LSRI Speaker Series - Audio

Over the past 25 years, user interface designers and usability engineers have studied and refined human-computer interaction techniques with the goal of improving people’s productivity and experience. But the target of these efforts — the end user — is fast becoming a thing of the past. Many people now construct or extend software on their own, building artifacts that range from email filters to spreadsheet simulations to interactive web applications. These individuals are end user developers who build their own ad hoc solutions to everyday computing needs. Will end user developers help to resolve the software crisis? Given the right tools, people may be able to rapidly develop custom solutions to a range of context-specific computing requirements, eliminating the wait for IT professionals to analyze and engineer a solution. Or are these individuals a threat to our computing infrastructure? End user developers are informal programmers with no training in software construction methods or computing paradigms. They have little intrinsic motivation to test their products for even basic concerns like correctness or safety. In this talk I argue that the transformation of end user to end user developer is well underway and discuss the prospects for maximizing the benefits to society while addressing the risks.

Over the past years, we have been developing a computer learning technology called a Teachable Agent. The work leverages the common wisdom that people "really" learn when they have to teach. After a few years of positive results, we decided to get a better look at the mechanisms that drive learning in social interaction. Most cognitively inspired theories of learning point to the useful questions and ideas that arise in social interaction. But, can we really reduce the learning benefits of social interaction to a question of information flow? In this talk, I will present "laboratory" style data that tightly controls the types of information that arise in social interaction. I will show that learning from social interaction cannot be wholly ascribed to the different types of information that arise. For example, in a wizard of oz study, people thought they were interacting with a person or a computer, and information exchange was held constant across conditions. People learned more when they thought it was a person; people were more aroused when they thought it was a person; and finally level of arousal was correlated with learning.

I seek to establish insight into varieties of modeling that occur, recurrently, in students', teachers', and curriculum developers' experiences with The Geometer's Sketchpad. In this process, I attempt to contrast the conventional, practical sense of mathematical modeling-modeling of situations and phenomena to generate and predict plausible outcomes-to at least two other available forms or types of modeling practice, that I find especially relevant to mathematics education in their foundational didactic intent.

In considering the geometric figure, Kant distinguishes between image--the traditional visual diagram--and schemata, the generalized concept of that diagram that "can never exist anywhere except in thought." Dynamic Geometry figures produced by software such as The Geometer's Sketchpad bridge this divide through flexible, "rubbery" diagrams that (under manipulation) transform into any valid realization of their defining geometric constraints, but at any instant retain the immediacy and tangibility of specific images. In this talk, Sketchpad's author explores the implications of Dynamic Geometry visualization on mathematical inquiry and pedagogic practice in the context of school (6-12) mathematics, and describes implementation concerns in the design and development of Dynamic Geometry software.

Problem solving is one of the most important goals of any science course. However it is notoriously difficult to improve students’ problem solving abilities, and many students never develop competence. This is particularly true for open-ended or case-based problems – which are also more difficult to assess. We use a number of methods including a suite of software tools and inventories that allow us to assess both student problem solving strategy, student ability, and metacognitive activity as they change over time. Using these tools we can predict how a student will perform on subsequent problems with a 90% probability. Now that we have a set of fairly robust assessment materials, we have begun to develop and investigate intervention methods designed to improve student problem solving strategies and abilities. These methods include collaborative grouping, metacognitive strategies, laboratory projects, and concept maps. The effects of these interventions will be discussed, with regard to student ability, developmental level, and gender.

Design is an inherently interdisciplinary enterprise and the design of learning technologies is no exception. Learning technology designers must consider issues from a range of disciplines, such as software design and human-computer interaction (HCI), learning sciences, and related content domains. But while designers and researchers can draw from existing work in these different disciplines, there are still many questions to explore about the design, use, and impact of learning technologies. From a learning sciences perspective, there is much to learn about how learners work with technologies in different contexts and what the ultimate impacts of those technologies are, especially as we consider new media and communication functionalities. From an HCI perspective, there is much to learn about specific design methods and frameworks that go beyond the typical HCI focus on usability to focus on developing and assessing learning technologies. The development process thus leads to a disciplinary interplay: oour understanding of learners and learning leads to certain design approaches, which leads to learning technologies that we can assess to gain knowledge about learners and learning, which can lead to refined design approaches and the cycle continues to build our knowledge of HCI and learning.

Detecting and Adapting to When Students Game the System: Students use intelligent tutors and other types of interactive learning environments in a considerable variety of ways. In this talk, Dr. Ryan Baker will present research on automatically detecting and adapting to when students "game the system", attempting to succeed in a learning environment by exploiting properties of the system rather than by learning the material and trying to use that knowledge to answer correctly. Dr. Baker will present a set of studies that establish that gaming the system is replicably associated with low learning, and will present evidence on which motivations, attitudes, and affective states are associated with the choice to game the system. He will also discuss evidence that the relationship between gaming and learning differs, depending on when and why a student chooses to game.

Acts into Artifacts: Computational Tools to Support Experience Capture and Reflection: Dr. Smith’s research deals with the design and evaluation of systems that capture aspects of everyday experiences for reflection and learning. Dr. Smith will discuss a current project that examines ways to have fantasy sports players reflect on their decision making and enhance their reasoning with statistical analyses. Time permitting, he will discuss other lab projects that look more broadly at the ways that captured experiences can be used to reflect on everyday experiences and act as a bridge for increasing knowledge and performance.

Learning how to use mathematics curriculum materials effectively is arguably an important part of the work of teaching. Through my work on the BIFOCAL Project, a multi-year professional development project aimed at supporting middle school math teachers' use of curriculum materials, I began to think about the precise role that these materials play in the work of teaching, which led to my dissertation study. Briefly, the focus of my dissertation is an examination of how experienced middle school math teachers use the teacher guide from the Connected Mathematics Project (CMP) to inform their planning and instructional decisions around mathematical tasks. In addition to my experiences as a researcher, I have served as an instructor for mathematics methods and content courses for preservice elementary teachers. In regards to curriculum materials, little guidance and support is often provided for elementary preservice teachers in using math curriculum materials despite the prevalence of these materials in elementary classrooms. For this reason, I designed tasks and activities in my courses to help preservice teachers learn to use these materials effectively. In this talk, I will first describe my professional development work with inservice teachers in the BIFOCAL Project, and then talk at some length about my dissertation study, and finally move to discuss my research related to preservice elementary teachers' use of math curriculum materials in methods and content courses.

Closing the Participation Gap: Creating a Technical and Learning Infrastructure to Support the Analysis of the Impact of Ubiquitous Computing on Urban Youth

Educators seeking to motivate students often do so by inquiring into students’ interests and designing instruction anchored in such interests. This approach is based on psychological theories of individual (long-term) interests, which propose that a person’s extended, self-motivated pursuit of topically related activities flow directly and simply from her relationship to the topic or domain. As an example, a child’s continued engagement with a set of dinosaur-related activities is said to stem from her interest in the topic of dinosaurs.

Standards-based reforms in mathematics education place issues of equity front and center. Indeed, curriculum and instruction that is aligned with national standards appear to lead to more equitable outcomes for students (NCTM, 2000; Schoenfeld, 2002). However, many scholars argue that the reform movement does not go far enough in terms of equity (Apple, 1992; Gutierrez, 2002; Gutstein, 2003). These scholars argue for the importance of "critical mathematics," that is, the infusion of political themes and goals into the standards-based mathematics curriculum. Proponents of critical mathematics claim that such an approach has the potential to be more equitable than standards-based instruction because, for example, it allows students to use mathematics to develop their understandings of personally relevant sociopolitical matters (e.g. racial profiling, gentrification) and what they can do to change them for the better.

Recent advancements in educational technologies have led to an explosion of visualization software for teaching and learning science, particularly chemistry. To varying degrees, visualization tools help teachers and students perceive the imperceptible objects and phenomena of the chemical world. Although some visualization tools have seen great success in the classroom, others have had little impact on student learning and understanding. The present talk explores a novel cognitive model that both motivates the use of computer-based visualization tools for teaching chemistry and explains the variability in learning outcomes that result from their use. First, I argue for a more complete model of teaching and learning in chemistry that empirically defines the role of visualization tools in the classroom. Using data from tandem psychometric and protocol studies, I identify some unique difficulties with learning chemistry that constrain the possible affordances of visualization tools.

Although preservice elementary school teachers (PSTs) have been shown to lack the understanding of multidigit whole numbers necessary to teach in ways that empower students mathematically, little is known about their conceptions. I draw upon the extensive research on children's understanding of multidigit whole numbers to explicate PSTs' conceptions of these numbers. I develop a framework for PSTs' conceptions of multidigit whole numbers and use that framework to describe their conceptions and their difficulties in the context of the standard algorithms. I then link the PSTs' conceptions in the context of the standard algorithms to their performance in other contexts.

The term data visualization is often used to describe computer software or its products. I argue that learning sciences research can benefit from conceptualizing data visualization instead as a mode of shared sense-making, in which the co-construction of meaning is mediated by visual data artifacts. This process can be studied at sociocultural and microgenetic levels of analysis, for purposes of better understanding the multiple literacies and trajectories of learning in which visual data are employed. In this talk I present a microgenetic analysis of these social processes of data visualization in groups of 6th-grade students, evidenced in their emergent discourse practices in small group work over the course of an extended science investigation using visual data. A comparison of two students' patterns of participation in their respective small groups -- each a student with low levels of talk in the group overall -- highlights differences in the construction of roles for non-dominant students with respect to domain discourse around data. Implications for science learning are interpreted in the context of particular concepts and skills evidenced by each student in post interviews.

Decisions, Decisions: Assessing Students' and Preservice Teachers' Use of Scientific Evidence

Scaffolding Students in Writing Evidence-Based Scientific Explanations: Developing evidence-based explanations is a critical aspect of science. Recent science reform documents and efforts advocate that students develop scientific inquiry practices, such as the construction and communication of scientific explanations.

Scaffolding Students in Writing Evidence-Based Scientific Explanations: Developing evidence-based explanations is a critical aspect of science. Recent science reform documents and efforts advocate that students develop scientific inquiry practices, such as the construction and communication of scientific explanations.

Race, Identity, and Mathematics Literacy: African American Counternarratives

Race, Identity, and Mathematics Literacy: African American Counternarratives

Geologists, biologists, climatologists, seismologists and other scientists nowadays use a diversity of sensing devices and measuring instruments to record aspects of the earth, in order to investigate, predict and reason about a particular aspect of the environment. A major part of their research involves mapping, matching and noticing patterns and anomalies from the masses of datasets that they collect over time. However, it is very difficult to become competent at accomplishing these forms of analyses. Local and global connections have to be continuously made when moving between the physical and digital worlds. How might we help students (and scientists) learn how to do this kind of complex interlinking and high-level reasoning? In my talk, I will describe an ongoing project I am involved in at Indiana University where a team of computer scientists, interaction designers and environmental scientists are developing networked mobile recording/measuring/communication tools, intended to be used by groups of students when out in the field. The tools have been designed to enable easy access, updating and comparison of a variety of contextually-relevant datasets, visualizations and information when measuring and sensing aspects of the environment. An underlying assumption is that by juxtaposing the activities of measuring and analysis in this way, students can begin to learn the art of grown-up science more effectively. To support this claim, I will present findings from a preliminary field study where groups of students used our tool to measure, hypothesize and analyze about how and why a wetland restoration site was changing over time.

Geologists, biologists, climatologists, seismologists and other scientists nowadays use a diversity of sensing devices and measuring instruments to record aspects of the earth, in order to investigate, predict and reason about a particular aspect of the environment. A major part of their research involves mapping, matching and noticing patterns and anomalies from the masses of datasets that they collect over time. However, it is very difficult to become competent at accomplishing these forms of analyses. Local and global connections have to be continuously made when moving between the physical and digital worlds. How might we help students (and scientists) learn how to do this kind of complex interlinking and high-level reasoning? In my talk, I will describe an ongoing project I am involved in at Indiana University where a team of computer scientists, interaction designers and environmental scientists are developing networked mobile recording/measuring/communication tools, intended to be used by groups of students when out in the field. The tools have been designed to enable easy access, updating and comparison of a variety of contextually-relevant datasets, visualizations and information when measuring and sensing aspects of the environment. An underlying assumption is that by juxtaposing the activities of measuring and analysis in this way, students can begin to learn the art of grown-up science more effectively. To support this claim, I will present findings from a preliminary field study where groups of students used our tool to measure, hypothesize and analyze about how and why a wetland restoration site was changing over time.

Abstract Recent policy demands for external accountability are challenging instructional leaders to rethink how they have traditionally guided the practices of teaching and learning in schools. I will discuss how a new conception of instructional leadership is emerging across the country that focuses on how local leaders and teachers build data-driven instructional systems (DDIS) in their schools. I will argue that a learning sciences perspective, grounded in distributed cognition and the situational distribution of leadership practice, provides a unique perspective for accessing and representing how school leaders are building socio-technical systems to facilitate information flows about student achievement in their schools. The DDIS model describes how leaders create and use artifacts to coordinate a series of organizational functions involving 1) data acquisition, 2) data reflection, 3) program alignment and integration, 4) instructional design, 5) formative feedback and 6) test preparation. To illustrate how DDISs work in practice, I will review data collected in a year-long study of four schools to describe how the leaders structure opportunities to engage in data-driven decision making. Rather than reducing teaching and learning to mechanical processes as feared by many critics of accountability policies, I will show how the collaborative design work involved in DDIS assembly results in powerful professional communities well-suited to address chronic problems of instructional practice in schools.

Abstract Recent policy demands for external accountability are challenging instructional leaders to rethink how they have traditionally guided the practices of teaching and learning in schools. I will discuss how a new conception of instructional leadership is emerging across the country that focuses on how local leaders and teachers build data-driven instructional systems (DDIS) in their schools. I will argue that a learning sciences perspective, grounded in distributed cognition and the situational distribution of leadership practice, provides a unique perspective for accessing and representing how school leaders are building socio-technical systems to facilitate information flows about student achievement in their schools. The DDIS model describes how leaders create and use artifacts to coordinate a series of organizational functions involving 1) data acquisition, 2) data reflection, 3) program alignment and integration, 4) instructional design, 5) formative feedback and 6) test preparation. To illustrate how DDISs work in practice, I will review data collected in a year-long study of four schools to describe how the leaders structure opportunities to engage in data-driven decision making. Rather than reducing teaching and learning to mechanical processes as feared by many critics of accountability policies, I will show how the collaborative design work involved in DDIS assembly results in powerful professional communities well-suited to address chronic problems of instructional practice in schools.

Telling, adapting, and performing stories: How literacy meets identity

Telling, adapting, and performing stories: How literacy meets identity

Kendler and Kendler (1962) are remembered for their bold challenge to the behaviorist tenet, widely accepted in the middle of the 20th century, that the learning process functions in an identical manner across species and across the human life cycle. To the contrary, they argued, learning develops. Young children learn via associationist mechanisms, but by age 7, the learning process has been transformed into one involving internal mediating concepts that connect overt stimuli and responses. Today it is apparent that the Kendlers overstated their case in claiming that young children do not form concepts. There is ample evidence to the contrary, and a different explanation for age differences on Kendlers' learning tasks is required. Following the Kendlers' work, the question of developmental changes in the learning process was largely put aside, as interest in children's learning declined in general. It is now, however, a somewhat different question than it was in the Kendlers' day. Rather than formation of S-R bonds, learning is now more likely to be defined as "change in understanding" (Schoenfeld, 1999). In this context, it is productive to resurrect the question largely abandoned following the Kendlers' work. A study is described of 11-12-year-old children and young adults engaged in an identical learning task. Results support the proposal that learning comes to operate under increasing executive control in the years between middle childhood and early adulthood. Adults, it is suggested, are more likely to employ a meta-level executive allowing them to maintain dual representations, one of their existing understanding and the other of new information they are being asked to register. The executive allows these two representations to be maintained simultaneously and attended to flexibly. Without it, there exists only a singular experience of "the way things are" as a vehicle for understanding the world. New information may be assimilated to it, but no executive is available to monitor and manage the process.

Kendler and Kendler (1962) are remembered for their bold challenge to the behaviorist tenet, widely accepted in the middle of the 20th century, that the learning process functions in an identical manner across species and across the human life cycle. To the contrary, they argued, learning develops. Young children learn via associationist mechanisms, but by age 7, the learning process has been transformed into one involving internal mediating concepts that connect overt stimuli and responses. Today it is apparent that the Kendlers overstated their case in claiming that young children do not form concepts. There is ample evidence to the contrary, and a different explanation for age differences on Kendlers' learning tasks is required. Following the Kendlers' work, the question of developmental changes in the learning process was largely put aside, as interest in children's learning declined in general. It is now, however, a somewhat different question than it was in the Kendlers' day. Rather than formation of S-R bonds, learning is now more likely to be defined as "change in understanding" (Schoenfeld, 1999). In this context, it is productive to resurrect the question largely abandoned following the Kendlers' work. A study is described of 11-12-year-old children and young adults engaged in an identical learning task. Results support the proposal that learning comes to operate under increasing executive control in the years between middle childhood and early adulthood. Adults, it is suggested, are more likely to employ a meta-level executive allowing them to maintain dual representations, one of their existing understanding and the other of new information they are being asked to register. The executive allows these two representations to be maintained simultaneously and attended to flexibly. Without it, there exists only a singular experience of "the way things are" as a vehicle for understanding the world. New information may be assimilated to it, but no executive is available to monitor and manage the process.

American children usually find a free-flowing, open format approach to classroom discussion called Collaborative Reasoning to be intellectually stimulating and personally engaging. In this talk, I will present initial evidence about the response of the children from two sites in China and one site in Korea to Collaborative Reasoning discussions. The expected discourse of these discussions is a radical departure from the prevailing patterns of discourse in Asian homes and schools. Thus, according to some theorists, the performance of the children should have been awkward, at best. Based on analysis of discussion transcripts and individually-written reflective essays, I will suggest answers to the following questions: Could Chinese and Korean children manage their own discussions with little or no help from the teacher? Were the children attentive and engaged? Did the children display rhetorical moves, or ‘argument stratagems’, similar those observed among American children? Did skills of argument children acquired during oral discussion transfer to written argument?

American children usually find a free-flowing, open format approach to classroom discussion called Collaborative Reasoning to be intellectually stimulating and personally engaging. In this talk, I will present initial evidence about the response of the children from two sites in China and one site in Korea to Collaborative Reasoning discussions. The expected discourse of these discussions is a radical departure from the prevailing patterns of discourse in Asian homes and schools. Thus, according to some theorists, the performance of the children should have been awkward, at best. Based on analysis of discussion transcripts and individually-written reflective essays, I will suggest answers to the following questions: Could Chinese and Korean children manage their own discussions with little or no help from the teacher? Were the children attentive and engaged? Did the children display rhetorical moves, or ‘argument stratagems’, similar those observed among American children? Did skills of argument children acquired during oral discussion transfer to written argument?

Dr. Hilda Borko’s presentation focuses on the teacher professional development component of the STAAR project. STAAR – Supporting the Transition from Arithmetic to Algebraic Thinking – is a multi-year, multi-site research program funded through an IERI grant. The research team at the University of Colorado at Boulder is developing and studying a professional development program intended to help teachers foster algebraic thinking in their classrooms.

Dr. Hilda Borko’s presentation focuses on the teacher professional development component of the STAAR project. STAAR – Supporting the Transition from Arithmetic to Algebraic Thinking – is a multi-year, multi-site research program funded through an IERI grant. The research team at the University of Colorado at Boulder is developing and studying a professional development program intended to help teachers foster algebraic thinking in their classrooms.

Ten years ago, I realized that case-based reasoning, an approach to designing computer programs that could reason based on their experiences, suggested ways of promoting productive learning in people. Based on that insight and on CBR's implied cognitive model, my research group and I have designed a project-based inquiry approach to middle school science called Learning by Design. LBD takes into account the cognitive model proposed by CBR as well as the constraints and opportunities afforded by middle-school classrooms and students. By studying the strengths and weaknesses of the approach as it has been implemented in a variety of venues in the Atlanta area, we've discovered opportunities for designing and integrating several kinds of technology appropriate not just to LBD classrooms, but to project-based inquiry classrooms more generally.

Ten years ago, I realized that case-based reasoning, an approach to designing computer programs that could reason based on their experiences, suggested ways of promoting productive learning in people. Based on that insight and on CBR's implied cognitive model, my research group and I have designed a project-based inquiry approach to middle school science called Learning by Design. LBD takes into account the cognitive model proposed by CBR as well as the constraints and opportunities afforded by middle-school classrooms and students. By studying the strengths and weaknesses of the approach as it has been implemented in a variety of venues in the Atlanta area, we've discovered opportunities for designing and integrating several kinds of technology appropriate not just to LBD classrooms, but to project-based inquiry classrooms more generally.

By facilitating the growth of a culture of collaboration and rigorous scientific thinking in middle school science classrooms, we've been able to promote significant learning of and engagement in scientific reasoning. I present some of what we've learned about how to promote a classroom culture and the learning that ensues from it.

By facilitating the growth of a culture of collaboration and rigorous scientific thinking in middle school science classrooms, we've been able to promote significant learning of and engagement in scientific reasoning. I present some of what we've learned about how to promote a classroom culture and the learning that ensues from it.

Jay Lemke (Ph.D., University of Chicago) is Professor in the School of Education, Department of Educational Studies, at the University of Michigan and Co-Editor of the journal Critical Discourse Studies. Before coming to Michigan, he was Executive Officer of the Ph.D. Program in Urban Education at the City University of New York Graduate Center and co-editor of Linguistics and Education. His research interests include science education, new learning technologies, multimedia semiotics, discourse analysis, and applications of complex systems theory to the study of social, cultural, and institutional change.

Jay Lemke (Ph.D., University of Chicago) is Professor in the School of Education, Department of Educational Studies, at the University of Michigan and Co-Editor of the journal Critical Discourse Studies. Before coming to Michigan, he was Executive Officer of the Ph.D. Program in Urban Education at the City University of New York Graduate Center and co-editor of Linguistics and Education. His research interests include science education, new learning technologies, multimedia semiotics, discourse analysis, and applications of complex systems theory to the study of social, cultural, and institutional change.