This paper introduces innovative software for efficient English language learning that incorporates machine learning and natural language processing techniques to personalize the vocabulary acquisition process for English language learners. The software was designed to enhance extensive reading by generating English language learning materials for learners based on their interests and proficiency levels. The software begins by administering a brief and straightforward vocabulary test to learners. The test is used to identify words that may be unknown to the learners from 12,000 words. The machine-learning algorithm identifies words that are most likely to be unknown to the learner based on their test performance. The software then prompts the learner to select a topic of interest such as science or music. Thereafter, the software generates personalized English language learning materials for the learner, which contain texts with specific vocabulary related to the selected topic. The material is generated using ChatGPT. The software highlights unknown words in the text, which the learner can check using a dictionary. The software then generates new material incorporating the unknown words that the learner has checked, ensuring that the learner is exposed to a wide vocabulary in his area of interest. This process is repeated multiple times with the software generating new materials and incorporating new words that the learner has checked, thereby facilitating the efficient acquisition of new vocabulary. Through this process, the learners can engage in extensive reading, enabling them to read more in English and develop their reading skills, while simultaneously acquiring new vocabulary related to their interests. The innovative approach of the software in English language learning offers a personalized, adaptive, and efficient approach to extensive reading. This can help learners improve their English proficiency by reading in a manner tailored to their interests and proficiency levels. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

GCFGlobalLearning is a non-profit organization committed to creating life-changing opportunities through an innovative virtual education project that incorporates technological tools. Our platform offers free courses to learners worldwide, available in English, Spanish, and Portuguese. Since our launch, we have welcomed millions of learners. Our current focus is on incorporating artificial intelligence tools that will enhance our learners’ experience. To achieve this, we have developed a recommender system and a learning content search and organization tool that personalizes our learners’ learning journey. Even with limited information about our learners, we can enhance their experience through the use of these AI tools. In this paper, we introduce the platform’s primary components, detail how we overcome our limited learner information scenario, and share our vision of incorporating more artificial intelligence innovations in the future. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

In this chapter, we explore group counseling interventions for Black males and explain the Achieving Success Everyday (ASE) group model for racial and mathematical development. We use critical race theory (CRT) as a framework to analyze school counseling (SC) and mathematics literature that focuses on Black male students to inform the reconceptualization of the ASE group model for school counselors. We examine the programs and interventions that have been published with Black male participants in school settings within the SC literature. We also examine programs and interventions that have been specially designed to improve Black males’ mathematics skills. We specifically focus on gathering findings that provide successful outcomes for Black males in public schools. We examine literature that reflects the role school counselors (SCs) take when supporting Black male students’ academic, social, emotional, college, and career identity development. We believe uncovering ideas to capture Black males’ experiences in school settings could shed light on how to foster Black excellence. Gaining an understanding of programs and interventions for Black male students through a CRT lens could inform future research, policy, and practice in SC while combating ongoing racism that continues to persist. © 2024 Sam Steen and Canaan Bethea Published under exclusive licence by Emerald Publishing Limited.

Learning assistants (LAs) increase accessibility to instructor–student interactions in large STEM lecture classes. In this research, we used the Formative Assessment Enactment Model developed for K-12 science teachers to characterize LA facilitation practices. The Formative Assessment Enactment Model describes instructor actions as eliciting or advancing student thinking, guided by their purposes and the perspective they center as well as by what they notice about and how they interpret student thinking. Thus, it describes facilitation practices in a holistic way, capturing the way purposes, perspectives, noticing, interpreting, and actions are intertwined and working together to characterize different LA actions. In terms of how perspectives influence actions, eliciting and advancing moves can be enacted either in authoritative ways, driven by one perspective that has authority, or in dialogic ways, driven by multiple perspectives. Dialogic practices are of particular interest because of their potential to empower students and center student thinking. Our analysis of video recordings of LA–student interactions and stimulated recall interviews with 37 introductory physical science lectures’ LAs demonstrates that instead of as a dichotomy between authoritative and dialogic, LA actions exist along a spectrum of authoritative to dialogic based on the perspectives centered. Between the very authoritative perspective that centers on canonically correct science and the very dialogic perspective that centers the perspectives of the students involved in the discussion, we find two intermediary categories. The two new categories encompass a moderately authoritative perspective focused on the LA’s perspective without the claim of being correct and a moderately dialogic perspective focused on ideas from outside the current train of thought such as from students in the class that are not part of the current discussion. This spectrum further adds to theory around authoritative and dialogic practices as it reconsiders what perspectives can drive LA enactment of facilitation other than the perspective of canonically correct science and the perspectives of the students involved in the discussion. This emerging characterization may be used to give LAs and possibly other instructors a tool to intentionally shift between authoritative and dialogic practices. It may also be used to transition towards more student-centered practices.

Purpose The purpose of this study is to examine how student agency influences career decision-making for doctoral students in biological sciences. The authors address the following questions: How do biological science graduate students navigate career indecision? And how does agency relate to their experiences with career indecision? Design/methodology/approach The authors analyzed interview data collected from 84 PhD biology graduate students. Researchers used a grounded theory approach. After open codes were developed and data were coded, code reports were generated, which were used to determine themes. Findings More than half of the sample had not committed to a career path, and undecided students were bifurcated into two categories: Uncommitted and Uncertain. Uncommitted graduate students demonstrated agency in their approach and were focused on exploration and development. Uncertain students demonstrated less agency, were more fearful and perceived less control and clarity about their options and strategies to pursue career goals. Practical implications Findings suggest some forms of indecision can be productive and offer institutional leaders guidance for increasing the efficacy of career development and exploration programming. Originality/value Research on doctoral student career decision-making is often quantitative and rarely explores the role of agency. This qualitative study focuses on the relationship between student agency and career indecision, which is an understudied aspect of career development.

PurposeThe purpose of this study is to examine how doctoral students in the biological sciences understand their research skill development and explore potential racial/ethnic and gender inequalities in the scientific learning process. Design/methodology/approachBased on interviews with 87 doctoral students in the biological sciences, this study explores how doctoral students describe development of their research skills. More specifically, a constructivist grounded theory approach is employed to understand how doctoral students make meaning of their research skill development process and how that may vary by gender and race/ethnicity. FindingsThe findings reveal two emergent groups, technicians who focus on discrete tasks and data collection, and interpreters who combine technical expertise with attention to the larger scientific field. Although both groups are developing important skills, interpreters have a broader range of skills that support successful scholarly careers in science. Notably, white men are overrepresented among the interpreters, whereas white women and students from minoritized racial/ethnic groups are concentrated among the technicians. Originality/valueWhile prior literature provides valuable insights into the inequalities across various aspects of doctoral socialization, scholars have rarely attended to examining inequalities in research skill development. This study provides new insights into the process of scientific learning in graduate school. Findings reveal that research skill development is not a uniform experience, and that doctoral education fosters different kinds of learning that vary by gender and race/ethnicity.

Introduction: Informational graphics and data representations (e.g., charts and figures) are critical for accessing educational content. Novel technologies, such as the multimodal touchscreen which displays audio, haptic, and visual information, are promising for being platforms of diverse means to access digital content. This work evaluated educational graphics rendered on a touchscreen compared to the current standard for accessing graphical content. Method: Three bar charts and geometry figures were evaluated on student (N = 20) ability to orient to and extract information from the touchscreen and print. Participants explored the graphics and then were administered a set of questions (11-12 depending on graphic group). In addition, participants' attitudes using the mediums were assessed. Results: Participants performed statistically significantly better on questions assessing information orientation using the touchscreen than print for both bar chart and geometry figures. No statistically significant difference in information extraction ability was found between mediums on either graphic type. Participants responded significantly more favorably to the touchscreen than the print graphics, indicating them as more helpful, interesting, fun, and less confusing. Discussion: Accessing and orienting to information was highly successful by participants using the touchscreen, and was the preferred means of accessing graphical information when compared to the print image for both geometry figures and bar charts. This study highlights challenges in presenting graphics both on touchscreens and in print. Implications for Practitioners: This study offers preliminary support for the use of multimodal, touchscreen tablets as educational tools. Student ability using touchscreen-based graphics seems to be comparable to traditional types of graphics (large print and embossed, tactile graphics), although further investigation may be necessary for tactile graphic users. In summary, educators of students with blindness and visual impairments should consider ways to utilize new technologies, such as touchscreens, to provide more diverse access to graphical information.

Mentoring promotes underserved students’ persistence in STEM but is difficult to scale up. Conversational virtual agents can help address this problem by conveying a mentor’s experiences to larger audiences. The present study examined college students’ (N= 138 ) utilization of CareerFair.ai, an online platform featuring virtual agent-mentors that were self-recorded by sixteen real-life mentors and built using principles from the earlier MentorPal framework. Participants completed a single-session study which included 30 min of active interaction with CareerFair.ai, sandwiched between pre-test and post-test surveys. Students’ user experience and learning gains were examined, both for the overall sample and with a lens of diversity and equity across different, potentially underserved demographic groups. Findings included positive pre/post changes in intent to pursue STEM coursework and high user acceptance ratings (e.g., expected benefit, ease of use), with under-represented minority (URM) students giving significantly higher ratings on average than non-URM students. Self-reported learning gains of interest, actual content viewed on the CareerFair.ai platform, and actual learning gains were associated with one another, suggesting that the platform may be a useful resource in meeting a wide range of career exploration needs. Overall, the CareerFair.ai platform shows promise in scaling up aspects of mentoring to serve the needs of diverse groups of college students. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Developing models and using mathematics are two key practices in internationally recognized science education standards, such as the Next Generation Science Standards (NGSS) [1]. However, students often struggle at the intersection of these practices, i.e., developing mathematical models about scientific phenomena. In this paper, we present the design and initial classroom test of AI-scaffolded virtual labs that help students practice these competencies. The labs automatically assess fine-grained sub-components of students’ mathematical modeling competencies based on the actions they take to build their mathematical models within the labs. We describe how we leveraged underlying machine-learned and knowledge-engineered algorithms to trigger scaffolds, delivered proactively by a pedagogical agent, that address students’ individual difficulties as they work. Results show that students who received automated scaffolds for a given practice on their first virtual lab improved on that practice for the next virtual lab on the same science topic in a different scenario (a near-transfer task). These findings suggest that real-time automated scaffolds based on fine-grained assessment data can help students improve on mathematical modeling. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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.