Introductory laboratory courses play an important role in student learning in introductory geoscience courses. In an attempt to quantify different effects on student learning, we evaluated the influence of six factors: situational interest, course format, course, lab topic, lab level of inquiry, and Teaching Assistant (TA). Data were collected from six introductory geoscience laboratory courses at five public research institutions for four semesters. Student learning was measured using pre- and post- course surveys with three content questions for each of six lab topics considered per course. Lab topics studied were selected by each course instructor and learning survey questions were aligned directly to the lab activities of each course. Unexpectedly, some labs were offered online during the study period, which is included as a potential learning factor (course format). Odds ratio analyses indicate that of all our factors, the topic of the lab activity, the TA lab instructor, and the course students are in, are strong predictors of student learning. Of the lab topics, there are higher odds of student learning for lab activities on Minerals, Earth's Interior, and Earthquakes. We do not propose that student interest, inquiry levels and course format are not important to student learning, but our data collection and analyses show they are not as important as lab topics and course factors in this dataset. These findings suggest that lab topics with lower odds ratios are prime opportunities for potential improvements to support student learning. To address the influence of courses, our further work will consider more nuanced analyses of factors related to individual courses such as individual lab activities at institutions and TA influences.

Decades of research have demonstrated that student retention, engagement, and learning are enhanced through implementation of active learning strategies in the classroom. There are an increasing number of studies that have tested various active learning interventions in atmospheric science courses, but little data exists on the implementation of active learning across all courses or classrooms, which has already been systematically explored in other STEM disciplines. Handlos et al. (2022) represents the only multi-institutional evaluation of classroom practices in the field of atmospheric science. One of their key results was that the instructional strategy of case studies was used by a majority of participants at all course levels, though the degree to which they were implemented in an active manner was unclear. Accordingly, the goal of this study is to characterize the spectrum of pedagogical considerations and approaches used to implement case studies across undergraduate atmospheric science courses. To understand case study implementation in classrooms, atmospheric science instructors across the U.S. were invited to participate in an online survey. The survey asked instructors to provide information on courses in which case studies are used as an instructional strategy. Specifically, the survey asked about characteristics such as specific courses in which they are used, frequency of use, length of time spent in class or lab, expected learning outcomes or student skills, and classroom implementation approach, including the role of instructor versus students. This presentation will provide an overview of case study use across the undergraduate atmospheric science curriculum, including types of activities that leverage case studies as well as inferences regarding active versus passive instructional methods. Comparisons among lower-level versus lower-level courses will be shown, as well as sensitivities to instructor and institutional demographics. Information regarding instructor motivations and intended outcomes will also be described as context for the survey results.

Spatial thinking research has informed geoscience education research, yet current theoretical frameworks face growing empirical and practical challenges. In this presentation, we will consider three issues hindering spatial thinking research in the geosciences, especially as related to the Newcombe and Shipley (2014) typology: 1) limited empirical support for the 2 x 2 partitioning of spatial thinking types; 2) challenges classifying spatial thinking with cognitive strategies rather than geoscience problem solving; and 3) the inadequacy of existing frameworks to describe spatial thinking in fluid-Earth science disciplines. In response to these challenges, we propose geoscience education research include an ecological approach to spatial thinking that focuses on how geoscientists attend to and use information available in the environment. We will discuss how this approach reframes spatial thinking research from identifying the spatial skills necessary for success in the geosciences to understanding what environmental information geoscientists use to solve geoscience problems and how we can best guide students to recognize this information. We argue that this bottom-up, task-centered perspective can complement existing frameworks and offer new directions for both research and instruction across the full breadth of geoscience disciplines.

Spatial thinking is widely recognized as playing a critical role in developing geoscience expertise, yet less is known about how variation in student's spatial abilities impacts their learning of dynamic Earth systems. For a spatially complex geoscience process such as understanding stream processes, a learner could conceivably draw on spatial skills from the four typologies of Newcombe and Shipley (2014): intrinsic-static, intrinsic-dynamic, extrinsic-static, and extrinsic-dynamic. Physical models like Emriver's Em2 stream table may reduce the cognitive load by externalizing dynamic processes and enabling embodied manipulation. However, it remains unclear whether such tools benefit learners of varying spatial abilities equally. This study tests an Aptitude-Treatment Interaction (ATI) hypothesis: instructional effectiveness depends on learner characteristics, such that guidance may compensate for lower spatial ability while minimally guided exploration may better support higher spatial thinkers. In Spring 2026, we are conducting an interaction test using a two-way factorial design in an upper-level hydrology course (n = 28), crossing spatial thinking (measured by the Spatial Thinking Aggregate Test, or STAT; Sabatini, 2024) with instructional condition (self-guided vs. instructor-guided stream table interaction). Based on initial STAT results, students were categorized as relatively high or low spatial thinkers then randomly assigned to instructional conditions. Following the intervention, students complete a spatially intensive task requiring them to modify model parameters to produce targeted erosion patterns. Performance is evaluated based on success, number of attempts, and time to completion. Students also complete structured reflections to examine differences in reasoning strategies and spatial problem-solving processes.We hypothesize (1) main effects of instruction type and spatial thinking and (2) a significant interaction in which instructor guidance disproportionately benefits lower spatial thinkers, consistent with ATI and cognitive load theory. Findings will clarify when and for whom embodied physical models support learning of spatially complex, dynamic Earth systems in addition to being engaging.

Broadening participation in STEM, particularly in geoscience, requires approaches that increase awareness, reduce structural barriers to participation, and foster opportunities to successfully "try on" the discipline. The Seismology Skill Building Workshop (SSBW) is a free MOOC that has developed scientific computing skills of more than 2,500 participants within a seismology context. Recent studies of the SSBW have shown its success in attracting a diverse population, including ~33% non-geoscience majors, producing large skill gains and increased intent to pursue geoscience. These results have been interpreted as due to efficacious and equitable instructional design choices, but the long-term impacts of the workshop for broadening participation in STEM were unknown. To explore this, we designed a longitudinal survey exploring participants' subsequent actions and perspectives on the SSBW's influence. The survey was distributed to all participants, 2020-2024, who had completed the SSBW (n=751) and received 153 complete responses. We found 79% of current students and 70% of geoscience majors had engaged in post-SSBW scientific computing, coursework, or research. However, only 57% of those currently employed and 55% of non-geoscience majors had post-SSBW engagement, primarily due to lack of opportunity. Over 80% of respondents said the SSBW had a "moderate" to "very great" influence on their post-SSBW engagement. Intriguingly, over 60% of non-geoscience majors chose great to very great, compared to ~40% for geoscience majors. When asked about graduate school, 88% of all survey participants were interested or already in graduate school (85% for non-geoscience, 90% for geoscience), and only 11% of participants did not receive an offer upon applying. We also found that although confidence in scientific computing grew the most during the SSBW, it has continued to grow. Overall, these results suggest the SSBW, and other opportunities like it can impact the recruitment and retention of large numbers of students into the geosciences.

Previous studies have reported that student achievement improves with student-centered instruction, but this has not yet been quantified, and the relationship between student learning and the use of active learning strategies has not yet been reported for geoscience courses. Using newly designed lessons in introductory geoscience courses taught by four faculty at separate US public institutions, we compare student learning gains for three categories of instruction (student-centered, transitional, and teacher-centered). The style of instruction is measured by direct observations using RTOP and COPUS observation protocols. Student learning is measured with two paired sets of questions; one compares students' responses on exam questions with those at the start of the semester; the second compares clicker question responses at the start and end of the class period when the lesson was taught. Pre- and post-instruction surveys also ask students to rate their interest in the lesson topic. Post-instruction surveys additionally ask students to report perceptions of their learning. We developed five new introductory geoscience lessons and report here on results for the Critical Minerals lesson. Student learning in the Critical Minerals lesson was greater when instruction was observed in the student-centered category than the teacher-centered category. Student learning gains are higher for exams than for clicker questions. A quantitative assessment of the extent of student learning will compare incremental instructional changes from teacher-centered to student-centered categories of instruction.

Constructivist pedagogy emphasizes building new knowledge from prior experiences through active, hands-on learning. Many students who take introductory geoscience courses arrive with little to no formal or even informal exposure to the field. This raises the question: Does everyone have the same chance to succeed in introductory geoscience classrooms?In physics education research, Salehi et al. (2019) tested whether introductory physics performance could be explained by incoming knowledge or demographic factors. Building on that framework, this study examines whether demographic gaps in introductory geoscience reflect preparation differences and whether prior interest or informal science experiences predict success.This (N = 945) examined potential predictors of final exam performance in introductory geoscience courses. Students completed a geoscience concept inventory and surveys measuring interest in geoscience, natural sciences, and STEM, as well as frequency of informal geoscience-related experiences. Structural equation modeling was used to test direct and mediated relationships among demographics, preparation, experiential exposure, and exam performance.Results suggest that introductory geosciences classrooms can function as genuine and accessible entrance points into the geosciences field. Neither gender, first-generation status, nor prior informal science experiences significantly predicted final exam performance in the full structural model. Although students entered with different levels of interest and exposure, these differences did not determine academic outcomes in any significant way. Mediation pathways through interest or informal engagement were also not statistically significant in predicting success. For geoscience educators committed to expanding access and equity, these findings are promising. Success in introductory geoscience does not appear to hinge on privileged preparation or prior interest, positioning these courses as true gateways into the field, spaces where all students have a meaningful opportunity to succeed and feel welcomed inside the geosciences.

Self-efficacy, or one's belief in their own ability to perform a task, is often investigated as a predictor of academic persistence and performance. The Math Your Earth Science Majors Need project developed the Geoscience Mathematics Self-Efficacy Scale (GeoMSES) that builds on prior work in measurement of self-efficacy for mathematics by focusing specifically on students' capacity to apply mathematical skills to typical problems encountered in majors-level undergraduate geoscience courses or in professional geoscience settings. The scale was developed as part of program evaluation research for a set of 14 co-curricular math and statistics modules designed to augment existing geoscience curricula. This 18-item tool was validated using data from students at 20 different institutions. The data had high internal reliability and stability and items were highly intercorrelated, yet not redundant. Our results show that the scale consistently measures student confidence across diverse groups, scores correlate with actual math performance, and items can be used individually to assess specific skills (e.g., vectors or linear regression) or as a full set for program evaluation. The GeoMSES can augment or serve as a less threatening alternative to traditional achievement measures and performance-based rubrics. Instructors and researchers can use this tool to identify "confidence gaps," tailor their teaching strategies, and evaluate the impact of math-integrated geoscience curricula.