Wednesday, December 14, 2016
Monday, December 5, 2016
Dr. Brian Belland is giving an invited talk titled “Making Problem-Centered Approaches Work: The Role of Scaffolding in Educating Future Learning Designers” at Pusan National University (South Korea) on .
Abstract: Scaffolding is support that helps students engage in activities (e.g., problem solving) that are beyond their unassisted capabilities. As such, it is an essential tool to facilitate the use of problem-centered instructional models, which have become very prominent in the USA and other parts of the world due to the need to help students develop problem solving skills in concert with content knowledge. Dr. Brian Belland presents lessons learned and directions for future research that stem from a project on meta-analysis of computer-based scaffolding in STEM education. Within the project, Belland and colleagues conducted traditional (between group), Bayesian network (within-group), and Bayesian (between group) meta-analyses of scaffolding in STEM education at the K-12, college, graduate, and adult levels. Within these syntheses, particularly strong effects were found among college and graduate level populations. Belland will provide examples of scaffolding strategies that were particularly efficacious in different contexts.
Tuesday, November 22, 2016
Computational Communities: An Ethnocomputing Framework for Building School - Community Connections
The presentation argues that ethnocomputing - the study of culture and computing wherever they interact - offers a way to open up new possibilities for deep socio-technical connections between schools and local communities. Through two case studies, the presenter will show how ethnocomputing opens up the affordances of socio-technical communities in ways that include but not limited to students' cultural heritage.
Date: December 1, 2016 At: Education Building Room 282.
Save the Date!
Saturday, November 19, 2016
Wednesday, November 16, 2016
The Department of Instructional Technology & Learning Sciences (ITLS) at Utah State University invites applications for its doctoral scholars program. This program guarantees 4 years of full tuition and stipend support, coupled with engagement in research projects directed by outstanding faculty. The ITLS Ph.D. program is nationally and internationally recognized for its research related to design and learning. It prepares scholars for positions in universities and research organizations. Faculty areas of specialization include problem-centered instruction, gaming and mobile learning, learning through Making, STEM education, instructional and interface design, learning analytics, and engaging underserved populations through technology. For more detail about the research of individual faculty, please visit http://itls.usu.edu/
Applications for the 2017-2018 doctoral cohort are being accepted through . To apply, go to http://rgs.usu.edu/
graduateschool/admissions/ apply/. Please direct any inquiries about the program or admissions process to Dr. Andrew Walker, department head, by email at firstname.lastname@example.org or by phone at (435) 797-2614. The department website can be found at http://itls.usu.edu/.
Saturday, November 5, 2016
Using Computational Tools to Understand Students’ Sociocultural Learning in Technologically Mediated Learning Environments-
Alejandro AndradeIndiana University Bloomington, EDUC 282
With the goal of advancing our understanding of, and to better optimize support for, how people learn, the use of new technologies that reliably detect fine-grained patters of student actions are gaining traction in the learning sciences. In particular, with computational tools that capture large amounts of learning traces, and analytic techniques that help examine them, researchers can study learning in an unobtrusive way, and look at a high-resolution picture of how the learning process actually occurs. From my own ongoing research, I bring three examples to illustrate how computational tools can be used to study the learning that takes place in technologically-enhanced learning environments. In the first study, I demonstrate the use of sensing technologies to design, and monitor, embodied activities with elementary students that leverage physical movement to support the learning of scientific concepts in the context of ecosystems. Analyses of students’ interviews and log data show that students can learn from such embodied activities, and also that distinct patterns in students’ physical movements are associated with students’ conceptual understanding and learning gains. The second study is an ongoing research in an introductory undergraduate engineering course where we make use of a text-mining approach. We use text-mining algorithms to understand and assess how collaboration impacts the quality of students’ answers within Peer Investigation Groups (PIGs) across various problem-based learning units. In mining students’ text-based data (i.e., PIG artifacts and collaboration transcripts) and comparing them to various expert benchmarks, we are able to visualize the development of disciplinary discourse, and the particular moments in which the group approaches to a more normative way of talking about the problem at hand. Finally, I will briefly introduce a study, currently under design, in which we would like to understand, from a sociocultural framework, students’ activities, attention, and emotional states in face-to-face learning interactions (e.g., a classroom or a museum exhibit) by tracking their physical movements and facial expressions using analytical tools based on computer vision. In concluding, I will discuss the instructional implications of these computational tools for the design of new, technologically-enhanced learning environments