It’s Personal

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I’m learning a valuable lesson this week. Don’t make a general statement in a piece of writing without backing it up with research. Be able to verify where an idea or stance comes from – on who’s shoulders do you stand when you say something.

The statement I made, in haste, but reflected from many years of reading about the topic, relates to the personalization of learning. Yet, I did not defend that statement with supporting documentation. Here’s my effort to correct that omission, and learn from the lesson.

First, the ‘call out’ on my error of omission. “You mentioned personalized learning as a current argument in education, “particularly with technology’s role in this personalization, with a push/pull relationship between the human behind the personal OR the big data analytics behind the personalization.” Do you have references to support this statement?”

I took some time to push away from this question, to contemplate my omission, and then pull myself back to the task of rectifying this error.  This post is an effort to make a defence, of sorts, with a hope that this will connect to future areas of research.

  • First, I reviewed the references for this specific differentiation between personal and personalization. It primarily derives from writing by Stephen Downes (2016) in a blog post titled Personal and Personalized Learning, where he lays out the observable differences. Downes contends

“it may be preferably to embrace an alternative to personalized learning, which might be called personal learning. In the case of personal learning, the role of the educational system is not to provide learning, it is to support learning. Meanwhile, the decisions about what to learn, how to learn, and where to learn are made outside the educational system, and principally, by the individual learners themselves.”

  • This view is further developed with readings from ISTE around defining personalization with a focus on the use of educational technology (ed tech). While Bayse (2018) suggests that “in the case of personalized learning, allowing students to make suggestions and control their own academic experiences”, I would suggest that is not necessarily the case in the future learning environments suggested by these companies marketing personalized learning.

While these first references identify the shift in perspective required for personal learning to occur, they do not identify how technology in education and ed tech companies are pushing the personalization of learning with the integration and perceived need for learning analytics.

  • The New Media Consortium Horizon Report in 2013 presents information about the impact of learning analytics in higher education. With big data comes bigger surveillance, as this report suggests.

“Sophisticated web tracking tools within these settings already can track precise student behaviors, recording variables such as number of clicks and time spent on a page, and increasingly more nuanced information such as resilience and retention of concepts. Inclusion of behavior-specific data adds to an ever-growing repository of student-related information, making the analysis of educational data increasingly complex.” (NMC Horizon Report Higher Education Edition, 2013, p. 25)

This particular view of how ed tech and learning analytics are being integrated into the ethos of higher education teaching and learning sounds like it’s a good thing, but there is an alternative viewing student learning as a compilation of clicks and time spent.

  • Over the years, I have read and reflected on the work of Diane Oblinger, who has written extensively about the integration of technology into higher education teaching and learning. In a recent Educause Review article, Oblinger (2018) states “Machine learning allows computers to “consume” information such as medical records, financial data, purchases, and social media and then develop predictions or recommendations.” While the notion of personalization is not at the forefront of Oblinger’s statement, there are implications for education when machine learning develops recommendations for student learning activities. Oblinger (2018) furthers my thinking by stating that although  “the thought of tasks being performed by a machine can be disquieting, who performs the task is less important than the outcome. Is the task done better by “man” or “machine”? Robots can be more precise and reliable in advanced manufacturing or medicine, for example.”

Will this become true in education as well? While there is some ‘evidence’, there is an organization focused on research specifically in the area of learning analytics, as seen from Siemens’ information about the Society of Learning Analytics Research.

  • This is contrasted by the writing of Audrey Watters, who’s publications prompt deeper thought about technology in teaching and learning. Watters’ recent contribution in the foreward in An Urgency of Teaching by Morris, S. M. & Stommel, J. (2018), states

“We all spend much of our day now clicking on things, a gesture that is far too often confused with “engagement.” (“Engagement” — a word that has come to mean “measurable” and “marketable.”) And because students now spend much of their time clicking on things — and in turn, generating incredible amounts of data — teachers and administrators are told they must pour through these machine-generated signals, an action that is far too often confused with “care.”

This compares to the click counting and time on task perspective of student learning presented by the NMC Horizon Report above – neither will determine when learning has occurred.

Deeper learning and long term memory of topics is facilitated through human interactions, hospitality in the classroom, conversations that reveal misconceptions and shape understanding, and the interactions with ‘human – others’.

References

Bayse, D. (2018). Personalized vs. differentiated vs. individualized learning. International Society for Technology in Education (ISTE). Retrieved from https://www.iste.org/explore/articleDetail?articleid=124

Downes, S. (2016). Personal and personalized learning. [weblog]. Retrieved from https://www.downes.ca/cgi-bin/page.cgi?post=65065

New Media Consortium. (2013). Horizon Report 2013 Higher Education Edition. Retrieved from http://www.nmc.org/pdf/2013-horizon-report-HE.pdf

Oblinger, D. (2018, August 27). Smart machines and human expertise: Challenges for higher education. Educause Review, 53(5). Retrieved from https://er.educause.edu/articles/2018/8/smart-machines-and-human-expertise-challenges-for-higher-education

Siemens, G. (2012, April). Learning analytics: envisioning a research discipline and a domain of practice. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 4-8). ACM. SoLAR, (n.d.). About. Society for learning analytics research. Retrieved October 1, 2013, from http://www.solaresearch.org/mission/about/

Watters, A. (2018). Foreward. In Morris, S. M. & Stommel, J., An urgency of teachers. Pressbooks. Retrieved from https://criticaldigitalpedagogy.pressbooks.com/front-matter/forward/