In this dissertation, I drew on analytical frames found in genre theory to examine digital storytelling as a cultural practice with historically developed genre features, practices, and structures. A central concern was to examine how genre mediated ongoing discursive work. I conducted interviews with designers and facilitators from four socially influential programs of digital storytelling to understand the cultural practice as simultaneously durable and dynamic. Attending to a corpus of facilitator-nominated digital stories, I developed genre-informed discourse analytical methods to explore how locally manifested genre features embodied ideological orientations, institutional pressures, and individual intentions. Analysis of ethnographic data allowed me to describe the four programs as dialectically connected to each other through a shared meaning potential they drew from and added to. In the mean time, each program developed temporarily stabilized genre practices in response to contingent social, cultural, institutional, and personal needs and intentions. Digital stories manifested genre features that indexed collective ideological and experiential knowledge. I suggest that we treat temporality as one dimension of genre features.

This study explores the reasoning that emerged among eight high school juniors and seniors as they participated in a classroom teaching experiment addressing stochastic conceptions of sampling and statistical inference. Toward this end, instructional activities engaged students in embedding sampling and inference within the foundational notion of distributions of sample statisticspatterns of dispersion that one conceives as emerging in a collection of a sample statistics values that accumulate from re-sampling under essentially identical conditions. The study details students engagement and emergent understandings in the context of instructional activities designed to support them. Analyses highlight these components: the design of instructional activities, classroom conversations and interactions that emerged from students engagement in activities, students ideas and understandings that emerged in the process, and the design teams interpretations of students understandings. Moreover, analyses highlight the synergistic interplay between these components that drove the unfolding of the teaching experiment over the course of 17 lessons in cycles of design, engagement, and interpretation. These cycles gave rise to four interrelated phases of instructional engagements: Phase 1: Orientation to statistical prediction and distributional reasoning; Phase 2: Move to conceptualize probabilistic situations and quantify unusualness; Phase 3: Move to conceptualize variability and distribution; Phase 4: Move to quantify variability and extend distribution. Analyses reveal that students experienced significant difficulties in conceiving the distribution of sample statistics and point to possible reasons for them. Their difficulties centered on composing and coordinating objects into a hierarchical structure with actions in imagined re-sampling scenarios that involve: a population of items, selecting items from it to accumulate a sample, recording the value of a statistic of interest, repeating this process to accumulate a collection of values, structuring such collections and conceiving patterns within and across them in ways that support making statistical inferences.

Although prior research as shown that generating explanations encourages students to learn new content with deeper understanding and to monitor their own comprehension more effectively, helping students learn how to explain properly remains a significant challenge. This study investigated the use of software agents as learning partners in an activity where students generated explanations about river ecosystem concepts. <p>The results of the experiment demonstrated that software agents can have a positive impact as learning partners in a virtual world environment. It was found that the agents encouraged the use of explanation resources designed to help students generate more effective explanations. Students working with the agents generated deeper explanations than students who did not interact with an agent. A summary report of student explanations produced for the participating teacher was perceived to be a useful source of feedback.

Research in the learning sciences has moved toward a focus on the conditions in which knowledge is learned and applied (e.g. Bransford, Brown, & Cocking, 2000; CTGV, 1997). However, instructional designs still tend to focus primarily on the material or physical conditions for applying knowledge, not the social or personal context of that knowledge (Lave & Wenger, 1991; Hay & Barab, 2001). This study takes as its premise that learning to perform a professional role in a domain involves more than the acquisition of knowledge propositions in that domain; learning a role transforms identity and practice (Wenger, 1998). For this dissertation, a learning experience is designed and evaluated with an explicit focus on learning a role for new employees at a health care corporation. The designed intervention used intentional language and multimedia stories to guide the new employees adoption of their role. The design had the effect of facilitating understanding of the role as measured by pre- and post-writing measures and interviews. Based on the study, trajectories of role change are described and design principles for role-based learning are proposed.

This study explores the complex relationship between teachers understandings of mathematics and their classroom practices. The study details students engagement in a segment of a university course designed to position pre-service teachers to develop a coherent understanding of functions as covariation of quantities. With regards to this instruction, this study was guided by two research questions that dealt with understanding (a) the pre-service teachers mathematical development and then (b) how the pre-service teachers emerging understanding of function as covariation impact how they envision and enact instruction, with particular emphasis on the pre-service teachers ability to orchestrate conceptual conversations about significant mathematical ideas. Analyses highlight the fact that one teaches what they know pre-service teachers particular understandings of mathematical content have a significant impact on their pedagogical conceptualizations of the content. It is these pedagogical conceptualizations of content and the related images that serve to guide the pre-service teachers decisions and instructional actions. The study concludes with suggestions for ways in which appropriate pedagogical conceptualizations of the content might be developed.

Probability and statistical inference are important ideas with a remarkably wide range of applications. However, psychological and instructional studies conducted in the last two decades have consistently documented poor understanding of these ideas among different population across different settings. The purposes of this dissertation study are to understand teachers understandings of probability and statistical inference; and to develop theoretical frameworks for understanding teachers understandings. To this end, our research team conducted an eight-day seminar with eight high school statistics teachers in the summer of 2001. The data we collected include videotaped sessions and interviews, teachers written work, and researchers field notes. My analysis of the data revealed that: 1) There was a complex mix of conceptions and understandings of probability and statistical inference, both within individual teachers and among the group of teachers, that are often situationally triggered, which are often incoherent when the teachers try to reflect on them, and which do not support their attempts to develop coherent pedagogical strategies regarding probability and statistical inference; 2) teachers conceptions of probability and statistical inference are highly compartmentalized: They did not understand probability and statistical inference as a scheme of interconnected ideas, but rather, ideas that are isolated from one another; 3) many teachers had a conception of learning as knowing how to solve problems, and teaching as displaying the expertise of problem solving. These conceptions of learning did not support their engagement in reflective conversations about the ideas in probability and statistical inference. The implications of these results include: 1) Understanding statistical inference and teaching effectively entails a substantial departure from teachers' prior experience and their tacit beliefs; and 2) the goal of teachers professional development should be helping the teachers develop understandings of probability and statistical inference as a scheme of interrelated ideas by exerting a great amount of coerced effort in helping teachers develop the capacity and orientation in thinking of a distribution of sample statistics.

The purpose of this dissertation was to document the development of a professional teaching community and the means of supporting its emergence and concurrent learning as situated in the institutional context of the school district. In this process, I related the realized learning trajectory of this professional teaching community and of the participating teachers to both the means by which it was supported and organized, and to the institutional setting in which the teachers worked. The results of this analysis will generalize to other cases in that it will enable researchers and teacher educators to adapt the means by which the learning of the professional teaching community was supported to the organizational characteristics of the school systems in which they are working in a conjecture-driven manner.

This study analyzes the development of statistical reasoning during several mathematics classes of an intact fourth-grade classroom. The teacher and her students were members of a multi-year teacher-researcher collaborative effort. In all, fourteen class sessions were videotaped, one on January 27, 2000 and the rest from April 6, 2000 to May 18, 2000. Data sources include this video recording, made using a single camera, and rough transcripts of the class talk, written at the time of the videotaping. In the course of the lessons, the students and their teacher worked through statistical ideas and problems about data describing differently sized bubbles, people, and plants. The lessons were analyzed several different ways, including looking at the order and connectivity of turns of talk, the frequency of mention of different topics, the comparisons made between different data sets, and how arguments were formed about expectations and distributions.

This research explored how allowing students to actively control an electrical circuit simulation in real-time helps them better understand the complex behavior of electrical circuits. Many students, even at the college level, have misconceptions about electricity that make the subject more difficult to teach and learn via traditional methods such as lecture or textbooks. In this study, students used a unique real-time control interface to an animated circuit simulation in order to enactively model how an AC voltage source controls the current flow in a circuit. In enactive modeling, the student is an agent participating in the behavior of a dynamic system and is controlling one or more temporal aspects of the changes occurring in the system. After only a 30 minute tutoring session with the circuit simulation, students significantly gained in their understanding of some difficult concepts about circuit behavior, as measured by a multiple choice conceptual test. In particular there was evidence that students were able to overcome common misconceptions about the temporal behavior and flow of electrical current.

The purpose of this study was to assess the effects of three instructional media on learning among adults in developing countries. Participants included 90 women from Central and South America randomly assigned to one of three modes of instruction: narrative only, narrative plus still images, or narrative plus video segments. At the conclusion of a presentation in one of the three modes of instruction, each participant was tested on four categories of learning: recall of facts, recall of procedures, demonstration of stepwise procedures, and demonstration of conditional procedures. Test results revealed that the addition of still images to narrative had no bearing on the recall of facts but had a positive bearing on the recall and demonstration of procedures for participants with seven or more years of schooling. The addition of video to narrative, by comparison, appears to have raised scores for all participants with respect to recall and demonstration of procedures -- raising scores for participants with zero to six years of schooling more dramatically and more consistently than those with seven or more years of schooling.