Search results

This paper aims to investigate the relationship between student emotions, professors' performance and course ratings and difficulty.

Natural language processing models are used to extract six basic emotions and several categories of professors' harmful performance from nearly one million student reviews randomly selected from the website ratemyprofessors.com. These features are used in regression analysis to analyse their relationship with numerical ratings of course quality and course difficulty.

Negative emotions and bad performance by professors are detected more often for low-rated courses and courses perceived as more difficult by students. Positive emotions are seen for highly rated and less challenging courses.

This paper shows that natural language processing tools can be used to enhance and strengthen the quality assurance processes at universities. The proposed methods can improve the often-contested student evaluation of teaching practices, help students make better and more informed choices about their courses and assist instructors to better tailor their teaching approaches and create a more positive learning environment for their students.

This paper presents a novel analysis of how student emotions and poor performance by professors, derived automatically from teacher evaluations by students, affect course ratings. Results also lead to a novel hypothesis that the student–course emotional match or student tolerance of bad behaviour by professors can affect the performance of students and their chances of completing their degree.

Although educators would likely agree that values and ethics are important in all disciplines, they have particular importance for practice-oriented fields. These applied professionals need to solve complex social problems that require the application of ethical standards and value perspectives. While the importance of value-engaged practice is known to the applied field, there is little research and conversation about how values can be integrated into teaching. This chapter synthesizes values-education approaches in various practice-based disciplines such as public administration (PA), program evaluation, social work, and public health. This chapter draws from empirical and theoretical works as well as the authors' experiences developing, participating in, and conducting values-based research on professionals and professional education.

With the increasing popularity of online courses, their quality has become a public concern. Based on the perspective of knowledge management, this study aims to identify comprehensive and granular quality factors of online courses and analyze the relationships between the factors.

Following the principles of the grounded theory, interpretive structural modeling and cross-impact matrix multiplication applied to classification (MICMAC) analysis methods, this research uses reviews and comments garnered from Zhihu, which is the most popular online question-and-answer community in China, to conduct the analysis.

Based on the text data, 50 factors that potentially affect the quality of online courses are obtained. The analysis identifies the hierarchical relationships and dependent correlations between the factors.

The research uses the knowledge transformation model to classify content elements according to their degree of descriptiveness and provides practical and effective suggestions for improving the quality of online courses.

Sexual health is insufficiently addressed in health care and higher education, which can lead to lower quality of life and negative health outcomes. To improve the situation, it is necessary to address both the needs of patients and professionals and collaboratively engage in finding sustainable solutions. The purpose of this paper is to explore the feasibility and value of large-scale digital coproduction in higher education.

A study of a project that developed seven interprofessional, digital master-level courses covering different topics related to sexual health. The project was performed through digital coproduction in higher education, with over 100 persons with various backgrounds working together online in designing content and novel digital learning activities.

Large-scale digital coproduction in higher education is feasible and valuable, but the process demands sensitive leadership, understanding of coproduction processes and willingness to learn from each other. To meet the demands from practice it is important to understand the complexity, ever-changing and unpredictable working life changes which, in turn, demands engagement in continuous learning, training activities and the need for formal education.

The study provides learning of the feasibility of the value of large-scale digital coproduction in higher education, which is a novel way of working in higher education.

This chapter proposes authentic leadership as a generic competence and an integral part of doctoral education regardless of field of study. The authors explore its potential to enhance the development of doctoral candidates and academics and search for answers to the questions: Can and should authentic leadership be developed as a generic competence in doctoral education? How can it be designed and implemented in a doctoral training module? What would its learning outcomes be? The authors address these questions in the context of doctoral education. They assert that authentic leadership training should be mandatory for all doctoral candidates, and that supervisors should be actively engaged in the development of this underappreciated transferrable skill.

This paper aims to identify and evaluate resolutions to key learning and teaching challenges in very large courses that involve practical mathematics, such as foundational finance.

A design-based research approach is used across three semesters to iteratively identify practical problems within the course and then develop and evaluate resolutions to these problems. Data are collected from both students and teachers and analysed using a mixed-method approach.

The results indicate that key learning and teaching challenges in large foundational finance courses can be mitigated through appropriate consistency of learning materials; check-your-understanding interactive online content targeting foundational concepts in the early weeks; connection points between students and the coordinator to increase teacher presence; a sustained focus on supporting student achievement within assessments; and signposting relevance of content for the broader program and professional settings. Multiple design iterations using a co-design approach were beneficial to incrementally improve the course and consider multiple perspectives within the design process.

This paper develops a set of design principles to provide guidance to other practitioners who seek to improve their own courses.

The use of design-based research and mixed-method approaches that consider both student and teacher perspectives to examine the design of very large, foundational finance courses is novel.

The paper aims to explore and examine the factors that influence the post-consumption behavioral intentions of education consumers with the help of online reviews from a Massive Open Online Course (MOOC) platform in the knowledge payment context.

The paper adopted a novel mixed-method approach based on natural language processing (NLP) techniques. Variables were identified using topic modeling drawing upon 14,585 online reviews from a global commercial MOOC platform (Udemy.com). The relationships among identified factors, such as perceived quality dimensions, consumption emotions, and intention to recommend, were then tested from a cognition-affect-behavior (CAB) perspective using partial least squares structural equation modeling (PLS-SEM).

Results indicate that course content quality, instructor quality, and platform quality are strong predictors of consumers' emotions and intention to recommend. Interestingly, course content quality displays a positive effect on invoking negative emotions in the MOOC context. Additionally, positive emotions mediate the relationships between three perceived qualities and the intention to recommend.

Limited research has been conducted regarding MOOC consumers' post-consumption intentions in the knowledge payment context. Findings of this study address the limited literature on MOOC qualities and consumer post-consumption behaviors, which contribute to a comprehensive understanding of MOOC learners' experiences at a meso-level for future paid-MOOC creators.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2021-0482/

This chapter provides an in-depth examination of the quality assurance process in the higher education system of Iraq and the Kurdistan Region of Iraq (KRI) in terms of standards, processes, and procedures. More specifically, the chapter aims to examine the impact of the quality assurance process on the quality development of education in Iraq and Kurdistan Region, as well as identify the challenges that staff (top management and faculty members) face at various higher education institutions therein. For this purpose, a qualitative/quantitative analysis was conducted, which involved reviewing existing official policies, reports, and forms; interviewing top officials (presidents, vice-presidents, quality assurance directors) at a few higher education institutions (public and private); and developing a survey questionnaire that detected the perspective of top officials and faculty members regarding the level of impact quality assurance has had on the development of higher education. A total of 284 university staff members were surveyed from different universities in Iraq and Kurdistan. A total of 29 universities from Iraq and Kurdistan were represented in the survey. The respondents came from a variety of colleges and departments at public and private universities, with 79% of respondents coming from public universities. Study results demonstrate that quality assurance has contributed significantly to the improvement of university staff performance. There are a number of recommendations made within this chapter for educational leaders, which could lead to the further development of quality practices and the upgrading of the higher education system.

This study aims at assessing item fairness in students' evaluation of teaching based on students' academic college using measurement invariance analysis (MI).

The sample of this study consists of 17,270 undergraduate students from 12 different academic colleges. SET survey consists of 20 Likert-type items distributed to four factors: planning, instruction, management and assessment was used to collect the data. The Lavaan R package with confirmatory factor analysis (CFA) was used to evaluate measurement invariance (MI). Four models of CFA were investigated and assessed: the configural model, the metric model, the scalar model and the residual invariance model. ANOVA was used to test the differences in SET according to academic colleges.

MI analysis showed that the four levels of MI models are supported. ANOVA test showed that means of SET total scores are statistically different according to students' academic colleges. College of “Education” has the highest SET mean (88.64 out of 100), and all the differences between the College of Education’s SET mean and other colleges' SET means are statistically significant.

The study recommends that higher education institutions test the MI of SET according to academic colleges and then use colleges with the highest SET at the university level as internal benchmarking to develop and enhance their teaching practices.

This study is probably the only study that tested MI according to students' colleges before testing the differences between colleges in SET. If MI is not supported, then the comparisons between academic colleges are not applicable.

The purpose of this study is to investigate how professionals who are continuing their education rate a higher education quality management course with an emphasis on reflective learning and real problem-solving. The audited course consists of module-based teaching, while students work on an improvement project at their workplace between course sessions. This study has a twofold aim: to contribute to the design of quality improvement courses based on doing as we learn and to offer insight into the use of a final grading method that consist of a folder with reports from the intermediate work steps and a final report.

After completing the course, students received a survey with questions and statements about the course content, delivery and final grading methods. They answered these questions on a seven-point Likert scale and also answered open-ended questions.

It is clear that professional students value the interweaving of theory with real-life training, and they value module-based teaching in which theory is reviewed and applied to practical problems. Reflective learning was achieved through feedback from both teachers and fellow students on various interim reports. Students’ employers benefit from the course, as students gain experience with quality improvement. The grading of a final report on the improvement project based on three sub-assignments was highly appreciated.

Developers in courses in quality improvement benefit from learning how this course is structured, assessed and how participants perceived its components.

The course design with modules and intermediate work steps, where the students apply theory in quality improvement to a real project at their workplace, is an original concept. The modules correspond to the plan, do, check and act (PDCA) methodology.