Search Results (11)

This study examines the evolution and main trends in the number of students, teaching staff and graduates in Romania’s pre-university education system over the period 1990–2024 (and 1990–2023 for graduates), employing ARIMA models to generate forecasts up to the year 2027. The research is grounded in the premise of profound structural transformations within the Romanian educational system, driven by demographic decline, external migration, recurrent reforms, and shifts in resource allocation. The descriptive analysis highlights a pronounced downward trend for all three variables (students, teaching staff and graduates), reflecting the continuous reduction in the school-age population and the restructuring of the educational network. The statistical tests employed, such as Shapiro–Wilk, Augmented Dickey–Fuller, Durbin–Watson, Breusch–Godfrey and ARCH, validate the selected optimal ARIMA models: ARIMA(1,1,1) for teaching staff, ARIMA(4,1,3) for students, and ARIMA(3,1,5) for graduates. The forecasting results indicate that this declining trend is expected to persist through 2027: the number of teaching staff is estimated to decrease to approximately 178,700 individuals, the number of students is estimated to decrease to around 2.78 million, and the number of graduates is projected to fall until 2026, followed by a potential slight stabilization in 2027. The Spearman correlation analysis indicates strong associations among all variables, suggesting that their dynamics are predominantly shaped by demographic and migratory factors. Granger causality analysis shows that changes in birth rates lead to rapid adjustments in teaching staff within 2–3 years. No significant short-term causality is found for the number of students or graduates, though demographic effects appear after 5–6 years for students, indicating long-term impacts on the school population. This study underscores the importance of econometric methods in informing educational policy, particularly in the context of the marked contraction of the school-age population. It also highlights the need for strategic planning regarding human resources in education, per-student funding, the reorganization of the school network, and curriculum adaptation. Full article

Behavioral and educational researchers increasingly rely on rich datasets that capture how students respond to technology-enhanced instruction, yet few open resources document the full pipeline from experimental design to data curation in authentic classroom settings. This data descriptor presents a clustered quasi-experimental dataset on the impact of an instructional architecture that combines virtual reality (VR) simulations with artificial intelligence (AI)-driven formative feedback to enhance undergraduate students’ communication and problem-solving performance. The study was conducted at a large private university in Mexico during the 2024–2025 academic year and involved six intact classes (three intervention, three comparison; n = 180). Exposure to AI and VR was operationalized as a session-level “dose” (minutes of use, number of feedback events, number of scenarios, perceived presence), while performance was assessed with analytic rubrics (six criteria for communication and seven for problem solving) scored independently by two raters, with interrater reliability estimated via ICC (2, k). Additional Likert-type scales measured presence, perceived usefulness of feedback and self-efficacy. The curated dataset includes raw and cleaned tabular files, a detailed codebook, scoring guides and replication scripts for multilevel models and ancillary analyses. By releasing this dataset, we seek to enable reanalysis, methodological replication and cross-study comparisons in technology-enhanced education, and to provide an authentic resource for teaching statistics, econometrics and research methods in the behavioral sciences. Full article

With rapid urbanization, improving school quality in compulsory education is critical for optimal educational resource allocation. This study integrates a random forest machine learning model, GIS spatial analysis, and a spatial econometric model to examine the spatiotemporal differentiation of school quality in Dalian, China, in 2016 and 2020, as well as its relationships with the construction land development cycle, population density, and housing prices. The findings reveal a core–periphery structure, with overall school quality on the rise and basic facility configuration exerting a stronger impact than teacher strength. Among internal resources, per capita sports venue area (PCSFA) and per capita teaching equipment value (PCTRE) contribute most significantly to school quality, while high-quality clusters in traditional educational hubs, university-covered areas, and transitional zones spur improvements in surrounding schools. The population density, housing prices, and the construction land development cycle all positively correlate with school quality, highlighting the need for coordinated action among urban planners, education authorities, and housing regulators to ensure that land development, housing affordability, and school facility investments advance equitable access to quality education. These results provide a novel perspective on compulsory education quality assessment and offer a valuable foundation for guiding education policies and urban development strategies. Full article

This paper proposes a nonlinear teaching approach, based on learning theories in cognitive psychology, with a special focus on large-cohort economics modules. The fundamental rationale is to match the features of teaching with the nature of learning. This approach was implemented in an undergraduate economics module, which received qualitative feedback and quantitative evaluation. Formal econometric models with both binary and continuous treatment effects were developed and estimated to quantify the effects of the proposed approach. Evidence shows that the nonlinear teaching approach significantly improves the effectiveness and efficiency of the learning-teaching process but does not promote student attendance. Full article

This article uses student evaluation of teaching (SET) data for 947 faculty members affiliated with 90 U.S. colleges and universities to study the presence of a teaching quality rating premium for clinical economics faculty relative to traditional tenure-track economics faculty. Based on OLS estimation, we find this difference ranges between 3.9% and 4.8% and is robust to different econometric model specifications. Moreover, the average treatment effect from a propensity score weighting approach suggests that the difference ranges between 5.8% and 6.1%. Lastly, our analysis produces an institutional ranking of economics departments based on department-level SETs. Overall, our findings are encouraging signs for the hiring and retention of clinical faculty in economics departments. Full article

This paper presents the findings of 12 years of data from studying the teaching of econometrics. The first course on the topic of econometrics has always been a challenging course for both students and instructors. Students come from different quantitative backgrounds, and mostly with the prejudice that this is one of the most challenging courses in their academic career. We showed that using Classroom Response Systems (CRSs) such as polls closes the achievement gap between students from higher and lower quantitative levels. Besides students’ performance, we also investigated instructor performance through teaching and course evaluations utilizing data from 38 classes over the course of 12 years. We showed that the instructor performance is higher under the in-class modality compared to the online modality and showed that this gap in performance between the two modalities widens as students’ grades improve; a positive association between grades and instructor performance under the in-class modality exists; however, the association is negative under the online modality. Full article

Even though research focused on inclusive education in Romania for institutions within the primary and secondary education system has been carried out, there are not many studies that approach the factors determining a favorable inclusion of students in higher education institutions. The central goal of the article consisted in investigating what impacts the willingness and openness for inclusive education for Romanian universities and the potential impact of five constructs of variables applied on fifteen universities from Romania. The outcomes of the quantitative (econometrical) analysis (a survey based on a questionnaire) showed the major impact of the variables of “policies and structures of the university”, “curriculum and pedagogy/teaching strategies”, “community and social integration”, and “accessibility and resources for students” (all focused on students with special needs) on the “willingness and openness for inclusive education” for Romanian universities. The variable of “communication and transparency” (focused on students with special needs) was associated with a medium influence on the “willingness and openness for inclusive education” for Romanian universities. This paper underlines the importance of incorporating the necessary training, support, flexibility, and resources to respond to a variety of student needs in order to improve inclusive education within higher education institutions in Romania. Full article

This article was prepared for the Special Issue “Celebrated Econometricians: Katarina Juselius and Søren Johansen” of Econometrics. It is based on material recorded on 30 October 2018 in Copenhagen. It explores Søren Johansen’s research, and discusses inter alia the following issues: estimation and inference for nonstationary time series of the I(1), I(2) and fractional cointegration types; survival analysis; statistical modelling; likelihood; econometric methodology; the teaching and practice of Statistics and Econometrics. Full article

This study focuses on identifying personality traits in computer science students and determining whether they are related to academic performance. In addition, the importance of the personality traits based on motivation scale and depression, anxiety, and stress scales were measured. A sample of 188 students from the Computer Engineering Schools of the Pontifical Catholic University of Valparaíso was used. Through econometric two-stage least squares and paired sample correlation analysis, the results obtained indicate that there is a relation between academic performance and the personality traits measured by educational motivation scale and the ranking of university entrance and gender. In addition, these results led to characterization of students based on their personality traits and provided elements that may enhance the development of an effective personality that allows students to successfully face their environment, playing an important role in the educational process. Full article

Education for sustainable development (ESD) has presented long-lasting interest for researchers and policy makers. Despite a significant body of research, more in depth empirical studies are required for a better understanding of how sustainable development goals are applied in higher education and how sustainable behavior could be shaped via ESD. The need for this kind of research arises from, first, the scarceness of existing studies that explore economic and business higher education, and, second, the necessity to properly assess the connection between ESD principles and students’ behavior. Following this rationale, the present paper aims to provide an overview of how students’ sustainable behaviors are shaped via their perception of sustainable campus initiatives, teaching staff involvement and curricula. Statistical and econometric analysis applied on data collected via a survey on students from Bucharest University of Economic Studies (N = 1253) provides findings on the extent to which the awareness of sustainable development-specific issues acquired through education leads to sustainable behavior among students. According to the results, we argue that an increasing share of sustainable development topics combined with teaching staff involvement to raise awareness of sustainability issues are crucial to students’ sustainable behavior. However, on-campus actions are unlikely to change behavior unless they are optional rather than compulsory. Our findings ratify that, since education is one of the main drivers of sustainable development, there is an urgent need for coherence in shaping higher education according to sustainability issues. Full article

Building on arguments by Joshua Angrist and Jörn-Steffen Pischke arguments for how the teaching of undergraduate econometrics could become more effective, I propose a redesign of graduate econometrics that would better serve most students and help make the field of economics more relevant. The primary basis for the redesign is that the conventional methods do not adequately prepare students to recognize biases and to properly interpret significance, insignificance, and p-values; and there is an ethical problem in searching for significance and other matters. Based on these premises, I recommend that some of Angrist and Pischke’s recommendations be adopted for graduate econometrics. In addition, I recommend further shifts in emphasis, new pedagogy, and adding important components (e.g., on interpretations and simple ethical lessons) that are largely ignored in current textbooks. An obvious implication of these recommended changes is a confirmation of most of Angrist and Pischke’s recommendations for undergraduate econometrics, as well as further reductions in complexity. Full article