Picture this: the value of multiple visual representations for student learning of quantum concepts in general chemistry

Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being [loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about abstract topics such as atomic and molecular structure. There is further gain if students’ difficulties with these representations are targeted through the use additional instruction such as a workbook that requires the students to exercise their visual modeling skills

Scientific reasoning abilities of non-science majors in physics-based courses

We have found that non-STEM majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower pre-instruction on the Lawson's Classroom Test of Scientific Reasoning (LCTSR) in comparison to national average STEM majors. The majority of non-STEM students can be classified as either concrete operational or transitional reasoners in Piaget's theory of cognitive development, whereas in the STEM population formal operational reasoners are far more prevalent. In particular, non-STEM students demonstrate significant difficulty with proportional and hypothetico-deductive reasoning. Pre-scores on the LCTSR are correlated with normalized learning gains on various concept inventories. The correlation is strongest for content that can be categorized as mostly theoretical, meaning a lack of directly observable exemplars, and weakest for content categorized as mostly descriptive, where directly observable exemplars are abundant. Although the implementation of research-verified, interactive engagement pedagogy can lead to gains in content knowledge, significant gains in theoretical content (such as force and energy) are more difficult with non-STEM students. We also observe no significant gains on the LCTSR without explicit instruction in scientific reasoning patterns. These results further demonstrate that differences in student populations are important when comparing normalized gains on concept inventories, and the achievement of significant gains in scientific reasoning requires a re-evaluation of the traditional approach to physics for non-STEM students.Comment: 18 pages, 4 figures, 3 table

Report on a Boston University Conference December 7-8, 2012 on 'How Can the History and Philosophy of Science Contribute to Contemporary U.S. Science Teaching?'

This is an editorial report on the outcomes of an international conference sponsored by a grant from the National Science Foundation (NSF) (REESE-1205273) to the School of Education at Boston University and the Center for Philosophy and History of Science at Boston University for a conference titled: How Can the History and Philosophy of Science Contribute to Contemporary U.S. Science Teaching? The presentations of the conference speakers and the reports of the working groups are reviewed. Multiple themes emerged for K-16 education from the perspective of the history and philosophy of science. Key ones were that: students need to understand that central to science is argumentation, criticism, and analysis; students should be educated to appreciate science as part of our culture; students should be educated to be science literate; what is meant by the nature of science as discussed in much of the science education literature must be broadened to accommodate a science literacy that includes preparation for socioscientific issues; teaching for science literacy requires the development of new assessment tools; and, it is difficult to change what science teachers do in their classrooms. The principal conclusions drawn by the editors are that: to prepare students to be citizens in a participatory democracy, science education must be embedded in a liberal arts education; science teachers alone cannot be expected to prepare students to be scientifically literate; and, to educate students for scientific literacy will require a new curriculum that is coordinated across the humanities, history/social studies, and science classrooms.Comment: Conference funded by NSF grant REESE-1205273. 31 page

Designing Effective Questions for Classroom Response System Teaching

Classroom response systems (CRSs) can be potent tools for teaching physics. Their efficacy, however, depends strongly on the quality of the questions used. Creating effective questions is difficult, and differs from creating exam and homework problems. Every CRS question should have an explicit pedagogic purpose consisting of a content goal, a process goal, and a metacognitive goal. Questions can be engineered to fulfil their purpose through four complementary mechanisms: directing students' attention, stimulating specific cognitive processes, communicating information to instructor and students via CRS-tabulated answer counts, and facilitating the articulation and confrontation of ideas. We identify several tactics that help in the design of potent questions, and present four "makeovers" showing how these tactics can be used to convert traditional physics questions into more powerful CRS questions.Comment: 11 pages, including 6 figures and 2 tables. Submitted (and mostly approved) to the American Journal of Physics. Based on invited talk BL05 at the 2005 Winter Meeting of the American Association of Physics Teachers (Albuquerque, NM

Characterizing lab instructors' self-reported learning goals to inform development of an experimental modeling skills assessment

The ability to develop, use, and refine models of experimental systems is a nationally recognized learning outcome for undergraduate physics lab courses. However, no assessments of students' model-based reasoning exist for upper-division labs. This study is the first step toward development of modeling assessments for optics and electronics labs. In order to identify test objectives that are likely relevant across many institutional contexts, we interviewed 35 lab instructors about the ways they incorporate modeling in their course learning goals and activities. The study design was informed by the Modeling Framework for Experimental Physics. This framework conceptualizes modeling as consisting of multiple subtasks: making measurements, constructing system models, comparing data to predictions, proposing causes for discrepancies, and enacting revisions to models or apparatus. We found that each modeling subtask was identified by multiple instructors as an important learning outcome for their course. Based on these results, we argue that test objectives should include probing students' competence with most modeling subtasks, and test items should be designed to elicit students' justifications for choosing particular modeling pathways. In addition to discussing these and other implications for assessment, we also identify future areas of research related to the role of modeling in optics and electronics labs.Comment: 24 pages, 2 figures, 5 tables; submitted to Phys. Rev. PE

Students' Understanding of Direct Current Resistive Electrical Circuits

Research has shown that both high school and university students' reasoning patterns regarding direct current resistive electric circuits often differ from the currently accepted explanations. At present, there are no standard diagnostic examinations in electric circuits. Two versions of a diagnostic instrument called Determining and Interpreting Resistive Electric circuits Concepts Tests (DIRECT) were developed, each consisting of 29 questions. The information provided by the exam provides classroom instructors a means with which to evaluate the progress and conceptual difficulties of their students and their instructional methods. It can be used to evaluate curricular packages and/or other supplemental materials for their effectiveness in overcoming students' conceptual difficulties. The analyses indicate that students, especially females, tend to hold multiple misconceptions, even after instruction. During interviews, the idea that the battery is a constant source of current was used most often in answering the questions. Students tended to focus on current in solving the problems and to confuse terms, often assigning the properties of current to voltage and/or resistance. Results indicated that students do not have a clear understanding of the underlying mechanisms of electric circuit phenomena. On the other hand, students were able to translate easily from a "realistic" representation of a circuit to the corresponding schematic diagram.Comment: This article has been accepted for publication in the American Journal of Physics - Physics Education Research Supplement. No known publication date as ye

Developing Teaching Materials By Using Computer-Assisted Problem-Based Learning

Computer-Assisted Problem-Based Learning (CAPBL) as a learning approach requires good teaching materials to make the learning process works effectively according to the characteristics and objectives of problem-based learning approach. Similarly in mathematics, appropriate teaching materials are adjusted to the characteristics of the subjects of mathematics that need to be delivered through CAPBL support towards the achievement of learning objectives. CAPBL is a learning approach that concerned extremely to the emphasis ofcomplex and open-ended problem as the basis for learning that will be faced by students in small groups; the emphasis of the role of students as who are responsible for their own learning; and the emphasis of the role of teacher as a facilitator, assisted by computer as a media that is expected to facilitate the learning process. Defining a clear idea of the problems; group learning; student role; teacher role; and assessment in problem-based learning and the role of computer in CAPBL will make the development of teaching materials matches to the characteristics of PBL itself. When that happens, CAPBLwill work effectively to be used on the teaching materials as well as it supports the learning process. Key Words: Problem-Based Learning, Computer Assissted Problem-Based Learning, teaching materials

Rich environments for active learning: a definition

Rich Environments for Active Learning, or REALs, are comprehensive instructional systems that evolve from and are consistent with constructivist philosophies and theories. To embody a constructivist view of learning, REALs: promote study and investigation within authentic contexts; encourage the growth of student responsibility, initiative, decision making, and intentional learning; cultivate collaboration among students and teachers; utilize dynamic, interdisciplinary, generative learning activities that promote higher-order thinking processes to help students develop rich and complex knowledge structures; and assess student progress in content and learning-to-learn within authentic contexts using realistic tasks and performances. REALs provide learning activities that engage students in a continuous collaborative process of building and reshaping understanding as a natural consequence of their experiences and interactions within learning environments that authentically reflect the world around them. In this way, REALs are a response to educational practices that promote the development of inert knowledge, such as conventional teacher-to-student knowledge-transfer activities. In this article, we describe and organize the shared elements of REALs, including the theoretical foundations and instructional strategies to provide a common ground for discussion. We compare existing assumptions underlying education with new assumptions that promote problem-solving and higher-level thinking. Next, we examine the theoretical foundation that supports these new assumptions. Finally, we describe how REALs promote these new assumptions within a constructivist framework, defining each REAL attribute and providing supporting examples of REAL strategies in action