Showing posts with label ecove. Show all posts
Showing posts with label ecove. Show all posts

Thursday, May 24, 2012

classroom observation software

Two comments (1 recent) on video analysis software, a post for end of 2009, recommend the use of ‘classroom walk through’ software to collect, archive and complete interim analysis of class room based observations. The two are ecove and observe4success. Both require download of specialised software to assist with the archiving and analysis of classroom observations.

I had a look through itunes apps on my ipad and find there are quite a few software tools out there for classroom observations, with ipad app options to link data collected on the ipad with PC resident main archive. Examples include classroom mosaic, ecove – general, special ed., administrator, esl.,  assessa+/ faculty tools,  reflect live,  lessonnote and tower mobile / randa tower. Most ipad apps are free but will only really work if they are synched to the PC or Mac based central repository. Therefore, the apps are for ease of data collection.

In the main, the tools revolve around checklists and collation methods for later discussions with indvidual teachers or for comparisons of teachers' classroom teaching across subject or year levels. I can work out that the tools will provide for consistency of data gathering. However, in professional development for teaching, it is the 'conversation' and reflection on the data that are important rather than the actual quantitative findings from how software collects and collates the data. The tools can also be useful for research data collection. But again with proviso to ensure it augments qualitative data, for example videos of class activities.

Seeing these tools are being now used in a 'mobile learning' way does provide some good ideas on how to use similar approaches to help students learn. They provide for a means for students to gather data from field trips, labs, practical workshops etc. and have the data collated for later followup, discussion, analysis etc.

Monday, September 21, 2009

Video analysis software for multimodal data analysis

While browsing through literature on multi-modal analysis, I came across studiocode as a video data analysis software tool. I then asked around CPIT and found out the sports science people were using a NZ developed product called silicon coach which is developed specifically to analyse sports performances but also provides capabilities for comparison of individual performances and to build up resources based on annotations made on videos. Many video analysis software has a sports orientated slant as this is where it is most useful for analysing the performance of athletes.

I then did the usual google search and came up with a short article which recommended four video data analysis tools including studiocode (Mac OS only). The other three are annotation which is only Mac based but seemed to have an attractive, user friendly interface for US$299; ecove with a byline of software for gathering data while observing behaviour, runs also on Palm OS & Pocket PCs for US$189; & Observer xt which has both Mac & Windows versions plus a version for mobile devices, seems to have all the bells & whistles (like studiocode).

A comprehensive list of qualitative data analysis software provided over thirty examples with about a third capable of video and audio analysis. These include:-

Transana which is developed by the University of Wisconsin and open source and cost US$50 for single user and US$500 per project.

Dart fish which provides a free download trial for 30 days

Atlasti which is a standard qualitative data analysis provides for multimedia coding and supposed to be similar to nVivo.

Hyperresearch $399 as another alternative to the more expensive sports based video analysis tools.

A couple which are freeware to have a look at include Elan and signstream.

So plenty of choice for the moment, the most likely ones will need to be evaluated against nVivo. I am looking for one which will be easy to use as one of the goals of implementing multi-modal analysis protocols for observing teaching & learning at CPIT is to devolve the analysis to tutors.