Basics of qualitative research: Grounded theory procedures and techniques

https://link.springer.com/content/pdf/10.2307%2F3343168.pdf

Development as Freedom

What Video Games Have to Teach Us about Learning and Literacy

Many people in "literate" societies, when asked to define literacy, almost always do so in terms of reading
and writing abilities This narrow interpretation of literacy, an
offspring of reductionist psychology, has reigned supreme in many academic and educational contexts for decades, greatly shaping literacy theories and classroom practices Within the past ten years, however, a large body of multidisciplinary
research has begun to undermine the authority of this
perspective by situating literacy in larger social practices

Social Linguistics and Literacies: Ideology in Discourses.

Ethnologue: Languages of the World

The proliferation of touchscreen devices has made soft keyboards a routine part of life. However, ultra-small computing platforms like the Sony SmartWatch and Apple iPod Nano lack a means of text entry. This limits their potential, despite the fact they are quite capable computers. In this work, we present a soft keyboard interaction technique called ZoomBoard that enables text entry on ultra-small devices. Our approach uses iterative zooming to enlarge otherwise impossibly tiny keys to comfortable size. We based our design on a QWERTY layout, so that it is immediately familiar to users and leverages existing skill. As the ultimate test, we ran a text entry experiment on a keyboard measuring just 16 x 6mm - smaller than a US penny. After eight practice trials, users achieved an average of 9.3 words per minute, with accuracy comparable to a full-sized physical keyboard. This compares favorably to existing mobile text input methods.

/pdf/zoomboard-a-diminutive-qwerty-soft-keyboard-using-iterative-22gbxsvso5.pdf

ZoomBoard: a diminutive qwerty soft keyboard using iterative zooming for ultra-small devices

We describe and illustrate the beginnings of a general framework for the design and analysis of educational games. Our students have used it to analyze existing educational games and to create prototype educational games. The framework is built on existing components: a method for precisely specifying educational objectives, a framework for relating a game’s mechanics, dynamics, and aesthetics, and principles for instructional design grounded in empirical research in the learning sciences. The power of the framework comes from the components themselves, as well as from considering these components in concert and making connections between them. The framework coordinates the many levels at which an educational game must succeed in order to be effective. We illustrate the framework by using it to analyze Zombie Division and to generate some redesign ideas for this game.

/pdf/toward-a-framework-for-the-analysis-and-design-of-4m7hta0so8.pdf

Toward a Framework for the Analysis and Design of Educational Games

Providing university teachers with high-quality opportunities for professional development cannot happen without data about the classroom environment. Currently, the most effective mechanism is for an expert to observe one or more lectures and provide personalized formative feedback to the instructor. Of course, this is expensive and unscalable, and perhaps most critically, precludes a continuous learning feedback loop for the instructor. In this paper, we present the culmination of two years of research and development on EduSense, a comprehensive sensing system that produces a plethora of theoretically-motivated visual and audio features correlated with effective instruction, which could feed professional development tools in much the same way as a Fitbit sensor reports step count to an end user app. Although previous systems have demonstrated some of our features in isolation, EduSense is the first to unify them into a cohesive, real-time, in-the-wild evaluated, and practically-deployable system. Our two studies quantify where contemporary machine learning techniques are robust, and where they fall short, illuminating where future work remains to bring the vision of automated classroom analytics to reality.

/pdf/edusense-practical-classroom-sensing-at-scale-1bjudzt0gj.pdf

EduSense: Practical Classroom Sensing at Scale

Previous research has shown that self-explanation can be supported effectively in an intelligent tutoring system by simple means such as menus. We now focus on the hypothesis that natural language dialogue is an even more effective way to support self-explanation. We have developed the Geometry Explanation Tutor, which helps students to state explanations of their problem-solving steps in their own words. In a classroom study involving 71 advanced students, we found that students who explained problem-solving steps in a dialogue with the tutor did not learn better overall than students who explained by means of a menu, but did learn better to state explanations. Second, examining a subset of 700 student explanations, students who received higher-quality feedback from the system made greater progress in their dialogues and learned more, providing some measure of confidence that progress is a useful intermediate variable to guide further system development. Finally, students who tended to reference specific problem elements in their explanations, rather than state a general problem-solving principle, had lower learning gains than other students. Such explanations may be indicative of an earlier developmental level.

/pdf/evaluating-the-effectiveness-of-a-tutorial-dialogue-system-1gwtxn8o0i.pdf

Evaluating the Effectiveness of a Tutorial Dialogue System for Self-Explanation

Dialectal differences are one explanation for the systematically reduced test scores of children of color compared to their Euro-American peers. In this work, we explore the relationship between academic performance and dialect differences exhibited in a learning environment by assessing 3rd grade students’ science performance after interacting with a “distant peer” technology that employed one of three dialect use patterns. We found that our participants, all native speakers of African American Vernacular English (AAVE), demonstrated the strongest science performance when the technology used AAVE features consistently throughout the interaction. These results call for a re-examination of the cultural assumptions underlying the design of educational technologies, with a specific emphasis on the way in which we present information to culturally-underrepresented groups.

Amy Ogan

Papers

ZoomBoard: a diminutive qwerty soft keyboard using iterative zooming for ultra-small devices

Toward a Framework for the Analysis and Design of Educational Games

EduSense: Practical Classroom Sensing at Scale

Evaluating the Effectiveness of a Tutorial Dialogue System for Self-Explanation

The Effects of Culturally Congruent Educational Technologies on Student Achievement