Abbott, Saul, Parker & Beichner, Am J Phys PER Suppl (2000)

Can one lab make a difference?

J. M. Saul, D. S. Abbott, G. W. Parker & R. J. Beichner, American Journal of Physics, Physics Education Research Supplement, 68(S1), S60-S61 (2000). (link to journal article)

Hammer & Elby, Proceedings of the 4th International Conference of the Learning Sciences (2000)

Epistemological Resources

D. Hammer & A. Elby, in Proceedings of the Fourth International Conference of the Learning Sciences, B. Fishman & S. O'Connor-Divelbiss (Eds.), Mahwah, NJ, p 4-5 (2000).

Abstract: Research on epistemologies has presumed a unitary ontology of "beliefs"; we propose a manifold ontology of "resources" and discuss implications for instruction.

Elby, J of Mathematical Behavior (2000)

What students' learning of representations tells us about constructivism

A. Elby, Journal of Mathematical Behavior, 19, p 481-502 (1999). (html version)

Abstract: This paper pulls into the empirical realm a longstanding theoretical debate about the prior knowledge students bring to bear when learning scientific concepts and representations. Misconceptions constructivists view the prior knowledge as stable alternate conceptions that apply robustly across multiple contexts. By contrast, fine-grained constructivists believe that much of students' intuitive knowledge consists of unarticulated, loosely-connected knowledge elements, the activation of which depends sensitively on context. By focusing on students' intuitive knowledge about representations, and by fleshing out the two constructivist frameworks, I show that they lead to empirically different sets of predictions. Pilot studies demonstrate the feasibility of a full-fledged experimental program to decide which flavor of constructivist describes students more adequately.

Hammer, Amer J of Physics (2000)

Student resources for learning introductory physics

D. Hammer, American Journal of Physics, Physics Education Research Supplement, 68(S1), S52-S59 (2000). (html version)

Abstract: With good reason, physics education research has focussed almost exclusively on student difficulties and misconceptions. This work has been productive for curriculum development as well as in motivating the physics teaching community to examine and reconsider methods and assumptions, but it is limited in what it can tell us about student knowledge and learning. This article suggests the study of student resources for learning, with an emphasis on the practical benefits to be gained for instruction.

Hammer, Inquiring into Inquiry Learning and Teaching in Science (2000)

Teacher inquiry

D. Hammer, in Inquiring into Inquiry Learning and Teaching in Science, J. Minstrell & E. vanZee (Eds), Washington DC: American Association for the Advancement of Scieince, p 184-215 (2000) (Also 1999, In the Paper Series of the Center for the Development of Teaching at EDC, in Newton, MA) (html version)

Abstract: The progessive agendas of science education reform, in particular that of promoting student inquiry, place substantial intellectual demands on teachers. If these reforms are to succeed, the education community must do more to appreciate and address those demands. This paper presents three examples of high school physics teachers' conversations about "snippets" of each others' work with students. The purposes are (1) to hightlight the central role and intellectual demands of teacher inquiry, in particular teacher diagnosis of students' strengths and needs; (2) to suggest that teachers often experience and express their diagnoses in terms of instructional strategies, and (3) to suggest that the value of education research for instruction should be understood primarily with respect to what it may contribute to teacher inquiry.

Redish, Conf: Physics Teacher Beyond 2000 (2000)

Who needs to learn physics in the 21st century and why?

E. F. Redish, plenary lecture, GIREP Conference: Physics Teacher Education Beyond 2000, Barecelona, Spain (Aug 2000).

Abstract: In this talk I consider what physics can offer to students, both as physics majors and in other sciences. The recent increases in the technological character of the workplace appear likely to continue, leading to increasing numbers of individuals who should learn something about science. For many of these people, understanding the character of science, including learning new ways to think about and analyze the physical world, is an essential component of what they need to learn. In the next few years, we will need to figure out exactly what we can usefully teach them and how to do it effectively in the short time they are in a physics class. The critical information for this discussion comes from a careful consideration of what it means to think about and understand science and from careful observations of the actual thinking processes of incoming physics students.

Bao & Redish, Conf: Phys Teacher Beyond 2000 (2000)

What can you learn from a (good) multiple choice exam?

L. Bao & E. F. Redish, contributed paper, GIREP Conference: Physics Teacher Education beyond 2000, Barcelona, Spain (2000).

Abstract: The information that a teacher typically extracts from a multiple-choice exam is limited. Basically, one learns: How many students in my class can answer each question correctly? Careful studies of student thinking [1] demonstrate that student responses may reflect strongly held naïve conceptions and that students may function as if they think about a particular topic using contradictory models (typically their naïve model and the scientific one taught in class). We have developed tools for extracting information about the state of knowledge of a class from multiple-choice exams that goes beyond how many students answered each question correctly. First, a mathematical function, the concentration factor, allows one to determine whether a particular question triggers students’ naïve models. Second, by treating the students as if they can exist in “mixed states” of knowledge, we create methods of extracting measures of the state of confusion of the class. By this we mean how likely the students are to used mixed models. Our method assists in the construction of multiple-choice tests that respond to what is known about the difficulties students bring into classes and we provide ways of extracting more detail about what students have learned than traditional analysis tools.