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Online Teaching and Learning Research Seminars

The Online Teaching and Learning Research Seminars program supports multi-institutional research on topics related to college-level online and blended/hybrid teaching and learning. Each year, individual researchers at higher education institutions around the world are invited to apply for one of eight participant spots. Accepted participants will collaborate on research over two academic years including week-long, in-person meetings each summer in Corvallis, OR.

Apply now

 Applications due Nov. 30, 2018

Seminar goals

  • Build community among online teaching and learning researchers from a range of institutions
  • Create space for multi-institutional collaboration and networking around online teaching and learning research
  • Publish research findings to advance the field of online teaching and learning in a range of mediums (peer-reviewed papers, white papers, reports, etc.)

Seminar description

The first cohort of the research seminars program is invited to explore the concept of learning analytics from a systems perspective.

Analytics, or the process of extracting data for application, has been utilized by sciences such as physics and biology since as early as 1970 (Baker & Inventado, 2014). However, the use of analytics for educational purposes, or learning analytics, is more recent, with factors such as an increase in data and improved technology contributing to the recent growth over the past decade. Current learning analytics journals, conferences, and publications present learning analytics as an emerging subfield with projected growth in higher education (e.g. Avella, Kebritchi, Nunn, & Kanai, 2016; Siemens, 2013). The evolving nature of this subfield is evidenced by varying definitions of learning analytics in recent literature (e.g. Siemens, 2013; Viberg, Hatakka, Bälter, & Mavroudi, 2018), though most discussions broadly define learning analytics as the use of large online datasets to improve learning processes (Avella et al., 2016; Brown, 2012). Proponents suggest that learning analytics can transform higher education (online, hybrid, and face to face) at the student, instructor, and institutional level by providing easily accessible data paired with actionable solutions (Siemens, 2013).

As analytics in higher education has become increasingly widespread (Baker & Inventado, 2014), research has supported benefits such as increased understanding of students’ behaviors (e.g. Wong, Li, & Choi, 2018). However, some suggest that analytics efforts are still in “infancy” in educational contexts (Zhang, Zhang, Zou, & Huang, 2018), and research overall has not found sufficient evidence for learning analytics improving outcomes (Viberg et al., 2018). This suggests that additional attention to the development, use, and evaluation of learning analytics across settings (including online and hybrid communities) could benefit learning outcomes in higher education.

Due to the broad skillset involved in the design and application of these programs, past teams who have developed learning analytics in educational environments have been multidisciplinary (Siemens, 2013). Increased discussion and collaboration amongst professionals from varying backgrounds across institutions can move the field of learning analytics forward. For example, while learning analytics can benefit individual instructors as they seek to understand the students in their courses, learning analytics can also benefit institutions as a whole. Through exploring learning analytics from a systems perspective (or analytics at an institutional level) the research seminars program will encourage studies that include various stakeholders involved in the process of implementing and utilizing learning analytics across institutions.

In particular, we are interested in supporting projects that examine:

  • Student engagement with learning analytics (e.g. issues of awareness, privacy, impacts on learning outcomes, etc.)
  • Faculty engagement with learning analytics (e.g. issues of awareness of what data is available, privacy, use of data, data literacy training, needs assessments related to learning analytics, etc.)
  • Learning analytics as behavior analytics (e.g. questions of how learning analytics is defined and what data are being measured and collected, how data informs interventions, etc.)
  • Applied learning analytics (e.g. how data is influencing course design, curriculum development, instructional design practices, etc.)
  • Institutional capacity to support learning analytics (e.g. decision making around platform purchasing, community training on data literacy, leadership use of learning analytics, impacts on institution staffing structures, privacy issues and debates, etc.)

The goal of the Online Teaching and Learning Research Seminars program is to facilitate collaboration within diverse cohorts of scholars and practitioners in higher education. We invite scholars and practitioners representing a range of disciplines to apply.

References

Avella, J. T., Kebritchi, M., Nunn, S. G., & Kanai, T. (2016). Learning analytics methods, benefits, and challenges in higher education: A systematic literature review. Online Learning, 20(2), 13-29.

Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In J. Larusson & B. White (Eds.), Learning analytics (pp. 61-75). New York: Springer.

Brown, M. (2012). Learning analytics: Moving from concept to practice. EDUCAUSE Learning Initiative. Retrieved from http://net.educause.edu/ir/library/pdf/ELIB1203.pdf

Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380-1400.

Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98-110.

Wong, B. T. M., Li, K. C., & Choi, S. P. M. (2018). Trends in learning analytics practices: A review of higher education institutions. Interactive Technology and Smart Education, 15(2), 132-154.

Zhang, J. H., Zhang, Y. X., Zou, Q., & Huang, S. (2018). What learning analytics tells us: Group behavior analysis and individual learning diagnosis based on long-term and large-scale data. Journal of Educational Technology & Society, 21(2), 245-258.

Timeline

Ecampus will support multi-institutional collaborative research on this theme/topic over a two-year period including three one-week summer meetings on the Oregon State University campus.

Summer 2019 (July 15-19, 2019)
Participants will meet to develop research questions plan small team research projects to be conducted throughout the following year.
Summer 2020 (July 13-17, 2020)
Participants will meet to share their initial results, plan data analysis, and plan the research activities for year two.
Summer 2021 (July 26-30, 2021)
Participants will meet to share their results of year two research and plan for the dissemination of results and the continuation of their work.

Seminar leaders

Katie Linder

Katie Linder, PhD
Research Director, Ecampus
Oregon State University

Katie Linder, PhD, is the research director for Oregon State University Ecampus, where she provides leadership in producing original research on online teaching and learning for faculty and administrators. She is the author of The Blended Course Design Workbook: A Practical Guide, and the co-editor of High-Impact Practices in Online Education: Research and Best Practices. She also hosts “Research in Action,” a weekly podcast about topics and issues related to research in higher education

Katie Linder

Rob Nyland, PhD.
Research and Innovation Team Manager
eCampus Center, Division of Extended Studies
Boise State University

Rob Nyland, PhD. is the eCampus Research and Innovation Team Manager at Boise State University, where he leads a team that performs research in online learning, learning analytics, and OER. He has previously worked as a Learning Engineer for Learning Objects, and as a full-time faculty member of Multimedia Design and Production at Lake Washington Institute of Technology. He is a recipient of the 2017-2018 OER Research Fellowship sponsored by the OER Research Group and funded by the William and Flora Hewlett Foundation. He has published articles in such journals as Journal of Computing in Higher Education, International Review of Research in Open and Distributed Learning, and TechTrends.

Seminar logistics

Expenses: Accepted participants collaborate over two academic years, with three one-week in-person summer meetings in Corvallis, OR. Each participant accepted to the program will receive accommodation (including lodging), all meals, as well as a $500 travel stipend for the annual in-person meetings.

Travel and Accommodation: We will provide transportation to/from Portland International Airport (PDX) or Eugene Airport (EUG) and the Oregon State University campus for accepted participants. If you will be driving to the campus, please let us know in advance so we can arrange for a parking permit. Each participant will have a private hotel room at a hotel near Oregon State University’s campus.

Meals: All meals will be provided. Participants will be able to receive modifications for dietary restrictions or accommodations.

About the Ecampus Research Unit: The Ecampus Research Unit conducts award-winning research on online education. Its mission is to make online teaching and learning research actionable.

About Oregon State University: Oregon State University (OSU) is an international public research university that draws people from all 50 states and more than 100 countries. OSU has two campuses, 11 colleges, 15 experiment stations, 35 Extension offices and more than 200 academic programs.

About Corvallis: Corvallis is located in the heart of the Willamette Valley, within 90 minutes of the Portland Metropolitan area, the Oregon coast and world-class skiing. Corvallis has a residential population of more than 58,000.

Application

To ensure a diverse range of perspectives and contexts, participants for the research seminar program will be selected from a range of institution types and disciplinary backgrounds.

Application timeline:

  • Due Date: Nov. 30, 2018
  • Notification date: Dec. 17, 2018

To apply to be participant in the Ecampus Research Seminars program, complete the application and additional materials described below. In addition to an abbreviated CV and letter of support from a department/unit head, applicants are also required to include the following information:

  1. Research Interests
    Describe your interests in this year’s seminar topic including any specific area of this topic that you are most interested in examining. Note: we are not asking for specific research questions since those will be developed in this program. (200 words max)
  2. Professional experience
    Describe how this year’s seminar topic fits within your existing professional/scholarly work? (200 words max)
  3. Institutional context
    1. Describe your position within the context of your institution.
    2. Describe your involvement with online teaching and learning at your institution.
    3. Describe the current number and/or scale of online courses and programs at your institution.
    4. Describe how you are involved in learning analytics at your current institution?

    (300 word max)

  4. Demographic variables
    Are there any demographic or background variables that are relevant to your interest in this year’s seminar topic? If yes, please describe. (200 word max)
  5. Research Methods
    1. Describe your experience with research methodology.
    2. Which research methods do you anticipate would be helpful in exploring this research topic? (regardless of your experience with the methods).
    3. Which research methodologies would you need training or support in prior to implementation?

    (300 words max)

  6. Potential contributions
    Describe your unique expertise and/or experience that you would bring to the study of this year’s seminar topic. (200 words max)

Apply now

 Applications due Nov. 30, 2018

Questions?

Please direct your questions about the ECRU Research Seminars to Katie Linder, director of Ecampus Research Unit.