Hannah Sevian

Analysing how Scientists Explain their Research: A rubric for measuring the effectiveness of scientific explanations

The present article presents a rubric we developed for assessing the quality of scientific explanations by science graduate students. The rubric was developed from a qualitative analysis of science graduate students’ abilities to explain their own research to an audience of non‐scientists. Our intention is that use of the rubric to characterise explanations of science by scientists, some of whom become professors, would lead to better teaching of science at the university level. This would, in turn, improve retention of qualified and diverse scientists, some of whom may elect to become science teachers. Our rubric is useful as an instrument to help evaluate scientific explanations because it distinguishes between the content knowledge and pedagogical knowledge of scientists, as well as a scientist’s ability to integrate the two in the service of a clear and coherent explanation of his or her research. It is also generally useful in evaluating, or self‐evaluating, science explanations by science professors and researchers, graduate students preparing to be scientists, science teachers and pre‐service teachers, as well as students who are explaining science as part of learning.

Reasoning about benefits, costs, and risks of chemical substances: mapping different levels of sophistication

The ability to evaluate options and make informed decisions about problems in relevant contexts is a core competency in science education that requires the use of both domain-general and discipline-specific knowledge and reasoning strategies. In this study we investigated the implicit assumptions and modes of reasoning applied by individuals with different levels of training in chemistry when engaged in a task that demanded the evaluation of the benefits, costs, and risks (BCR) of using different chemical substances. We were interested in identifying and characterizing different levels of sophistication in the use of chemistry concepts and ideas in BCR reasoning. Our qualitative study elicited reasoning patterns that ranged from intuitive to mixed to normative, with students mostly in mid-undergraduate years demonstrating reasoning that was a mixture of intuitive and chemical ways of thinking. Intuitive reasoning was governed primarily by affective impressions about the substances under evaluation. Consideration of compositional, structural, and energetic features of substances was observed with increased training in chemistry, with a tendency to mix particle-level explanations with intuitive assumptions. Normative thinking shifted toward proactive use of appropriate disciplinary knowledge, recognition of a need for more data about bulk properties particularly on large scales, and consideration of pros, cons, and trade-offs. Implications are discussed for ways to improve the undergraduate chemistry curriculum so that students gain proficiency in making productive judgments and informed decisions.

Learning Chemistry to Enrich Students’ Views on the World they Live In

Chemistry presents a unique position among the sciences as an area of study in which students have opportunities to consider consequences of actions with personal and societal ramifications, both in the present and for the future. In particular, chemistry education can offer students opportunities to practice using chemical knowledge to evaluate benefits, costs and risks associated with products and processes, and to make informed decisions based on reasoned evaluation.

Use of representation mapping to capture abstraction in problem solving in different courses in chemistry

A perspective is presented on how the representation mapping framework by Hahn and Chater (1998) may be used to characterize reasoning during problem solving in chemistry. To provide examples for testing the framework, an exploratory study was conducted with students and professors from three different courses in the middle of the undergraduate chemistry curriculum. Each participants reasoning while solving exam problems was characterized by comparing the stored knowledge representation used as a resource and the new instance representation associated with the problem being solved. Doing so required consideration of two ways in which abstraction occurs: abstractness of representations, and abstracting while using representations. The representation mapping framework facilitates comparison of the representations and how they were used. This resulted in characterization of reasoning as memory-bank or rule-based (rules processes), or similarity-based or prototype (similarity processes). Rules processes were observed in all three courses. Similarity-based reasoning seldom occurred in students, but was common to all of the professors’ problem solving, though with higher abstractness than in students. Examples from the data illustrate how representation mapping can be used to examine abstraction in problem solving across different kinds of problems and in participants with different levels of expertise. Such utility could permit identifying barriers to abstraction capacity and may facilitate faculty assessment development.

Student Outcomes from Innovations in Undergraduate Chemistry Laboratory Learning.

Abstract Much of the research on implementation of novel curriculum, instruction, and assessment in undergraduate science laboratory courses in the U.S. has been funded by public funding agencies. A review and analysis was conducted of awards made between 2000 and 2008 from the National Science Foundation that have focused on laboratory learning in undergraduate chemistry. The study is concerned with characterizing the types of interventions that occurred, and what was studied and learned related to student learning and associated outcomes. For projects that concluded by August, 2011, an overview is presented of the current ‘state of the art’ of the empirical knowledge base, in the interest of suggesting gaps and opportunities for further study. The findings are also contrasted with a recent summary of the state of chemical education research, largely focused at undergraduate level teaching and learning, that was presented in a review paper commissioned by the National Academies of Science as part of a consensus study on discipline-based education research.

Comparison of learning in two context-based university chemistry classes

ABSTRACT Context-based learning (CBL) is advocated as beneficial to learners, but more needs to be understood about how different contexts used in courses influence student outcomes. Gilbert defined several models of context that appear to be used in chemistry. In one model that achieves many criteria of student meaning-making, the context is provided by ‘personal mental activity’, meaning that students engage in a role to solve a problem. The model’s predicted outcomes are that students develop and use the specialised language of chemistry, translate what they learn in the immediate context to other contexts, and empathise with the community of practice that is created. The first two of these outcomes were investigated in two large-enrolment university chemistry courses, both organised as this CBL model, in which students were introduced to kinetic molecular theory (KMT). Sample 1 students (N1 = 105) learned KMT through whole-class kinaesthetic activity as a human model of a gas while focusing on a problem identifying substances in balloons filled with different gases. Sample 2 students (N2 = 110) manipulated molecular dynamics simulations while focusing on the problem of reducing atmospheric CO2. Exam answers and pre-/post-test responses, involving a new KMT context, were analysed. Students in Sample 1 demonstrated a stronger understanding of particle trajectories, while Sample 2 students developed more sophisticated mechanistic reasoning and greater fluidity of translation between contexts through increased use of chemists’ specialised language. The relationships of these outcomes to the contexts were examined in consideration of the different curriculum emphases inherent in the contexts.

Epistemic games in substance characterization

Problem solving is lauded as beneficial, but students do not all learn well by solving problems. Using the resources framework, Tuminaro J., and Redish E. F., (2007), Elements of a cognitive model of physics problem solving: Epistemic games, Physical Review Special Topics-Physics Education Research, 3(2), 020101 suggested that, for physics students, this puzzle may be partially understood by paying attention to underlying epistemological assumptions that constrain the approaches students take to solving problems while working on them. They developed an approach to characterizing epistemic games, which are context-sensitive knowledge elements concerning the nature of knowledge, knowing and learning. As there is evidence that context-activated knowledge influences problem solving by students in chemistry, we explored identifying epistemic games in students’ problem solving in chemistry. We interviewed 52 students spanning six courses from grade 8 through fourth-year university, each solving 4 problems. Using 16 contexts with substance characterization problems, we identified 5 epistemic games with ontological and structural stability that exist in two larger epistemological frames. All of these epistemic games are present at all educational levels, but some appear to grow in across educational levels as others recede. Some games also take lesser and greater precedence depending on the problem and the chemistry course in which students are enrolled and the context of the problem. We analyze these results through a frame of learning progressions, paying attention to students’ ideas and how these ideas are contextualized. Based on this analysis, we propose teaching acts that instructors may use to leverage the natural progressions of how students appear to grow in their capacity to solve problems.

Capturing Students' Abstraction While Solving Organic Reaction Mechanism Problems across a Semester.

Students often struggle with solving mechanism problems in organic chemistry courses. They frequently focus on surface features, have difficulty attributing meaning to symbols, and do not recognize tasks that are different from the exact tasks practiced. To be more successful, students need to be able to extract salient features, map similarities to problems seen previously, and extrapolate while solving problems. In short, students must be able to recognize and generate abstractions. To help students in learning to solve problems, we need a better understanding of the nature of students’ capacity for abstraction. Building upon an exploratory study (Sevian H., Bernholt S., Szteinberg G. A., Auguste S. and Perez L. C., (2015), Use of representation mapping to capture abstraction in problem solving in different courses in chemistry, Chem. Educ. Res. Pract., 16(3), 429–446), we applied the representation mapping model of Hahn and Chater (1998a) to characterize the abstraction employed by students while solving mechanistic problems in organic chemistry, and to measure students’ growth in abstraction capacity across a semester. This model operationalizes abstraction by considering (a) the ways in which students match existing knowledge to new instances (abstracting) and (b) the level of abstractness of students’ representations. We describe characteristic indicators of abstracting and abstractness. Trends were observable in the abstraction present in the reasoning of successful and unsuccessful problem solvers. Students who proposed plausible solutions used both strict or partial matching, but students who proposed implausible solutions tended to use strict matching. Students who proposed plausible solutions utilized higher levels of abstractness. This indicates that flexibility in abstraction processes may be important to successfully solve problems. The findings have implications for developing instructors’ assessment practices in ways that build students’ abstraction capacity.

How does STEM context-based learning work: what we know and what we still do not know

ABSTRACT Context-based learning (CBL) has influenced teaching and learning science in many countries over the past decades. Twelve years ago, a special issue on CBL was published in this Journal, focusing on CBL curriculum development. Seven papers in this current special issue on CBL now address the question of how a context influences the learning process. The papers focus on the stimulation of learning STEM subjects within contexts, how the learning process occurs and is enhanced, and the application of contexts in different settings. The approaches, results, and implications of the papers are located in a larger view that considers the question of what must be the case if a student not only engages in the tasks of learning but also succeeds at them. Concerning willingness and effort by learners, the papers draw conclusions about which STEM-related interests of students endure and are ephemeral across a decade, design criteria for maximising students’ situational interest, and students’ engagement with content and context simultaneously. Focusing on the opportunity to teach and learn, the papers reveal how a professional development approach functions to support STEM teachers to develop CBL materials, and how specific scaffolding acts in teaching bring students to more complex reasoning. Regarding good teaching, insights are offered on how metacognitive prompts improve teaching. Centring on the social surround that supports teaching and learning, a comparison of two contexts for teaching the same content reveals which aspects of the contexts move student learning forward. From this mapping, paths toward future research are projected.