Gender Bias and Temporal Effects in Standard Evaluations of Teaching

Buser, Whitney; Hayter, Jill K.; Marshall, Emily C.

doi:10.1257/pandp.20191104

Cited by 12 publications

(8 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interestingly, early studies has shown that the post-course or semester evaluations in SET, to some extent, are significantly biased against female teachers. Also, many of the educational institutions rely exclusively on SET for decision-making purposes regarding the teachers (Boring, Ottoboni, & Stark, 2016;Whitney, Hayter, & Marshall, 2019). The findings on how the students evaluate their teachers' performance through the ECOA SET (see: the section on Data sampling and participants) revealed more comments for male teachers (52218) than for females (41072).…”

Section: Discussionmentioning

confidence: 99%

Impact of students evaluation of teaching: a text analysis of the teachers qualities by gender

Okoye

Arrona‐Palacios

Camacho-Zúñiga

et al. 2020

Int J Educ Technol High Educ

View full text Add to dashboard Cite

Today, modern educational models are concerned with the development of the teacher-student experience and the potential opportunities it presents. User-centric analyses are useful both in terms of the socio-technical perspective on data usage within the educational domain and the positive impact that data-driven methods have. Moreover, the use of information and communication technologies (ICT) in education and process innovation has emerged due to the strategic perspectives and the process monitoring that have shown to be missing within the traditional education curricula. This study shows that there is an unprecedented increase in the amount of text-based data in different activities within the educational processes, which can be leveraged to provide useful strategic intelligence and improvement insights. Educators can apply the resultant methods and technologies, process innovations, and contextual-based information for ample support and monitoring of the teaching-learning processes and decision making. To this effect, this paper proposes an Educational Process and Data Mining (EPDM) model that leverages the perspectives or opinions of the students to provide useful information that can be used to enhance the end-to-end processes within the educational domain. Theoretically, this study applies the model to determine how the students evaluate their teachers by considering the gender of the teachers. We analyzed the underlying patterns and determined the emotional valence of the students based on their comments in the Students Evaluation of Teaching (SET). Thus, this work implements the proposed EPDM model using SET comments captured in a setting of higher education.

show abstract

Section: Discussionmentioning

confidence: 99%

Impact of students evaluation of teaching: a text analysis of the teachers qualities by gender

Okoye

Arrona‐Palacios

Camacho-Zúñiga

et al. 2020

Int J Educ Technol High Educ

View full text Add to dashboard Cite

show abstract

“…Their study examines the application of SETs in principles of economics courses at multiple institutions on three separate occasions during the semester in order to determine whether the evaluations of male and female instructors change throughout an academic term, specifically after the first exam is returned. Tests presented by Buser et al [17] point toward a negative effect on evaluations for female instructors relative to male instructors associated with returning grades, thus highlighting the importance of temporal effects (related to gender) in the application of SETs.…”

Section: Gender and Other Demographic Effects In Setsmentioning

confidence: 98%

“…As one moves toward academic disciplines wherein female instructors are more common, the ratings of female instructors by female students rise. Lastly, in light of earlier findings of a gender effect in SETs, Buser et al [17] investigate whether gender differences in SETs vary over the course of a semester. Their study examines the application of SETs in principles of economics courses at multiple institutions on three separate occasions during the semester in order to determine whether the evaluations of male and female instructors change throughout an academic term, specifically after the first exam is returned.…”

Section: Gender and Other Demographic Effects In Setsmentioning

confidence: 99%

The Student Evaluation of Teaching Premium for Clinical Faculty in Economics

Bordere,

Carter,

Caudill

et al. 2024

Education Sciences

View full text Add to dashboard Cite

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.

show abstract

“…The authors note that there still exists some issues and challenges in relation to the pedagogical transformations, hand-inhand with the impact of the digital teaching and acceleration of the new innovative models and practices form learning, that can only be achieved through a culture of educational innovation and conceptual understanding of how the effectiveness of the learning processes and outcomes are assessed [18], [76], [81], [113], [114]. A lot of higher educational institutions rely exclusively on SET evaluations for assessment of the teachers' performance and learning outcomes of the students [53], [115], [116], and there are also evidence in the literature that information (educational datasets) about the teaching and learning processes (which are stored at an unprecedented rate in the databases of the different institutions) can be used to understand and drive the educational systems forward [8], [27], [49], [89], [117], [118]. VOLUME 11, 2023 In triangulation with the method and objectives of this current study, educational organizations such as The Association for Institutional Research (AIR) [119] and The Professional and Organizational Development Network in Higher Education (POD) [120] are already pioneering several themes that are focused on students/learning assessment, institutional effectiveness and use of (educational) data for informed decision-making and support of the educators or educational processes to include (i) Assessment and Evaluation initiatives that are focused on research and methods that are both externally or internally driven from the institutional perspective for planning, accreditation, amongst others, in pursuit of improved and equitable student' and institutional success (ii) Data and Technology that features the technical and ethical creation/manipulation of data and structuring through appropriate analytic tools for decision making, predictive models, and machine learning (iii) Institutional Effectiveness which constitute of student-focused paradigm that explores the roles of information retrieval (IR), information extraction (IE), and Assessment in leading institutional data strategies and strategic planning for improvement of the students' success (iv) Use of Data that proves important for improved student success with attention to institutional and student contexts, [119], [120] etc., as uncovered in this study.…”

Section: A Implications Of This Studymentioning

confidence: 99%

A Text Mining and Statistical Approach for Assessment of Pedagogical Impact of Students’ Evaluation of Teaching and Learning Outcome in Education

Okoye

Daruich

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Technology-enhanced learning (TEL) is now at the heart of teaching and learning process in many higher education institutions (HEIs). Today, educators are faced with the challenges of pedagogically specifying what tools, methods, and technologies are used to support the teachers and students, and to help maintain/sustain a continuous education and practices. This study shows that there is an opportunity in the use of (educational) datasets derived about the teaching and learning processes to provide insights for fostering the education process. To this effect, it analyzed the students' evaluation of teaching (SET) dataset (n = 471968) collected within a higher education setting to determine prominent factors that influences the students' performance or the way (TEL-based) education is being delivered, including its didactical impact and implications for practice. Theoretically, the study employed a mixed methodology grounded on integration of the Data-structure approach and Descriptive decision theory to study the rationality behind the students' evaluation of the teaching and performance. This was done through the Textual data quantification (qualitative) and Statistical (quantitative) analysis. Qualitatively, the study applied the Educational Process and Data Mining (EPDM) model (a text mining method) to extract the different sentiments and emotional valence expressed by the students in the SET, and how those characteristically differ based on the period and type of evaluation they have completed (between 2019 to 2021). For the quantitative analysis, the study used a multivariate analysis of covariance (MANCOVA) and multiple pairwise comparisons posthoc tests to analyze the quantified information (average sentiment and emotional valence) extracted from the SET data to determine the marginal means of effect the different SET types and evaluation period have on the students' learning outcomes/perception about the teaching-learning process. In addition, the study empirically discussed and shed light on the implications of the main findings for TEL-based Education, particularly implemented by the HEI during the analyzed periods. The scholastic indicator from the study shows that while the flexible digital models or instructional methods are effective for continuous education,The associate editor coordinating the review of this manuscript and approving it for publication was Biju Issac .

show abstract

Gender Bias and Temporal Effects in Standard Evaluations of Teaching

Cited by 12 publications

References 10 publications

Impact of students evaluation of teaching: a text analysis of the teachers qualities by gender

Impact of students evaluation of teaching: a text analysis of the teachers qualities by gender

The Student Evaluation of Teaching Premium for Clinical Faculty in Economics

A Text Mining and Statistical Approach for Assessment of Pedagogical Impact of Students’ Evaluation of Teaching and Learning Outcome in Education

Contact Info

Product

Resources

About