Project Area 1: Writing-to-Learn Pedagogy in STEM

Zinsser called writing “thinking on paper” and an extensive body of research has shown that writing has the capacity to support deep conceptual learning across disciplines. Writing is an integral part of scholarly work in science disciplines, but writing in science classrooms is relatively under-used. This project seeks to address this disconnect by investigating faculty conceptions of classroom writing to inform dissemination efforts and by investigating the ways in which writing promotes conceptual learning in science.

Faculty beliefs and use of writing-based pedagogies in the STEM classroom

We conducted a large-scale study of faculty use and beliefs about classroom writing drawing data from a national survey of STEM faculty from research institutions (n=4891) and interviews from a subset (n=33) stratified by discipline, rank, gender, and writing use.10 Analysis of survey data revealed disciplinary differences in the use of writing in the classroom where earth (88%) and life sciences (79%) reported higher use of writing as compared to physical sciences (~60%). Engineering (73%) and computer sciences (65%), which are more applied, were intermediate in reported use. Patterns emerged in terms of most frequently reported factors influencing faculty use of writing in the classroom, which revealed the clustering of life and earth sciences and of physical and applied sciences.

Through interview analysis, we generated a model describing faculty orientations toward writing in the classroom. These orientations were organized along two vectors including stance toward the role of writing in the classroom and reported use of writing in their own teaching. Some faculty who believe that writing does not belong in the science classroom (traditionalist) whereas others believe that writing is integral to learning (Writer). There are also faculty who believe writing is valuable for learning but logistically too difficult (Idealist).  Finally, there are faculty who use writing, but consider it to be to tool for communication rather than for learning (Utilitarian). Faculty from all of the STEM disciplines fell into each of the four orientations, suggesting that membership in a discipline does not necessarily correspond to a particular stance toward writing.

Investigation of the Role of Writing in STEM Learning

Although writing-to-learn is known to impact learning, very little has been reported regarding how writing promotes learning. Our approach to understanding the role of writing in learning is multi-pronged involving both traditional education research methods and more contemporary data science methods. Furthermore, we’ve conducted studies in a range of disciplines including chemistry,11,12,13 engineering,14 biology,15 and statistics.16

In one such study, we investigated the role of peer review of student writing in mediating misconceptions about foundational biology topics.15 Student misconceptions are an obstacle in STEM courses and, unless remediated, may continue causing difficulties in learning as students advance in their studies, and WTL assignments promote in-depth conceptual learning by allowing students to explore their understanding of a topic. This study sought to determine if and what types of misconceptions are elicited by WTL assignments and how the process of peer review and revision leads to remediation or propagation of misconceptions. We examined multiple writing assignments and determined that the prevalent mode of remediation arose through directed peer review comments followed by correction during revision.  It was also observed that additional misconceptions were elicited as students revised their writing in response to general peer review suggestions.  In this study, we used a novel research approach to provide a richer understanding of the role of writing in conceptual learning. Furthermore, we identified a number of new misconceptions that had not previously been reported in the biology education literature.

Project Area 2: The Development of Knowledge for Teaching Chemistry

We know very little about how college science instructors’ knowledge of and beliefs about teaching affect their actions in the classroom. Research that elucidates STEM knowledge for teaching is crucial for achieving national education reform because the successful adoption of educational innovations depends greatly on the instructor. The overarching goal of this project is to understand how people learn to teach college science so that we, and others, can change what people learn about teaching at this level.

Inferential Measures of Knowledge for Teaching Chemistry Topics

One form of teaching knowledge is knowledge of students understanding of a topic, which includes both 1) knowledge of the prerequisite understanding that is needed for learning a topic; and 2) knowledge about why a topic is difficult to learn.1 We investigated this type of knowledge for teaching a variety of chemistry topics including Thin-layer Chromatography,Concentration,3 Solubility,3 NMR Spectroscopy,4 Acid-base Chemistry,5 and reaction mechanisms.. Our approach relies on several methods including questionnaires, interviews, and content representations (i.e. map of content pathways in the curriculum). In each study, we found that graduate students made only modest gains in knowledge for teaching with experience. These studies are the first to measure this type of knowledge among graduate students particularly and revealed nuanced information about how each of these topics is likely to be taught. Building from these results we are working to understand how this knowledge translates into teaching practice in the classroom.

The Development of Graduate Student Instructors’ Teaching Knowledge

This study is focused on understanding how graduate students’ development of teaching knowledge, which is the underlying knowledge that shapes teachers’ actions and decisions in the classroom.6 This theory assumes that what teachers know (the tacit knowledge they hold for teaching) influences what they do in the classroom (how they use that knowledge in practice). To expand our understanding of what graduate students know about teaching we conducted in-depth interviews with twenty graduate students from three institutions regarding their knowledge and beliefs about teaching.7 Graduate students’ reported relying more heavily on affective strategies (e.g. being supportive and accessible) to support student learning relative to cognitive strategies (e.g. breaking concepts down into simpler ideas). They also reported relying on their own experiences as students and being constrained by the context in which they are learning to teach.  While many training methods are proposed for supporting graduate student-teacher learning they are not grounded in empirical studies of this distinct class of instructors. The results of this study provide an improved understanding that can be used to inform training in the future.

Project Area 3: Ways of Thinking and Knowing in Science

Science education is often focused on conveying what scientists know rather than how scientists think.17 We are interested in understanding how students learn to think like scientists in different learning environments.

Learning to Interpret and Reason about Spectral Data

Scientific reasoning, which is a fundamental aspect of scientific practice, is understudied in science education research.18 To address this gap, we are examining reasoning that occurs during spectral interpretation because NMR spectroscopy is routinely used by chemists conducting synthetic work.19 At the same time spectral interpretation is quite complex and therefore challenging to teach and learn. When interpreting NMR spectra chemists form mental representations that categorize the features of visual data and information.20,21 In forming their mental map novices may rely on surface features of the graph whereas an expert will examine underlying features.22 This study is predicated on the idea that examination of this mental map and the reasoning processes that accompany it will reveal how expertise in spectral interpretation develops.

To examine the underlying knowledge structure that governs this categorization and to capture how chemists with a range of expertise interpret and reason using spectral features we employed eye-tracking and retrospective think-aloud interviews. Eye-tracking involves measuring an individual’s eye movements as they complete a visual-based task and the patterns of their gaze can be linked to their thought process. 23 Retrospective think-aloud involves participants watching a recording of their eye movements after they completed a spectral interpretation task.  During the interview, participants verbalize in detail what they were viewing and thinking as they completed the task.24 This study elicited both invalid assumptions and heuristics used by students in interpreting spectral data that were used to investigate the differences between unsuccessful and successful problem solvers.25 Students who were unsuccessful drew on multiple invalid assumptions including 1) assuming that the N+1 rule always holds; 2) spectral data is absolute; 3) incorrect visuospatial analysis; and that 4) inaccurate ideas (i.e. separate peaks for the same molecule can vary in concentration). These were accompanied by heuristics like overgeneralizing learned rules or using a single peak as representative of the full molecule. The co-occurrence of multiple invalid assumptions and heuristics was indicative of an unsuccessful problem solver.

Chemistry Doctoral Student Development of Independent Thinking

The central goal of doctoral programs is to develop independent researchers through the production of new knowledge. The development of graduate students’ independence and ability to generate research ideas is a difficult process. To better understand how graduate students develop research autonomy we interviewed graduate students and faculty advisors (N=14) from Chemistry Departments at three R1 institutions.26 Analysis of the faculty interviews revealed a breadth of conceptions about what it means to do independent research and strategies they use to promote research autonomy in their doctoral students. Faculty promoted autonomy in a variety of ways including, modeling thinking, providing direct feedback, withholding help, and relying on the research group to communicate expectations. The analysis also revealed that the development of autonomy differs by subdiscipline, particularly in disciplines where skills and techniques are not typically learned prior to graduate school.

We Acknowledge the following sources of funding:

NSF CAREER: Understanding and Supporting Outsider STEM Teachers Learning to Use Place-based Culturally Relevant Education in the Classroom Award  2045505

NSF NNA – EHR-Polar DCL 2017: Collaborative Research: Researching Apun: Students Using Local, Traditional, and Science Knowledge Bases to Investigate Arctic Snow Processes Award 1821884

NSF IUSE: Collaborative Research: Accelerating the pace of research and implementation of Writing-to-Learn pedagogies across STEM disciplines Award 1524967

University of Michigan Third Century Initiative: M-Write: Engaged Learning Through Writing

University of Michigan Academic Innovation Fund: In My Shoes: Stepping into a Different Perspective about Shared Experiences at the UM

University of Michigan NINI (New Infrastructure / New Infrastructure: Diversity, Equity, and Inclusion): Instructional Coaching: A Community-based Approach to Inclusive STEM Teaching

Gilbert Whitaker Fund for the Improvement of Teaching: Improving Chemistry Teaching Through Instructional Coaching


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