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1. CHARACTERIZATION OF UNDERGRADUATE BIOLOGY INSTRUCTORS’ GOALS AND STRATEGIES FOR IMPLEMENTING QUANTITATIVE REASONING

   Khushal, Anum (August 2025, University of Nebraska Digital Commons)

   Quantitative reasoning (QR) is the ability to apply mathematics and statistics in the context of real-life situations and scientific problems. It is an important skill that students require to make sense of complex biological phenomena and handle large datasets in biology courses and research as well as in professional contexts. Biology educators and researchers are responding to the increasing need for QR through curricular reforms and research into biology education. This qualitative study investigates how undergraduate biology instructors implement QR into their teaching. The study used pedagogical content knowledge (PCK) and a QR framework to explore instructors’ instructional goals, strategies, and perceived challenges and affordances in undergraduate biology instruction. The participants included 21 biology faculty across various institutions in the United States, who intentionally integrated QR in their instruction. Semi-structured interviews were used to collect data focusing on participants’ beliefs, experiences, and classroom practices. Findings indicated that instructors adapt their QR instruction based on course level and student preparedness. In lower-division courses, strategies emphasized building foundational skills, reducing math anxiety, and using scaffolded instruction to promote confidence. In upper-division courses, instructors expected greater math fluency but still encountered a wide range of student abilities, prompting a focus on correcting misconceptions in integrating math knowledge and fostering deeper conceptual understanding in biology. Many instructors reported that their personal and educational experiences, especially struggles with math, often shaped their inclusive and empathetic teaching practices. Additionally, instructors’ research backgrounds influenced instructional design, particularly in the use of authentic data, statistical tools, and real-world applications. Instructors’ teaching experiences led to refinement in lesson planning, pacing, and active learning strategies. Despite their efforts, instructors faced both internal and external challenges in implementing QR, including discomfort with teaching math, time limitations, student resistance, and institutional barriers. However, affordances such as departmental support, interdisciplinary collaboration, and curricular flexibility helped to overcome some of these challenges. This study highlights the complex relationships between instructors’ experiences, beliefs, and contextual factors in shaping QR instruction. This calls for professional development that supports reflective practice, builds interdisciplinary competence, and promotes instructional strategies that bridge biology and mathematics and will help instructors design a learning environment that better support students’ development of QR skills. These findings offer valuable guidance for professional development aimed at helping biology instructors incorporate quantitative reasoning into their teaching. Such efforts can better equip students to meet the quantitative demands of modern biology and promote their continued engagement in STEM fields through more inclusive and integrated instructional approaches. 

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2. #let’s-discuss: Analyzing Students’ Use of Emoji when Interacting with Course Readings

   https://doi.org/10.1007/s40593-024-00401-5  

   Blobstein, Ariel; Facciotti, Marc T; Igo, Michele; Karger, David; Ravi, Prerna; Sripathi, Kamali; Gal, Kobi (May 2024, International Journal of Artificial Intelligence in Education)

   Abstract Emoji are commonly used in social media to convey affects, emotions, and attitudes. While popular in social media, their use in educational contexts has been sparsely studied even though emoji can be a natural way for students to express what they are feeling about the learning material. This paper studies how students use instructor-selected emoji when relating to and engaging with educational content. We use an online platform for collaborative annotations where discussions are embedded into the readings for the course. We also make it possible for students to use 11 unique emoji-hashtag pairings to express their thoughts and feelings about the readings and the ongoing discussion. We provide an empirical analysis of the usage of these emoji-hashtag pairs by over 1,800 students enrolled in different offerings of an introductory biology course from multiple academic terms. We also introduce a heat map, which allows the instructional team to visualize the distribution and types of emoji used by students in different parts of the reading material. To evaluate the heat map, we conducted a user study with five instructors/TAs. We found that instructors/TAs use the heat map as a tool for identifying textbook sections that students find difficult and/or interesting and plan to use it to help them design the online content for future classes. Finally, we introduce a computational analysis for predicting emoji/hashtag pairs based on the content of a given student post. We use pre-trained deep learning language models (BERT) to predict the emoji attached to a student’s post and then study the extent to which this model generated in an introductory biology course can be generalized to predict student emoji usage in other courses. 

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3. Improving Biostatistics Instruction through an Iterative Flipped Classroom Approach

   Li, Qingxia; Hui, Dafeng; Gross, Thomas (January 2026, Hawaii International Conference on Education)

   Preparing students for STEM careers requires educational approaches that bridge conceptual understanding with practical skill development. This is particularly critical in biostatistics, a foundational course for students pursuing careers in research and data-driven fields. Traditional instruction often emphasizes conceptual knowledge without providing sufficient opportunities for authentic, hands-on data analysis. Research-embedded flipped classroom (REFC) models offer a promising alternative by delivering conceptual content through pre-class videos and using in-class time for guided analysis of real-world data. This approach may enhance students’ statistical proficiency, analytical confidence, and perceptions of STEM careers. This study evaluated the iterative implementation of a REFC model across three cohorts of undergraduate students enrolled in biostatistics courses at two Historically Black Colleges and Universities (HBCUs). A total of 493 responses from 359 students were analyzed using a factorial design comparing traditional instruction (IAU) with three REFC iterations. Measures included a 20-item biostatistics quiz (ω = .75–.84), the 12-item Career Interest Questionnaire (CIQ; ω = .92–.96), and the 25-item STEM Semantics Survey (STEMSS; ω = .79–.92). Results revealed a significant interaction between instructional cohort and time of assessment for biostatistics knowledge, F(3, 427) = 7.15, p < .001, η_p² = .05. Only Cohort 3—characterized by consistent instructional strategies, conceptual review during class, and use of StatCrunch software—showed significant gains from pre- to post-test and outperformed both the IAU and earlier REFC cohorts. No significant changes were observed across cohorts on measures of STEM interest or attitudes. Findings suggest that iterative refinement of REFC strategies can meaningfully improve students’ biostatistics knowledge, though additional supports may be needed to influence career interests. Recommendations include structured in-class reviews, learner-aligned technology, and modest incentives for engagement. Further research is needed to explore how enhanced statistical skills can translate into long-term STEM career aspirations, particularly across diverse institutional contexts and earlier stages of education. 

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4. Use of personal storytelling in educational videos promotes student engagement and science identity in undergraduate biology courses

   https://doi.org/10.1128/jmbe.00084-25  

   Molder, Amanda L; Anderton, Brittany; Howell, Emily; Goodwin, Sarah; Behrman, Shannon; Ellefson, Marina (October 2025, Journal of Microbiology & Biology Education)

   Hsu, Jeremy L (Ed.)

   ABSTRACT: In this era of information abundance and digital connectivity, educational videos are a transformative and widely used resource in STEM higher education. Much of what is known about the effective use of educational videos comes from analyzing videos used for content delivery and the impacts on knowledge gains or behavioral engagement with videos. Less is known about how videos may impact students’ affective learning experiences, feelings, and attitudes or how to effectively use videos in science education beyond just as a content-delivery tool. This study explored the impact of three distinct video styles: a whiteboard animation, a recorded discovery lecture by one of the discoverers, and a documentary short film featuring both discoverers in conversation on student outcomes in a large-enrollment undergraduate biology class. Students were randomized to watch one of these three formats, all covering the same scientific content (i.e., the Meselson and Stahl experiment), followed by a post-video survey. The documentary film, “The Most Beautiful Experiment,” which integrated interpersonal storytelling and informal dialog, had the most significant impact on outcomes related to affective learning, including science identity, attitudes about biology, speaker relatability, and emotional engagement. No significant differences in knowledge gains were observed across video styles. This study highlights the potential of personalized and embodied video formats to enrich STEM education and warrants further research into their broader applications. 

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5. Confidence disparities: Pre-course coding confidence predicts greater statistics intentions and perceived achievement in a project-based introductory statistics course.

   https://doi.org/10.1080/26939169.2023.2183287  

   Rosenbaum, J.; Dierker, L. (January 2023, Journal of statistics and data science education)

   Self-efficacy is associated with a range of educational outcomes, including science and math degree attainment. Project-based statistics courses have the potential to increase students’ math self-efficacy because projects may represent a mastery experience, but students enter courses with preexisting math self-efficacy. This study explored associations between pre-course math confidence and coding confidence with post course statistical intentions and perceived achievement among students in a project-based statistics course at 28 private and public colleges and universities between fall 2018 and winter 2020 (n=801) using multilevel mixed-effects multivariate linear regression within multiply imputed data with a cross-validation approach (testing n=508 at 20 colleges/universities). We found that pre-course coding confidence was associated with, respectively, 9 points greater post-course statistical intentions and 10 points greater perceived achievement on a scale 0–100 (0.09, 95% confidence interval (0.02, 0.17), p=0.02; 0.10, 95% CI (0.01, 0.19), p=0.04), and that minoritized students have greater post-course statistical intentions than non-minoritized students. These results concur with past research showing the potential effectiveness of the project-based approach for increasing the interest of minoritized students in statistics. Pre-course interventions to increase coding confidence such as pre-college coding experiences may improve students’ post-course motivations and perceived achievement in a project-based course. Supplementary materials for this article are available online. 

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