Friday, January 13, 2012
NERLA 2012 - First North East Regional Learning Analytics Symposium
1. From Academic Analytics to Learning Analytics - Michael Vetter-Brandeis University
2. Leveraging Existing Data - Banach & Gammell-ECSU, Allen-UCONN
3. Identifying Places for Pedagogical Intervention - Johann Ari Larusson-Brandeis & Brandon White-Berkeley
4. NERLA 2012 Final proceedings
Where:
Southbridge Hotel and Conference Center
14 Mechanic St.
Southbridge, Massachusetts
When:9:00 am - 3:30 pm
Note: Registration begins at 7:30am
Workshop Organizer: Johann Ari Larusson of Brandeis University
The growing prevalence of educational technology solutions – from the installation of learning management systems to the creation of student blogs – has provided educational institutions with a wealth of information reflecting how their communities engage in the transmission and acquisition of knowledge. The activity captured by each of these methods has an opportunity to provide insight into the core processes of teaching and learning. However, the means of analyzing this data has yet to keep pace with the steadily accumulating amount of information. Basic questions concerning the use of the data arise. How can the information collected enrich students’ learning experiences? How can an institution effectively organize its data? How can an institution apply this information to refine its own educational and organizational strategies? Learning analytics provides a means of answering these questions.
Learning analytics (LA) refers to the collection, analysis, and application of data accumulated throughout the semester to assess the behavior of educational communities. Through the use of statistical techniques and predictive modeling, the ultimate goal is to optimize both student and faculty performance, to refine pedagogical strategies, to streamline institutional costs, to determine students’ engagement with the course material, to highlight potentially struggling students and to alter pedagogy accordingly, to fine-tune grading systems using real-time analysis, and to allow instructors to judge their own educational efficacy. LA encompasses a range of cutting-edge educational technologies that provide all members of an institution’s community with a window into what actually takes places over the trajectory of a student’s learning. Involvement in LA technologies and pedagogies allows educators and scholars to engage in a contemporary and innovative approach to an educational issue that is sure to remain an integral part of higher education for years to come.
This symposium focuses on connecting individuals across disciplines and professions, from both academia and industry, who all share a genuine interest in learning analytics. Through the symposium, participants will be able to network and share groundbreaking results, latest design ideas, findings from short or longitudinal integration and deployment studies, tools, methods, ideas, and so on.
Who should attend?
Scholars, researchers, developers, IT professionals, directors, library personnel, undergraduate and graduate students, directors, Chief Technology and Information Officers, university administrators, private industry or anyone and everyone interested in Learning Analytics. Participation is also welcomed from anyone outside the “North East” region of the United States.
Event Schedule:
7:30am – 9:00am Registration and Coffee
9:00am – 10:00am Welcome / Introduction to Symposium
10:00am – 12:00pm Paper Sessions
10:00am
Shifting Actors and Shifting Audiences: From Academic Analytics to Learning Analytics
Author: Michael Vetter, Brandeis University
Abstract: Learning analytics (LA) is an emerging field in which data is collected and analyzed to assess students’ classroom behaviors. As an attempt to quantify or predict student success, LA can be used to begin to unpack the “black box” resulting from increased use of academic technologies. LA’s origins, however, are in the earlier field of academic analytics (AA). The two approaches diverge, however, in terms of the audiences that they target, and in terms of the actors called upon to put their implementations into place. This paper seeks to resolve the conceptual distinction between the two methods by examining a host of individual tools that represent possible first-generation LA implementations. From these examples, a model of the ideal actors and audience for LA is extracted, with a theoretical discussion of its possible implications.
10:40am
Leveraging Existing Data: Indicators of Engagement as Early Predictors of Student Retention
Authors:
Patricia Banach, Director of Library Services, Eastern Connecticut State University
William Gammell, Associate Vice President for Academic Affairs, Eastern Connecticut State University
Abstract: Various measures of student engagement and academic risk were analyzed based on three years of data at Eastern Connecticut State University. Among the data considered was Freshman orientation data collected by the J. Eugene Smith Library. The extent to which the students completed the three parts of the mandatory orientation program was determined to be strongly predictive of retention. Since the Library orientation occurs in the first three weeks of the fall semester for all first- time full time students, the University is now planning to flag students for pro-active advising once their Library orientation completion status is determined. Other data reflecting evidence of student engagement was also analyzed and showed varying degrees of validity as retention predictors.
11:20am
Identifying Places for Pedagogical Intervention: A Use Case of the “Point of Originality” Tool
Authors:
Johann Ari Larusson, Academic Technology Architect, Brandeis University
Brandon White, Doctoral Candidate, University of California, Berkeley
Abstract: This paper describes a new tool that enables instructors to perform objective evaluation of student work through the identification of original content in writing. Evidence shows that the tool can be predictive of students' performance in the course, as well as of their engagement in a technology-mediated activity. By visualizing otherwise subjective information in a way that is objectively intelligible, the goal is to provide educators with the ability to monitor student investment in concepts related to the course syllabus, and to extend or modify the boundaries of the syllabus in anticipation of pre-existing knowledge or trends in interest. The paper provides a comprehensive walk-through of the tool’s feature set, and provides possible scenarios depicting how it might be used by instructors regularly throughout a semester.
12:00pm – 1:00pm Lunch
1:00pm – 2:15pm Keynote Malcolm Brown, Director of the EDUCAUSE Learning Initiative
2:15pm – 2:45pm Hands-on Learning Analytics work/exercise
2:45pm - 3:30pm Wrap-up and Results from Hands-on Work
3:30pm End
Registration Cancellation Policy
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