Evidence Based Design, Rooted in Cognitive Science
Acrobatiq is privileged to have deep roots in cognitive science and online learning research from Carnegie Mellon’s Open Learning Initiative (OLI).
As we develop new courses and innovative approaches to using learning data to improve learning outcomes, we will continue to partner with OLI on research, and to bring those exciting new findings to market.
Acrobatiq will collaborate with other research organizations as well, such as the Pittsburgh Science of Learning Lab. And in keeping with OLI’s tradition, academic researchers conducting experiments in online learning will have access to Acrobatiq’s technology platform at no cost.
Highlights of OLI Research Findings
Acrobatiq’s adaptive, data-driven courseware is the first in a new generation of interactive and comprehensive learning solutions that draws on the success of more than a decade of research from Carnegie Mellon University’s Open Learning Initiative.
Based on the Science of Learning, Supported by Evidence
Since 2001, OLI has been at the forefront of scientifically-based research on the impact of online learning environments on student success. Results at multiple institutions point to accelerated learning, reduced student attrition and significant correlations between learning activities and learning gains. The following studies highlight a few of the research findings:
Faster learning in hybrid courses
The Open Learning Initiative: Measuring the effectiveness of the OLI statistics course in accelerating student learning. Journal of Interactive Media in Education. Marsha Lovett, Oded Meyer, & Candace Thille, 2008.
Researchers sought to determine if students using the Statistics course would learn at a different pace than students in a traditional face-to-face course format. Results exceeded expectations. Students completed the OLI Statistics course in 8 weeks, with 2 class meetings per week, while students in the face-to-face format completed the course in 15 weeks, with 4 class meetings per week. Although OLI students spent no more time studying statistics outside of class than their traditional peers, they demonstrated learning outcomes that were as good or better than those of their peers. They also retained the information in tests 1+ semester later.
Reduced time to completion and cost savings at multiple institutions
Interactive Learning Online at Public Universities: Evidence from Randomized Trials, William G. Bowen, Matthew M. Chingos, Kelly A. Lack, & Thomas I. Nygren, 2012.
Non-profit research organization Ithaka S+R compared a hybrid version of the Statistics course with a traditional face-to face Statistics course using randomly assigned students at six public universities. Students in the hybrid format had comparable or better learning gains and took 25% less time to achieve the same outcomes. Managing Director of Ithaka S+R, Deanna Marcum wrote, “The results of this study are remarkable; they show comparable learning outcomes for this basic course, with a promise of cost savings and productivity gains over time.”
Multiple courses, faster completion, and improved learning outcomes
Open Learning Initiative Courses in Community Colleges: Evidence on Use and Effectiveness. Julia Kaufman, Sarah Ryan, Candace Thille & Norman Bier, 2013.
In a major study involving several OLI courses used in U.S. community colleges, students using the courseware covered 33% more content in the same time as their peers in traditional courses and achieved a 13% learning gain, compared to 2% by peers in traditional face-to-face courses.
For more information on our ongoing courseware efficacy research, please see the research links below. If you, or your institution, is interested in participating in research projects focused on collecting, measuring, and reporting on students’ learning using online courseware, please contact us.
In 2007, Carnegie Mellon conducted a series of “do no harm” studies with the OLI statistics course. The studies show that students using the OLI course, as an online course with minimal instructor contact, performed as well or better than students in traditional instructor-lead classes.
This 2011 study conducted by ITHAKA, a nonprofit research organization, demonstrates the same results using the OLI statistics course outside of Carnegie Mellon—in several large public institutions. Learn More.
OLI STUDY ON ACCELERATING STUDENT LEARNING WITH OLI STATISTICS
This study, conducted at Carnegie Mellon University, shows that students using the OLI statistics course at Carnegie Mellon achieved the same or better learning outcomes as students in the traditional course in half the time.
Lovett, M., Meyer, O., & Thille, C. (2008). The Open Learning Initiative: Measuring the effectiveness of the OLI statistics course in accelerating student learning. Journal of Interactive Media in Education.
Additional Publications From the Research Team at The Open Learning Initiative
- Bier, N., Lovett, M., & Seacord, R. (2011). An Online Learning Approach to Information Systems Security Education.Proceedings of the 15th Colloquium for Information Systems Security Education. Fairborn, OH: CISSE.
- Thille, C. (2010). Educational Technology as a Transformational Innovation. The White House Summit on Community Colleges Conference Paper.
- Thille, C. & Smith, J. (2010). Learning Unbound: Disrupting the Baumol/Bowen Effect in Higher Education. Futures Forum. American Council on Education 2010.
- Steif, P. S. & Dollár, A. (2009). Web-based Statics Course: Study of Usage Patterns and Learning Gains. Journal of Engineering Education, 98, 321-333.
- Bajzek, D., Brooks, J., Jerome, W., Lovett, M., Rinderle, J., Rule, G. & Thille, C. (2008). Assessment and Instruction: Two Sides of the Same Coin. In G. Richards (Ed.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2008 (pp. 560-565). Chesapeake, VA: AACE.
- Davenport, J., Yaron, D., Klahr, D., & Koedinger, K. (2008). When do diagrams enhance learning? A framework for designing relevant representations. International Conference of the Learning Sciences, 2008.
- Davenport, J., Yaron, D., Klahr, D., & Koedinger, K. (2008). When do diagrams enhance science learning? First Annual Inter-Science of Learning Center Conference.
- Dollár, A. & Steif, P. S. (2008). An interactive, cognitively informed, web-based statics course. International Journal of Engineering Education, 24, 1229-1241.
- Jerome, W., Rinderle, J. & Bajzek, D. (2008). Tools for Constructing Targeted Feedback in Online Instruction. In G. Richards (Ed.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2008 (pp. 3753-3759). Chesapeake, VA: AACE
- Thille, C. (2008). Creating open learning as a community based research activity. In Iiyoshi, T. & Kumar, V. (Ed.), Opening Up Education: The Collective Advancement of Education through Open Technology, Open Content, and Open Knowledge. Cambridge, MA. MIT Press.
- Dollár, A. & Steif, P.S. (2007). Enhancing traditional classroom instruction with a web-based statics course. Frontiers in Education, Milwaukee, Wisconsin, October 2007
- Easterday, M.W., Aleven, V., & Scheines, R. (forthcoming). Tis better to construct than receive: The effects of diagramming tools on learning to analyze social policy. Proceedings of 13th International Conference on Artificial Intelligence in Education (AIED- 2007).
- Pagliano, O., Brown, W. E., Rule, G., & Bajzek, D. (2007) Improving animation tutorials by integrating simulation, assessment, and feedback to promote active learning. Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. Reprinted with permission of AACE (http://www.aace.org).
- Arnold, A., Scheines, R. & Beck, J. E. (2006). Feature discovery in the context of educational data mining: An inductive approach. Proceedings of the AAAI2006 Workshop on Educational Data Mining, Boston, MA.
- Bajzek, D., Burnette, J. & Rule, G. (2006). Constructing computer models to provide accurate visualizations and authentic online laboratory experiences in an introductory biochemistry course. In G. Richards (Ed.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2006 (pp. 14-19). Chesapeake, VA: AACE.
- Brown, W. E., Lovett, M., Bajzek, D., & Burnette, J. M. (2006). Improving the feedback cycle to improve learning in introductory biology using the digital dashboard. Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. Reprinted with permission of AACE (http://www.aace.org).
- Arnold, A., Scheines, R., Beck, J., & Jerome, B. (2005). Time and attention: Students and tasks. AAAI-05: Educational Data Mining, Technical Report WS-05-02 AAAI Press.
- Scheines, R., Leinhardt, G., Smith, J., & Cho, K. (2005). Replacing lecture with web-based course materials. Journal of Educational Computing Research, 32, 1, 1-26.
- VanLehn, K., Lynch, C., Schulze, K., Shapiro, J., & Shelby, R. (2005). The Andes physics tutoring system: Five years of evaluations. Proceedings of the 12th International Conference on Artificial Intelligence in Education. 2005.
- Wheeler, W., D. Danks, J. Ramsey, R. Scheines, J. Smith, & A. Thompson, (2001), Developing and deploying online courses with Jcourse. Proceedings of the Association of the Advancement of Computing in Education (AACE).