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1. The Centrality of Black Identity for Black Students in Engineering

   Mobley, Catherine ; Brawner, Catherine E. ; Brent, Rebecca ; Orr, Marisa K. ( January 2021 , Collaborative Network for Engineering and Computing Diversity (CoNECD) Conference)

   Introduction and Theoretical Frameworks Our study draws upon several theoretical foundations to investigate and explain the educational experiences of Black students majoring in ME, CpE, and EE: intersectionality, critical race theory, and community cultural wealth theory. Intersectionality explains how gender operates together with race, not independently, to produce multiple, overlapping forms of discrimination and social inequality (Crenshaw, 1989; Collins, 2013). Critical race theory recognizes the unique experiences of marginalized groups and strives to identify the micro- and macro-institutional sources of discrimination and prejudice (Delgado & Stefancic, 2001). Community cultural wealth integrates an asset-based perspective to our analysis of engineering education to assist in the identification of factors that contribute to the success of engineering students (Yosso, 2005). These three theoretical frameworks are buttressed by our use of Racial Identity Theory, which expands understanding about the significance and meaning associated with students’ sense of group membership. Sellers and colleagues (1997) introduced the Multidimensional Model of Racial Identity (MMRI), in which they indicated that racial identity refers to the “significance and meaning that African Americans place on race in defining themselves” (p. 19). The development of this model was based on the reality that individuals vary greatly in the extent to which they attach meaning to being a member of the Black racial group. Sellers et al. (1997) posited that there are four components of racial identity: 1. Racial salience: “the extent to which one’s race is a relevant part of one’s self-concept at a particular moment or in a particular situation” (p. 24). 2. Racial centrality: “the extent to which a person normatively defines himself or herself with regard to race” (p. 25). 3. Racial regard: “a person’s affective or evaluative judgment of his or her race in terms of positive-negative valence” (p. 26). This element consists of public regard and private regard. 4. Racial ideology: “composed of the individual’s beliefs, opinions and attitudes with respect to the way he or she feels that the members of the race should act” (p. 27). The resulting 56-item inventory, the Multidimensional Inventory of Black Identity (MIBI), provides a robust measure of Black identity that can be used across multiple contexts. Research Questions Our 3-year, mixed-method study of Black students in computer (CpE), electrical (EE) and mechanical engineering (ME) aims to identify institutional policies and practices that contribute to the retention and attrition of Black students in electrical, computer, and mechanical engineering. Our four study institutions include historically Black institutions as well as predominantly white institutions, all of which are in the top 15 nationally in the number of Black engineering graduates. We are using a transformative mixed-methods design to answer the following overarching research questions: 1. Why do Black men and women choose and persist in, or leave, EE, CpE, and ME? 2. What are the academic trajectories of Black men and women in EE, CpE, and ME? 3. In what way do these pathways vary by gender or institution? 4. What institutional policies and practices promote greater retention of Black engineering students? Methods This study of Black students in CpE, EE, and ME reports initial results from in-depth interviews at one HBCU and one PWI. We asked students about a variety of topics, including their sense of belonging on campus and in the major, experiences with discrimination, the impact of race on their experiences, and experiences with microaggressions. For this paper, we draw on two methodological approaches that allowed us to move beyond a traditional, linear approach to in-depth interviews, allowing for more diverse experiences and narratives to emerge. First, we used an identity circle to gain a better understanding of the relative importance to the participants of racial identity, as compared to other identities. The identity circle is a series of three concentric circles, surrounding an “inner core” representing one’s “core self.” Participants were asked to place various identities from a provided list that included demographic, family-related, and school-related identities on the identity circle to reflect the relative importance of the different identities to participants’ current engineering education experiences. Second, participants were asked to complete an 8-item survey which measured the “centrality” of racial identity as defined by Sellers et al. (1997). Following Enders’ (2018) reflection on the MMRI and Nigrescence Theory, we chose to use the measure of racial centrality as it is generally more stable across situations and best “describes the place race holds in the hierarchy of identities an individual possesses and answers the question ‘How important is race to me in my life?’” (p. 518). Participants completed the MIBI items at the end of the interview to allow us to learn more about the participants’ identification with their racial group, to avoid biasing their responses to the Identity Circle, and to avoid potentially creating a stereotype threat at the beginning of the interview. This paper focuses on the results of the MIBI survey and the identity circles to investigate whether these measures were correlated. Recognizing that Blackness (race) is not monolithic, we were interested in knowing the extent to which the participants considered their Black identity as central to their engineering education experiences. Combined with discussion about the identity circles, this approach allowed us to learn more about how other elements of identity may shape the participants’ educational experiences and outcomes and revealed possible differences in how participants may enact various points of their identity. Findings For this paper, we focus on the results for five HBCU students and 27 PWI students who completed the MIBI and identity circle. The overall MIBI average for HBCU students was 43 (out of a possible 56) and the overall MIBI scores ranged from 36-51; the overall MIBI average for the PWI students was 40; the overall MIBI scores for the PWI students ranged from 24-51. Twenty-one students placed race in the inner circle, indicating that race was central to their identity. Five placed race on the second, middle circle; three placed race on the third, outer circle. Three students did not place race on their identity circle. For our cross-case qualitative analysis, we will choose cases across the two institutions that represent low, medium and high MIBI scores and different ranges of centrality of race to identity, as expressed in the identity circles. Our final analysis will include descriptive quotes from these in-depth interviews to further elucidate the significance of race to the participants’ identities and engineering education experiences. The results will provide context for our larger study of a total of 60 Black students in engineering at our four study institutions. Theoretically, our study represents a new application of Racial Identity Theory and will provide a unique opportunity to apply the theories of intersectionality, critical race theory, and community cultural wealth theory. Methodologically, our findings provide insights into the utility of combining our two qualitative research tools, the MIBI centrality scale and the identity circle, to better understand the influence of race on the education experiences of Black students in engineering. 

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2. An Inquiry into the Use of Intercoder Reliability Measures in Qualitative Research

   Wilson-Lopez, A. ; Minichiello, A. ; Green, T. ( July 2019 , ASEE Annual Conference proceedings)

   In this theory paper, we set out to consider, as a matter of methodological interest, the use of quantitative measures of inter-coder reliability (e.g., percentage agreement, correlation, Cohen’s Kappa, etc.) as necessary and/or sufficient correlates for quality within qualitative research in engineering education. It is well known that the phrase qualitative research represents a diverse body of scholarship conducted across a range of epistemological viewpoints and methodologies. Given this diversity, we concur with those who state that it is ill advised to propose recipes or stipulate requirements for achieving qualitative research validity and reliability. Yet, as qualitative researchers ourselves, we repeatedly find the need to communicate the validity and reliability—or quality—of our work to different stakeholders, including funding agencies and the public. One method for demonstrating quality, which is increasingly used in qualitative research in engineering education, is the practice of reporting quantitative measures of agreement between two or more people who code the same qualitative dataset. In this theory paper, we address this common practice in two ways. First, we identify instances in which inter-coder reliability measures may not be appropriate or adequate for establishing quality in qualitative research. We query research that suggests that the numerical measure itself is the goal of qualitative analysis, rather than the depth and texture of the interpretations that are revealed. Second, we identify complexities or methodological questions that may arise during the process of establishing inter-coder reliability, which are not often addressed in empirical publications. To achieve this purposes, in this paper we will ground our work in a review of qualitative articles, published in the Journal of Engineering Education, that have employed inter-rater or inter-coder reliability as evidence of research validity. In our review, we will examine the disparate measures and scores (from 40% agreement to 97% agreement) used as evidence of quality, as well as the theoretical perspectives within which these measures have been employed. Then, using our own comparative case study research as an example, we will highlight the questions and the challenges that we faced as we worked to meet rigorous standards of evidence in our qualitative coding analysis, We will explain the processes we undertook and the challenges we faced as we assigned codes to a large qualitative data set approached from a post positivist perspective. We will situate these coding processes within the larger methodological literature and, in light of contrasting literature, we will describe the principled decisions we made while coding our own data. We will use this review of qualitative research and our own qualitative research experiences to elucidate inconsistencies and unarticulated issues related to evidence for qualitative validity as a means to generate further discussion regarding quality in qualitative coding processes. 

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3. Boundary Spanning and Engineering: A Qualitative Systematic Review

   https://doi.org/10.1002/jee.20219  

   Jesiek, Brent K. ; Mazzurco, Andrea ; Buswell, Natascha T. ; Thompson, Julia D. ( August 2018 , Journal of Engineering Education)

   Engineers are often expected to span organizational, cultural, stakeholder, geographic, temporal, and other boundaries. Yet, few studies on boundary spanning have appeared in the engineering education literature, suggesting the need for improved theoretical and conceptual foundations to guide empirical studies of boundary spanning in engineering.

   To develop a more comprehensive understanding of boundary spanning, this study addresses five research questions: (a) What types of boundaries have been identified as topics of interest? (b) How are boundary spanners and boundary spanning defined? (c) What types of activities and behaviors comprise or have been linked to boundary spanning? (d) What individual competencies and characteristics have been proposed or studied as important for boundary spanning? and (e) What boundary spanning themes are most prominent in studies of engineers and other technical professionals?

   Using a qualitative systematic review process, we identified and analyzed 72 scholarly papers from multiple disciplines. Multiple reviewers coded each paper using a hybrid deductive‐inductive content analysis process to identify key themes related to boundary spanning.

   The analysis resulted in a framework consisting of six boundary types, three types of roles and definitions, and five types of activities. Discussion of boundary spanning competencies was limited in the collected works, and only seven papers exclusively focused on engineers. We conclude by proposing boundary spanning as an important meta‐attribute for engineers and a promising lens for investigating engineering practice. We also relate our findings to the engineering education literature and suggest directions for future research.

    

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4. Documenting professional learning focused on implementing high-quality instructional materials in mathematics: the AIM–TRU learning cycle

   https://doi.org/10.1186/s40594-022-00362-y  

   Russell, John Lawson ; DiNapoli, Joseph ; Murray, Eileen ( July 2022 , International Journal of STEM Education)

   To increase teachers’ capacity to implement high-quality instructional materials with fidelity in their classrooms through a video-based professional learning cycle, the Analyzing Instruction in Mathematics Using the Teaching for Robust Understanding framework (AIM–TRU) research–practice partnership was formed. Drawing upon the design-based research paradigm, AIM–TRU created the initial design for the professional learning cycle and wanted to engage in continued iterative redesign as the year progressed. This necessitated a method, common among those who adjust their designs when applying them in context, by which to document and justify changes made over time to our model. The research contained in this article used qualitative methods to articulate and test the design underlying our professional learning cycle by advancing conjecture mapping, a device by which the embodiments of the design are made transparent to be analyzed in practice.

   The initial design conjectures and activity structures teachers engaged in through our model of professional learning were refined to address three themes that emerged. Firstly, it was found that the ways participants engaged with the mathematics of the lesson were underwhelming, in large part, because our own definition of what rich talk around mathematics should entail was lacking in details such as the mathematical objects in the lesson, the presence of multiple solution pathways, or the various representations that students could use. Second, talk structures did not always allow for equitable exchanges among all teachers. Finally, activity structures did not encourage teachers to delve deeply into the mathematics so they could perceive the lesson as a coherent piece of their own classroom curriculum. Our design conjectures and activity structures were revised over the course of the year.

   Our use of conjecture mapping allowed us to address the concern with research–practice partnerships that they should develop and utilize tools that make the systemic inquiry they engage in transparent, allowing for other researchers, practitioners, and stakeholders to see the complete design process and make use of the findings for their local context. Implications for this process as a tool for those who pilot and scale professional development are raised and addressed.

    

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5. A human‐centred learning analytics approach for developing contextually scalable K‐12 teacher dashboards

   https://doi.org/10.1111/bjet.13383  

   Wiley, Korah ; Dimitriadis, Yannis ; Linn, Marcia ( September 2023 , British Journal of Educational Technology)

   This paper describes a Human‐Centred Learning Analytics (HCLA) design approach for developing learning analytics (LA) dashboards for K‐12 classrooms that maintain both contextual relevance and scalability—two goals that are often in competition. Using mixed methods, we collected observational and interview data from teacher partners and assessment data from their students' engagement with the lesson materials. This DBR‐based, human‐centred design process resulted in a dashboard that supported teachers in addressing their students' learning needs. To develop the dashboard features that could support teachers, we found that a design refinement process that drew on the insights of teachers with varying teaching experience, philosophies and teaching contexts strengthened the resulting outcome. The versatile nature of the approach, in terms of student learning outcomes, makes it useful for HCLA design efforts across diverse K‐12 educational contexts.

   What is already known about this topic

   Learning analytics that are aligned to both a learning theory and learning design support student learning.

   LA dashboards that support users to understand the associated learning analytics data provide actionable insight.

   Design‐based research is a promising methodology for Human‐Centred Learning Analytics design, particularly in the K‐12 educational context.

   What this paper adds

   Leveraging a longstanding, yet fluid, research‐practice partnership is an effective design‐based research adaptation for addressing the high variation in instructional practices that characterize K‐12 education.

   Using both quantitative and qualitative data that reflects students' developing knowledge effectively supports teachers' inquiry into student learning.

   Teachers' use of learning analytics dashboards is heavily influenced by their perspectives on teaching and learning.

   Implications for practice and/or policy

   Impact on student learning outcomes, alongside usability and feasibility, should be included as a necessary metric for the effectiveness of LA design.

   LA dashboard developers should both leverage learning data that reflect students' developing knowledge and position teachers to take responsive pedagogical action to support student learning.

   LA researchers and developers should utilize a long‐term, yet fluid, research‐practice partnership to form a multi‐stakeholder, multidisciplinary design team for Human‐Centred Learning Analytics design.

    

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