2014 — 2017 |
Berland, Matthew Steinkuehler, Constance |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Situating Big Data: Assessing Game-Based Stem Learning in Context @ University of Wisconsin-Madison
This REAL project arises from the 2013 solicitation on Data-intensive Research to Improve Teaching and Learning. The intention of that effort is to bring together researchers from across disciplines to foster novel, transformative, multidisciplinary approaches to using the data in large education-related data sets to create actionable knowledge for improving STEM teaching and learning environments in the medium term and to revolutionize learning in the longer term. The project team aims to understand how to use data collected from the environment in which learning technologies are used to do the following: (1) allow automated assessment that takes the full range of classroom activities and discussions around use of the technology into account in providing customized feedback recommendations; (2) come to better understand how learning and the context in which it is happening interact; and, (3) provide theory-informed and evidence-based advice for refining learning approaches and activities. This will make it easier for teachers to manage ongoing assessment and to adapt classroom activities to learners' needs in learner-centered, project-based, and inquiry-driven learning environments. Results of this project will lay the foundations for making assessment regular, routine and ongoing and to take a fuller range of learning activities into account. This, in turn, will allow better personalization and ongoing feedback and scaffolding for learners. Results will enhance understanding of how to assess and foster not only disciplinary learning, but also disposition, identity development, and long-term participation.
The PIs seek to integrate theories of situated cognition with analysis of big data. They will explore how to integrate clickstream data from technology with key forms of multimodal data describing the contexts in which the technology is being used, e.g., individual and group discourse (online and in-room), individual and curricular artifacts, classroom assessments, and school performance, to generate a data-driven methodology for: (1) understanding the learning happening in technology-rich learning environments; (2) assessing development and needs of individuals within those environments in ways that will suggest adaptations and scaffolding; and (3) investigating situated cognition. They aim to make it easier to manage ongoing assessment and to adapt classroom activities to learners' needs in learner-centered, project-based, and inquiry-driven learning environments. They will investigate how to (1) enable consideration of the full ecosystem of learning and data collected across it when assessing learning and engagement, and (2) identify what is working and not working to foster learning in a situation. They will demonstrate where and how useful data are situated in the learning ecology when learners are engaged in hands-on and discourse-rich learning activities, and how to use these data to assess effectiveness and impact of interventions. Their plan involves matching important patterns in hand-coded qualitative data to patterns of automatically collected data; this will allow them to identify the patterns in automated data collection that can be used as indicators of factors such as understanding, confusion, learning, and participation.
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2017 — 2018 |
Steinkuehler, Constance Squire, Kurt Davidson, Richard (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Exp: Tenacity: Self-Regulation of Attention and Its Relationship With Learning @ University of Wisconsin-Madison
The Cyberlearning and Future Learning Technologies Program funds efforts that support envisioning the future of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects explore the viability of new kinds of learning technologies by designing and building new kinds of learning technologies and studying their possibilities for fostering learning and challenges to using them effectively. So-called 'non-cognitive' factors such as grit, tenacity, and perseverance have drawn renewed attention from researchers, policy makers, and the public. Cutting across all three concepts is the fundamental idea of 'self-regulation,' or the ability to monitor and appropriately regulate one's attention. Self-regulation skills are critical for success in today's era of rapid technological and social change. Luckily, evidence is accumulating that such skills can be taught. New technologies for collecting, tracking, and reporting data offer great promise for developing and scaffolding students' ability to self-regulate. One such tool is the touch tablet application entitled Tenacity. Tenacity is a tablet based application for middle schoolers designed to train and track the user's attentional self-regulation. Prior research found that, after using the tool for roughly 20 minutes per day for a period of two weeks, students showed significant improvements in self-regulation skills. In this project, researchers will adapt the existing prototype application for more accessible use on wearable devices, add a data dashboard for monitoring one's skill development over time, and then assess its use and effectiveness in the natural environment both inside and outside the classroom. The results will be a market ready application for wearable technologies (smart watches) for self-regulating attention, empirical results assessing its use and impact among everyday users, and the public release on iTunes of the software for dissemination and assessment at mass scale.
Specifically, the research team will adapt the current prototype for use on the Apple iWatch, debug and polish its ability to train and track breath-counting accuracy intermittently throughout the day, and implement data visualization tools for use by users and their parents and teachers. They will then assess its effectiveness in an 8-week experimental study using a pretest/posttest control group design with teens (13-15 years old). Finally, they will release the tool to the public via the Apple App Store to examine its use and effectiveness at mass scale. The hypothesis is that systematic use of Tenacity will result in behavior change on standard measures for attention, foster a more productive conceptual understanding of self-regulation, increase self-regulation skills on first order tasks (i.e., direct skill improvement measures within the application) and second order variables, such as school grades and social wellbeing, and increase school affiliation.
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