Workshop Description
                                    Workshop Chairs
Much of the research in LAK to date has been “student facing”, that is, using data to better
understand learners and their need or to create interventions that directly support or
influence learners. This workshop takes the perspective on how Learning Analytics can drive
improvements in teaching practices, instructional and curricular design, and academic
program delivery. While this does influence student outcomes in the long term, the data
gathered and evidence generated is more instructor and administrator facing. We have seen
examples of how LAK can help build the case for instructional, curricular, or programmatic
change and further how LAK can be used to foster acceptance of change processes by
teachers, administrators, and other stakeholders in the educational enterprise. When
successful, these kinds of changes are often associated with educational reform or culture
shifts in educational practice.

This workshop offered those in the LAK community an opportunity to share and explore how
educational data, its analysis and visualization, and the evidence derived can change/improve
the context of learning. The main research and practice questions addressed in this workshop
were:
    • How to provide relevant and actionable information to faculty, teaching assistants,
       departmental and college administrators to encourage a greater emphasis on student
       learning and use of evidence-based practices, thus encouraging a continuous
       improvement approach to teaching and learning.
    • How to create visualization and data collection tools and approaches that encourage
       a community of instructors and administrators to engage in making evidence-based
       decisions to improve student learning whether at the activity, lesson, course, series,
       department, college or university-wide levels.
    • How to extract information from the multiple modalities used in instructional
       environments and help capture, represent and evaluate faculty instructional
       approaches, student-faculty engagement, student-student interactions and student-
       technology interactions.
    • How to represent, summarize and mobilize data from human interactions and
       student-technology interactions to motivate change and quality improvement. Is
       there a way to make the data and representations more useful for promoting
       sustainable change?
    • How to change the evaluation of instructional activities to be more formative,
       actionable and multi-dimensional in nature, emphasizing individual and group
       improvement rather than a one-size fits all student survey by which instructors or
       courses are judged and compared. Ideally such evaluation systems would go well
       beyond student satisfaction as the sole measure of good teaching and should include
       learning outcomes, utility of outcomes, applicability to future learning, match or fit
       between learner and instructor, and more.
    • How can analytics help the individual instructor to examine the success of a course
       that they teach? By including the analysis of individual courses we will keep the
       interest of all instructors, and not just those concerned with larger questions of course
       sequences and curricula. Curricula are built of individual classes of course, and campus
      authorities at all levels need tools for examining the success and impact of individual
      courses.

Nine submissions were received for the workshop. After being reviewed by the program
committee, seven of those papers were accepted for presentation at this Workshop.