Background: Extensive research has documented the importance of faculty advisors for graduate students' experiences and outcomes. Recent research has begun to provide more nuanced accounts illuminating different dimensions of advisor support as well as attending to inequalities in students' experiences with advisors. Purpose: We extend the research on graduate student advisor relationships in two important ways. First, building on the concept of social capital, and in particular the work on institutional agents, we illuminate specific benefits associated with student-advisor relationships. Second, we advance prior work on inequality in advisor relationships by examining students' experiences at the intersection of race and gender. Research Design: To illuminate the nuances of graduate students' experiences with advisors, this study included interviews with 79 students pursuing PhD's in biological sciences. Thematic coding revealed several important dimensions of benefits associated with advisor relationships. Corresponding codes were grouped into three categories, describing three groups of students with notably different experiences with advisors. Findings: The data revealed three distinct student-advisor relationship profiles which we term scholars, subordinates, and marginals. The three groups had vastly different experiences with access to knowledge and resources, access to networks, and cultivation of independence. Moreover, the distribution across these three groups was highly unequal with unique patterns observed at the intersection of race and gender. White men benefited from both racial and gender privilege and were notably overrepresented in the scholars group while White women and racial/ethnic minority (REM) students were more likely to be socialized as subordinates. REM men had the least favorable experiences with the majority of them being in the marginal category, along with a substantial proportion of White and REM women. Notably, even experiences of negative relationships with advisors were gendered and raced: REM men's negative relationships with advisors were characterized by benign neglect while women primarily experienced conflictual relationships. Conclusion and Recommendations: The findings illuminate important consequences of student-advisor relationships and pronounced inequalities in who has access to benefits accrued through those relationships. Creating more equitable experiences will necessitate substantial attention to improving mentoring and eliminating gender and racial/ethnic inequalities in faculty support.

Dialogue Acts (DAs) can be used to explain what expert tutors do and what students know during the tutoring process. Most empirical studies adopt the random sampling method to obtain sentence samples for manual annotation of DAs, which are then used to train DA classifiers. However, these studies have paid little attention to sample informativeness, which can reflect the information quantity of the selected samples and inform the extent to which a classifier can learn patterns. Notably, the informativeness level may vary among the samples and the classifier might only need a small amount of low informative samples to learn the patterns. Random sampling may overlook sample informativeness, which consumes human labelling costs and contributes less to training the classifiers. As an alternative, researchers suggest employing statistical sampling methods of Active Learning (AL) to identify the informative samples for training the classifiers. However, the use of AL methods in educational DA classification tasks is under-explored. In this paper, we examine the informativeness of annotated sentence samples. Then, the study investigates how the AL methods can select informative samples to support DA classifiers in the AL sampling process. The results reveal that most annotated sentences present low informativeness in the training dataset and the patterns of these sentences can be easily captured by the DA classifier. We also demonstrate how AL methods can reduce the cost of manual annotation in the AL sampling process. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Help from virtual pedagogical agents has the potential to improve student learning. Yet students often do not seek help when they need it, do not use help effectively, or ignore the agent's help altogether. This paper seeks to better understand students' patterns of accepting and seeking help in a computer-based science program called Betty's Brain. Focusing on student interactions with the mentor agent, Mr. Davis, we examine the factors associated with patterns of help acceptance and help seeking; the relationship between help acceptance and help seeking; and how each behavior is related to learning outcomes. First, we examine whether students accepted help from Mr. Davis, operationalized as whether they followed his suggestions to read specific textbook pages. We find a significant positive relationship between help acceptance and student post-test scores. Despite this, help accepters made fewer positive statements about Mr. Davis in the interviews. Second, we identify how many times students proactively sought help from Mr. Davis. Students who most frequently sought help demonstrated more confusion while learning (measured using an interaction-based ML-based detector); tended to have higher science anxiety; and made more negative statements about Mr. Davis, compared to those who made few or no requests. However, help seeking was not significantly related to post-test scores. Finally, we draw from the qualitative interviews to consider how students understand and articulate their experiences with help from Mr. Davis.

As part of a larger project focused on exploring development of mathematical modelling competencies among post-secondary STEM majors enrolled in advanced mathematics, we developed a pair of parallel multiple-choice modelling competencies assessments. In this chapter, we provide a technical report of item development, scale calibration, and validation of the assessment. We used multiple statistical approaches, including classical test theory (CTT), item response theory (IRT), and principal component analysis (PCA) to document item behaviours, scale properties, and dimensionality of a developing multiple-choice assessment of mathematical modelling competencies designed for post-secondary STEM majors. We share analyses and inferences, making recommendations for the field in pursuing such assessments. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Math achievement in U.S. high schools is a consistent predictor of educational attainment. While emphasis on raising math achievement continues, school-level interventions often come at the expense of other subjects. Arts courses are particularly at risk of being cut, especially in schools serving lower socioeconomic status youth. Evidence suggests, however, that arts coursework is beneficial to many educational outcomes. We use data on 20,590 adolescents from the High School Longitudinal Study of 2009 to answer two research questions: (1) Does student accumulation of fine arts courses across different topic areas relate positively to math test scores in high school? (2) Does school SES differentiate this potential association? Results indicate that youth attending higher-SES schools take more art courses and taking music courses is related to higher math test scores. However, this benefit only seems to only apply to more socially advantaged student bodies. Results reveal a site of additional educational advantage for already privileged youth.

Analogies are known to be powerful tools for making sense of unfamiliar ideas in terms of already understood concepts. Science students regularly encounter unfamiliar ideas, such as microscopic objects that are invisible to our everyday experience and behaviors dictated by quantum mechanics. An understanding of basic concepts of quantum mechanics is useful in many disciplines, especially with the growing field of quantum information sciences and technologies. Physics researchers often use analogies in their own research and science communicators use them to make quantum ideas accessible to K-12 students and across STEM disciplines, but analogy use in upper-division teaching has been less researched. Our research goal is to understand how analogies are used to teach quantum mechanics, and specifically, what prior knowledge is used as a basis for analogies within two widely used quantum mechanics textbooks. This textbook analysis shows the most common bases for analogies include: mathematical structures from linear algebra, which are applied to model quantum systems; everyday life examples, which are used to make quantum systems more familiar and understandable; and macroscopic classical phenomena, which are used to highlight differences between classical and quantum mechanics. We also find authors use different conventions, based on the various cue words that authors use to indicate analogy-based reasoning. In the STEM classroom, this research has implications for enhancing student learning about abstract topics in science.

In interviews with physics students and early career physicists, we ask about their experiences with having impairments in the physics setting and physics culture. In this paper, we highlight how experiences shared by participants as disabled people in physics represent clusters of models of disability. Specifically, we apply a theoretical framing of a three-dimensional disability model space, with axes defined as medical versus social (i.e., cause); tragedy versus affirmative (i.e., effect); and minority group versus universal (i.e., ability/disability dichotomy). For example, in this framework, providing accommodations is described by a cluster of the social and minority models of disability. By analyzing participants' experiences in physics through this disability framework, we aim to identify the models that underpin supportive experiences and support the development of policies and professional development for the physics community towards benefiting disabled people. Through analysis and comparison of these models and participants' narratives, we offer a discussion and possible guidelines for instructors interacting with students with disabilities, opportunities for those with disabilities to deconstruct their own prior experiences and analyze potential misinterpretations that may arise from the models.

Designing physics courses that support students' activation and development of expert-like physics epistemologies is a significant goal of Physics Education Research. However, very little research has focused on how physics students' interactions with course structures resonate with different epistemological views. As part of a course redesign effort to increase student success in introductory physics, we interviewed introductory physics students about their experiences with course structures and their learning and belonging beliefs. We present here a case from this broader data corpus in which a student, Robyn, discusses his epistemological views of physics problem solving and his experiences with physics lectures, office hours, and discussion sections. We find that Robyn's physics epistemology manifests consistently across his interactions with each of these different course structures, suggesting a possible resonance between students' beliefs and their experiences with course structures and the value of further investigation into the potential merits of comprehensive course design.

Learning using Computer-Assisted Instruction (CAI) demands a high level of attention given the tendency to be distracted and mind-wander. How does the online STEM instructor know when learners are having attentional problems and the extent to which these problems affect learning? In the present study, the visual attentional and cognitive state of physics graduate students were probed while they went through a multimedia instructional module to refresh their knowledge of Newton's II Law. Data from an eye tracker, webcam, egocentric glasses, screen recording, and mouse and keyboard events were integrated to record learners' attention overt attention to the learning environment (+/-) and thinking about learning content (+/-) to analyze students' attention spans during learning from this module. On average, learners were found to be on-task and on-screen for a vast majority of time, with evidence of mind wandering. The learning module improved the participants efficiency with which they answered the questions correctly on a post-test relative to the pre-test. Further, there is a positive albeit statistically non-significant correlation between the improvement from pre- to post-test efficiency and the time spent on-screen and on-task during the module.

An understanding of vectors and vector operations is crucial for success in physics, as this serves as the foundation for various essential concepts, including motion and forces. Previous research indicates that only a fraction of introductory physics students have a usable knowledge of vectors and vector operations, and that more attention should be given to how students make sense of vectors. We examined classroom video data from an introductory physics course wherein students worked collaboratively through learning activities to introduce vectors and vector operations. During these activities, students' employment of gesture as a representational mode facilitated group sense-making. We propose a preliminary taxonomy of gestures for representing vector magnitudes, directions, and initial and terminal points. By identifying and characterizing the gestures used by students, we can gain insights into their learning processes and conceptual understanding of vectors, which can inform instructional design and teaching practices.