formative pedagogical technical counseling and teaching practice, the latter of which was enhanced by the former. In the linear regression analysis, the best model of pedagogical technical counseling is made from socio-formation, which predicts a 71% improvement of teaching practice. As a result, this form of counseling benefits both professionalization and teaching practice through metacognition.

Research shows that children's reading proficiency levels in the early grades positively correlate with students' future academic achievement. This study provides the first-ever analysis of reading achievement trajectories for a cohort of students in grades 3 to 5 in 2014–17 in Hawaii schools. Hawaii serves a diverse student population whose characteristics differ in ways often overlooked by standard US racial and ethnic classifications. Our analysis shows that Native Hawaiian and Pacific Islander students not only start at a lower reading proficiency than their peers in Grade 3, but the achievement gap widens as they move from Grade 3 to Grade 5. Moreover, we find a strong association between students' third-grade performance and reading achievement growth rate above and beyond all other factors in our longitudinal model. The difference in performance patterns between student subgroups across the elementary grades can serve as an accurate baseline for yearly monitoring. In light of our findings, we discuss implications for policy and practice.

The purpose of this qualitative research is to analyze the reflective thinking process of prospective elementary teacher in numeracy problems in terms of their mathematical disposition. The subjects in this study were 26 prospective elementary school teachers who had attended elementary mathematics lectures. The focus in this research is the process of mathematical reflective thinking in solving story problems of a two-variable linear equation system in terms of the level of mathematical disposition. The research instrument consisted of a disposition questionnaire, a reflective thinking ability test and the researcher himself as the main instrument. Good mathematical reflective thinking skills are supported by disposition, by constantly monitoring one's own performance, reflecting on one's own performance, reasoning on one's own performance, considering the overall situation, the habit of analyzing the relationship between variables, being flexible in various alternative solutions to mathematical problems and trying to solve mathematical problems. From the results of this study, lecturers can develop learning media, scaffolding, or teaching materials that accommodate different dispositional abilities of prospective teachers that can be used to improve the reflective thinking process.

The purpose of this study was to increase student activity and learning outcomes by applying peer tutor learning methods combined with interactive case methods in online learning mode through Electronic Learning Aid (ELENA) and Zoom meeting. This study was carried out with a classroom action research (CAR) design in three cycles of implementation. This study was carried out in the even semester of 2020/2021 in the Cost Accounting course. Data collection methods used are documentation, observation, and tests. Student learning activities in online learning through ELENA and Zoom meetings have been recorded to show changes and improvements in the quality of student learning activities. The data analysis method used is quantitative descriptive analysis. The application of the peer tutor learning with the interactive case methods has been going well through the Zoom meeting and ELENA and is able to have an impact on student activities and learning outcomes in the Cost Accounting course. The increase in student learning activities can be seen in the increased ability of students to ask questions, provide responses or answers, and express opinions or ideas during lectures. Student learning outcomes also experienced a significant increase, which was 7.5%. Students who act as tutors can carry out their duties well.

The purpose of the study is to explore the ways of involving university stakeholders specifically in updating educational services. It combined exploratory and observational research methods which relied on qualitative or quantitative data gathered through the researcher-designed and validated tools which were the empirical and methodological contributions to the previous research. The five most frequent choices that might encourage the stakeholders to donate or invest in an educational institution were as follows: a portfolio of the use of donations, investments, or grants, having a stake in the educational services of more than 7%, having access to budgeting and cost reporting, having a share in the institutions’ profit and being one of the decision-makers. The factors that discouraged investors from investing in education were as follows: distrust of the activity of the educational institutions in terms of addressing the stakeholders’ needs or interests, lack of engagement or cooperation, institutional and government-imposed barriers between them and the institutions, uncertainty concerning the efficiency of the institutions and inefficient use of the resources by the institutions. The initiative was complimentarily perceived by stakeholders in terms of collaboration and investment opportunities. It was also found beneficial by the sampled students.

The purpose of this study was to compile and statistically analyze the results of research studies that examined students' problem-solving skills in worksheets. The research method used was a meta-analysis. The study search was conducted from 2013 to 2022 in Google Scholar and the Garuda portal databases. The search yielded 40 studies that met the inclusion criteria for extraction from research and development, experimental, and quasi-experimental. From the extracted results, 45 comparisons of data were examined. Microsoft Excel was used to calculate the effect size of the problem-solving worksheet. This study yielded a value of 1.281 for the entire study, indicating that the worksheet had a significant and positive impact on students' problem-solving skills. The results indicate the need to develop worksheets to improve students' problem-solving skills.

The implementation of learning activities in schools has not provided opportunities or encouragement for students in developing their procedural knowledge. This research aimed to test the effectiveness of developing Bloom’s Taxonomy revision-oriented learning activities to grade IV elementary learners’ procedural knowledge capabilities and learning outcomes. This research used quasi-experiment with a quasi-experimental design which consisted of a posttest-only control design. The population of this study was sixth-grade students of 9 schools with an overall number of 229 students. The sample in the study was 50 students, there were 26 students from the experimental class and 24 students from the control class. A test method with 10 question items was used as a data collection method. The data analysis methods and techniques used were quantitative descriptive analysis and inferential statistical analysis. Then the data were analyzed using the MANOVA test assisted by the IBM SPSS Statistics 21.0 program. The hypothesis test results showed a significance value of .000 (Sig<.05). It can be concluded in procedural capabilities and learning outcomes between groups of students there is a significant difference from following learning by implementing Bloom's Taxonomy Revision oriented learning activities with the experimental and control group.