History | Participation | Current Schedule | Previous Talks
|
Pittsburgh has a long tradition of being a center for studying the psychology of scientific reasoning, although typically spread across labs and institutions. In the Fall of 2001, Kevin Crowley and Christian Schunn started the Pittsburgh Scientific Reasoning Supergroup. It meets on Fridays from 12:00 - 1:30 in LRDC (2nd or 9th floor). This group brings together the faculty, postdocs, and graduate students in Pittsburgh interested in the psychology of scientific reasoning. The Supergroup is so named to emphasize that the group is more than one particular faculty member's lab group. The group takes different formats each time it convenes, including research presentations, project kickoff talks, hot-topic discussions, manuscript feedback sessions, and, when in season, practice job talks for the post-docs and grad students. Regardless of what the "main event" is for each meeting, the group begins at noon with pizza (provide to those who RSVP) and a little chat time so that people can check in with each other and exchange informal information about their current work. While there are a core group of over 30 regular participants, we also post the topic of each Supergroup at least a week in advance, so that the core group is augmented by others who come when the topic is relevant to them.
If you are interested in attending the Supergroup meetings and would like to be on the topics mailing list, please send email to Carmela Rizzo <crizzo@pitt.edu>.
April 29th, 2005: Ellice Forman, A framework for studying scientific argumentation in inquiry-oriented classrooms
In this talk, I will present an analytic framework for studying collective scientific argumentation that is derived, in part, from 15 years of experience conducting ethnographic research on discourse in inquiry-oriented mathematics and science classrooms, taught by exemplary teachers. In the classrooms I’ve studied, the teachers engaged their students in complex reasoning and problem solving activities so that science was not viewed as “revealed truth” and mathematics was not seen as a set of algorithmic routines and number facts to memorize. Instead, these teachers attempted to create a community where students could actively engage in inquiry (e.g., use multiple strategies to solve problems, examine
rich data sets to identify patterns and make inferences, communicate their findings to each other, reflect on and evaluate strategies and findings, conduct multiple cycles of investigation). My perspective on classroom discourse in science and mathematics has been influenced by sociocultural theories of learning as participation and by sociolinguistic theories of language in use. Thus, I view learning as a process of socialization and enculturation in classroom practices and see discourse as an important learning mechanism. My analytic framework has three major components for describing instructional processes in inquiry-oriented classrooms: the establishment of classroom discourse norms through explicit and implicit
means; student uptake of scientific argumentation; and the development of scientific identities. After I present this framework, I will illustrate it with examples from my published research and from an on-going study of argumentation in a high school biology classroom.April 1st, 2005: Yaron Doppelt, Achieving high and quality adoption in science education reform – Collaboration between teachers and researches using design-based learning
How does a design-based approach help researchers collaborate with teachers in order to achieve a wide and sustainable curriculum reform? Learning through planning and making projects provides the possibility for free and continuous passage among motor action, concrete thinking and formal thinking. Students gain experience in solving real world problems, presenting different solutions, and learning from their mistakes. In this study a design-based learning environment was implemented within nine urban public middle schools with 859 pupils. The development of the learning module aimed at bridging the gap between the existing learning environment and science standards. I created an atmosphere of collaboration
between teachers, teachers’ leaders, resource teachers and researchers. Students designed and built electrical alarm systems to learn electricity concepts over a 5-week period using authentic engineering design methods. Both quantitative and qualitative tools were used to investigate the research effort. Findings show that design-based learning assisted teachers in engaging students in various learning activities using a variety of teaching methods. Three approaches were identified in the ways teachers implemented the program.
This study demonstrates high and quality adoption of the learning module by the district and the teachers. The quality adoption is characterized by teacher interaction with each other and with researchers during workshops, a significant adoption rate, the construction of different learning-materials that teachers prepared, and the different approaches teachers used to implement the module. The methodology that was implemented in this research can be repeated in different educational and research settings.March 18th, 2005: Brian White (Department of Biology, UMass, Boston), Exploring Hypothesis Testing with Undergraduate Biology Students
Testing hypotheses is an essential part of the scientific process and an important component of science education at all levels. We have been
investigating how the nature of the hypothesis-testing task effects students' hypothesis-testing processes. We are also investigating the
relationship between hypothesis-testing process and learning outcomes. In one set of studies, we have coarse-grained data comparing process and
outcome from small-scale variations of an inquiry-based lab exercise, the Red and White Yeast Lab (RWYL). These show measurable effects on process
with no effect on outcome. In another set of studies, we have fine-grained data comparing students' hypothesis testing in two very different lab
exercises: the RWYL and the Virtual Genetics Lab. Students in these labs show very different hypothesis-testing behavior; in future work, we hope to
explore these differences in detail.March 4th, 2005: Matthew M. Mehalik, A Cognitive Network Analysis of Innovation: Environmentally Sustainable Textiles
What are effective ways of accomplishing innovative design? Innovative design involves going beyond what all other forms of design must do: it requires the integration of aspects of context into the design process itself so that new designs and non-incremental changes to contexts are produced-- not just new devices, and not just adapting new devices to existing contexts. What this means is that issues associated with the context of design assume heightened relevance to understanding, learning, and teaching effective innovative design.
This talk will consist of a case presentation of how new ideas in environmental design were used to transform an international manufacturing network that was on the verge of closing down because of global competitiveness and product novelty challenges into an award winning market leader. Designers and directors united around a vision to create a new textile market—one based on principles of environmental design. How did they accomplish this goal, and what can we learn from this case?
The analysis uses an original cognitive network framework to describe how this innovation network functioned and changed. The framework consists of three network states: A state (1) in which one actor or small elite group of actors has an overall representation and black boxes others into specific roles whose purpose(s) those persons only partly, or do not, understand; A state (2) in which no group of actors has a comprehensive view. In this state actors construct and renegotiate trading zones that permit them to work together while still pursuing their own enterprises and/or goals;and A state (3) in which all participants share a common representation.
Networks shift among these states. The framework is used as a tool to help practitioners and students reflect upon how to be strategic in their ability to work with others and to achieve innovative designs. It also serves as a methodological attempt to bridge a divide in approaches to analyzing socio-technical networks that tend to divorce the sociological and the
cognitive by explaining network behavior that resonates with actor-network and distributive cognitive perspectives.
The author followed a participant-observer methodology. He conducted multiple, in-depth interviews with and worked occasionally in conjunction with several of the mangers, consultants, and designers in the role as an academic consultant. An evaluation of the economic and environmental performance of the network was conducted using corporate financial, operational, and environmental reporting data.February 11th, 2005: Gaea Leinhardt, One Firm Spot: Leveraging Chemistry Homework for Learning
This work is the result of a three year collaboration within the Chemistry Collective which is housed at CMU and led by David Yaron. In this talk I present an argument that overall learning in a college level chemistry course is primarily influenced by two factors: the self-directed studying of students for exams and the engagement with carefully designed homework activities. This argument is supported both by results from a multiple regression analysis and by a manipulation in which knowledge prior to studying but after instruction was compared to knowledge after studying. I also suggest that these results can be unpacked and understood in more detail through the use of a structural equation model, which is presented as well. Given that far less is known about college level learning in science under natural conditions than is known about earlier levels of science learning this work makes a contribution to the development of more formal and complete specifications of the requirements for improved science instruction.
February 4, 2005: Jen Cartier & Wendy Sink, Transforming Science Teaching One Big Idea At A Time
The Pittsburgh Partnership for ENERGizing Science is an ongoing collaboration between Pitt faculty and graduate students in STEM disciplines and science education, the science curriculum director and resource teachers of Pittsburgh Public School District, and individual PPSD teachers in grades 3-8. The overarching goal of this work, which is funded through the GK-12 program at NSF, is to support and improve science learning experiences for students in urban classrooms. Our approach to meeting this goal has been to focus on instructional materials implementation and revision as a leverage point for strengthening teachers’ content knowledge and pedagogical strategies. The graduate student fellows within the partnership are paired with individual PPSD teachers and these teams spend a combined 15 hours weekly planning for and engaging in classroom instruction. The teams also participate in semi-structured plan-teach-reflect sessions throughout the year, attend monthly meetings for all partnership members, and develop “outreach” projects to disseminate new knowledge, materials, and strategies to other PPSD teachers and parents.
In this presentation, we will describe the theoretical and philosophical commitments that undergird our professional development endeavors within the Partnership, share examples of participants’ work (instructional materials revisions, reflective journals, etc.), and describe future research connected to the project.January 21st, 2005: Taryn Melkus Bayles (UMBC), STEM Teacher Education: Increasing Awareness and Interest in Engineering for K-12 Students
The University of Maryland Baltimore County (UMBC) College of Engineering (COE) has set in motion a series of initiatives which provide STEM Teacher Education aimed at increasing both the awareness of and interest in engineering for K-12 students. The first initiative was the development and delivery of an Introduction to Engineering Workshop for High School STEM Teachers and Counselors three-day summer workshop with the ultimate aim of helping teachers and counselors increase engineering awareness and encourage & prepare students for careers in engineering. This workshop has led to several NSF grants which incorporate teacher training, which include, Introduction of Engineering through Mathematics, STEM Talent Expansion Program and Engineering Inquiry-Based Learning Modules for Technology Education, which is a NSF funded Instructional Materials Development project which will enhance and develop the thinking-skills and problem-solving abilities of secondary students by developing new curricula that incorporate hands-on experiences with “real world” engineering design and decision making exercises. The new curricula will specifically target the requirements of the Maryland Technology Education Content Standards which are in alignment to the ITEA (International Technology Education Association) Standards for Technological Literacy as well as state standards in science, mathematics, reading and social studies. Other STEM teacher education initiatives include Hands on Science Outreach, Project Lead the Way, Computer Mania Day, and the Urban Teacher Education program, which has led to UMBC’s SUPER STEM Education program. Details of these initiatives will be presented.
January 14th, 2005: Laura J. Moin, Where Can We Find and How to Recruit Future K-12 Science & Math Teachers? A Search by Academic Year, Discipline, Academic Performance Level, and Experience
In the U.S., there is a serious shortage of qualified math and science teachers. For example, in 2000, 61% of high schools and 48% of middle schools experienced difficulty filling these vacancies. This shortage perpetuates a vicious cycle: poor K-12 preparation causes a decline in scientific literacy, further increases socio-economic stratification, and ultimately threatens our nation’s global positioning. Teacher recruitment programs typically incorporate some type of early teaching experience (i.e. public classroom exposure or one-on-one tutoring) given the beliefs that K-12 teaching interest drops throughout the college years and that any teaching experience, most particularly experiences at the K-12 level, would encourage recruits to pursue teaching careers. In addition, a sadly infamous notion perpetuates the idea that low performing science, engineering, and math (SEM) majors resort to K-12 teaching. Until recently, these views have remained unquestioned due to the absence of empirical data supporting or disqualifying them. In my talk, I present surprising data from two universities suggesting that these assumptions and beliefs about teaching career interest are wrong and explore reasons for why they are wrong. These results will aid policymakers, math and science teacher recruiters, and teacher educators in making most effective use of this traditional undergraduate candidate pool and in designing more effective K-12 science and math teacher recruitment programs.
December 3rd, 2004: Sam Donovan, Tree Thinking: Understanding Biological Phenomena through Descent with Modification
Many generalizations in biology involve invoking an evolutionary explanatory framework. Explaining biological phenomena from an evolutionary perspective is difficult for students and generally resistant to instructional interventions. Biology education has focused on model based explanations to the point that the historical relationships between species (patterns of descent with modification) are often overlooked as a powerful explanatory context. Thus, there currently exists a significant discrepancy between the ways that biologists' reason about patterns in nature and the conceptual tools that most students are exposed to in biology courses. This presentation will provide an overview of a new research program aimed at exploring the disciplinary characteristics of tree thinking and how students' understanding in this area develops. The research involves analyses of the ways that experts use phylogenetic relationships as
organizational, communication and analytic tools, and investigations into students' intuitive notions of species and the relationships between species. Preliminary results from studies of students' representations of biological diversity, interpretations of tree figures, and decoding of
information in text figures will be presented and discussed.October 22, 2004: Chris Schunn, Reciprocal Evaluation for Learning Science Writing
An interesting note about the discovery vs. direction instruction debate in science education is that it neglects another potentially powerful way of learning science content and process: reciprocal evaluation. Many science class activities, regardless of level, are done in a dyad or other group setting, just as scientific research is typically done in a collaborative setting. The group setting permits for some division of labor, which is very helpful, if not crucial in science. But it also makes for another learning opportunity. We know that reciprocal teaching can produce strong learning for the teacher (e.g., Brown & Palinscar, 1989). But we know much less about the validity of feedback from a peer, and its impact on the recipient of peer feedback. There are certainly many obvious reasons to suspect the quality of feedback from peers.
One of the domains in which reciprocal evaluation can play an important role is learning how to write about science, which is itself an important skill to develop through science education. In my talk, I will present some evaluations of the SWoRD (Scaffolded Writing and Rewriting in the Discipline) system (Cho & Schunn, 2003), which uses reciprocal evaluation to make possible writing assignments in large lecture science content courses. A variety of methods are used by the system to increase the accountability of students to the evaluation and feedback process, as well as to increase the validity of grades generated through this reciprocal evaluation process. I will argue that the general approach does produce valid and reliable feedback, and, more surprisingly, the feedback that students receive is more useful than the feedback that they would get from the instructor. I will also discuss some data on student perceptions of the reciprocal evaluation.
September 10, 2004: Agnieszka Kosminska Kristensen, Learning a science concept collaboratively in a multimedia learning environment
This study investigated how pairs of students’ collaborated to learn about a complex science concept (The action potential) from computer-based multimedia educational program. The goal of this research was to examine the impact of collaboration in the multimedia learning environment and the influence of multiple (external) representations’ on individual students’ learning.
The results of this study suggest that students’ collaborative interaction with the program seems to encourage dialog about the domain with the program as a reference.
The analyses of the effect of the multiple (external) representations’ on students’ learning suggests that presenting different representations simultaneously, each communicating unique information about a different aspect of the concept, facilitates deep understanding and learning of the science concepts.
June 25, 2004: Junlei Li & David Klahr, To Align or Not to Align? -- A Case Study of "Mile-wide, Inch-Deep" Science Education rooted in Standards and Assessments
Our goal in this talk is twofold: (a) to present a partial report on the first 9 months of our Lesson Planning Project, (first described in our Supergroup presentation last Fall), and (b) to facilitate a broader range
discussion about aligning the middle school science curriculum (and perhaps, research in science education) with standards and assessments. One of the first steps in our approach to lesson planning was to combine a task analysis of the goals of science education -- the standards -- with the outcome measures adopted by a local district -- annual standardized testing, and attempt to align them in terms of optimal instructional content. We describe how these constraints present a nearly impossible task for under-equipped and under-trained science teachers that results in an (almost) inevitably broad, but shallow, curriculum.In order to start a constructive discussion about possible solutions to this fundamental problem, our presentation will compare the rationales and approaches behind two such attempts: one adopted by the Allegheny Intermediate Unit, and the other adopted by our project team of researchers and teachers (Lesson Planning Project).
We seek input on the broader question of researcher's, teacher's, administrator's, and policy-maker's responsibilities within these real world constraints.
April 30, 2004: Yaron Doppelt and Matthew M. Mehalik, Enhancing Science Education in Eighth Grade Using a Design-Based Immersion
Design-based learning engages students in ways that enhance their abilities to solve real-life problems and to reflect on their learning processes. This style of active learning enables students to relate such problems to science concepts. Even though national and state science standards specify requirements for curriculum in middle schools to address these goals, the current learning environment has room for considerable improvement in these areas.
The presenters will provide an overview of their research project involving the development and implementation of a new electronics module with 900 eighth-grade science students in 39 classes in a local public school district. The module is intended to engage students in active learning concepts, design activities, systems thinking methods, and portfolio assessment. The project enables students to design, construct, document and reflect on their experience during a design process of an electrical alarm system. The module integrates several system thinking concepts, such as: thinking of needs and purposes, generating alternative solutions, making choices, and reflecting. Students engage in tasks similar to the ways engineers practice design and analyze systems.
The researchers have integrated their individual previous research experiences in project-based learning, systems engineering, and design for creating a student module, a teacher’s guide, a series of workshops, observation tools, a knowledge test, a learning environment questionnaire and portfolio assessment scaffolding.
The researchers will present in this talk preliminary findings, such as: teacher strategies for implementing this module, various classroom atmospheres, and results from a pilot school, such as student portfolio assessments. The presenters will report on several dimensions of the development and implementation of this module, addressing such questions in the context of design-based learning, such as:
What are some characteristics of design-based learning?
How do the learning environment characteristics in design-based learning differ from inquiry-based learning?
What are some benefits of reflecting on teachers’ experiences in implementing design-based learning as a way of impacting their professional development?
How do high achievers and low achievers perform in a design-based learning environment?
Our initial findings are that design-based learning enhances the performance of all students, especially low achievers and that the interaction and collaboration among teachers and researchers has improved the module, teacher practice, and development.
March 19, 2004: Takeshi Okada, Creativity by Copying: How Examples Inspire Innovation
The goal of this study was to investigate whether an experience copying others' drawings facilitated subjects' artistic creativity. Thirty undergraduates participated individually in a three-day-drawing experiment. They were randomly assigned into three groups. In the Experimental Group subjects copied two abstract drawings and then drew their own original work. In the Reproduction Group subjects copied the same two abstract drawings and then drew another picture in the artist's style. In the Control Group subjects did not do any copying but continued to draw their own original drawings. Based on ratings by two modern artists, findings suggested that post-test drawings by subjects in the Experimental Group were rated more creative than the drawings of subjects in the Control Group. In addition, the styles of drawings by subjects in the Experimental Group were quite different from those of subjects in the Reproduction Group. We suggest that copying actually facilitated the creation of new styles of drawing. Two further analyses revealed how subjects who had copied others' drawings could produce creative drawings. First, subjects were initially constrained by a belief that they should draw things realistically. Then, they relaxed this constraint by means of copying abstract pictures. Second, according to protocols of the copying process, copying forced subjects to explore their original expression through comparison with other artworks.
February 27, 2004: Jim Greeno, Cognition and Learning in Activity: Progress Toward a (More) Coherent Theory of Understanding, Thinking, and Learning Considered as Aspects of InteractionLearning and cognition can be analyzed as aspects of activity systems, where people interact with each other and with the material and informational systems in their environments. The goal is to represent and explain
processes by which such systems accomplish understanding, reasoning, problem solving, conceptual learning, etc. Analyses are needed at multiple levels; I propose three: elementary operations, tasks, and development. I will review findings that illustrate progress at each of these levels, including some recent results and preliminary findings of current research.January 23, 2004: BaoHui Zhang, Exploring Middle School Science Students‚ Computer-based Modeling Practices and Their Changes Over Time
A model is a simplified representation of a system that concentrates attention on specific aspects of the system such as more complicated ideas, objects, events, or processes. Constructing, testing, and evaluating models is central to scientists‚ daily practices (Clement, 2000; Latour, 1987; Penner, 2001). Computer-based modeling software with scaffolds has made modeling accessible to young students over the past two decades (e.g. Jackson, Stratford, Krajcik, & Soloway, 1994; Mandinach, 1989). However, few studies have described the modeling practices of middle school science students and how they change over time. Modeling practices reflect the reasoning processes, such as planning and synthesizing, of a series of
actions and conversations that help modelers to complete modeling tasks, make sense of what they are doing, and communicate their ideas with others.This study, conducted at an independent school, follows a design-based research approach. Seventh graders from three classes taught by two experienced teachers participated. Two pairs of target students were chosen from each class for observation. Students created computer-based models after their investigations in a water quality unit and a decomposition unit. The initial modeling cycle for water quality lasted for four days in the fall season, the second cycle for water quality lasted three days in the following winter season, and the third cycle for decomposition lasted two days in the spring season. The major data source is video that captured student pairs‚ computer screen activities and their conversation. The data were analyzed in terms of the efficiency, meaningfulness, and purposefulness of students‚ modeling practices.
Results indicate that with appropriate scaffolding from the modeling program and the teachers, students performed a variety of valuable modeling practices such as planning, analyzing, synthesizing, evaluating, and publicizing. In general, student modeling practices became more efficient, meaningful, and purposeful over time.
December 12, 2003: Jorge Larreamendy-Joerns, Understanding and Question Asking in Evolutionary Biology: An Expert-Novice Comparison
Asking questions is a cognitive and discursive activity of paramount importance for learning and understanding. Extant models of question-asking in the context of reading (Otero & Graesser, 2001; Ram, 1991, 1994) suggest that questions are posed when expectations are violated or inconsistencies arise (knowledge clash hypothesis), when knowledge gaps are detected (knowledge deficit hypothesis), and when explanations are sought. Consistently, questions have been categorized according to the processing level where clashes and deficits occur (e.g., word-level, sentence-level, text-base, situation model). Despite the level of specification of existing models, little attention has been devoted to the content of questions, seemingly under the assumption that content is contingent and variable, while the structural location and cognitive function of questions are more general and therefore more subject to formalization. Yet, strong regularities can be found within content domains. Disciplines are often structured around typical queries and core explanatory patterns. As a result disciplines may offer clues to readers about the kinds of questions that are worth asking and the explanations that are worth pursuing.
In this presentation, I report on a study that adds to the existing literature by investigating question-asking in the context of a disciplinary domain with an eye to exploring how questions are affected by expertise levels. The domain (evolutionary biology) is highly patterned in terms of explanatory goals and question types. Four groups of participants (N = 66) with varying degrees of expertise in evolutionary biology (lay, novices, quasi-experts and experts) were asked to read scientific texts adapted from authentic sources, think aloud during reading and verbalize questions. Verbal protocols were analyzed to identify major cognitive activities during reading (question-asking, hypothesizing, analogy-making, instantiating and meta-comments) and questions were further classified into domain-sensitive categories. Results indicate that the increasing specificity of questions is associated with increasing levels of expertise. Quasi-experts and experts tended to ask questions aligned with critical components of explanatory schemas and to search for essential information instead of venturing hypotheses. Results suggest that question posing is an attempt to bridge knowledge gaps and constitutes a hallmark of expertise.
November 7, 2003: Junlei Li & David Klahr (CMU), From Cognitive Models of Reasoning to Lesson Planning for Inquiry
In the spirit of using the Supergroup as a forum for describing new projects as well as final reports, we are using this presentation to gather constructive feedback for a newly-funded three-year project aimed at improving science teachers’ lesson planning skills and procedures. The project is sponsored by the Cognition and Student Learning Grant from the U.S. Department of Education. The research is situated in the four urban middle schools operated by the Pittsburgh Catholic Diocese.
Science Education Standards defines what broad topics students should know and by when. Standardized Achievement Testing defines when learning is considered “good enough”. In an ideal state, a teacher’s lesson planning bridges these two ends. But how can teachers teach each concept deeply when they have so many topics to cover? How can they teach critical thinking when the accountability tests emphasize the basic recall of content? As cognitive researchers, we are also interested in whether targeting children’s higher-order thinking skills is feasible within the classroom and compatible with standardized testing.
Our project adopts a three-phase design experiment, maximally immersing the researchers into real urban classrooms. The project progression is as follows:
Phase I
To understand the needs of the classrooms and the crafts of the teachers, the researchers follow 7 urban school science teachers in their classrooms for one week at a time. The researchers also analyze various education standards and standardized achievement tests to assess the broader demand on schools and teachers.
Phase II
To develop a practical lesson planning method, the researchers actually plan and teach the science lessons themselves in these classrooms for up to one month at a time. The researchers do not dictate the lesson topics, but rather, pull the topics from what the teachers have to teach. This also
provides a first-person opportunity for the researchers to be helped by and to help each individual teacher.
Phase III
To help the teachers integrate the lesson planning methods, the researchers will model and coach the methods in classrooms bit by bit over an extended period of “researcher to teacher” and “teacher to teacher” collaboration.October 10, 2003: Ryan Shaun Baker, Albert Corbett, Kenneth Koedinger , Remediating Resilient Overgeneralization in Data Representation
Representing information in an appropriate form is essential to being able to analyze it. We have discovered that students learning new ways to represent data tend to inappropriately transfer knowledge of familiar bar graphs when creating histograms and scatterplots. For example, when asked to draw a scatterplot to show how the price of a brand of peanut butter relates to its quality, students tend to place a categorical variable, the name of the brand, on the X axis rather than the appropriate quantitative variable (price). This negative transfer is resilient both to simple scaffolding (such as labeling the variables the student should use directly on the graph), and to direct instruction and practice creating scatterplots.
We present a set of computational models in ACT-R which suggest that these students fail to distinguish what types of information are used in different representations of data. We use these ACT-R models to inform the design of a new cognitive tutor lesson for this domain. In this new lesson, we repeatedly require the students to distinguish between what types of information can be used in bar graphs and scatterplots when choosing what information to place in their graph. We are in the middle of a study of the impact of using this lesson with approximately half of the data back, the preliminary results seem to indicate that this intervention substantially reduces the frequency of this type of error.
June 13, 2003: John J. Clement, Imagistic Simulation During Scientific Model Construction
In this talk I will look at two case studies, one from an expert and one from a student. Both subjects give evidence for generating new models for understanding different science phenomena during their video taped protocols. I will use data on spontaneous imagery reports, depictive hand motions, and other observations to generate hypotheses concerning: (1) the relationship between “runnable” schemas and imagery during mental simulation; and (2) how assembling a scientific model from simpler runnable schemas can “transfer imagery and runnability” to the model. One source of support for the last hypothesis comes from observing similar depictive hand motions as a subject thought about an analogue or source case and also when he or she thought about the developing target model. By the end of their learning episodes both the expert and the student appear to have a runnable model where the runnability has been transferred or “inherited” from one or more runnable source schemas.
May 9, 2003: Larry G. Richards, The Virginia Middle School Engineering Education Initiative: Teaching Engineering in the Middle Schools
At the University of Virginia, we have undertaken a major project to design, implement, test, and distribute Engineering Teaching Kits (ETKs) for use in middle school science and math courses. Each ETK will emphasize the engineering design approach to problem solving. A new senior design course sequence for fourth year Mechanical Engineers allowed 37 undergraduate students to participate in this project. Six ETKs are under development: submersible vehicles, gels and brain perfusion, simple machines, solar car design, design for sustainability, and engineering materials. Two graduate students from the Curry School of Education worked with the teams to develop lesson plans and assessment procedures. In this paper, we will review our approach to developing ETKs, briefly describe each of the ETKs, and assess the efficacy of a senior design course for developing instructional materials for middle schools. Two ETKs will be featured in this talk: Under Pressure - the submersible vehicle project and Ra Power the solar car team.
Mar 28, 2003: Clark Chinn, Authentic Scientific Reasoning in the Classroom
In several recent papers, I have argued that many of the scientific inquiry tasks developed for use in science instruction differ in important ways from authentic scientific inquiry. Many inquiry tasks used in schools require reasoning processes that are qualitatively different from the processes employed in real scientific reasoning. Moreover, school inquiry tasks appear to be based on an epistemology that differs from the epistemology of authentic science. This suggests that there is a need to develop school inquiry tasks that come closer to authentic scientific inquiry. However, given that science students have difficulty even with simple inquiry tasks, is it really feasible to use more complex, more authentic tasks in science classes?
In this talk, I will present an overview of a series of studies in which I have endeavored to engage middle school students in scientific inquiry that is as authentic as possible and yet is still within their cognitive capabilities. I will provide examples of how students have performed in these studies, and I will discuss some of the obstacles to successful classroom implementation. Then I will discuss one of these studies in more detail. The study examines how students reason about highly uncertain observational evidence. Eighth graders and undergraduates worked in dyads with more than 30 images of a fictional planet. The images were conceptually based on drawings of Mars made by Martian astronomers in the late 1800s. Like the Martian astronomers, the students were faced with widely divergent images that presented starkly different interpretations of the planet, and it was extremely challenging to work out which planetary features were “real” and which were not. Dyads differed greatly in the heuristics they used as they attempted to resolve the conflicts among the planetary images.Mar 14, 2003: John Opfer, The Meaning of Life: How Children Identify Living Kinds
A model case of categorization and conceptual change is the inclusion of plants and animals in the single, superordinate category living things. The protracted development of this category raises several interesting questions. Why do children so readily learn that animals are living things, yet take so much longer to learn that plants are? Must children change their mind about the meaning of "life", or do they need to learn something subtle about plants? In this talk, I explore the hypothesis that children's theory of life is centered on the property of goal-directed action and that children's categorization of entities as living things--whether animal, plant, or microorganism--is chiefly made on this basis. The protracted development of the living things category, I argue, does not stem from any difficulty in learning to categorize plants as living things, but from their difficulty in categorizing plants as goal-directed agents.
Feb 28, 2003: Randi Engle, Categorization of Emergent Processes by Students with Different Types of Expertise: Is There Something Special About Being a Double Major in Science?
In this talk, I'm going to report about some intriguing, but very preliminary, results from a project I've been doing with Micki Chi. The project focuses on Micki's theory for why some scientific "misconceptions" are particularly persistent. In a nutshell, Micki's theory claims that many difficult-to-understand science concepts are instances of "emergent processes." Students' misconceptions occur in part because they do not recognize which concepts are such emergent processes, instead miscategorizing them as commonsense causal processes. To more directly see whether the problem involves such a miscategorization, I conducted a novice-expert study (modeled on Chi, Feltovich & Glaser, 1981) in which students sorted emergent and non-emergent processes drawn from 3 scientific disciplines: biology, chemistry, and physics. So far, we have found that: (1) the degree to which students kept emergent and non-emergent processes separate in their free sorts was correlated with their explicit references to features of an emergent processes schema; and (2) most interestingly, undergraduates pursuing double majors in science showed better understanding of the emergent schema on both of these measures than either doctoral students or single majors studying science. I am especially interested in following up on this last result. Is the multidisciplinary nature of students' background responsible for the findings, or is it just that the students we tested were particularly gung-ho about science? We're looking forward to your comments and suggestions.
Feb 7, 2003: Gary Benenson, Understanding How Students Learn Core Concepts of Technology
This paper argues for research into how students learn the basic concepts of technology. The ideas in this paper arose from the experiences of the City Technology project, which are described briefly at the outset. There is an outline of some of the key concepts of technology, followed by some comparisons between technology and science education. The main body of the paper cites examples from City Technology showing how some of these basic ideas of technology arise in the classroom. All of the evidence cited is anecdotal. The concluding section makes a case for a systematic research program to explore how these concepts can be learned and taught.
Dec 6, 2002: Amy Masnick, Children's Reasoning About Error and Data Variability
In formal scientific reasoning contexts, anomalies and inconsistencies in data are often referred to as error. In elementary school science classes, children typically carry out simple science experiments and are asked to reason about them. In these settings, there is usually little discussion of error, and the experiments are expected to return a pre-specified set of results. However, even in these constrained contexts, there is often variation in the data, due to a range of factors at each stage of the experiment. I will present data from a series of studies examining elementary school students' reasoning about anomalies in science experiments and data.
Nov 22, 2002: David Klahr, Paths of Learning and their consequences: Discovery Learning versus Direct Instruction in elementary school science teaching
The widespread belief that discovery learning is superior to direct instruction in early science education warrants careful empirical assessment. In a study with 112 third and fourth grade children, we measured the relative effectiveness of these two instructional approaches at two points in the learning process (a) during the initial acquisition of the basic cognitive objective: the design of simple, unconfounded experiments, and (b) during the subsequent transfer and application of this domain-general process skill to more diffuse and authentic reasoning associated with the evaluation of science fair posters. Our analysis revealed not only that many more children learned from direct instruction than from discovery learning, but also that when asked to make broader, richer scientific judgments the (many) children who learned about experimental design from direct instruction performed as well as those (few) children who discovered the method on their own. These results challenge predictions derived from the presumed superiority of discovery approaches for deeper, longer lasting, and “more authentic” understanding of scientific reasoning processes, and suggest instead, a more nuanced examination of the most effective mixes and the most suitable matches between topic and pedagogy.
Note: please arrive early: in order to safeguard the speaker, security personnel will be checking for dangerous materials (tomatoes, eggs) that may be concealed by pro-discovery learning attendees.Nov 1, 2002: Ellice Forman, Learning to Explain in a Third Grade Classroom
As investigators have begun to study mathematics classrooms in which communication is a central priority, an important teaching dilemma has emerged (Lampert, 1985; Lampert et al. 1996). Teachers of communication-rich elementary school classrooms may be faced with a problem enforcing norms that value students' attempts to use and explain strategies that are meaningful to them and norms that value some strategies over others due to their reliance upon more sophisticated mathematical concepts (Franke & Carey, 1997; O'Connor, 2001). For example, should students who employ more mathematically concise strategies be encouraged to criticize the more cumbersome strategies of their classmates? My presentation will illustrate this teaching dilemma and its resolution through an analysis of student work and class discussion that occurred in one third-grade classroom during a two-part lesson.
In addition, we decided to use Hilton's (1990) work in discursive psychology to inform our understanding of classroom communication. Hilton proposed that causal explanations, being part of a conversation, must be interpreted as specific answers to questions posed by listeners to speakers in a given social context: "The verb to explain is a three-place predicate: Someone explains something to someone" (1990, p. 65). Thus, we were interested in investigating whether the teacher's and her students' justifications for their mathematical strategies showed evidence of Hilton's three part conversational model for explanations: speaker (or author); audience; written or spoken products.
I selected Mrs. Porter's third-grade classroom as the site of an ethnographic study because she made oral and written mathematical communication a priority. Our research team observed and recorded mathematics lessons in this classroom twice a week from early September until the middle of December 1998. I chose a two-part lesson for analysis in this presentation because Mrs. Porter designed the task and its instructional context in order to address the teaching dilemma mentioned above. This task, which we call strategy choice, required students to evaluate the strategies used by unknown peers (the work of some of Mrs. Porter's former students).
Our first set of findings came from the initial lesson during which the students chose which strategy or strategies they preferred and explained their reasons in writing. Those reasons fell into two categories: easy to understand or efficient. Next, we examined a whole class discussion of the strategy choices. In this analysis, we highlighted the degree to which each student expressed his or her sensitivity to the likely characteristics of the unknown authors and audiences as well as to the attributes of the written strategies. In my talk I will present the findings of our discourse analysis and a framework for understanding "what counts" as an adequate explanation in this classroom community.
Oct 18, 2002: Jennifer Cartier, Looking to Scientific Practice to Inform Instructional Strategies: What Understandings Develop?
Educators have come to agree that understanding in science includes familiarity with conceptual material ("content") and insight into how knowledge is created through inquiry. Recent reform initiatives such as Project 2061/Benchmarks (AAAS, 1993) and the National Science Education Standards (NRC, 1996) attest to the emphasis on both experiencing and understanding inquiry in science. There remains, however, significant controversy about what inquiry-based science education should look like and to what extent it can—or even should—reflect actual scientific practice.
In this Friday’s presentation, I will first discuss a “practice framework” (developed by the MUSE collaborative at UW-Madison) that is based largely on recent work in science studies and reflects cognitive goals and methodologies of practicing scientists. The framework has been the basis for curriculum development and instruction in biology and physical/Earth science within high schools near Madison, WI and inner-city Washington D.C. I will summarize research on student achievement in one of the MUSE units: Earth-Moon-Sun astronomy.
In the second part of the talk, I will address the issue of how to take what we’ve learned about developing student understanding in MUSE classrooms and apply it to teacher professional development. In particular, I will describe a new research project, funded by NSF, in which I plan to work with PPS elementary teachers to develop and implement instructional strategies (and materials where necessary) for effectively using kit-based science materials to engage students in realistic inquiry.It is undeniable that national and statewide reform initiatives, bolstered by renewed emphasis on high stakes testing, are putting pressure on teachers to adopt inquiry-based instructional techniques. Unfortunately, utilizing inquiry-based curriculum materials and providing hands-on learning experiences in classrooms (i.e. "doing the kits") are not enough to enable students to "engage in … the same activities and thinking processes [italics added] as scientists who are seeking to expand human knowledge of the natural world" (NRC, 2000, p. 1). To accomplish this tall task, teachers will need support in developing greater understanding about the nature of scientific inquiry and ways of implementing inquiry instruction into their classrooms. The proposed study will examine how specific professional development opportunities enable teachers to adopt more inquiry-based practices, and, of at least equal importance, what students' achieve as a result of the implementation of appropriate inquiry pedagogy in elementary school classrooms.
Sept 27, 2002: Kevin Crowley, Signage to Seed Science Talk in Pittsburgh's Public Places
I will describe a new line of work where we are installing science-oriented signage in public locations around Pittsburgh. The idea of the signage is to seed everyday conversations about science in places where broad cross-sections of the city converge. I will describe work done at Kennywood the last two summers, including learning outcomes from our first full installation (The Phantom's Revenge) and our in-progress work on the LogJammer. I will describe our first installation for a public park (Anderson Playground in Schenley Park). With three years of new funding from NSF, this collaborative venture between LRDC, Family Communications, and Carnegie Mellon is now in the planning stages for further installations and research. I will close the talk by outline our plans for future work and looking to you all for criticism, feedback, and advice.
Sept 13, 2002: Christian Schunn, Project Kickoff: The long-term impact of a model-based curriculum on scientific reasoning in middle schoolers
A core component of scientific reasoning is the ability to reason with various abstractions of the world, which can be collectively called models. They include physical large and small scale reproductions, tables, graphs, computer simulations, and equations. There has been considerable design-experiment based research showing that science curricula centered on models appears to be effective. However, many open questions remain. How do models affect learning? What is the long-term impact of a model-based curriculum on understanding of scientific process and science content? Do the different forms of models differential support scientific reasoning and learning? I will describe a project using the MARS middle school science curriculum that was designed to answer these questions through a longitudinal study of 1000 middle school students.
July 12, 2002: Brad Morris, Rethinking logical reasoning skills from a strategy perspective
We propose a conceptual framework for explaining logical reasoning in terms of competing strategies. Contrary to previous theories in which a single method is applied to all classes of logical reasoning problems, we suggest that multiple strategies are available to apply to various classes of logical reasoning problems. Each strategy has unique processing demands and each class of problem has unique task demands. A strategy is more likely to be used when its processing demands match a problem's task demands. However, several different strategies are likely to be used, at least on occasion, for every type of logical reasoning problem. The Logical Strategy Model (LSM) specifies how each strategy may be distinguished theoretically and empirically.
March 15, 2002: Amy Masnick, Reasoning from Data: The Effect of Sample Size and Variability on Children's and Adults' Conclusions
Interpretation of data is a critical part of scientific experimentation because it involves applying one?s background theoretical knowledge to the characteristics of data to draw conclusions. Though many researchers have examined the impact of background knowledge on making conclusions, few have considered what characteristics of the data itself children use in this task. In this study, 3rd graders, 6th graders, and college undergraduates were presented with a series of datasets that varied in sample size, consistency in data pairs and variability relative to the mean. At all ages, participants showed sensitivity to overlapping data points in comparative datasets, but there were age differences in the influence of sample size, the confidence in conclusions drawn from the data, and the justifications for these conclusions. These datasets were presented in a fairly abstract context, and I will discuss plans for further studies using richer contexts that may affect how children attend to features of the data.
Feb 22, 2002: David Klahr, Some new evidence on understanding evidence: can preschoolers distinguish determinate from indeterminate evidence?
The ability to distinguish between determinacy and indeterminacy is essential in many domains, including causal reasoning, decision-making, and scientific discovery. The topic has been investigated with different emphases, methods and rubrics, including "possibility or necessity," "possibility or impossibility," "certainty or uncertainty," "sufficiency or insufficiency," and "knowing or guessing". Not surprisingly, a consistent picture of its developmental course has yet to emerge. Alas, the evidence on indeterminacy is indeterminate.
One reason for this lack of resolution comes from the relatively large grain size at which the process of evidence interpretation has been studied. That is, most investigators have taken a binary view of indeterminate versus determinate situations, rather than a nuanced approach that is sensitive to particular kinds of indeterminate evidence patterns. Fay and Klahr‚s (1996) analysis of responses to different types of evidence patterns revealed substantial differences in preschoolers‚ ability to correctly interpret different patterns of indeterminate evidence. Although children did quite well on many forms of indeterminate evidence, there was one type of indeterminate evidence that they usually interpreted (erroneously) as determinate. Fay and Klahr called children‚s reasoning approach to such patterns the "positive capture" strategy because a single positive instance seemed to capture children‚s attention and, in effect, blind them to the fact that unexplored evidence actually rendered the problem indeterminate.
In the present experiments, Zhe Chen and I decided to investigate how deeply entrenched the positive capture strategy is. There are two commonly used methods of exploring the robustness of children‚s failures to exhibit adult levels of performance on various tasks. One approach is to recast formal, abstract problems in everyday, "pragmatic" contexts by introducing familiar content. Such studies have revealed the powerful role of pragmatic context in children‚s inductive reasoning. The other common approach is to provide children with extensive experience and/or direct instruction in the domain, and then to measure the rate and extent of knowledge acquisition and retention.In this talk, I will describe a pair of experiments with 4- and 5-year old children that used each of these approaches. In Experiment 1 we examined whether and how children‚s performance could be improved by presenting tasks in a richer and more socially meaningful context, and in Experiment 2 we provided extensive problem-solving experience and explicit feedback to facilitate learning. What do you think we found?
Feb 8, 2002: Kurt Van Lehn, Physics tutoring systems: The big picture
Mechanics, and Newton's law in particular, is a favorite task domain in Cognitive Science, with hundreds of papers to its credit. What have we learned? How can those findings be translated into effective tutoring systems? This talk will attempt to sketch a "big picture" of physics cognition. It will cover the major types of knowledge that have been proposed to underlie phyiscs, the major methods for assessing physicis expertise and which assessments tap which types of knowledge. It will briefly sketch the two major theories of physics learning, then totally ignore one of them. Based on the other one, methods for teaching each type of knowledge are presented, along with several tutoring systems that are being developed here for assisting learners. Evaluations of the systems will be presented if time permits.
Jan 30, 2002: Micki Chi, "Causal" and "Emergent" Explanatory Mechanisms: Overcoming misunderstandings in science
Numerous science and everyday concepts of processes that middle and high school students encounter in their curriculum (such as electricity, heat flow, natural selection) are particularly troublesome for them to learn with deep understanding. They have pre- or alternative conceptions that are naive, intuitive, and scientifically incorrect. Having these alternative conceptions seems to make it much more difficult for students to learn the scientifically correct ones. This paper provides a conceptual analysis that explains this difficulty in learning. The analysis essentially suggests that students misrepresent these processes as a kind of causal, rather than emergent event. Several features of causal and emergent processes are identified, and these features constitute a preliminary specification of the mechanisms underlying emergent and causal processes. Concepts of processes are often misunderstood because students attribute a "causal" explanatory mechanism to the relationship between the behavior at the micro (or individual or molecular) level, and the behavior at the macro level. Reasons for why students commit such misattribution will also be discussed. The implication of this analysis is that teaching students how to recognize an "emergent" process from a "causal" process will help them improve their understanding.
Dec 14, 2001: Gaea Leinhardt, Beyond Evaluation: Exploring the Effects of Web Based InstructionIn this presentation I will review the program of research that has been conducted to date surrounding a college level course, "Causal Reasoning Online" designed by Richard Scheines. The point of the talk is to show how one can start with somewhat trivial (in the scientific sense) questions of efficacy and cost effectiveness and move towards more complex and compelling sets of studies in the context of exploring University level instructional reform. One context that frames the set of studies is a talk given by Herb Simon titled, "Need Teaching Be a Loner Sport?" In this talk Simon argued that in order for teaching to become a focus of intellectual activity for the teacher it had to become worthy of being at the center of intellectual, social, and collaborative activity. At a second layer of interpretation I will try to show how the specific processes used in the design, evaluation, and research surrounding Causal Reasoning Online produced just such a collaboration and intellectual engagement. Finally, I will describe how the effort is being expanded to five other educational improvement efforts guided by the leadership of Joel Smith.
Nov 16, 2001: Logically Speaking:Adult and child production of logical connectives in natural language
Scientific reasoning involves a large amount of logical reasoning (inductive, deductive, abductive). Thus, a core question for the development of scientific reasoning ability is the issue of how logical reasoning develops. I will present a cross-sectional study that examines the relationship between parent and child production levels of the logical connectives AND, OR, NO, & NOT. The results of this study demonstrate that what children hear and produce differs between connectives, within connectives (pragmatic usage), and between ages. These data suggest that the statistical structure of the language environment has a large influence on the development of basic logical reasoning skills.
Nov 9, 2001: Kalyani Raghavan, Impact of Model-Centered Instruction on Student Learning
The Model Assisted Reasoning in Science (MARS) project seeks to promote model-centered instruction as a means of improving middle-school science education. The sixth-grade curriculum was field-tested in several sites during the 1999-2000 and 2000-2001 school years. Evaluation included three major components: paper-and-pencil tests of scientific reasoning administered to all MARS students before and after instruction; written concept tests administered to all MARS students after instruction; and blind performance interviews conducted with a small group of MARS students after instruction. To compare performance of students receiving MARS instruction with that of students receiving alternate science instruction, the interviews were conducted with a sample of non-MARS students at the same school. The concept test and the reasoning pre- and post-tests were also administered to non-MARS students at selected field-test schools. Results indicate that MARS instruction has a positive impact on student learning of fundamental science concepts and reasoning skills. These results will be presented along with evidence that this positive impact is at least partly due to model assisted reasoning.
Oct 12, 2001: Jennifer Slawinski Blessing, The ability of children and adults to predict and explain another's wrong reasoning
The research on children's ability to understand the mental states of themselves and others was extended to examine how well children understand a developmental misconception held by other children. Kindergartners and first graders and adults were asked to predict and explain the reasoning of a child who applied this misconception on a scientific problem-solving task (physical rules of gravity). In addition, participants did the same on a preference task used to control for the ability to draw inferences based on behavioral evidence and to use those inferences to make predictions. Adults and children in both grades were quite skillful at predicting and explaining a child's performance on a preference-based control task. Both kindergartners and first graders were comparably less successful at predicting and explaining the child's scientific misconception, particularly in comparison to adults. Children were able to predict the errors made by the target child on only about half of the trials and could explain their correct predictions in terms of the specific misconception only 8% of the time. Previous research has shown that 5- to 8-year-old children understand that others may hold false beliefs about arbitrary and momentary states of reality. The findings of the present study, however, reveal that children are less successful when asked to predict and explain reasoning based on a fundamental misconception of the world.
Sept 28, 2001: Kevin Crowley, Just in time explanatory support from Power Girl
How do features of the museum learning environment support spontaneous family conversations about science? In previous work I have described the role of parent "explanatoids" in everyday family activity and have discovered that, in at least some settings, boys appear to hear more explanatoids than girls. Focusing on a set of five electricity exhibits at the San Jose Children's Discovery Museum, we have completed a new design experiment to test exhibit enhancement strategies that influence parents' perceptions of whether exhibits were interesting to and appropriate for girls. The resulting set of modifications revolve around "Power Girl", a Latina character who is portrayed as a tinkerer, inventor, and co-explorer of the set of exhibits. Video-taped observations of a few thousand family interactions were collected while exhibits were in base-line state, modified with just the image of Power Girl, and modified with the image plus a sign that posed open-ended questions to visiting families.
The data set has been coded and analyses are now under way. Preliminary findings show a replication of the basic gender difference in parent explanation when exhibits were in the baseline state: Parents were about twice as likely to explain to boys than to girls. When the linking graphic of Power Girl was added to the exhibits, the level of parent explanations to girls rose to about the same level as boys, who saw no decrease in parent explanations from baseline. However, in Phase 3, when open-ended questions were added in addition to the linking graphic, we found a surprising decrease in parent explanation to girls. My working hypothesis is that the open-ended question strategy supported by the Phase 3 signs competed with the strategy parents might spontaneously adopt, which is mostly focused on explicating causal links in sequence of exhibit activity. Findings will be discussed in light of the potential long-term role for simple parent explanations in shaping children's encoding of everyday evidence and constraining children's inferences and theory building.
Sept 14, 2001: Christian Schunn, Now They See the Point:Improving Scientific Reasoning Through Making Predictions
Previous research on scientific reasoning has found that many students find it difficult to think about the theoretical level when asked to design experiments. Two studies are reported that explore whether forcing students to make predictions before running their experiments improves their scientific reasoning performance. Both studies find that, if they do make predictions, students become more focused on the theories they are being asked to test. The students become more likely to make conclusions about the theories under test and they design experiments more relevant to the theories under test. However, the advances in experiment quality come at a cost in experiment quantity---students cannot conduct as many experiments, and thus may learn somewhat less about empirical effects in the system, when forced to make predictions. Theoretically, these results suggest that even undergraduate students have difficulties coordinating searching in the theory space with search in the experiment space. Practically, these results suggest that discovery-based systems should always include enforced prediction phases.