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The integration of making activities in classrooms provides a crucial opportunity for all students to gain equitable participation access to learning activities. However, for making to be incorporated into more classrooms, teachers must be adequately prepared with relevant knowledge and skills. This study is the first to compare the science learning outcomes associated with making to those stemming from standard learning curricula and experiences within a classroom setting. We examine the learning outcomes of 219 students across multiple sections of one teacher's 9th-grade science classes. While five sections of students were taught using the school's standard learning curriculum, four sections of students engaged in an integrated maker curriculum. A mixed methods approach offers a comprehensive look at the affordances and limitations of maker-based classroom science instruction by coupling student science learning outcomes with student and teacher reflections on instruction and learning. Findings indicate that students had better learning outcomes in science class when learning occurred through maker technologies than the school's standard learning curriculum.

While previous research documents that women in STEM doctoral programs tend to fare better when their advisor shares their gender identity, this study provides new insights into the role of student-advisor gender identity congruence, relying on a longitudinal sample of doctoral students in biology and using structural equation and latent growth curve modeling. Findings show that advisor gender played an inconsistent and typically indirect role in predicting student outcomes. Further, all students, regardless of gender, tended to report higher quality advising when their advisor was a woman, pointing to potential gender inequities in advising expectations of faculty. Implications for research, theory, and practice are discussed.

The properties and functions of complex systems apply across a variety of domains of science and are at the heart of the solutions to many global crises facing the world today. As such, understanding of complex systems has been increasingly recognized as a core goal of science education. Learning about complexity-related concepts and phenomena is persistently considered difficult for many students--even at the undergraduate level, but traditional pedagogical approaches have been unsuccessful in teaching complex systems effectively. Evidence indicates that agent-based participatory simulations can be promising for this purpose. Using mixed methods, cross-case analysis, we examined how undergraduates experience changes in their understanding of the watershed as a complex ecosystem with the use of a particular agent-based participatory simulation called the UVA Bay Game. While one of the cases yielded evidence of nonsignificant quantitative change between pre- and post-simulation concept maps, this study observed an overall positive increase of complex system understanding through both concept map analysis and narrative reflections on learning. Our findings extend the current understanding of the role of participatory agent-based simulations in teaching and learning about complex systems in classrooms. Implications and limitations are discussed.

Threshold concepts are transformative elements of domain knowledge that enable those who attain them to engage domain tasks in a more sophisticated way. Existing research tends to focus on the identification of threshold concepts within undergraduate curricula as challenging concepts that prevent attainment of subsequent content until mastered. Recently, threshold concepts have likewise become a research focus at the level of doctoral studies. However, such research faces several limitations. First, the generalizability of findings in past research has been limited due to the relatively small numbers of participants in available studies. Second, it is not clear which specific skills are contingent upon mastery of identified threshold concepts, making it difficult to identify appropriate times for possible intervention. Third, threshold concepts observed across disciplines may or may not mask important nuances that apply within specific disciplinary contexts. The current study therefore employs a novel Bayesian knowledge tracing (BKT) approach to identify possible threshold concepts using a large data set from the biological sciences. Using rubric-scored samples of doctoral students' sole-authored scholarly writing, we apply BKT as a strategy to identify potential threshold concepts by examining the ability of performance scores for specific research skills to predict score gains on other research skills. Findings demonstrate the effectiveness of this strategy, as well as convergence between results of the current study and more conventional, qualitative results identifying threshold concepts at the doctoral level.

Despite increased enrolment of women and students from underrepresented racial/ethnic groups in doctoral programs, notable inequalities in academic careers persist. We investigate one potential source of these inequalities: publication rates during graduate school. Results, based on a sample of doctoral students in biological sciences across 53 institutions, indicate that both white women and students from underrepresented racial/ethnic groups (African American and Latinx) have lower publication rates than white men. Notably, these gaps grow over time and are not explained by background factors, socialization experiences, or family obligations. The same patterns persist for first-authored publications for African American and Latinx students, but not white women, suggesting potentially differential mechanisms of exclusion. Implications for research and practice are discussed.

Guided by theories of socialization and possible selves, this study examines how STEM doctoral students perceive their academic and professional trajectories. More specifically, we rely on four years of interview data from 66 doctoral students in the biological sciences to explore students' perceived trajectories, focusing on the salient identities and experiences that shape the way students identify and describe their graduate experiences over time. Findings reveal wide variation in terms of how students described their trajectories, with some students describing linear trajectories and/or unchanging career interests, while others described their developmental trajectories as highly turbulent and non-linear. These perceived trajectories were largely shaped by student-advisor interactions, the value students placed on becoming "independent" scientists, and the privilege students brought with them to their graduate programs.

This study seeks to understand the daily violence endured by queer youth. We use Queer Battle Fatigue, Ahmed's cultural politics of emotion, and STEM identity theories to make meaning of youth's experience. We draw from audio recordings and transcriptions of 15 queer youth over the course of a summer and fall LGBTQ + maker camp in a rural town in the Intermountain Western part of the United States. Findings show that the maker camp environment provided queer campers casual conversations about microaggressions and violence endured at school. In this context, STEM served as a cover (concealed goals) in three ways: emotion, validation/advice, and safety. This particular environment provided them recognition and validation of both their STEM and queer identities, allowing the group to be able to casually mention these instances of violence they had endured.

Working memory is an essential mechanism in the cognitive learning process. However, its definitions and mechanisms remain a topic of debate. Miller-Cotto and Byrnes ("Journal of Educational Psychology," "112"(5), 1074-1084, 2020) reported a comparison of three models of working memory to determine which best accounted for data obtained from a national US dataset of young children over time (Early Childhood Longitudinal Study of Kindergarten). In comparing these models, which they derived from competing theories of working memory, they found that: (1) one of the tested models best fit the available data; and (2) the model parameters were similar across content domains, concluding that one specific theory of working memory was best supported. The study reported here is an attempted replication of this work. We implemented a multi-phase effort at replication, first undertaking a review of the literature surrounding competing theories of working memory to aid interpretation of results, then attempting a direct replication, and lastly applying an alternative modeling technique to appropriately differentiate between between- and within-person variance. Neither effort succeeded in fully replicating the original findings. Instead, we found that parsing between- and within-person variance is an essential strategy for appropriately interpreting the relationships between working memory and domain learning. Doing so led to support for different models across domains, and interpretation of aspects of these models through the lens of relevant theory suggested alternative strategies for examining these issues in future research.

Research on cognitive load theory has historically focused on identifying the processes and strategies that enhance learning outcomes. Less attention has been given to the ways in which cognitive load may interact with the motivational and emotional aspects of learning. The aim of the present study is to examine the extent to which experienced cognitive load directly impacts self-efficacy during course-based instruction, after controlling for learning. In Study 1, results showed that within-time measurements of undergraduate students (n = 390) revealed a strong negative association between reported cognitive load and self-efficacy. However, across-time measurements revealed a positive relationship in which higher load predicted increased self-efficacy at later time points. Study 2 (n = 281) showed similar results using a different measure of cognitive load. Findings point to increases in self-efficacy being a consequence of the cognitive load imposed by instruction, rather than a precursor of the decision to invest mental effort. Furthermore, the differential relationships between cognitive load and self-efficacy within and across time highlight different types of motivational costs associated with invested mental effort as perceived by students. As a result, within and across time impacts of cognitive load offer both an enhanced understanding of cognition–motivation interactions and a potentially new approach to empirically differentiating between and quantifying intrinsic and extraneous load types. Educational Impact and Implications Statement: Cognition and motivation have traditionally been examined separately with little attention paid to how the cognitive processing of information itself may influence motivational beliefs. This study uses cognitive load theory to analyze the ways in which mental effort shapes concurrent and subsequent self-efficacy. Findings indicate that effort allocated to content difficulty positively predicts self-efficacy across time, and effort allocated to other factors such as unhelpful features of instruction and instructional materials negatively predicts concurrent self-efficacy. These results suggest that effort allocation due to instructional features has an important role to play on learners' motivation, independent of how much they learn, so instructional design decisions are important to consider even when they do not seem to directly impact learning outcomes. [ABSTRACT FROM AUTHOR]

Using a national sample of 336 biology Ph.D. students, this study classified students based on their interactions with faculty and peers, and investigated longitudinal changes in their interaction classifications over 3 years. We also examined associations between students' interaction classifications, their demographic backgrounds (e.g., gender, international student status, first-generation status, and underrepresented racial/ethnic minority status), and doctoral outcomes (e.g., sense of belonging, satisfaction with academic development, institutional commitment, and scholarly productivity). The findings revealed that three distinct subgroups existed among the current sample of biology Ph.D. students, with respect to their interactions with their faculty and peers: high interaction with faculty and peers, high interaction with peers only, and low interaction with faculty and peers. However, such patterns of doctoral students' interactions with faculty and peers tended to, in general, be stable over time. In addition, while the differential effects of demographic variables on changes in these interaction patterns were widely founded, such changes were not substantially linked to doctoral student outcomes. Implications for research on doctoral education and socialization theory are discussed.

Structural equation modeling is an ideal data analytical tool for testing complex relationships among many analytical variables. It can simultaneously test multiple mediating and moderating relationships, estimate latent variables on the basis of related measures, and address practical issues such as nonnormality and missing data. To test the extent to which a hypothesized model provides an appropriate characterization of the collective relationships among its variables, researchers must assess the "fit" between the model and the sample's data. However, interpreting estimates of model fit is a problematic process. The traditional inferential test of model fit, the chi-square test, is biased due to sample size. Fit indices provide descriptive (i.e., noninferential) values of model fit (e.g., comparative fit index, root-mean-square error of approximation), but are unable to provide a definitive "acceptable" or "unacceptable" fit determination. Marcoulides and Yuan have introduced an equivalence-testing technique for assessing model fit that combines traditional descriptive fit indices with an inferential testing strategy in the form of confidence intervals to facilitate more definitive fit conclusions. In this paper, we explain this technique and demonstrate its application, highlighting the substantial advantages it offers the life sciences education community for drawing robust conclusions from structural equation models. A structural equation model and data set (N = 1902) drawn from previously published research are used to illustrate how to perform and interpret an equivalence test of model fit using Marcoulides and Yuan's approach.

In the laboratory-based disciplines, selection of a principal investigator (PI) and research laboratory (lab) indelibly shapes doctoral students' experiences and educational outcomes. Framed by the theoretical concept of person-environment fit from within a socialization model, we use an inductive, qualitative approach to explore how a sample of 42 early-stage doctoral students enrolled in biological sciences programs made decisions about fitting with a PI and within a lab. Results illuminated a complex array of factors that students considered in selecting a PI, including PI relationship, mentoring style, and professional stability. Further, with regard to students' lab selection, peers and research projects played an important role. Students actively conceptualized trade-offs among various dimensions of fit. Our findings also revealed cases in which students did not secure a position in their first (or second) choice labs and had to consider their potential fit with suboptimal placements (in terms of their initial assessments). Thus, these students weighted different factors of fit against the reality of needing to secure financial support to continue in their doctoral programs. We conclude by presenting and framing implications for students, PIs, and doctoral programs, and recommend providing transparency and candor around the PI and lab selection processes.

High attrition rates have been a defining characteristic of doctoral education for decades, representing a loss of time, talent, and effort for departing students and their faculty. This qualitative study uses a biomedical science doctoral student sample to collect "real time" data on attrition within the first 2 years of doctoral training. Eighteen students, who represented 16 distinct universities, were interviewed as they engaged in the withdrawal process. Using the conceptual frames of socialization and social cognitive career theory, we explored experiences that preceded these students' doctoral program withdrawals. Furthermore, we examined how expressed roles of students' self-efficacy, outcome expectations, and professional goals contributed to the withdrawal process. Findings indicate that faculty advising (both positive and negative), laboratory rotation experiences, self-efficacy components, and changing professional goals all play a role in the early doctoral program attrition process.

ABSTRACT For some time, there has been a call for cross-disciplinary teaching within the business disciplines. With the rise of data and analytics, there is an opportunity for cross-disciplinary teaching by integrating technology throughout the business curriculum. However, many business professors have little experience in cross-disciplinary teaching. We hope to rectify this by introducing an approach that uses prelecture material to prepare students for learning concepts and terms that are not core to the focal class. In a study that combines Structured Query Language (SQL) coding with an audit principle called Benford's Law, we analyze the impact of adding prelecture material about Benford's Law on student's cognitive load, knowledge gained, and instructional efficiency. Results indicate that students who received a prelecture on Benford's Law outperformed the control group in performance measures related to Benford's Law, and that the instructional efficiency on Benford's Law was also higher for the treatment group. We did not find any significant differences in cognitive load between the two groups, nor did the treatment group perform significantly better when tested on the SQL concepts. We conclude that cross-discipline teaching is a fine balance between each discipline and communicating to students the importance of both disciplines is key.

We surveyed over 300 graduate students at a Southeastern research university to increase our understanding of their perceptions of (a) the connection between teaching and research, (b) the means by which integration occurs, and (c) the extent to which teaching and research contribute to a shared skill set that is of value in both contexts. We also examined differences across disciplines in the perception of this teaching-research nexus. Overall, findings indicate that graduate students perceive important relationships between teaching and research, and they point toward opportunities for administrators to promote teaching and research integration.

Research Questions: While community college transfer (i.e., upward transfer) represents an important mechanism for advancing equity across STEM fields, existing studies of gender and women's participation within computer science have largely excluded the perspectives of upward transfer students. We address this gap in the literature by exploring transfer receptivity and gender discrimination within computer science, guided by the following questions: (1) How do upward transfer computer science students report their receptivity experiences, and how might this differ by gender? (2) How do upward transfer computer science students make meaning of receptivity experiences, and how might that meaning making be shaped by gender? Methods: We use a sequential mixed methods design, relying on longitudinal survey and interview data from upward transfer computer science majors, collected throughout students' first year at the receiving university. Results: Findings reveal that, relative to men, upward transfer women report greater experiences of transfer stigma and challenges accessing resources at the receiving university. Qualitative findings document additional nuances in how upward transfer students—especially women—describe resilience as they navigate the university campus, encounter navigation challenges at the university, and make meaning of various manifestations of transfer stigma on campus. Contributions: In addition to implications for research and theory, we discuss what universities can do to foster a more receptive environment for upward transfer women. Specific recommendations focus on ensuring that spaces for women in computing are inclusive of transfer students and, likewise, creating supportive transfer cohort communities that are inclusive of women. [ABSTRACT FROM AUTHOR]

Faculty and peer interactions play a key role in shaping graduate student socialization. Yet, within the literature on graduate student socialization, researchers have primarily focused on understanding the nature and impact of faculty alone, and much less is known about how peer interactions also contribute to graduate student outcomes. Using a national sample of first-year biology doctoral students, this study reveals distinct categories that classify patterns of faculty and peer interaction. Further, we document inequities such that certain groups (e.g., underrepresented minority students) report constrained types of interactions with faculty and peers. Finally, we connect faculty and peer interaction patterns to student outcomes. Our findings reveal that, while the classification of faculty and peer interactions predicted affective and experiential outcomes (e.g., sense of belonging, satisfaction with academic development), it was not a consistent predictor of more central outcomes of the doctoral socialization process (e.g., research skills, commitment to degree). These and other findings are discussed, focusing on implications for future research, theory, and practice related to graduate training.

Research on cognitive load theory (CLT) has focused primarily on identifying the mechanisms and strategies that enhance cognitive learning outcomes. However, CLT researchers have given less attention to the ways in which cognitive load may interact with the motivational and emotional aspects of learning. Motivational beliefs have typically been assumed to be merely a precursor to the cognitive process. This view provides an incomplete picture of the dynamic relationship between cognitive load and motivational beliefs. In this review, we synthesize previous scholarly efforts concerning the motivational effects of anticipated investment of mental effort, new developments in the expectancy-value theory of motivation, and recent findings implicating cognitive load in the formulation of motivational beliefs. By conceptualizing cognitive load as motivational cost, we argue that motivational beliefs are an important outcome that results from instruction. We examine recent empirical evidence supporting this proposition and consider the implications for the further development of both CLT and motivational theories through their integration.

Background: STEM participation is often associated with the disenfranchisement of historically marginalized individuals. Disrupting these standing injustices to establish rightful presence with equitable opportunity, access, and cultural standing to shape and pursue STEM endeavors in ways that are inclusive of individuals' identities is a critical objective. However, research to understand and facilitate STEM experiences of queer youth what are also navigating their own relationships with gender- and heteronormativity is limited. Making—employing STEM to design artifacts in an informal learning environment—can disrupt conventional approaches to STEM activity in ways that support inclusive STEM engagement through crafting and personalized design. Method: This social design experiment examines the ways in which the design of maker activities and spaces can support queer rightful presence within STEM spaces. Findings: We found that maker communities can frame and collectively engage issues of identity formulation that are both dynamic and fluid in nature as part of bolstering STEM affinity. As participants' multifaceted identities unfolded through making projects that deliberately invited identity into design, they established rightful presence for intertwined queer and STEM identities. Contribution: This study extends the rightful presence framework to engage fluid, queer identities and illustrates making rightful presence practices that deliberately engage multifaceted identities. [ABSTRACT FROM AUTHOR]

Within this integrative review, cognitive load theory (CLT) is asserted as a powerful framework for conceptualizing human cognitive processes within learning. The relationship between cognition and emotion is then examined and further integrated within the scope of CLT. Emotion regulation strategies are discussed and adaptive strategies are proposed as being of particular relevance to broadening the theoretical and practical impacts of CLT. Central to the argument of this review is the use of cognitive reappraisal as a potential mitigator of cognitive load. Cognitive reappraisal involves reframing or reassessing understandings or beliefs that underlie an emotional response, which may mitigate cognitive load imposed by maladaptive emotion. It is proposed that effectively integrating adaptive emotion regulation strategies such as cognitive reappraisal in our pursuit of more effective cognitive functioning will aid in the development of a more integrated model of cognition and emotion within CLT. [ABSTRACT FROM AUTHOR]

We explore and critically reflect on the research development of eight science or engineering doctoral students serving as research assistants over the course of an academic year. We use a cognitive apprenticeship framework, assumed to explain doctoral students' skill development, to interpret narratives of skill development for students and their faculty supervisors, and compare these narratives against empirical measurements of student research skill development over the course of an academic year. We found abundant evidence for the "cognitive" component of cognitive apprenticeship, but questionable evidence for the "apprenticeship" component. We suggest that cognitive apprenticeship can be particularly potent in the development of students' research skills through research assistantship, but not without deliberate intention of both faculty supervisor and student.

Cognitive Task Analysis (CTA) interview technique iscommonly used to elicit knowledge of subject-matter expertsand to design instruction better focused on what experts don’tknow they know. However, the knowledge of how to conductan effective interview is, itself, largely implicit. In this studywe performed protocol analysis on a set of interviewtranscripts from an expert CTA practitioner to elicit thecognitive processes of conducting CTA interviews. We alsoconsulted expert CTA practitioners to identify the strategiesthat they used during the interviews. We present keystrategies that were employed by the expert CTA practitionersto ensure comprehensiveness and accuracy in the informationcollected, such as looking for perceptual cues (e.g.considering verbs such as “determine”) to ascertain adequacyof SME’s responses and selection of follow-up questions. Wepresent a production rule model as a detailed description ofthe cognitive processes underlying expert CTA interviewing

Although first-generation students represent a substantial proportion of doctoral students, few studies have examined their experiences and outcomes. We contribute to this nascent area of inquiry by comparing experiences and outcomes of first-generation and continuing-generation students during the first 3 years of doctoral education. Contrary to expectations, the results based on a national sample of PhD students in biology revealed remarkable similarity in experiences and outcomes between first-generation and continuing-generation students. One notable exception to this overall pattern of similarity was research productivity in the second year. By examining the relationships between students' experiences and outcomes over time, the findings illuminate the unique ways in which socialization experiences are related to specific outcomes and the extent to which those relationships change across years. Thus, this study offers initial insights into the nuanced ways in which students' socialization experiences contribute to various outcomes of doctoral education.

This article shares findings from a multilevel analytic induction of administrators, teachers, and gifted students within specialized science, technology, engineering, and mathematics (STEM) schools about their beliefs regarding the role of standards and standardized tests in the education of gifted learners. Sharing results from a cross-case analysis of six schools, we explore the ways in which student experiences of standards-based learning differ from the perceptions of their teachers and school administrators. We found that there is no consensus across administrators, teachers, and students regarding the impact that standards have in the educational process or on outcomes within specialized STEM schools, though all community members value and seek to create deep learning opportunities for students.