On Mon, Jan 6, 2014 at 12:04 PM, Sameer Verma <sve...@sfsu.edu> wrote: > On Mon, Jan 6, 2014 at 12:28 AM, Martin Dluhos <mar...@gnu.org> wrote: >> On 3.1.2014 04:09, Sameer Verma wrote: >>> Happy new year! May 2014 bring good deeds and cheer :-) >>> >>> Here's a blog post on the different approaches (that I know of) to data >>> gathering across different projects. Do let me know if I missed anything. >>> >>> cheers, >>> Sameer >>> >>> http://www.olpcsf.org/node/204 >> >> Thanks for putting together the summary, Sameer. Here is more information >> about >> my xo-stats project: >> >> The project's objective is to determine how XOs are used in Nepalese >> classrooms, but I am intending for the implementation to be general enough, >> so >> that it can be reused by other deployments as well. Similarly to other >> projects >> you've mentioned, I separated the project into four stages: >> >> 1) collecting data from the XO Journal backups on the schoolserver >> 2) extracting the data from the backups and storing it in an appropriate >> format >> for analysis and visualization >> 3) statistically analyzing and visualizing the captured data >> 4) formulating recommendations for improving the program based on the >> analysis. >> >> Stage 1 is already implemented on both the server side as well as the client >> side, so I first focused on the next step of extracting the data. Initially, >> I >> wanted to reuse an existing script, but I eventually found that none of them >> were general enough to meet my criteria. One of my goals is to make the >> script >> work on any version of Sugar. >> >> Thus, I have been working on process_journal_stats.py, which takes a '/users' >> directory with XO Journal backups as input, pulls out the Journal metadata >> and >> outputs them in a CSV or JSON file as output. >> >> Journal backups can be in a variety of formats depending on the version >> of Sugar. The script currently supports backup format present in Sugar >> versions >> 0.82 - 0.88 since the laptops distributed in Nepal are XO-1s running Sugar >> 0.82. I am planning to add support for later versions of Sugar in the next >> version of the script. >> >> The script currently supports two ways to output statistical data. To produce >> all statistical data from the Journal, one row per Journal record: >> >> process_journal_stats.py all >> >> To extract statistical data about the use of activities on the system, use: >> >> process_journal_stats.py activity >> >> The full documentation with all the options are described in README at: >> >> https://github.com/martasd/xo-stats >> >> One challenge of the project has been determining how much data processing >> to do >> in the python script and what to leave for the data analysis and >> visualization >> tools later in the workflow. For now, I stopped adding features to the script >> and I am evaluating the most appropriate tools to use for visualizing the >> data. >> >> Here are some of the questions I am intending to answer with the >> visualizations >> and analysis: >> >> * How many times do installed activities get used? How does the activity use >> differ over time? >> * Which activities are children using to create files? What kind of files are >> being created? >> * Which activities are being launched in share-mode and how often? >> * Which part of the day do children play with the activities? >> * How does the set of activities used evolve as children age? >> >> I am also going to be looking how answers to these questions vary from class >> to >> class, school to school, and region to region. >> >> As Martin Abente and Sameer mentioned above, our work needs to be informed by >> discussions with the stakeholders- children, educators, parents, school >> administrators etc. We do have educational experts among the staff at OLE, >> who >> have worked with more than 50 schools altogether, and I will be talking to >> them >> as I look beyond answering the obvious questions. >> > > We should start a list on the wiki to collate this information. I'll > get someone from Jamaica to provide some feedback as well. > >> For visualization, I have explored using LibreOffice and SOFA, but neither of >> those were flexible to allow for customization of the output beyond some a >> few >> rudimentary options, so I started looking at various Javascript libraries, >> which >> are much more powerful. Currently, I am experimenting with Google Charts, >> which >> I found the easiest to get started with. If I run into limitations with >> Google >> Charts in the future, others on my list are InfoVIS Toolkit >> (http://philogb.github.io/jit) and HighCharts (http://highcharts.com). Then, >> there is also D3.js, but that's a bigger animal. > > Keep in mind that if you want to visualize at the school's local > XS[CE] you may have to rely on a local js method instead of an online > library. > >> >> Alternatively or perhaps in parallel, I am also willing to join efforts to >> improve the OLPC Dashboard, which is trying to answer very similar questions >> to >> mine. > > I'll ping Leotis (cc'd) to push his dashboard code to github, so we > don't reinvent. >
For those who haven't seen the protoype that Leotis has (demo'd at OLPCSF summit), here it is using mock data. It's a prototype, so be gentle :-) http://108.171.173.65:8000/ cheers, Sameer > cheers, > Sameer > >> >> I am looking forward to collaborating with everyone who is interested in >> exploring ways to analyze and visualize OLPC/Sugar data in a interesting and >> meaningful way. >> >> Cheers, >> Martin _______________________________________________ Server-devel mailing list Server-devel@lists.laptop.org http://lists.laptop.org/listinfo/server-devel