SAS Curriculum Pathways and the path to Common Core success

Nadja Young
Nadja Young|February 20, 2012

Teachers have more than enough to juggle each day, lacking the time to search for, and find, high-quality curricular resources online. When I would search for lesson plan supplements, I would often get lost in Google's abyss of results, spending far too much precious time sifting through mediocre materials. Until one day, I saw the light. Mrs. Angie Stephenson, a neighboring English teacher, brought her freshmen into my classroom to use my computer lab for SAS Curriculum Pathways. She had her class upload their essays into the Writing Reviser tool allowing SAS' artificial intelligence to identify possible errors. Students then self-edited their work by making their own determination of how to improve their run-on sentences, fragments, dangling modifiers, verb tense issues, relative and dependent clauses, and more.

SAS Curriculum Pathways Writing Reviser

In the era of increased class sizes and the need to have students practice writing constantly to improve their proficiency, SAS Curriculum Pathways is the answer. What’s even better? This $75 million philanthropic effort of SAS is offered at no cost to educators!

I discovered this resource in my seventh year of teaching, and I truly hope that more educators explore it now in preparation for the Common Core State Standards (CCSS).  SAS Curriculum Pathways provides more than 200 Interactive Tools, 200 “read, research and respond” inquiries, 600 Web Lessons and 70 Audio Tutorials in the areas of Math, ELA, Social Studies, Science, and Spanish. These resources are mapped to each state’s standards; English language arts and math resources also map to the CCSS. Curriculum Pathways has won numerous recent awards for these advancements, including ones from eSchool News, District Administration and Technology & Learning magazines.

SAS announced today record registrations in 2011. Over 18,000 schools nationwide now take advantage of this powerful free resource. However, some schools combine Curriculum Pathways with other SAS educational tools, such as EVAAS, to fully leverage student data and individualize learning opportunities for all. See how one high school in Granville County, NC, has increased graduation rates over 20% in two years, while decreasing absences and discipline incidents. Teachers first used EVAAS’ individual student projections to identify which students needed to be challenged, or to be retaught concepts in new ways. They then used Curriculum Pathways to differentiate instructional activities based on specific student needs. NC’s Mooresville Graded School District even caught the attention of the NY Times with their successful 1:1 initiative. By combining EVAAS and Curriculum Pathways, they were able to maximize the use of their laptops with this technology-rich content. The engaging lessons capture students’ attention to more deeply explore challenging material. Spread the word and share this free resource with your education colleagues!

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Analytics helping transportation officials get the job done in tight financial times

Melissa Savage
Melissa Savage|February 9, 2012

The American Association of State Highway Transportation Officials recently released a top 10 list of transportation issues that will be “talked, written or tweeted and legislated about” in 2012.  

As expected, funding constraints and Congressional action on reauthorization appear on the list but the group also notes that natural disaster preparation, senior mobility, increasing intercity rail, traffic safety and meeting environmental regulations will be hot topics in 2012.

Number two on the list is getting the job done in a tight financial environment.  With reauthorization lagging at the federal level and many state budgets in bad shape, state Departments of Transportation have had to look for ways to conduct day-to-day operations and long-term planning efficiently.

In North Carolina, by using data analytics, the state DOT has been able to shave weeks—about 20 percent—off the overall planning timeline, translating into an estimated cost savings of $500,000. Working in partnership with the North Carolina Department of Water Quality, the NC DOT used LIDAR (a process using laser to chart topography) data to narrow the list of acceptable choices for new road construction from hundreds of options down to a handful.  This huge reduction allowed NC DOT to quickly determine the best possible options and focus planning efforts on those areas.  

Analysis showing predicted streams and wetlands within proposed road corridors

The pilot project earned an award from the Federal Highway Administration and NC DOT has been fielding requests for more information from the US Army Corp of Engineers, the US Environmental Protection Agency and state and local transportation agencies. As state DOTs continue to look for ways to do more with less, data analytics can yield significant time and money savings, keeping projects on time and under budget.

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Predictive policing is passé

Vincent Talucci
Vincent Talucci|February 2, 2012

My colleague, Steve Serrao, just published a blog post on the proliferation of varied law enforcement approaches and their related phraseologies. After reading, I concur – hence, this blog’s title. I am not a huge fan of the term “predictive policing”. While others may love it and live it, and I absolutely respect that, I have tried to remove it from my policing lexicon. (Wait – I used passé and lexicon in the same blog – that’s terrible).

One reason I dislike the term?  Given I work with SAS – a leader in the use of analytics – on law enforcement topics, anytime anyone with whom I may be remotely affiliated with stumbles upon an article, blog, or Facebook post about predictive policing, it is matter of time before I am inundated with the forwarded article, blog, or Facebook post. While I appreciate information sharing, I get the concept!

And, no, I have never seen “Minority Report.”

So with the above as context, I do get the concept – I have been doing policing stuff for a while and have daily discussions with law enforcement thought leaders who really get policing stuff. We discuss policing at the policy level and operational level; we look at its strategic value and its tactical value; and, more importantly, we look at how policies, operations, strategies and tactics can best serve their respective constituents and communities- (and as an aside- think of the possibilities when all this is synchronized!). While we talk about a lot of important policing stuff, one thing we really never focus on – policing naming conventions.

This is not inconsistent with (forgetting my day job for a second) how I think and feel as a citizen. For example, as a citizen I want to know that my kids are as safe as possible walking to school; I want to know that speeding on the main thoroughfare is being addressed; and, I want to know my police department is doing everything possible to solve the spate of burglaries in my neighborhood. Never once as a citizen have I thought, “Wow, I really wish our police employed an intelligence-led (or predictive or community or neighborhood or information-led) policing approach.”

While as a professional, I understand and embrace the nuances, differences and complementary aspects of varying policing styles; however, as a citizen, those terms matter very little to me – and my guess is that they matter very little to most citizens. What is front of mind for citizens? My kids are safe, speeding is down, the burglar has been arrested, and if I call for help, help will arrive.

While I absolutely get the predictive policing concept, I also believe the term in and of itself sets an unreasonable (and sometimes unreachable) goal for many agencies – predicting where that next crime will occur. While I understand that is not the actual message, not fully understanding or articulating the concept and its limitations could lead to confusion and put the police and community at odds when a crime does occur.

While I have difficulty with the term, I believe that predictive analytics can help law enforcement in measurable and meaningful ways by improving service delivery and maximizing their abilities to do an already difficult job. Regardless of an agency’s policing strategy, or what it is called, predictive analytics has much to offer in helping police better protect and serve.

 

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Local government impact of rising group medical and insurance costs, and what can be done

Bill Coleman
Bill Coleman|January 24, 2012

The single most costly employee benefit for any organization is health insurance, and the price is going up. From 2003-2009, the costs per hour worked for employee health insurance increased from $1.03 to $2.00. These costs continue to increase from 5%-7% per year. The reality is that employee health insurance costs will continue to be a drag on operating  budgets that are already stretched too thin.

Cities and counties are service provider organizations whose budgets are heavily dependent on head count. The greater these benefit costs, the fewer the personnel. This could result in lower service levels in important areas like public safety, environmental protection, safety inspections, and infrastructure maintenance, to name just a few.

Many human resource organizations have made an effort to control these costs. They've implemented programs to improve the health of their employees and/or identify life style choices that reduce the individual’s risk of developing or worsening already existing problems.  Examples include wellness, health screening and consumer driven health programs, cash incentives and others. These programs require separate funding which further adds to the cost of this important benefit. The question is,  how does the organization determine if these programs are having the desired effect on health benefit costs? Many organizations use group health insurance premium costs as the sole measure for program effectiveness.

One must go several steps further to truly measure cause and effect of these programs on medical and insurance costs. HR organizations need to track things like:

  • Employee and dependent participation in the program
  • Employee demographics
  • Changes in behavior/life style
  • Medical costs over time
  • Number and types of workers compensation claims
  • Safety classes attended
  • Group health insurance claims, submitted by type and amount
  • Cost of prescription drug claims and the relation to claimant history
  • Type of work done by the employee/dependents
  • Health insurance premium costs and other relevant data.

This information needs to be tracked and analyzed over time, and related to past claims history of all employees/dependents covered by any plan. It is important that this same analysis be done for those not participating in the various incentive programs as a control group.

The key to analyzing the immense amount of relevant data to answer performance questions is having state of the art data integration, data quality, business intelligence and predictive analytics tools. With those tools, HR can easily tell which programs or combination of programs are helping control or reduce medical and insurance costs, including workers compensation costs, and which are not. It can predict the likely future costs given the employee history and demographics. Programs can then be developed to control costs in advance. The strategies for cost control are limitless if one can understand the relevant data and the interrelationships among the various data elements.

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Analysis of 311 call data can lead to better service, lower costs

Bill Coleman
Bill Coleman|January 24, 2012

Many cities and counties are taking the lead of private industry and developing 311 call centers to consolidate incoming calls for service and information requests from citizens. The business advantages are clear:

  • Citizens have one number to call for service and information rather than having to waste time searching for the right number.
  • Citizens are not shuffled from department to department looking for the appropriate respondent.
  • Responses can be standardized for more consistent performance across all service areas.
  • City/County managers and elected officials can learn more quickly how timely response is across various departments.
  • Trained department staff can spend their time performing more professional work instead of answering the phone.  

These 311 call centers produce a wealth of data that can be used to evaluate organizational and departmental performance against key performance indicators. This data can be help identify service delivery problems within any function, reveal the location of larger city/county infrastructure or staffing problems  and evaluate response times and effectiveness of the response. 

Of course, in order to answer even these elementary questions the 311 call data must be supported by a software system that collects and arranges data based on key performance indicators (KPIs). It would be even better for organization credibility and public transparency if the KPIs were displayed in dashboards and score cards and available on the web.

Data integration, data quality and business intelligence reporting are all necessary to glean useful information from call system data. This information gives managers, elected officials and the public an accurate picture of current performance. If predictive analytics is added to the tool box and applied to call data, an entirely new level of analysis can be achieved.  Analytics will correlate 311 data with other available data (work order, maintenance, weather, consumption, omputer-ided ispatch and ublic afety records management system data, etc ) on the  water and sewer systems and equipment, pavement conditions, parks, traffic signalization, public buildings, solid waste and recycling or any other operation. 

It will create correlations and models that predict future infrastructure problems. Repairs and replacements can be made proactively to reduce overtime costs, prevent more expensive repairs and prevent environmental damage. The analysis can inform managers about the types and frequency of repairs and maintenance needed, which will allow more precise control of parts and equipment inventory kept on hand. The potential to improve service and lower operations costs using these data analysis tools is truly unlimited.

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A sad reality: Crises drive positive change within criminal justice

Vincent Talucci
Vincent Talucci|January 24, 2012

All too often an unspeakable tragedy leads to a needed policy or operational change through a newly-realized criminal justice system gap. While we continually work to minimize existing gaps, the reality is that as law enforcement evolves, so does the crime and so do the criminals.

In recognition of those lost through needless violence, we honor the families, friends and communities who forged ahead and helped turn their collective, and respective, tragedy into a positive change; a change focused on the goal of protecting others from similar tragedy.

Megan’s Law: Many may not be familiar with the name Megan Kanka; however, many are likely familiar with the term Megan’s Law. In 1994, Megan Kanka was a 7-year old girl who was lured into a stranger’s home on the promise of seeing a puppy; unbeknownst to most in Megan’s New Jersey neighborhood, that home was that of a convicted sex offender. Tragically, Megan’s life was taken by that person and the outrage led to the creation and nationwide adoption of Megan’s Law – focused on notification about and registration of convicted sex offenders.

Dru Sjodin National Sex Offender Public Website: In 2003, Dru Sjodin, a University of North Dakota college student, was abducted and later found murdered. The convicted murderer was a registered sex offender who had crossed state lines to commit the crime. Born from this tragedy was the Dru Sjodin National Sex Offender Public Website (NSOPW); the NSOPW web site states its purpose is to share “public sex offender data nationwide, working collaboratively for the safety of both adults and children.”

Criminal Justice Law Enforcement Automated Data Services (CJLEADS): In 2008, the lives of Eve Carson, a University of North Carolina student body president, and Abhijit Mahato, a Duke University graduate student, were taken two months apart by the same alleged attacker. The two murders led to an examination of existing information gaps that allowed dangerous persons to capitalize on a fragmented criminal justice system. In response, the North Carolina Legislature moved to close those existing gaps, build an integrated offender-centric repository and equip frontline criminal justice professionals with timely, relevant offender information so to maximize public safety. The Criminal Justice Law Enforcement Automated Data Services, or CJLEADS, allows for that comprehensive picture. Per the CJLEADS web site, CJLEADS is designed to: “…provide a comprehensive view of an offender's North Carolina criminal information in a single web based application….(and) allows users to develop a watch list of persons of interest and will notify the users when that person of interest has a change in status such as an arrest, pending court date, or release from custody.”

Thanks to Megan’s Law, parents now have a better sense of who lives among them in their neighborhoods.

Thanks to the NSOPW, victims now can readily locate their convicted attacker regardless of location within the United States.

Thanks to CJLEADS, offenders are held more accountable by enhanced information sharing.

While these are just a few examples of changes driven by crises, we must pause to honor the victims. Megan’s Law, the NSOPW and CJLEADS all exist due to unspeakable tragedies; while we cannot change their course, it is our continual hope that the resultant changes in policies, laws and systems help prevent similar tragedies from occurring.

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Using analytics to manage capital projects funding & costs

Bill Coleman
Bill Coleman|January 17, 2012

Cities and counties are responsible for building and maintaining the infrastructure to support a broad range of services. Local governments must develop and implement multiyear capital projects plans that provide infrastructure for things such as jails, courts, public office buildings, streets, bridges, parks, athletic complexes and community centers, water treatment and reclamation facilities, motor vehicle and equipment fleet to support police, fire and public works services, as well as other miscellaneous construction and equipment. Tracking the progress of all these complex projects is a formidable task.

Local governments are faced with accounting for hundreds of single and multiyear projects with combined budgets totaling hundreds of millions of dollars. Accurate accounting includes not only tracking project costs by category and progress toward completion, but also requires tracking the order and rate of expenditure from each revenue source (ie. General Fund, Utility Fund , bond debt, General Obligation revenue, Tax Increment Financing, grants, impact fees, donations, etc). Tracking the real time status of both revenues and expenditures is critical in managing the projects efficiently, and making future budget decisions.

One SAS local government customer had a capital projects budget that included 147 projects totaling $348,000,000. The budget staff spent two weeks each year creating a spreadsheet that would give the revenue and expenditure status of the 147 projects. This information is used to determine what funds are available for new projects. In addition, the staff spent weeks responding to scenarios requested by the town council. Faced with decisions about raising taxes, utility rates and/or issuing more debt to pay for needed projects, the immediate availability and accuracy of this information is critical. Using data integration and business intelligence software, the budget staff created an integrated, comprehensive report that identified the exact amounts available from, and the status of, each project.

This information was created in 30 minutes rather than two weeks. Budget decisions can now be made in minutes rather than in weeks, saving hours and hours of staff time and council time. The improved accuracy allowed the town to know in advance if there was enough available General Fund cash across several projects to fund a new street project, instead of having to issue another $20M in General Obligation bonds for the coming year. The availability of accurate capital project data resulted in annual savings of $2 million.

Large, metropolitan governments have multi-billion dollar capital project budgets. Imagine the huge savings in time and money, and the benefits to taxpayers, by applying advanced analytics software to those governments’ daily business problems.

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The art and science of seating charts

Nadja Young
Nadja Young|January 12, 2012

A’s in the front, Z’s in the back. How many of us grew up sitting in alphabetical order next to the same few classmates throughout school? While this is a quick and efficient way to learn student names, which is no easy task, it is not the most effective way to maximize academic success. As a former high school teacher, I have seen and felt the chemical reactions that take place in a classroom when best friends or arch enemies are sitting in close proximity to one another. I truly believe that seating charts are one of the easiest, most effective, and often underutilized ways to improve classroom management and set the semester off on a productive tone from day one. As we kick off the second semester in the 2011-2012 school year, one of the first steps teachers will take with new classes of incoming students is to create seating charts. These arrangements can and should be created in an artful, data-driven way to strategically set students up for success.

I used to spend hours scouring through different formal and informal data to seat students in optimal locations around my classroom. Student Information Systems provided information on previous class schedules, grades, attendance patterns, and sometimes discipline records and family circumstances. Individualized Education Programs (IEP’s), Limited English Proficent reports (LEP’s) and 504 Plans informed me of special needs, required modifications, and accommodations related to seating such as: near the board, near the teacher’s desk, near the door, etc. Then I would compare class rosters with teachers in my department so that we could share lessons learned from previous experiences with students. Lastly, student files in the record room provided a treasure trove of information, but that is an extremely time-consuming process that I honestly did not have time to utilize consistently.

All of the above fact-finding gave me hints about each student’s likelihood of success or failure in my class. However, it took a lot of precious time, and only gave pieces to a puzzle that I still had to assemble. Teachers who use SAS’ predictive analytics through EVAAS will hopefully be incorporating its Individual Student Projection data into this seating chart process. EVAAS gives teachers a much more accurate probability of each student’s success in their classes…at a single glance. Teachers can look at their new class rosters in EVAAS to see a graphic projection for how well each student is likely to perform on individual final exams. They can also look further into the future to a projection for student success on future milestones- like AP Exams, SAT, ACT, and various college readiness measures.

So how does this data improve seating chart creation? You first identify high achieving students and those who are “at-risk” of failing and needing additional early support. I liked intermixing my high achievers and at-risk students so that there could be some positive peer-to-peer assistance on daily basis. I always placed my “at-risk” students along the perimeter of the formation so that I could casually observe their work more frequently without making a special point to get to them (kids notice this type of “special attention” and often do not like it). I also made an effort to intermix students based on gender and grade-level, since I taught mixed-grade 9-12 courses. For example, you would not seat all of your high-achieving Senior boys together. They would finish their work at lightning speed and then want to socialize, creating a distraction to others who need more time and support. Likewise, although it would be efficient to group all special needs students together near my desk so that I could work with them at the same time, they would not benefit from the positive peer effect of seeking help and support from their classmates.

Getting seating charts right on the first day of school not only yields earlier productivity, but also alleviates the seemingly negative attention students feel when teachers need to move them around later in the semester. However, when changes do need to be made because classroom dynamics change as student relationships develop, it is always best to move a group or the entire class at once, rather than single out one or two kids who need rearranging. These are the tips that worked well for me, but I would love to hear other seating chart best practices from those of you in the classroom!

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Phone distraction just one part of traffic crash picture

Melissa Savage
Melissa Savage|January 9, 2012

During one week in December, two separate transportation agencies within the federal government made two major announcements.  First, the National Highway Traffic Safety Administration (NHTSA) – the government agency responsible for guiding traffic safety initiatives on the nation’s highways announced that crash fatalities had declined to record low rates.  Just a few days later, the National Transportation Safety Board – the government agency responsible for investigating major accidents involving all transportation modes – made a controversial recommendation, suggesting that all 50 states and the District of Columbia pass laws banning the use of portable electronic devices (PED) while driving.

Ten states and DC have hand-held bans requiring motorists to use blue-tooth or some other device when making a call while driving.  Thirty-five states ban texting while driving.  According to NHTSA, about 3,100 people were killed in 2010 due to distracted driving. 

For state legislators, before they go through the trouble of introducing, debating and passing an all-out ban on using PEDs while driving, they want to know if the need exists for such a law and if it will help.  Several studies have been conducted over the years on distracted driving and the effect on being able to safely operate a car.  But the nearly decade-long debate continues in state legislatures throughout the country—as shown by the fact that only ten states have a hands-free law and no state has a total ban.

The Insurance Institute for Highway Safety has studied the issue and has found that hands-free laws do not reduce the crash rate.  Conducting before and after studies in states with hands-free laws in place, IIHS discovered that the incidence of crashes did not go down.   

The recommendation from the NTSB is just that—a recommendation.  The NTSB doesn’t have the ability to force the states to act on the recommendation, but NHTSA and Congress usually take what the NTSB says seriously and some believe the recommendation gives the federal government the support they need to push the issue.

Following the release of the recommendation, the Governors Highway Safety Association called for more research on whether laws banning driver use of PEDs improve traffic safety. While data collection on driver distraction continues to build momentum in the states, taking a holistic view of crashes including the involvement of driver distraction would give decision-makers like state legislators the ability to make evidenced-based policy choices.  Legislators would be able to make policy decisions knowing whether or not such laws would make a difference.  Whether it’s a PED ban or requiring ignition interlock devices for drunk driving offenders, data analytics would take the guess work out of deciding which policies will make a difference.

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Moving local government to analytics-based enterprise performance management

Bill Coleman
Bill Coleman|January 2, 2012

Local governments are not immune to the rising demand for more accountability in government run services and programs, and the expenditure of public funds. Elected officials and citizens alike want to know what these programs accomplish for the public investment made. To date, the response to these questions and demands has been to establish some basic performance measures such as calls received, response times, work orders processed, pot holes filled, etc. There is seldom, if ever, an analysis of how these measures relate to the vision or mission of the organization; what these measures indicate about productivity; how the costs to the organization relate to the outcomes; and, there is no connection made to quality. In order to make this jump from basic KPIs to data that supports strategic decision making, counties and cities will need to move toward analytics-based performance enterprise management.

Analytics-based enterprise performance management offers the ability to optimize the efficiency and effectiveness of all of the functions of a local government by aligning all resources to established objectives, measure results and costs against targets, and analyze this data to identify opportunities for improvement.  More simply stated, it is a method of integrating financial and performance data to create a clear picture of the cost and effectiveness of all the functions and services of local government. When predictive analytics is added, local governments can determine how costs can be reduced and service levels improved across the organization.

For example, traffic safety is dependent upon the police department operating an effective program to control speed, intersection safety, impaired driving or other motorist related behavior. Congestion management is often the responsibility of the engineering department and signalization management group. (Yes, that group exists.) Traffic management, thoroughfare planning and site plan approval is the responsibility of the engineering and planning departments. The ability to integrate all of these related data sources and associated costs and apply analytics is key. Decision makers get a clear picture of how safe a city is at a particular point in time, and predictive capabilities to to know what changes will create a safer city.

Some people may equate "local" with "small", but local governments are large and complex and ripe for the use of analytics-based enterprise performance management.

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