Badging to support teaching and student engagement: An implementation of a school-based badging system

Badges and badging have recently emerged as a program within formal and informal education to improve learning experiences. Yet, there are very few empirical studies of their implementation within a school setting. This dissertation presents two studies of a badging system within a school-based setting. As a school-based intervention, ostensibly the badging system could impact both the students and the teachers involved. Therefore, one of the studies directs its lens on the participating students and the other study directs its lens on the participating teachers. The first study explores the relationship between student participation in the school’s badging system and students’ interests. Specifically, the paper uncovers some key elements of the badges that motivated students’ participation. The second study investigates the impact on teachers participating as facilitators within the badging system. Specifically, the study investigates if teachers learned new information about students that could be actionable for instruction, did the badging system influence their interactions with colleagues, and did the badging system influence their instruction in any way? The data suggest that the badging system provided teachers with new information about their students, but had minimal impact on the teachers’ collegial interactions and instructional practice. The contribution of this work is more than simply providing empirical findings to a nascent field. These findings suggest design features to a badging system to support student motivation as well as ways that teachers can accrue benefits from involvement. Furthermore, this study offers hypotheses related to badging that can be pursued in future studies

Can We Efficiently Help Adults Strengthen their Relational Practice?

Human interactions across settings shape young people’s learning and development, and building adult expertise in facilitating productive interactions takes deliberate practice and reflective experience. However, relational practices are not consistently part of adult learning for those who work with youth. We describe a 2-year design study to develop the Simple Interactions Leadership Program, a professional learning workshop focused on relational practices. We refined the program across 3 iterations with library and after-school staff (with a total of 41 participants). Iterative changes included adding participant-driven “try-it-out” projects, adding external accountability features, and combining staff from the library and after-school sectors. Using artifacts and memos from workshops and participants’ reflections, we found that these features incrementally improved participants’ engagement, depth of learning, and sense of professional community—which we suggest are three central goals for related professional development efforts. As a collective youth-serving field, we need effective and scalable ways to help adults recognize and strengthen their relational practices with young people. The Simple Interactions Leadership Program offers a flexible structure for professional learning focused on building expertise in relational practice while sustaining change and improvement through continuous reflection within communities of practice

Neighborhood Racial Characteristics, Credit History, and Bankcard Credit in Indian Country

We examine whether concerns about lenders’ discrimination based on community racial characteristics can be empirically substantiated in the context of neighborhoods on and near American Indian reservations. Drawing on a large-scale dataset consisting of individual-level credit bureau records, we find that residing in a predominantly American Indian neighborhood is ceteris paribus associated with worse bankcard credit outcomes than residing in a neighborhood where the share of American Indian residents is low. While these results are consistent with the possibility of lenders’ discrimination based on community racial characteristics, we explain why our findings should not be readily interpreted as conclusive evidence thereof. We further find that consumer’s credit history is a robust and quantitatively more important predictor of bankcard credit outcomes than racial composition of the consumer’s neighborhood, and that the consumer’s location vis-à-vis a reservation exhibits no effect on bankcard credit outcomes

Generating Relaxed, Obvious, and Dilemma Choices with Dunyazad

Dunyazad is a system which creates narrative choices à la Choose-Your-Own-Adventure books. It attempts to generate choices that achieve specific poetic effects. This paper demonstrates Dunyazad’s ability to manage player expectations by having it generate three distinct choice structures: obvious choices, relaxed choices, and dilemmas. Using answer set programming, Dunyazad’s choice generation system directly encodes a theory of choice poetics, so flaws in its output can inform both the system and the theory itself. Survey data presented here thus not only validate that players’ perceptions match Dunyazad’s intentions, but also have implications for the theory of choice poetics. Statistical analysis of our data indicates that Dunyazad can successfully construct obvious choices, relaxed choices, and dilemmas

Minstrel Remixed: User Interface and Demonstration

This demo features a user interface for authoring stories and story fragments for use by the Minstrel Remixed story generation system. It also demonstrates Minstrel Remixed in use, allowing users to author story fragments and then have Minstrel Remixed expand these fragments and generate stories based on them. The focus is on the interface for story-fragment authoring, which exposes Minstrel's graph- of-frames knowledge representation format to the user in an interactive manner. It also exposes Minstrel Remixed's story generation capabilities as they exist currently, including the Author-Level Planning (ALP) and Transform Adapt Recall Methods (TRAM) systems

Lessons Learned From a Rational Reconstruction of Minstrel

Scott Turner's 1993 Minstrel system was a high water mark in story generation, harnessing the concept of imaginative recall to generate creative stories. Using case-based reasoning and an author level planning system, Minstrel models human creative processes. However, the algorithmic and representational commitments made in Minstrel were never subject to principled and quantitative analysis. By rationally reconstructing Minstrel, we are able to investigate Turner's computational model of creativity and learn new lessons about his architecture. We find that Minstrel's original performance was tied to a well-groomed case library, but by modifying several components of the algorithm we can create a more general version which can construct stories using a sparser and less structured case library. Through a rational reconstruction of Minstrel, we both learn new architectural and algorithmic lessons about Minstrel’s computational model of creativity as well as make his architecture available to the contemporary research community for further experimentation

RoleModelVis: A Visualization of Logical Story Models

In this demo we present a visualization of formalized representations of story. Introducing the interactive to storytelling requires the management of experiences that a user creates by their decisions. These sorts of variations can have impact on not only the user, but also the retrievable content appropriate to present to the user. The overall contribution of this work is to identify the player impact of story variation by modeling supplementary variations, and systematically responding to player interaction through supplementary variation, while respecting the author’s intentions by maintaining the integrity of the core story skeleton

Choice Poetics by Example

Choice poetics is a formalist framework that seeks to concretely describe the impacts choices have on player experiences within narrative games. Developed in part to support algorithmic generation of narrative choices, the theory includes a detailed analytical framework for understanding the impressions choice structures make by analyzing the relationships among options, outcomes, and player goals. The theory also emphasizes the need to account for players’ various modes of engagement, which vary both during play and between players. In this work, we illustrate the non-computational application of choice poetics to the analysis of two different games to further develop the theory and make it more accessible to others. We focus first on using choice poetics to examine the central repeated choice in “Undertale,” and show how it can be used to contrast two different player types that will approach a choice differently. Finally, we give an example of fine-grained analysis using a choice from the game “Papers, Please,” which breaks down options and their outcomes to illustrate exactly how the choice pushes players towards complicity via the introduction of uncertainty. Through all of these examples, we hope to show the usefulness of choice poetics as a framework for understanding narrative choices, and to demonstrate concretely how one could productively apply it to choices “in the wild.”National Science Foundation (U.S.) (grant IIS-1409992