A Place to Practice and Reflect on BYOD4L

Cross posted from My Work Blog

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The fourth iteration of the short course Bring Your Own Devices for Learning (#BYOD4L) started today and as this will be my third iteration, I have decided to volunteer as a participant and mentor. The course is hosted on WordPress at byod4l.wordpress.com and it can also be followed by watching hashtag #byod4l on Twitter and other social networks. You can also contribute by joining the BYOD4Learning Community pages on Google+.

As for my personal plans, I am planning to use a OneNote Class Notebook (link) with at least one of my classes this semester. Therefore, as a way of learning the features of OneNote myself, particularly in the context of Bring Your Own Device (BYOD), I decided to use it as a place to publish my reflections and to share it with the whole community. Here’s the link: https://goo.gl/cx4dHM

QR Code to BYOD4L Shared OneNote Notebook
QR Code to BYOD4L Shared OneNote Notebook

It’s possible to collaborate within a OneNote notebook, so contact me @cpjobling (Twitter) or +ChrisJobling (Google+) if you want write access to this resource.

What’s new?

You may have noticed some differences to Fresh and Crispy since your last visit. The most significant is that my blogging platform is now Ghost rather than WordPress. I’m also now hosting my domain on DigitalOcean rather than CastIron coding. This means that I have my stuff on a complete virtual machine rather than space on a shared server.

I’ll be gradually moving my other resources over to my new domain over the next few weeks.

DALMOOC architecture – Reflections after Two Weeks

My personal view after two weeks:

  • edX – enrolment and discussion forum and the certification of learning via self-assessment (thanks to Matt Crosslin (@grandeped) for the clarification).
  • Course content … seems to be hosted outside edX in a WordPress blog.
  • Visual syllabus … not sure that it adds much but it looks nice.
  • Dual layer MOOC – more confusing than helpful — at least at first.
  • ProSolo – as the prime aggregator for the course it’s flawed; many of the daily digested materials are off-topic because it’s a contributor’s whole blog (and optionally comments) feed that is aggregated rather than posts tagged DALMOOC. As an engine for “social competencies” and peer assessment I think ProSolo may have some potential but I’m not convinced that my data is portable or that as a social space it’s better than the social networks where I’m already established.
  • Quick Help … maybe useful but I’ve not received any help from it yet and it’s tied to the edX forum so if you choose to work on the cMOOC layer it’s of limited use.
  • Agent mediated pair chatting in Bazaar with random pairing from a “lobby” which you have to turn up for at a particular time …! I appreciate the benefits and power of group work and the difficulties of achieving some form synchronous engagement across global timezones, but I’m sure that this is one way that I’d never choose for myself. Maybe that’s my British reticence compounded by my Yorkshire dourness.
  • Assignment bank … good idea stolenborrowed from DS106 but some of the assignments are a bit too difficult for people starting out.
  • Using the enrolled students as a captive research study. This is fairly standard for EduMOOCs but can still be a bit unnerving. To be fair, DALMOOC makes no secret of the fact that it’s happening and you can opt out once it was made clear that granting your permission to be observed wasn’t a pre-requisite of joining the course.
  • Using the enrolled students as beta testers … a bit naughty and potentially frustrating when the tools need that beta testing!
  • Giving students access to tools that they could never afford to use in their daily practice … nice but somewhat pointless. The free and open source tools may be harder to use but will at least be available to us to use when we are data analytics experts at the end of the course.

Having done one or two of these cMOOCs before, I’m perhaps more comfortable than some in sampling the facilities on offer and rejecting and moving on from those that do not add personal value. It’s still unfortunately the case that online courses are places that you have to go to for content, interaction and engagement. This one is unique in that it has more “centres of activity” than most!

So what do I do? I watch the videos, but mostly fail to read the readings. I try to attend the hangouts (or watch the recordings as soon as I can afterwards) because in a cMOOC these tend to be the main meeting/orientation points for the course. I tryfail to create artefacts that I share via my blog and twitter. I comment on tweets and blogs when I can. I take the assignments as suggestions and don’t feel that I need to do them allhaven’t attempted any of them. I’m happy to self-assess and don’t need peer or tutor assessment of my competencies.

What don’t I do? My mail client hasn’t been trained yet to surface the Sunday Email so I don’t read that! I ignore the daily emails and their equivalent on edX — primarily because of the issues with aggregation mentioned above. I don’t refuse to do the pre-course or post-course evaluations. I dislike receiving course evaluations as a teacher, and as a student I can appreciate why being asked to fill these in would not inspire positive feelings towards the course (or teaching) being evaluated.

Most importantly perhaps, I don’t worry about missing anything and needing to catchup.

In summary, if I leave this course having expanded my Personal Learning Network and learned a bit about the tools and techniques of Data Analytics for Learning, it’ll have been time well spent. If not, it’s cost nothing!

Local Barriers to Data Analytics for Teaching

The biggest barrier to exploiting data analytics for teaching and learning at my institution is lack of access to the actual data. The useful stuff that we are required to analyse and reflect on is packaged for us either in PDF reports or as unstructured tables on web pages. Presumably this is done to make our analysis easier, but it also has the effect of aggregating and filtering the data into forms that the University finds useful, or assumes that we will find useful, or perhaps are most useful for national statistics agencies. Unfortunately this makes drilling into the data difficult and limits the opportunities to gain new insights that access to the raw data would afford.

As a small experiment, I tried to copy some data, presented to me on the University’s Intranet as an HTML page containing numerous tables, and paste that general statistical information into an excel spreadsheet. I then tried to load that data into (Google) OpenRefine and Tableau. Both tools take the first table as their basis and a great deal of additional work would be required to get this into a form that would allow the analysis features to come into play.

This convinces me that the first stage of the data analysis cycle, getting the data into a structured format that can be used for analysis, will be a considerable challenge.

I know that the information comes out of a students record system (essentially a relational database) because one of the statistics pages documents the SQL queries that generate the data. Why this information cannot be sourced as a CSV endpoint (as some data such as class enrolments are) is an interesting question that I intend to ask.

On a positive note, senior management has heard of data analytics and is keen to exploit it to improve student outcomes. The problem is that because the data is in closely guarded silos distributed across the institution, they are vulnerable to the persuasive patter of the smart salesman who comes a-calling telling us that are problems are so unique that the only way forward is an expensive data analysis tool or a customised plugin in for the managed learning environment.

“putting powerful tools into the hands of individuals who might not quite understand them yet” (@psychemedia) is probably something that only the most enlightened university manager would dare to do.