I love that Johannes Klingbiel highlights having his own place on the Internet as a means to learn. While I suspect that part of the idea here is to learn about the web and programming, it's also important to have a place you can more easily look over and review as well as build out on as one learns. This dovetails in part with his third reason to have his own website: "to build". It's much harder to build out a learning space on platforms like Medium and Twitter. It's not as easy to revisit those articles and notes as those platforms aren't custom built for those sorts of learning affordances.

Building your own website for learning makes it by definition a learning management system. The difference between my idea of a learning management system here and the more corporate LMSes (Canvas, Blackboard, Moodle, etc.) is that you can change and modify the playground as you go. While your own personal LMS may also be a container for holding knowledge, it is a container for building and expanding knowledge. Corporate LMSes aren't good at these last two things, but are built toward making it easier for a course facilitator to grade material.

We definitely need more small personal learning management systems. (pLMS, anyone? I like the idea of the small "p" to highlight the value of these being small.) Even better if they have social components like some of the IndieWeb building blocks that make it easier for one to build a personal learning network and interact with others' LMSes on the web. I see some of this happening in the Digital Gardens space and with people learning and sharing in public.

[[Flancian]]'s Anagora.org is a good example of this type of public learning space that is taking the individual efforts of public learners and active thinkers and knitting their efforts together to facilitate a whole that is bigger than the sum of it's pieces.

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Zhou, Dong, and Amir Bashan. ‘Dependency-Based Targeted Attacks in Interdependent Networks’. Physical Review E 102, no. 2 (3 August 2020): 022301. https://doi.org/10.1103/PhysRevE.102.022301.

Jazayeri, A., & Yang, C. C. (2020). Motif Discovery Algorithms in Static and Temporal Networks: A Survey. ArXiv:2005.09721 [Physics]. http://arxiv.org/abs/2005.09721

Della Rossa, F., & DeLellis, P. (2020). Stochastic master stability function for noisy complex networks. Physical Review E, 101(5), 052211. https://doi.org/10.1103/PhysRevE.101.052211

Yu, Y. W., Delvenne, J.-C., Yaliraki, S. N., & Barahona, M. (2020). Severability of mesoscale components and local time scales in dynamical networks. ArXiv:2006.02972 [Physics]. http://arxiv.org/abs/2006.02972