Culturally and Linguistically Sustaining STEM Pedagogies

Additional Authors: John L. Pecore, Ph.D. (Professor, University of West Florida); Melissa K. Demetrikopoulos, Ph.D. (Director, Institute for Biomedical Philosophy)

A Practice-Based Learning Cycle to Develop Pre-Service Teachers’ Culturally and Linguistically Sustaining STEM Pedagogies

Over the years, multilingual learners (MLs) have not received equitable STEM education due to structural inequities, which often includes being excluded from advanced science classes and learning decontextualized language in segregated English for Speakers of Other Languages (ESOL) classes.^{19, 24-25} In science education, discussion on best practices for teaching science to MLs has centered on important theoretical tenets such as culturally sustaining pedagogies.^{1, 21} Studies produced a wealth of empirical data that bolsters the integration of science learning with language and literacy development.⁴ Additionally, extensive literature reviewed by Lyon and Tolbert (2022) has highlighted the importance of science educators supporting MLs in navigating the language demands inherent in scientific sense-making and practices.¹⁷ Buxton and Lee (2023) also emphasize using MLs’ rich multilingual and multicultural assets as the foundation of science knowledge building.⁵ Despite this progress in understanding best practices, science teachers often report that they do not feel adequately prepared to teach MLs, which significantly limits MLs’ opportunities to thrive in science classrooms and careers.^{17, 19}

Research on preparing pre-service science teachers to work with MLs has focused predominantly on developing culturally sustaining science pedagogies and language-integrated science instruction.^{4, 14, 16} Yet, creating opportunities to apply this pedagogical knowledge and making actual changes and innovations in instruction has received much less attention. In a typical teacher education program, pre-service teachers learn the knowledge and concepts early in their coursework and are only offered limited, if any, opportunities to practice actual teaching of MLs later in their practicum or student teaching. However, enacting culturally and linguistically sustaining science pedagogies requires not only learning knowledge and observing exemplary teaching but also purposeful practices with critical reflection and focused feedback.²

To address the limited practice opportunities in teacher preparation, this practice-based learning cycle uses mixed-reality simulated classroom environments in which pre-service teachers can apply instructional strategies to teach avatar students including an ML. In addition, the project provided multiple re-visiting and re-teaching opportunities at various points in the learning cycle. These practice opportunities are integrated with interactive learning modules to build pedagogical knowledge as well as reflexive spaces for pre-service teachers to critically evaluate their own teaching and contemplate constructive feedback from a mentor.

In this blog, we present our practice-based learning cycle to develop pre-service teachers’ culturally and linguistically sustaining STEM pedagogies, which is grounded in a language-based approach to content instruction and practice-based teacher education. We also present the comprehensive practice-based learning cycle integrating three technologies – online learning modules, avatar lab, and video assessment.

Language-Based Approach to “STEM” Instruction

Considerable research demonstrates ways to integrate language and content and assist teachers in understanding the role of language in constructing disciplinary knowledge.^{3, 8, 10-11} One framework is de Oliveira’s (2016, 2020, 2023) language-based approach to content instruction (LACI), which builds on six Cs of support for scaffolding content-area instruction for MLs: connection, culture, code-breaking, challenge, community and collaboration, and classroom interactions.^6-8 This project adapted LACI’s six Cs of support to be STEM specific (see Figure 1). Connection refers to connecting STEM instruction with students’ background knowledge and their lives. Culture refers to utilization of students’ diverse cultural and linguistic resources to their STEM learning. Code-breaking includes unpacking language functions and features to help students’ sense-making visible through the exploration of mathematical problems or scientific phenomena. Challenge relates to maintaining high academic expectations in high challenge-high support STEM classrooms. Community and collaboration entail co-constructing STEM knowledge as a learning community. Finally, classroom interactions focus on using a variety of interactional scaffolding moves to support STEM and language learning.

Figure 1. Language-Based Approach to STEM Instruction’s Six Cs of Support

Practice-Based Learning Cycle Using Three Technologies

During the past decade, scholars and teacher educators have made sustained efforts to shift teacher preparation from knowledge acquisition to knowledge application incorporating practice-based instructional activities.²⁶ These practice-based teacher education initiatives also shift attention away from teachers’ behavior and toward cognition such as decision-making and reflective practices. Grossman et al. (2009) proposed approximations of practice to provide novice teachers with opportunities to practice their knowledge, pedagogical skills, and professional identity in a safe environment and receive immediate feedback on their teaching from teacher educators or peers.¹²

To approximate teaching practices, mixed-reality simulated classrooms offer online practice opportunities through teaching avatar students. The combination of digital avatars and a human puppeteer achieves an authentic experience.^{15, 22} Through this experience, pre-service teachers can apply strategic thinking and action without being placed in a physical classroom.^{13, 18} Also, the availability of repeated teaching opportunities without actual students who might otherwise become confused or incorporate misconceptions makes this technology valuable to develop and hone pre-service teachers’ critical teaching skills.⁹ In this project, we use the Avatar Lab simulated classroom developed by Mursion^TM (mursion.com) with five avatar students (see Figure 2). One of the avatars, named Davy, is an ML from Cambodia. The goal of our pre-service teachers is to engage Davy in a science lesson about seasonal changes, applying culturally and linguistically sustaining STEM pedagogies.

Figure 2. Avatar Lab with Davy

Merely providing simulation practice opportunities does not ensure improving pre-service teachers’ pedagogies. We incorporated two other technologies with simulation practices for purposeful planning and critical reflection. Before teaching in the Avatar Lab, pre-service teachers engage in Canvas online learning modules that the research team developed. In these modules, pre-service teachers learn a wide range of strategies and concrete examples, analyze classroom videos, and discuss teaching ideas with peers. After teaching avatars, pre-service teachers engage in critical reflection in the GoReact video assessment platform (get.goreact.com). While watching their teaching video, they mark both the strategies applied and the missed opportunities and note their rationale of why and how they applied specific strategies or what they would do differently. Then, a mentor responds to the pre-service teachers’ reflections as well as providing her feedback and assessment in the same space. In this way, this video assessment tool fosters a more interactive and meaningful feedback process.

Finally, we integrated these three platforms as a comprehensive practice-based learning cycle (see Figure 3) adapting the five stages of the SHIFT cycle, which was originally used by Safe and Stengle (2020) to leverage pre-service teachers’ anti-oppressive pedagogies in live-actor simulations.²³ Our learning cycle consists of the five stages: prepare their lesson (Canvas); interact with avatar students and enact their pedagogies (Avatar Lab); react to their own teaching (GoReact); review a mentor’s feedback (GoReact); and reconsider and revise their lesson to reteach. After the baseline teaching to acquaint pre-service teachers with the avatar lab and gauge their initial understanding of teaching MLs, this cycle is repeated three times with different foci.

Figure 3. Practice-Based Learning Cycle

Learning Outcomes

The analysis of post surveys after each teaching session shows the participant pre-service teachers’ increased competencies in all six Cs of support. The greatest increases are demonstrated in code-breaking, culture, and challenge in which each approached an average increase of one full level on the four-scale rubric (0.83, 0.84, and 0.99, respectively) and which represented the three lowest competencies at baseline (2.21, 1.95, and 1.93, respectively). Figure 4 displays the three Cs of support with the greatest improvement shown by the increased percentage of participants who met and exceeded expectations from the baseline to the final teaching. The most significant improvement was in code-breaking, where only 29% of participants were above “Meet Expectations” at baseline compared to 75% in the final teaching attempt. Also, despite the low baseline, 36% of the participants exceeded expectations for culture by the end of the project. Moreover, pre-service teachers reported increases of approximately one third to one half of a level on the rubric for the remaining three Cs [connection (0.36), community and collaboration (0.52), and classroom interactions (0.61)] with over one third of participants exceeding expectations for community and collaboration and classroom interactions (36% and 35% respectively) by the end of the project.

Figure 4. Three Cs of Support with Greatest Improvement in STEM Instruction for Multilingual Learners

The analysis of teaching videos and individual interviews with selected exemplary students shows that pre-service teachers were able to deepen their understanding of language use tied to science practices. Beyond scientific facts and laws, they focused on science and engineering practices (e.g., analyze and interpret data and construct explanations), crosscutting concepts (e.g., finding a pattern), and core ideas (e.g., earth and the solar system) identified in the Next Generation Science Standards.²⁰ They also paid more attention to help Davy utilize language functions to engage in science practices (e.g., comparing and contrasting and justifying her findings) in addition to focusing on science vocabulary. Further, they were able to contextualize science concepts beyond science classrooms by actively bringing in local contexts and examples (e.g., daylight savings and impact on Florida coastal areas) and socioscientific issues (e.g., global warming and sea level rises). They were also able to facilitate Davy’s scientific sense-making through multimodal resources and materials (e.g., props, interactive websites, visuals, and graphs).

Moving Forward

This practice-based learning cycle using mixed-reality simulation along with online learning modules and video assessment provided a viable teacher education model to develop pre-service teachers’ culturally and linguistically sustaining STEM practices beyond vocabulary-focused or facts-based lessons for MLs. Teacher educators can expand upon more explicit connections to social justice and equity issues related to scientific phenomena. Future research can develop sustainable systems to implement a practice-based learning cycle, including navigating ways to provide cost-effective and widely accessible technologies. Simulation developers need to continuously maintain efforts to enhance the authenticity of avatar characters and the affordances of simulation to provide better approximations of practice.

Acknowledgments

Funding provided by NSF Award: 2215675. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.