Tuesday, November 22, 2016

ITSA Brown Bag Series with Faculty Candidate : Michael Lachney


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.

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Saturday, November 19, 2016

EdSurge with Dr. Victor Lee

  Get familiar with EdSurge. Dr. Victor Lee's, an ITLS faculty member's work was mentioned.


Eye-trackers that detect when your mind is wandering. Clothes that let you “feel” what it’s like to be in someone else’s body. Sensors that connect your heart rate to how engaged you are in class. These are the kinds of wearable technologies that could soon impact how we learn.
That was the takeaway from a recent gathering of researchers studying how personal data might improve learners’ self-awareness and performance. At the first ever aWEAR conference on the use of wearable technologies in education, held this week at Stanford University, experts shared how self-tracking tools like Fitbits and motion sensors might give humans insight about the way they learn. 
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Wednesday, November 16, 2016

Invitation for Applications for Doctoral Scholars Program

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/faculty/.

Applications for the 2017-2018 doctoral cohort are being accepted through January 31, 2017. 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 andy.walker@usu.edu or by phone at (435) 797-2614. The department website can be found at http://itls.usu.edu/.

Saturday, November 5, 2016

ITLS Candidate Presentation

Using Computational Tools to Understand Students’ Sociocultural Learning in Technologically Mediated Learning Environments-
Alejandro Andrade
Indiana University Bloomington
Thursday, 17 November, Noon-1pm, 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