Technology, Knowledge and Learning

, Volume 21, Issue 1, pp 143–149 | Cite as

Experience API: Flexible, Decentralized and Activity-Centric Data Collection

  • Jonathan M. Kevan
  • Paul R. Ryan
Emerging Technology Report


This emerging technology report describes the Experience API (xAPI), a new e-learning specification designed to support the learning community in standardizing and collecting both formal and informal distributed learning activities. Informed by Activity Theory, a framework aligned with constructivism, data is collected in the form of activity statements with the flexibility to describe a wide array of learning experiences from museum exhibits to learning environment interactions. Fast adoption by private sector tool developers and the majority of learning management systems used in academia suggests the specification may have long-term implications. This report summarizes major educational research opportunities and key challenges to implementation.


Alternative assessment Constructivism Activity theory Experience API xAPI Tin Can API Learning management system Virtual learning environment 


  1. Advanced Distributed Learning. (2013). xAPI-Spec. Retrieved from
  2. Advanced Distributed Learning. (2015a). Case studies and adopters. Retrieved from
  3. Advanced Distributed Learning. (2015b). Research and development focus. Retrieved from
  4. Advanced Distributed Learning. (2015c). xAPI community of practice overview. Retrieved from
  5. Berking, P., & Gallagher, S. (2014). Choosing a learning management system (No. 3.13) (pp. 1–117). Advanced Distributed Learning.Google Scholar
  6. Berland, M., Baker, R. S., & Blikstein, P. (2014). Educational data mining and learning analytics: Applications to constructionist research. Technology, Knowledge and Learning, 19(1–2), 205–220. doi: 10.1007/s10758-014-9223-7.CrossRefGoogle Scholar
  7. Book, P. A. (2014). All hands on deck: Ten lessons from early adopters of competency-based education. Boulder, CO: WICHE Cooperative for Educational Technologies. Retrieved from
  8. Bottom-Line Performance. (2014). Knowledge guru: Game-based learning platform. Retrieved from
  9. Bozalek, V., Ng’ambi, D., Wood, D., Herrington, J., Hardman, J., & Amory, A. (2015). Activity theory, authentic learning and emerging technologies towards a transformative higher education pedagogy. New York, NY: Routledge.Google Scholar
  10. Dahlstrom, E., Brooks, D. C., & Bichsel, J. (2014). The current ecosystem of learning management systems in higher education: Student, faculty, and it per spectives. Research report. Louisville, CO: ECAR, September 2014. Available from 2014 EDUCAUSE.CC by-nc-nd Retrieved from
  11. Drachsler, H., & Greller, W. (2012). Confidence in Learning Analytics. Retrieved from
  12. Duggan, M., & Smith, A. (2014). Social media update 2013. Retrieved from Pew Research Center:
  13. Engeström, Y. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of Education and Work, 14(1), 133–156. doi: 10.1080/13639080020028747.CrossRefGoogle Scholar
  14. Glahn, C. (2013, September). Using the ADL experience API for mobile learning, sensing, informing, encouraging, orchestrating. In next generation mobile apps, services and technologies (NGMAST), 2013 Seventh International Conference, IEEE 268–273.Google Scholar
  15. Glowa, L. (2013). Re-engineering information technology design considerations for competency education. A Competencyworks Issue Brief, International Association for K12 Online Learning.Google Scholar
  16. Groom, J., & Lamb, B. (2014). Reclaiming innovation. EDUCAUSE Review, 49(3).Google Scholar
  17. Jonassen, D. H., & Land, S. M. (1999). Theoretical foundation of learning environments. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  18. Jonassen, D. H., & Ronrer-Murphy, L. (1999). Activity theory as a framework for designing constructivist learning environments. Educational Technology Research and Development, 47(1), 61–79.CrossRefGoogle Scholar
  19. Kitto, K., Cross, S., Waters, Z., & Lupton, M. (2015). Learning analytics beyond the LMS: The connected learning analytics toolkit (pp. 11–15). Newyork: ACM Press. doi: 10.1145/2723576.2723627.Google Scholar
  20. Kroner, G. (2014). LMS data—the first year update. Retrieved from
  21. Kuutti, K. (1996). Activity theory as a potential framework for human-computer interaction research. In B. Nardi (Ed.), Context and consciousness: Activity theory and human-computer interaction (pp. 17–44). Cambridge, MA: MIT Press.Google Scholar
  22. Lim, C. P. (2002). A theoretical framework for the study of ICT in schools: A proposal. British Journal of Educational Technology, 33, 411–421.CrossRefGoogle Scholar
  23. MacNeill, S., & Kraan, W. (2011). Distributed learning environments. JISC CETIS. Google Scholar
  24. Megliola, M., De Vito, G., Sanguini, R., Wild, F., & Lefrere, P. (2014). Creating awareness of kinaesthetic learning using the Experience API: current practices, emerging challenges, possible solutions. In: CEUR Workshop Proceedings (Vol. 1238, pp. 11–22).Google Scholar
  25. Mwanza, D., & Engeström, Y. (2005). Managing content in e-learning environments. British Journal of Educational Technology, 36(3), 453–463.CrossRefGoogle Scholar
  26. Prinsloo, P., & Slade, S. (2013). An evaluation of policy frameworks for addressing ethical considerations in learning analytics. Third conference on learning analytics and knowledge (LAK 2013), 8–12 April 2013 (pp. 240–244). Belgium, Leuven: ACM.Google Scholar
  27. Richey, R. C., Klein, J. D., & Tracey, M. W. (2011). Chapter 8: Constructivist design theory. In: The instructional design knowledge base. New York, NY: Routledge.Google Scholar
  28. Schmitz, H. C., Wolpers, M., Kirschenmann, U., & Niemann, K. (2011). Contextualized attention metadata. In C. Roda (Ed.), Human attention in digital environments (pp. 186–209). Cambridge: Cambridge University Press.Google Scholar
  29. Silvers, A. (2014). Answers: How do I get started with xAPI? [Web log post]. Retrieved from
  30. Suthers, D., & Rosen, D. (2011). A unified framework for multi-level analysis of distributed learning. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, 64–74.Google Scholar
  31. Verbert, K., Manouselis, N., Drachsler, H., & Duval, E. (2012). Dataset-driven research to support learning and knowledge analytics. Journal of Educational Technology & Society, 15(3), 133–148.Google Scholar
  32. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge: Harvard University Press.Google Scholar
  33. Watson, W. R., & Watson, S. L. (2007). What are learning management systems, what are they not, and what should they become? TechTrends, 51(2), 28–29.CrossRefGoogle Scholar
  34. Wild, F., Mödritscher, F., & Sigurdarson, S. (2008). Designing for change: Mash-up personal learning environments. eLearning Papers, 9. Retrieved from
  35. Wilson, S., Liber, O., Johnson, M., Beauvoir, P., Sharples, P., & Milligan, C. (2006). Personal learning environments: challenging the dominant design of educational systems. In: E. Tomadaki & P. Scott, Innovative approaches for learning and knowledge sharing. Paper presented at EC-TEL 2006 Workshop (173–182).Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Distance Course Design and ConsultingUniversity of Hawaii at ManoaHonoluluUSA

Personalised recommendations