The bibliometrix package in R software, which is frequently used in the bibliometric analysis, was introduced in this research. The article aimed to illustrate the various analyses applied in a bibliometric study. For this purpose, articles containing the keyword "item response theory" (IRT) or "item response modeling" or "item response model" were searched in the Thomson Reuters Clarivate Analytics Web of Science (WoS at http://www.webofknowledge.com), and bibliometric data was downloaded. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) steps were followed in the study. Data from 3388 IRT-related articles on education and psychology, searched between 2001 and 2021, were used in the study. Data were analyzed with the bibliometrix package. Some of the stages in data analysis were shared with screenshots. As a result of data analysis through the real data set, the key concepts related to IRT were item response model, differential item functioning, psychometrics, assessment, measurement, reliability, validity, Rasch model, and measurement invariance. The countries with the highest number of citations in IRT studies were the USA, Canada, Netherlands, United Kingdom, and China, respectively. Turkey ranked 12th in IRT studies with 434 citations. It was thought that bibliometric analysis of articles related to IRT will shed light on researchers in the field of psychometrics.

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The present study explores the self-regulated learning (SRL) research published in English or Turkish language journals included in the Web of Science database from the beginning to 2021 via bibliometric analysis. The 2197 articles that met the eligibility criteria were included in the study. The results reveal that the research on SRL has been carried out mostly by scholars from the USA and has gained increased attention since the 2000s. The three most influential scholars of self-regulated research are Chia-Wen Tsai, Philip H. Winne, and Roger Azevedo; however, the two top documents by local citations belong to Barry J. Zimmerman (2008) and Paul R. Pintrich (2004) in the study. The analyzed studies cited the Journal of Educational Psychology and Contemporary Educational Psychology most. The results reveal that motivation, metacognition, self-efficacy, and learning strategies are the keywords that most frequently occur and co-occur in the analyzed studies along with SRL. The trend topics of SRL research have been learning analytics, flipped classrooms, and MOOCs since 2018.

This study aimed to investigate the impact of item features (i.e., content domain), student characteristics (i.e., gender), and school variables (i.e., school type) on students' responses to a nationwide, large-scale assessment in Turkey. The sample consisted of 7507 students who participated in the 2016 administration of the Transition from Primary to Secondary Education Exam (TPSEE, referred to as "TEOG" in Turkey). Explanatory item response modeling was used for analyzing the effects of content domain, gender, school type, and their interactions on students' responses to the science items on the exam. Five explanatory models were constructed to examine the effects of the item, student, and school variables sequentially. Results indicated that female students were more likely to answer the items correctly than male students. Also, students from private schools performed better than students from public schools. In terms of content, the biology items appeared to be significantly easier than the physics items. All interactions between the predictors were significant except for the Gender x School Type and Content x Gender x School Type interactions. The interactions between the predictors suggested that test developers, teachers, and stakeholders should be aware of potential item-level bias occurring in the science items due to complex interactions among the items, students, and schools characteristics.

The Teaching and Learning International Survey (TALIS) and the Programme for International Student Assessment (PISA) are large-scale measurements about teaching and learning. There is a link between TALIS indicators and PISA results. We investigated which countries are effective according to TALIS indicators as inputs and PISA 2015 mathematics, scientific, and reading literacy scores as outputs in this research. Common 24 countries' data from TALIS 2013 and PISA 2015 were analyzed. Data envelopment analysis was used in this quantitative research. Belgium, Denmark, Finland, Italy, Korea, Mexico, Netherlands, Norway, and Portugal were found to be effective countries in EMS 1.3, DEAP-XP 2.1, and R-4.0.3 software according to the input-oriented CCR model. Belgium, Canada, Denmark, Estonia, Finland, Italy, Japan, Korea, Mexico, Netherlands, Norway, and Portugal were found to be effective countries in EMS 1.3, DEAP-XP 2.1, and R-4.0.3 software according to the input-oriented BCC model. The results obtained from the BCC and CCR model differ partially. Italy and Norway should be taken as reference the mostly by ineffective countries for getting better PISA score according to both models analyzing with EMS 1.3, DEAP-XP 2.1, and R-4.0.3.