Search results

This paper focuses on the factors related to faculty workload in the context of resource scarcity to examine whether there is a relationship between them and grade inflation.

As for methodological novelty, the authors created an indicator of students' expectations about grades that is related to grade inflation and conducted regression analysis using cluster-robust error correction based on this indicator.

The results suggested that proper workload allocation among the faculty can mitigate grade inflation. Namely, such measures as control for concurrent courses, the length of courses and the labor intensity of the faculty are suggested for grade inflation prevention.

Academic literature posits that a steep increase in average grades might cause a long-term depreciation of the quality of higher education. This article is, therefore, focused on various factors connected with grade inflation in higher education. The authors highlighted problems associated with teaching evaluation imperfections, academic norm transformation and workload intensity.

This study analyzed the impact on the persistence of Chilean university students who had received a government-guaranteed loan (CAE).

Using academic and administrative data from 2016 to 2019, provided by 11 Chilean universities, a discrete-time survival model was constructed. The model was based on data of 5,276 students in the 2016 cohort and included sociodemographic variables, academic background prior to entering university and academic performance once in university. As a robustness check of our results to observable confounding, the analysis was repeated using a control group constructed using propensity score matching (PSM).

The results reveal that students who receive a bank loan (CAE) were more likely to remain in undergraduate studies for at least the first two years of university, as opposed to their peers who did not receive financial aid. In addition, they show the importance of academic performance in retention.

The article advances in the identification of the impact of bank loans on permanence. Although previous research has evaluated the impact of the CAE, it has been conducted on small samples of students. These studies also lacked student records associated with their academic performance at the university. The present research overcomes both weaknesses, allowing us to estimate the impact of the CAE on a larger population of students that is representative of the system.

Teamwork is necessary for engineering to address today’s complex challenges. Therefore, team members must improve their teamwork competencies for more significant team development and effectiveness. This study aimed to analyze how a non-directive coaching intervention model for an entire team influences the individual team members’ teamwork competencies.

Action research was used in this study with a quasi-experimental design featuring control and experimental groups comprising final-year engineering students from Universidad Politécnica de Madrid. The sample included 168 students, with 132 in the control group and 36 in the experimental group. The experimental group underwent a non-directive team coaching intervention involving three sessions. Competencies were evaluated using the teamwork competency test (TWCT), administered at the course’s beginning and end to measure progress.

The results show that the individuals who participated in the team coaching significantly increased their competencies, particularly “conflict resolution” and “feedback.”

This study’s value contributes to identifying the positive impacts of non-directive team coaching interventions on individual teamwork competencies, fostering collaborative skills and supporting collective goals.

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability.

The real-world samples comprised the enrolled records of 2,412 first-year students of a private university (UNI) in Taiwan. This work utilized decision trees (DT), multilayer perceptron (MLP) and logistic regression (LR) algorithms for constructing EPMs; under-sampling, random oversampling and synthetic minority over sampling technique (SMOTE) methods for solving data imbalance problems; accuracy, precision, recall, F1-score, receiver operator characteristic (ROC) curve and area under ROC curve (AUC) for evaluating constructed EPMs.

DT outperformed MLP and LR with accuracy (97.59%), precision (98%), recall (97%), F1_score (97%), and ROC-AUC (98%). The top-ranking factors comprised “student loan,” “dad occupations,” “mom educational level,” “department,” “mom occupations,” “admission type,” “school fee waiver” and “main sources of living.”

This work only used enrollment information to identify dropout students and crucial factors associated with dropout probability as soon as students enter universities. The extracted rules could be utilized to enhance student retention.

Although first-year student dropouts have gained non-stop attention from researchers in educational practices and theories worldwide, diverse previous studies utilized while-and/or post-semester factors, and/or questionnaires for predicting. These methods failed to offer universities early warning systems (EWS) and/or assist them in providing in-time assistance to dropouts, who face economic difficulties. This work provided universities with an EWS and extracted rules for early dropout prevention and intervention.

This article describes an effort to ease the tension between boundary spanning roles for interns participating in a yearlong Professional Development School (PDS) program. In order to do this, the structure of a Social Studies Methods course was revised to mimic a professional learning community (PLC) and assignments were not evaluated for grades.

A conceptual paper that relies on self-reflection as well as student reaction, work samples and survey data.

The findings demonstrate both practices contribute to a collegial and less stressful environment for interns, while not affecting the quality of work submitted.

This paper highlights two of the nine NAPDS essentials, Professional Learning and Leading (3) and Boundary Spanning (8), and describes the ways both are incorporated and addressed in a PDS situated methods course. Describing course revisions, including the implementation of an ungrading practice, provides examples for potential replication.

The purpose of the article is to gain more insight into factors that can explain students' success in business subjects. The focus is on the connection between performance in introductory courses in business mathematics (BM) and business statistics (BS) and success in various business subjects.

Use of a regression model with administrative data from a business school in Norway over a period of 10 years.

The findings show a strong correlation, especially in quantitative subjects. The results suggest that statistical skills are more strongly related to academic success than mathematical skills.

The data are collected from only one school. No information on undergraduates' personalities and behaviours is available.

There are limited published studies that have explored the relationship between success in statistics and later achievements in business courses. This is useful knowledge for planning the content of the bachelor's programme.

The purpose of this study is to generate knowledge about assessment methods in blended business education, which have become increasingly important to establish sustainable assessment practices that support knowledge acquisition for undergraduate students in business administration at a Colombian university.

For the analysis, a two groups comparison was performed using a nonequivalent control group design with a sample of 420 students. As this study wants to find insights to improve the knowledge on assessment topics in marketing research (MR) education, it was focused on the students from the business administration program. This study also uses individual scores from the state test as prior cognitive scores and the high school classification provided by the National Ministry of Education in Colombia (2012).

It was found that the variables that best predict performance on the MR course examinations were the mathematics skills and reading comprehension scores on the state test. The study also showed a better performance of female students on both assessment methods. There were no significant differences between the assessment methods or among the high school levels.

One of the limitations of this study is the limited number of items on the tests. Additionally, the authors recommend conducting an analysis of the differences between the testing items to provide a detailed explanation of students’ performance when comparing computer-based testing and paper-and-pencil testing.

Further design of teaching material and assessments online and offline, based on local and regional marketing problems, is suggested. As the current text and readings are more oriented to the English-speaking contexts, most of the problems presented are oriented to multinational companies and brands.

Insights into the skills required for future jobs provide valuable guidance (World Economic Forum, 2020). Essential skills for emerging roles, like data scientists, can find robust support within the MR course. To further enrich in-class and online exercises with Excel and SPSS, Colombian educators can leverage data sets obtained from sources like the national statistics office and international market intelligence databases available through the university’s library, including Passport and Statista. Engaging with authentic data sets provides students with a more profound understanding of practical applications in MR.

This approach facilitates the identification of key variables, such as assessment and cognitive abilities in math and reading, which predict students’ knowledge acquisition in MR. It not only offers insights into the relevant factors influencing learning in MR but also provides valuable feedback. Additionally, it suggests potential avenues for future research in this field.

Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common strategies is for the course convenor to proactively monitor student engagement with learning activities against their assessment outcomes and intervene timely. Learning analytics has been increasingly adopted to provide these insights into student engagement and their performance. This case study explores how learning analytics can be used to meet the convenor’s requirements and help reduce administrative workload in a large health science class at the University of New South Wales.

This case-based study adopts an “action learning research approach” in assessing ways of using learning analytics for reducing workload in the educator’s own context and critically reflecting on experiences for improvements. This approach emphasises reflexive methodology, where the educator constantly assesses the context, implements an intervention and reflects on the process for in-time adjustments, improvements and future development.

The results highlighted ease for the teacher towards the early “flagging” of students who may not be active within the learning management system or who have performed poorly on assessment tasks. Coupled with the ability to send emails to the “flagged” students, this has led to a more personal approach while reducing the number of steps normally required. An unanticipated outcome was the potential for additional time saving through improving the scaffolding mechanisms if the learning analytics were customisable for individual courses.

The results provide further benefits for learning analytics to assist the educator in a growing blended learning environment. They also reveal the potential for learning analytics to be an effective adjunct towards promoting personal learning design.

Dark triad (DT) personality traits, that is, Machiavellianism, narcissism and psychopathy, are socially unenthusiastic and predict a range of antisocial behaviors. Academic entitlement, similarly, demonstrates the students’ rising temptation of higher grades without putting corresponding efforts. Based on coercion theory, this research investigated power distance as mediator between DT and academic entitlement (externalized responsibility and entitled expectations). Further, this study examined DT model of personality as a predictor of academic entitlement in Chinese higher education institutions (HEIs).

Chinese HEIs were ascertained for data collection. Students (with bachelor’s, master’s and Ph.D. degrees) responded to 719 questionnaires for data analysis. Hypothesized relationships were examined through partial least squares structural equation model (PLS-SEM).

This study established positive and significant direct link between DT and academic entitlement. The indirect effect through power distance was found insignificant between the relationship of DT and academic entitlement.

Based on coercion theory, this study extends the prevailing literature through unexplored effects of DT on academic entitlement and role of power distance in Chinese HEIs. This study validated the effect of DT on academic entitlement; however, direct-only no-mediation of power distance between the relationships is novel in Chinese HEIs. Moreover, power distance as mediator is novel between the relationships. Hence, this study provides an understanding of mentioned associations and contributes to the literature.

This study investigates the following research question: What pedagogical strategies are necessary for the success of HyFlex course design? The findings to this question are based in new media literacies and help to further pedagogy in an emerging HyFlex model while also grounding in needed theorization.

This study uses design-based research (DBR) across two iterations and four doctoral, higher education courses, using mixed methods of data collection and analysis.

Six pedagogical strategies influential for HyFlex research are presented, each grounded in a new media literacy skill.

These six pedagogical strategies help practitioners grappling with the HyFlex or blended learning model merge traditional pedagogy with how this might be tailored for students entrenched in a participatory culture.