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.