Here are the slides from the 2013 CoSN presentation. This was a presentation compiling and summarizing projects for CoSN from students in Chris Dede's fall 2013 class at the Harvard Graduate School of Education. In addition, here are links to as well as individual slide decks from each of the teams. These contain additional details that we could not cover in the CoSN presentation. Conference Presentation Slides:

CoSN 2012 Presentation & Info Gathering - Help us out

Chris Dede, Alex Drier, and Heidi Larson presented the result of their work since the 2011 presentation. Come see the slides, and help us gather information by responding to the surveys below.

Slides: http://go.edc.org/CoSN-EDC-Harvard-2012

Survey on Mobile Use: http://go.edc.org/MobileDevices2012

Survey on your perspectives on Twitter Chats: http://go.edc.org/Twitter

ETLO Moodle Course environment:
http://moodle.etlo.org
cosn12/ cosn12
Mobile site button (top right)
Select “Cell Phones as Learning Tools”
Click on “Session One (Mobile)” link
To view Session One directly:
http://bit.ly/xH29T3

Thanks for Signing up!

Evaluation: http://go.edc.org/MobilePDEval-UsingData
Please complete our final evaluation even if you did not participate or stopped participating. This will help us to determine what worked, what didn't, and how we might improve upon the experience in the future.

Thank you! Thanks for signing up for our pilot using mobile devices as the vehicle for a PD experience. We appreciate your time and willingness to give this a try. We learned a lot, and we hope you did, too! We'll watch for you on Twitter and hope to work with you again.

Thank you Chris Dede, Ellen Mandinach, and Diana Nunnaley! We couldn't have done this without you. You can continue to receive insights from Diana & practical tips by subscribing to her blog: http://usingdata.terc.edu/.

Heidi Larson, Alex Dreier, and Kirsten Peterson
Education Development Center
http://edc.org/

Students–Partners in Formative Assessment Process

Research shows significant impact on student learning when classroom teachers routinely provide formative assessment feedback to students. The effect sizes of the impact of this practice are at the top of the list of what we can do to increase student learning at all levels.

And yet when discussing formative assessment with groups of teachers, the most common practice describes formative assessment as an event, not a process. In one formative assessment institute conducted with middle school science teachers, they were initially reluctant to design and administer a formative assessment probe until after they had done some instruction or review of the topic at hand. They were still very much in the mode of feeling the pressure to prepare students for any assessments rather than viewing this as an on-going process of checking for understanding – a process that continues throughout daily lessons and over time during coverage of any unit of instruction.

Moving toward the view of "formative assessment" as similar to what the batting coach does when hitters step into the cage to take practice swings or stand at the plate to meet the pitcher's ball opens the door to great insights about the other types of data we might collect during this process. How the coach tells the batter about how close or far they are from the best swing is also part of the art. What can we borrow from their techniques?

Structures to Support Effective Data Use

The human structures are the most essential element to high capacity data use. Carefully building a culture of trust where teams or groups of teachers take collective responsibility for their students' learning is where leadership needs to put it's energy and planning. Collaboration, the kind that can drive inquiry doesn't just happen. It does require knowledgeable facilitation or we can fall into the trap of many –we can make the data line-up to support what we already believe. Learning how to ask the right questions and check assumptions with data is at the heart of effective data use. And this kind of data use requires that good research becomes part of the data.

Right up there with need for the human structures is the need for a "structured process" for analyzing the data. In working with data leaders from several districts around the country who were nominated to participate in a project led by APQC in Houston, one of key elements of their successful interrogation of the data, was giving the teacher teams a structured process or protocol for analyzing the data. Having the data and being in a room with a group of colleagues wasn't sufficient for helping them them become open, for helping them make objective observations about what they saw in the data, or for helping them have reflective dialogue about what the data meant. Leadership can assist the process by always urging the data team to consider "what are the implications of what we've just learned from this data"? What further data do we need? Who needs to know this?

When teachers have the opportunity to begin asking the questions relative to "what are we doing well", what's working, what isn't working, who is learning, who isn't, the data structures themselves will become apparent and most of the data they've been overwhelmed by, will come into play. They will become more critical consumers of the data especially benchmark assessments and common assessments. This is when it gets real!

In terms of building the human structures or human capacity for analyzing the data, what have been your biggest challenges? Or your successes? Are there teams of teachers using their data well? How?

Do your teachers a process or protocol for analyzing the data? A structure?

Share your thoughts on Twitter - make sure to include our hash tag #edcmdata at the end of your tweet!

Vision for data

The literature is clear about the need for an explicit vision for data use, typically from the superintendent and the principals. Check out the IES practice guide on this topic.

Here are my questions to you all:

1. What should be included in a vision for effective data use in schools?
2. Do you have a vision for data use? Is it explicit; that is, do your educators and staff understand that data use is important?
3. How do you show the importance and communicate that vision? How can you make the vision more explicit?
4. What components go into showing that you have a vision? (i.e., proving resources, allowing for PD, providing for common planning time, incentivizing educators)?
5. If you don't have a vision for data use, why not?

Share your thoughts on Twitter - make sure to include our hash tag #edcmdata at the end of your tweet!

Starting Our Discussion of the Mobile Learning Article

Welcome to the initial discussion in the course! To help frame the article you read, below is a conceptual framework for mobile learning that came from a conference on this topic I co-hosted with Qualcomm last October (http://wirelessedtech.com/).

Mobile devices and other emerging educational technologies often do not achieve their potential because “old wine is put in new bottles.” For example, podcasting is touted as an educational solution, yet almost all podcasts have had limited impact on learning because they use the “teaching by telling, learning by listening” instructional model that characterized educational radio and portable tape recorders in generations past. In contrast, mobile broadband devices can hold “new wine,” such as highly engaging augmented realities (http://isites.harvard.edu/icb/icb.do?keyword=harp) that infuse virtual data and authentic, simulated experiences into real world settings, facilitating transfer of learning from classrooms to life situations. Further, the “bottle” itself may disappear as mobile broadband allows us to have all the powerful supports of classroom learning without the need for constraining education in time and space.

That said, mobile learning poses at least four key puzzles:

• Devices and Infrastructure: How can we best balance educational investments between the classic infrastructure of wired computers and the emerging infrastructure of wireless mobile devices?
• Safety and Privacy: How can we use Internet access and digital student data to enhance education, while preventing various forms of abuse?
• Digital Assets and Assessments: How can we drive innovation in digital learning materials and services when the education market is notoriously fragmented and slow to adopt, and when the strengths and limits of mobile devices for learning are not well understood?
• Human Capital: How can we empower educators and other stakeholders to realize the potential of anytime, anyplace mobile learning through evolutionary, revolutionary, and disruptive transformations that move beyond the model of industrial-era schooling?

Complicating the challenge is that barriers in each area create difficulties for progress in the others.

The article with which we begin our discussion sketches both the vision for mobile learning and some initial problems to confront. Which opportunities mobile learning can provide are most interesting to you? Which initial barriers are most problematic, given your situation? Share your thoughts on Twitter - make sure to include our hash tag #edcmdata at the end of your tweet!