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Assessment of attitudes towards statistics [ATS] is needed to support the success of statistics education in tertiary institutions, so measuring instruments with high accuracy is required. However, existing instruments to measure ATS have not considered the use of technology as an essential variable affecting success in statistics education. The current study sought to fill this gap by developing a standardized instrument to measure ATS and considering aspects of technology use as a necessity for statistics education in the modern era. The study involved 367 students from various study programs spread across several universities in Indonesia as participants. To examine the quality of the instrument, we performed factor analysis, reliability estimation, and item calibration. We calibrated items based on classical test theory [CTT] and item response theory [IRT] using the graded response model [GRM]. Exploratory factor analysis [EFA] indicated three main factors (i.e., interest, difficulty, and value) for measuring attitudes toward statistics. Factor loading of each factor component > 0.45, indicating that all items contributed to the main factor. Cronbach’s alpha coefficient of the three factors ranged from 0.784 to 0.929, indicating that the instrument was reliable. Item calibration based on CTT and IRT-GRM indicated that item performance was satisfactory regarding item endorsement and discrimination. In addition, the information function indicated that the instrument accurately measures attitudes from very low to very high levels. Overall, the psychometric properties of the instrument indicated that the instrument was valid, reliable, and feasible for use in practice and research in the field of education.

This study aims to examine the co-occurrence of several topics linked to factors that influence student learning success and explore the motor themes related to factors that influence student learning success. This study used the literature review method with data analysis using R Studio and VOSViewer software. Data analyzed were exported from the Scopus website from 2013 to 2023 of 383 documents. The research data analysis techniques used network mapping analysis of VOSviewer results (network visualization) and content analysis within the keywords and studies. The findings of this study presented the keywords (most frequent words, trending topics), co-occurrence network (thematic map and thematic evolution), and discussion of topics related to factors that influence student learning success. The basic themes identified were higher education and Covid-19. Meanwhile, gender and self-efficacy are motor themes that could be researched further as those can influence student learning performance in online learning. The findings of the bibliometric analysis were intended to reveal unique insights into the factors that determine student learning performance in distant learning and contribute to previously unexplored issues.

Quality research can positively impact the development of science and technology and improve the reputation of universities. This study investigates the determinant factors that affect the research performance of lecturers who obtain external funding. The sample was 41 lecturers who obtained external research funds from various institutions (e.g., Directorate of Research, Technology and Community Service, Ministry of Education, Culture, Research and Technology of the Republic of Indonesia; National Research and Innovation Agency of the Republic of Indonesia; and similar institutions) for the last three years (2021 - 2023). Cluster analysis using secondary data (Science and Technology Index or SINTA data) was conducted to determine research performance clusters (high and low). Discriminant analysis was conducted to determine the determinant factors affecting research performance achievement based on the cluster analysis results. The results revealed that internal factors, including mastery of English and interest in the research topics offered, are determinant factors that affect the research performance of lecturers receiving external funding. In external factors, eight determinant factors affect research performance, namely: support for dissemination of research results in journals, support from research assistant staff, satisfaction with awards from the university, satisfaction with awards from outside the university, support for research matching funds from the university, training in writing research proposals, ease of obtaining research permits from agencies outside the university, and adequacy of facilities at the university. Universities need to consider these factors to encourage the improvement of the research performance of lecturers receiving external funding.

Statistical literacy (hereafter SL) has been considered an important learning outcome in statistics learning in higher education, yet studies that focus on investigating the factors and conditions that influence students’ SL, especially mathematics education students, are still limited. This study seeks to uncover the factors and conditions that significantly contribute to the SL of mathematics education students. This survey study involved 1,287 mathematics education students from 21 higher education institutions in Indonesia. Linear regression analysis involving four predictor variables (i.e., gender, status of higher education institution, laptop ownership, and research preference) was performed to determine the variables that contributed significantly in predicting SL achievement. The results revealed that gender, higher education institution’s status, and laptop ownership contributed significantly, but research preference was not significant in predicting mathematics education students’ SL. Furthermore, laptop ownership was found to have the highest contribution in predicting mathematics education students’ SL. All findings and their implications are discussed.

Three popular models are used to describe the characteristics of the test items and estimate the ability of examinees under the dichotomous IRT model, namely the one-, two-, and three-parameter logistic models. The three-item parameters are discriminating power, difficulty, and pseudo-guessing. In the development of the dichotomous IRT model, carelessness or upper asymptote parameter was proposed, which forms a four-parameter logistic (4PL) model to accommodate a condition where a high-ability examinee gives an incorrect response to a test item when he/she should be able to respond to the test item correctly. However, the carelessness parameter and the 4PL model have not been widely accepted and used due to several factors, and people’s understanding of that parameter and strategies for estimating it is still inadequate. Therefore, this study aims to shed light on ideas underlying the 4PL model, the meaning of the carelessness parameter, and strategies used to estimate that parameter based on the extant literature. The focus of this study was then extended to demonstrating practical examples of estimating item and person parameters using the 4PL model using empirical data on responses of 1,000 students from the Indonesia Open University (Universitas Terbuka) on 21 of 30 multiple-choice items on the Business English test, a paper-and-pencil test. We mainly analyzed empirical data using the ‘mirt’ package in RStudio. We present the analysis results coherently so that IRT users would have a sufficient understanding of the 4PL model and the carelessness parameter, and they can estimate item and person parameters under the 4PL model.

Scoring quality has been recognized as one of the important aspects that should be of concern to both test developers and users. This study aimed to investigate the effect of scoring correction and model fit on the estimation of ability parameters and person fit in the polytomous item response theory. The result of 165 students in the Statistics course (SATS4410) test at one of the universities in Indonesia was used to answer the problems in this study. The polytomous data obtained from scoring the test results were analyzed using the Item Response Theory (IRT) approach with the Partial Credit Model (PCM), Graded Response Model (GRM), and Generalized Partial Credit Model (GPCM). The effect of scoring correction and model fit on the estimation of ability and person fit was tested using multivariate analysis. Among the three models used, GRM showed the best fit based on p-value and RSMEA. The results of the analysis also showed that there was no significant effect of scoring correction and model fit on the estimation of the test taker’s ability and person fit. From the results of this study, we recommend the importance of evaluating the levels or categories used in scoring student work on a test.

This study explores the correlation between technology utilization and language acquisition while analyzing the impact of moderating variables on this relation. Our meta-analysis approach analyzes data from 43 extracts out of 19 primary studies published between 2012 and 2021. Our data analysis employs a random-effect model utilizing a significance level of [Alpha] = 0.05. Additionally, the authors examine four moderating variables: level of education, location of research, proficiency in language, and year of publication. Technology-based language acquisition outperforms traditional methods, indicating a significant and moderate impact on the learning process. This study enhances comprehension of the efficacy of technology in language acquisition by identifying various factors, such as the geographical location of research, methods of assessing language proficiency, and technology type employed. However, there is insufficient evidence to support the notion that educational level or sample size significantly impact technology-based language acquisition. This meta-analysis highlights the importance of considering nuanced factors when integrating technology into language learning. The findings emphasize the possibility of technology to transform methods of acquiring language and urge additional investigation into customized strategies that optimize its advantages.

The use of mobile technology in physics education has become more prevalent, but more data about its effect on student academic performance needs to be collected. This meta-analysis examines the effects of mobile learning on student achievement in physics and any moderating factors. The study collected 36 primary studies from various scientific databases (Scopus, ERIC, DOAJ, Google Scholar) that met the inclusion criteria. The findings indicate that using mobile technology has a significant effect on student performance in physics compared to without mobile learning. Moderator analysis revealed differences in the effects of mobile learning on physics learning outcomes based on sample size, academic level, gender composition, learning media type, learning model type, learning outcome type, and measurement instrument type. However, no effect difference was observed in country status, publication year, sampling technique, and physics content. No publication bias was found in this study. Overall, the study suggests that mobile learning has a strong positive effect on student achievement in physics.

This explorative-descriptive study set out to examine the equivalence among Test of English Proficiency (TOEP) forms, developed by the Indonesian Testing Service Centre (ITSC) and co-founded by The Association for The Teaching of English as a Foreign Language in Indonesia (TEFLIN) and The Association of Psychology in Indonesia. Using a quantitative approach, the researchers collected the data through documenting the responses of those taking TOEP in 2016 and 2017, involving six TOEP forms in 2016 and four TOEP forms in 2017. All the forms were developed using the same test grid and construct to measure the listening and reading skills. The equality among the six forms was tested using the equating technique, which involved (1) the estimation of the item parameter using the Rasch model, (2) examination of the test characteristics curve for each form, and (3) interpretation of results. The results showed that all the TOEP forms used in 2016 and 2017 were equal with one another. It can be concluded then that the developed TOEP forms have the same level of difficulty and ensure justice for all test takers.

The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia, as well as the essential factors (attributes) that can explain it. This research used a data mining method. The data set used in this study is from an Indonesian university and contains demographic and academic records of 132,734 students. Demographic data (age, gender, marital status, employment, region, and minimum wage) and academic (i.e., grade point average (GPA)) were utilized as predictors of students' time to graduation. The findings of this study show that (1) the prediction model using the random forest and neural networks algorithms has the highest classification accuracy (CA), and area under the curve (AUC) value in predicting students' time to graduation (CA: 76% and AUC: 79%) compared to other models such as logistic regression, Naïve Bayes, and k-nearest neighbor; and (2) the most critical variable in predicting students' time to graduation along with six other important variables is the student's GPA.

Many studies reported the importance of character education for students to support their future success. Currently, the countries have strengthened the implementation of character education in their educational system, including Indonesia. Related to the previous statements, this research aimed to describe the impact of character education implementation as well as challenges and strategies of teachers in implementing the character education. This research was an evaluation research type using a goal-free evaluation model (impact evaluation) with a qualitative approach. The participants of the research were principals, teachers, students, parents, and community members from three provinces in Indonesia; East Kalimantan, Special Region of Yogyakarta, and West Nusa Tenggara. Data were collected through Focus Group Discussion (FGD) and also in-depth interviews. The data were then analysed using a model of Bogdan and Biklen to find out the refinement among themes and generate a detailed understanding. The findings showed that character education had a positive impact on increasing the students' character values including religiosity, personality, social attitude, and competitive attitude. Role-modelling by teachers and other members of the school community and parents, character-oriented activities, and moral and material support from educational stakeholders are key factors in character education implementation. However, some improvements need to be made, such as improving the teacher training and workshops and giving financial support (funding) for character education implementation.

International surveys, such as TIMSS and PISA, frequently put Indonesia in the low ranks. It is an indication that the higher-order thinking skills (HOTS) of students in Indonesia are still low. This research aims to analyze students' difficulties in solving problems that measure HOTS. This is a case study research with a qualitative approach. Participants studied were 93 high school students in grade XI. Data were collected using test instruments that measure HOTS, which was developed based on the standard contents of high school mathematics. The difficulties were analyzed descriptively by observing students' errors in answering HOTS test items. Students' errors were classified based on Newman's Error Procedure (NEP). The result shows that around 8.33% of the students had difficulties in comprehension, 15.59% in transformation, 32.53% in process skills, and 1.34 % in encoding.

Higher order thinking skill (HOTS) is one of the students' abilities that should be developed through teaching and learning. Teachers' knowledge about HOTS and its teaching and learning tactics is a key to successful education. The purpose of this research is to describe teachers' knowledge about higher order thinking skills (HOTS). The research involves qualitative study with the phenomenological approach. The research participants are 27 mathematics teachers from state and private junior high schools across 7 provinces in Indonesia. The researcher collected data with a test followed by focus group discussion (FGD) and interviews. The analysis of data involved Bogdan & Biklen model and descriptive statistics for data from the test. The analysis of FGD, and test data intends to get information on 6 sub-themes; teachers' knowledge about HOTS, importance of HOTS, teaching about HOTS to students, improving students' HOTS, measuring and assessing HOTS, and teachers' ability for solving HOTS-based problems. The results indicate that teachers' knowledge about HOTS, their ability to improve students' HOTS, solve HOTS-based problems, and measure students' HOTS is still low. There are facts, however, that teachers already understand the importance of HOTS and teaching it by using various innovative learning models.

One of useful theories in the educational and psychological assessment is an item response theory (IRT) that applies mathematical concepts. For students, constructing math concept to solve problems in IRT is very difficult and utilizing technology such as computer and software will help. In a qualitative approach, this study described how students constructed mathematical concepts in the item response theory using external mathematical representations integrated with technology. The participants were 19 graduate students. Data were collected through observation in 5 courses. The data were analyzed using Milles and Hubberman technique through reduction, display, and verification. The results showed that by using external representations and providing cases, presenting data in tables, the collaboration among the students to solve problems, create and demonstrate graphics utilizing technology to construct mathematical concepts, utilize the context assessment related to mathematical concepts, and also use graphs could support students' thinking for constructing mathematical concepts in IRT. [ABSTRACT FROM AUTHOR]