Maura Borrego

Development of a Taxonomy of Keywords for Engineering Education Research

The diversity of engineering education research provides an opportunity for cross-fertilization of ideas and creativity, but it also can result in fragmentation of the field and duplication of effort. One solution is to establish a standardized taxonomy of engineering education terms to map the field and communicate and connect research initiatives. This report describes the process for developing such a taxonomy, the EER Taxonomy. Although the taxonomy focuses on engineering education research in the United States, inclusive efforts have engaged 266 individuals from 149 cities in 30 countries during one multiday workshop, seven conference sessions, and several other virtual and in-person activities. The resulting taxonomy comprises 455 terms arranged in 14 branches and six levels. This taxonomy was found to satisfy four criteria for validity and reliability: (1) keywords assigned to a set of abstracts were reproducible by multiple researchers, (2) the taxonomy comprised terms that could be selected as keywords to fully describe 243 articles in three journals, (3) the keywords for those 243 articles were evenly distributed across the branches of the taxonomy, and (4) the authors of 31 conference papers agreed with 90% of researcher-assigned keywords. This report also describes guidelines developed to help authors consistently assign keywords for their articles by encouraging them to choose terms from three categories: (1) context/focus/topic, (2) purpose/target/motivation, and (3) research approach.

Development of a Taxonomy of Keywords for Engineering Education Research: Taxonomy of Keywords for Engineering Education Research

The diversity of engineering education research provides an opportunity for cross-fertilization of ideas and creativity, but it also can result in fragmentation of the field and duplication of effort. One solution is to establish a standardized taxonomy of engineering education terms to map the field and communicate and connect research initiatives. This report describes the process for developing such a taxonomy, the EER Taxonomy. Although the taxonomy focuses on engineering education research in the United States, inclusive efforts have engaged 266 individuals from 149 cities in 30 countries during one multiday workshop, seven conference sessions, and several other virtual and in-person activities. The resulting taxonomy comprises 455 terms arranged in 14 branches and six levels. This taxonomy was found to satisfy four criteria for validity and reliability: (1) keywords assigned to a set of abstracts were reproducible by multiple researchers, (2) the taxonomy comprised terms that could be selected as keywords to fully describe 243 articles in three journals, (3) the keywords for those 243 articles were evenly distributed across the branches of the taxonomy, and (4) the authors of 31 conference papers agreed with 90% of researcher-assigned keywords. This report also describes guidelines developed to help authors consistently assign keywords for their articles by encouraging them to choose terms from three categories: (1) context/focus/topic, (2) purpose/target/motivation, and (3) research approach.

After the Workshop: A Case Study of Post-Workshop Implementation of Active Learning in an Electrical Engineering Course

Engineering education research has empirically validated the effectiveness of active learning over traditional instructional methods. However, the dissemination of education research into instructional practice has been slow. Faculty workshops for current and future instructors offer a solution to promote the widespread adoption of active learning in engineering classrooms. However, most of the existing research has relied on faculty self-reporting to evaluate the success of engineering faculty workshops. Researchers have noted variations in self-reporting and the actual classroom implementation. In this paper, using classroom observations, faculty interviews, student surveys, and focus groups, the authors examine an engineering instructors postworkshop implementation of active learning in an electrical engineering course. The findings demonstrate the influence of faculty conceptions of teaching in the selection and design of activities and the subsequent impact of these design choices on student engagement. The authors report the instructors and students responses to the active learning exercises and present recommendations for engineering faculty development.

A classroom observation instrument to assess student response to active learning

Student resistance is often cited as a major barrier to facultys use of active learning, but there are few research-based strategies for reducing this barrier. To address the need for such strategies, we have initiated a project to identify specific, research-based strategies to significantly reduce student resistance to facultys use of active learning practices. In this work-in-progress paper, we describe the first phase of our research - the development and pilot testing of a classroom observation instrument to assess student responses to facultys use of active learning. This instrument, which draws upon other published observation protocols, will allow us to capture data about facultys use of and students response to active learning as we undertake our larger research project.

Transfer student pathways to engineering degrees: A multi-institutional study based in Texas

This work in progress paper describes a mixed methods study designed to investigate transfer student pathways as a means to increase engineering degree production and broaden participation in engineering careers. The study explores the framework of transfer student capital and its relevance for engineering transfer students. In this paper, we provide an overview of a survey instrument developed to collect data from more than 6,000 students who successfully transferred to one of four 4-year institutions in Texas as new engineering students between 2007 and 2014. Our study expands the small body of literature on engineering transfer students and sheds light on specific policies and practices that impact transfer.

Doctoral student funding portfolios across and within engineering, life sciences and physical sciences

Purpose n n n n nThis paper aims to determine the extent to which graduate student funding portfolios vary across and within engineering, life sciences and physical sciences academic fields for degree recipients. “Graduate student funding portfolios” refers to the percentages of students funded by fellowships, research assistantships, teaching assistantships, personal means and other sources within an organizational unit. n n n n nDesign/methodology/approach n n n n nUsing data from the Survey of Earned Doctorates data set, the authors analyze doctoral students’ self-reported primary mechanisms of funding across and within academic fields varying along the Biglan taxonomy. The authors used cluster analyses and logistic regression to investigate within-field variation in funding portfolios. n n n n nFindings n n n n nThe authors show significant differences in doctoral student funding portfolios across dimensions of the Biglan taxonomy characterizing academic fields. Within those fields, the authors demonstrate considerable variation in funding; institutions cluster into different “modes” of funding portfolios that do not necessarily map onto institutional type or control variables. n n n n nOriginality/value n n n n nDespite tremendous investment in graduate students, there has been little research that can help characterize at the program-level how graduate students are funded, either by internal or external mechanisms. As programs continue to feel the pressures of more limited resources coupled with increasing graduate enrollment demands, investigating graduate student funding at a macro level is becoming increasingly important so programs may better understand constraints and predict shifts in resource availability.

A New Scale for Measuring Engineering Identity in Undergraduates

Identity, or how people choose to define themselves, is gaining traction as an explanation for who pursues and persists in engineering. A number of quantitative studies have developed scales for predicting engineering identity in undergraduate students. However, the outcome measure of identity is sometimes based on a single item. In this paper, we present the results of a new two-item scale. The scale is adapted from an existing measure of identification with an organization that was developed by Bergami and Bagozzi [1] and refined by Bartel [2]. The measure focuses on the “cognitive (i.e., self-categorization) component of identification” (p. 556), and has been found to have high convergent validity with another, rigorous measure of identification with an organization or other entity created by Mael and Ashforth [3]. This measure utilizes one primarily visual and one verbal item to assess the extent to which an individual cognitively categorizes himself or herself as an engineer. The scale was administered to 1528 engineering undergraduate students during the 2016-2017 academic year. Internal consistency of the new engineering identity scale, as measured by Cronbach’s alpha, is 0.84. This new scale is an important step toward refining quantitative measures of, and the study of, engineering identity development in undergraduate students and other populations.

Strategies to mitigate student resistance to active learning

BackgroundResearch has shown that active learning promotes student learning and increases retention rates of STEM undergraduates. Yet, instructors are reluctant to change their teaching approaches for several reasons, including a fear of student resistance to active learning. This paper addresses this issue by building on our prior work which demonstrates that certain instructor strategies can positively influence student responses to active learning. We present an analysis of interview data from 17 engineering professors across the USA about the ways they use strategies to reduce student resistance to active learning in their undergraduate engineering courses.ResultsOur data reveal that instructor strategies for reducing student resistance generally fall within two broad types: explanation and facilitation strategies. Explanation strategies consist of the following: (a) explain the purpose, (b) explain course expectations, and (c) explain activity expectations. Facilitation strategies include the following: (a) approach non-participants, (b) assume an encouraging demeanor, (c) grade on participation, (d) walk around the room, (e) invite questions, (f) develop a routine, (g) design activities for participation, and (h) use incremental steps. Four of the strategies emerged from our analysis and were previously unstudied in the context of student resistance.ConclusionsThe findings of this study have practical implications for instructors wishing to implement active learning. There is a variety of strategies to reduce student resistance to active learning, and there are multiple successful ways to implement the strategies. Importantly, effective use of strategies requires some degree of intentional course planning. These strategies should be considered as a starting point for instructors seeking to better incorporate the use of active learning strategies into their undergraduate engineering classrooms.

‘Not hard to sway’: a case study of student engagement in two large engineering classes

ABSTRACT Although engineering education research has empirically validated the effectiveness of active learning in improving student learning over traditional lecture-based methods, the adoption of active learning in classrooms has been slow. One of the greatest reported barriers is student resistance towards engagement in active learning exercises. This paper argues that the level of student engagement in active learning classrooms is an interplay of social and physical classroom characteristics. Using classroom observations and instructor interviews, this study describes the influence of the interaction of student response systems and classroom layout on student engagement in two large active-learning-based engineering classrooms. The findings suggest that the use of different student response systems in combination with cluster-style seating arrangements can increase student engagement in large classrooms.

Research group experiences and intent to complete

Purpose n n n n nThe purpose of this study is to better understand the nature of graduate training experiences in research groups and to identify factors that may lead to increased student retention and success. n n n n nDesign/methodology/approach n n n n nSurveys administered at four US universities resulted in quantitative responses from 130 Master’s and 702 doctoral engineering students participating in graduate research groups. Missing data were imputed, and responses were weighted by gender, discipline, degree program and nationality. Exploratory factor analysis identified four factors describing research group experiences. Regression models were built for two outcomes: satisfaction with research group experience and intention to complete degree. Control variables included gender, discipline, degree program, nationality, year in program and institution. n n n n nFindings n n n n nFifty-five per cent of the variance in satisfaction was described by a model including agency, support, international diversity and group climate. Sixty-five per cent of variance in intent to complete was described by a model comprising international diversity, agency and support. Several control variables were significant. n n n n nOriginality/value n n n n nAgency and support in particular were the most influential predictors of both satisfaction and intention, suggesting that future efforts should emphasize stable funding, clear expectations, access to mentors and agency-building experiences to help students take an active role in their own success.