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Fix, Don’t Discard MCAS/PARCC

This fall I had one on one conversations with many of our state's leaders and experts on the misplaced opposition to testing in gen...

Wednesday, December 24, 2014

xAPI advice from Jim Goodell

From Jim Goodell:

An online activity might track every click, as a separate verb, but for offline activities I'd say the statement might represent a completed activity, something like:
URLs can be used as parts of the statement...
Actor = "https://plus.google.com/108636986437967834022/posts"
[identifier for Charlie, e.g. blog profile page URL, so...]
Object = [URL to "Bird House Activity" ...which could be the blog page in this case, but normally just describe the activity or learning resource, not the personal experience]

...then the "Bird House Activity" page should have human readable info describing the activity and LRMI metadata tags that give info including the alignment to learning objectives, e.g. LRMI has alignmentObject, CEDS has Learning Standard Item Association Type, e.g. "Bird House Activity" "assesses, requires, teaches" "[URL to adding fractions learning standard]"

So the statements are just identifiers, URIs that can be resolved to discover richer meaning. 

Friday, December 19, 2014

Report on P20 SLDSs

States are making progress building longitudinal databases that link individual students’ performance in K-12 with their experience in the workplace, but have been slowed a bit by privacy concerns and other obstacles, according to a federal audit.

The Government Accountability Office produced the report for the Senate HELP Committee. Among the findings: More than half the 48 states that received federal database grants now have the ability to track individuals from their early education into the workforce.

States are using the databases for research on numerous topics, including identifying students at risk of academic failure; tracking whether STEM teachers are more likely to leave classrooms for the private sector; and comparing the earnings of high school and college graduates. Some states are producing data-driven reports that analyze how well individual schools prepare students for college or career. At least 39 states have developed a specific research agenda for their databases.

But states reported they were hampered by laws in several states prohibiting the use of Social Security numbers in K-12 data. The lack of the Social Security numbers makes it more difficult to match an individual student’s educational records with his workplace records, which could include wages, unemployment claims and welfare applications. States also reported heated political debates about the databases and the potential impact on privacy.

The federal government has distributed at least $640 million in grants to states to build the longitudinal databases since 2006. Most of that money has come through the Education Department, though some is from the Department of Labor.

Netflix Academy - Great Educational Videos


Thursday, December 18, 2014

Horn on Blended Learning

Education Week
Published Online: December 9, 2014
Blended Learning Is About More Than Technology
By Michael B. Horn & Heather Staker

Battles between different philosophical camps in education are nothing new.

Whether it's knowledge vs. skills, memorization vs. project-based learning, small schools vs. comprehensive ones, the debates in education are often framed as a choice between "either-ors."

From John Dewey to Chester E. Finn Jr., countless education researchers have documented the fallacies in these dichotomies and the dangers of being too beholden to an "-ism," as Dewey wrote.

Many educators sense the folly as well. They know that at different times and in different circumstances, different approaches are best for students.

Despite this understanding, teachers are often handcuffed in their ability to steer their way toward a pragmatic middle ground. With limited blocks of time in a public school day and a set curriculum to work their way through, as well as the need to serve many students, each with unique learning needs, teachers must make trade-offs. More of one thing means less of another.

Blended learning—the mix of online and in-school learning—represents a way to break away from the trade-offs mentality, as Harvard Business School professor Clayton Christensen explains in the foreword to our new book, Blended: Using Disruptive Innovation to Improve Schools. (Christensen is also the co-founder, with Michael B. Horn, of the Christensen Institute, where both of us work.)

Done right, blended learning breaks through the barriers of the use of time, place, path to understanding, and pace to allow each student to work according to his or her particular needs—whether that be in a group or alone, on practice problems or projects, online or offline. It preserves the benefits of the old and provides new benefits—personalization, access and equity, and cost control.

The question is how educators can capture these benefits. Blended learning is not inherently good or bad. It is a pathway to student-centered learning at scale to allow each child to achieve his or her fullest potential, but it is not a guaranteed success.

More generally, too many schools have crammed computers into their classrooms over the years—spending many billions of dollars, with little to show for it. It is not unusual to see a district adopt educational technology only to see costs rise and student achievement decline.

So, how to proceed? The first rule is simple, even if it is counterintuitive. Do not start with the technology.

Instead, schools should follow a tried-and-true design process to innovate successfully. The first step is to pick a rallying cry by identifying the problem to solve or the goal to achieve. Some problems relate to serving mainstream students in core subjects, while others arise because of gaps at the margins—where schools cannot offer a particular course, for example. Both areas are worthy of innovation. In either case, though, the problem or goal must not be about technology—such as trying to solve a "lack of devices"—and lead to a deployment of technology for technology's sake.

"Blended learning is not inherently good or bad. It is a pathway to student-centered learning at scale."

With the problem or goal identified, it is important to state it in a "SMART" way—specific, measurable, assignable, realistic, and time-related—such that an organization will unambiguously know what success is and if it has been realized.

One common mistake is failing to bring the right people to the table to lead the effort. The result is that teachers are either stuck with tasks beyond their reach or too much bureaucratic oversight. Schools must match the right type of team and the right people to the scope of the problem.

The Milpitas, Calif., school district, for example, has created coordinating teams to support teachers innovating within their classrooms, and brought together heavyweight schoolwide design teams to rethink the very structure of some of their schools.

With the rallying cry in place and the right team organized, it is time to design. The starting point is to look at school from the viewpoint of students to understand what they are trying to accomplish in their lives and thus what motivates them. When leaders get the design right from their pupils' perspective, such that young people feel that school aligns perfectly with the things that matter to them, students arrive in class eager to learn.

This is not to say that educators should not instill certain core knowledge, skills, and dispositions in students, but that to accomplish these objectives seamlessly, schools should be intrinsically motivating. This means not only understanding what students are trying to accomplish, but also understanding the experiences they need to get those jobs done, and then assembling the right resources and integrating them in the right way to deliver those experiences.

We know that teachers are a crucial part of the student experience. But to gain teachers' buy-in, schools must work for teachers as well, which is why designing the teacher experience is the next step. Teachers have personal jobs to do in their lives, and the magic happens when schools offer experiences that are fulfilling for both students and teachers. Ensuring that teachers have opportunities to achieve, receive recognition, exercise responsibility, and advance and grow in their careers is critical. To provide teachers these motivators, institutions using blended learning are experimenting with extending the reach of great teachers, assigning teachers specialized responsibilities, employing team-teaching, awarding micro-credentials for achievement, and granting teachers increased authority.

The next step is the one where technology and devices finally enter the equation. The objective is to design the virtual and physical setup to align with the desired student and teacher experiences.

Some of the important questions that schools should ask when selecting content and software are: Should we build our own? Should we use one or multiple outside providers? Or should we adopt a facilitated-network solution—a platform that integrates modular content from a variety of sources? Considering devices—what type and how many—to match the software and student and teacher experiences is equally important.

Finally, teams should think through the physical environment in which students learn. Will the traditional egg-crate factory-model school design enable students and teachers to be successful? Or is a more modular environment that enables increased customization desirable? Increasing numbers of blended-learning programs are embracing the latter.

From here, it's time to put the vision into action. That means taking the choices from these different steps and piecing together a coherent instructional model.

After a team finishes designing, its work is still not done. Execution matters.

Schools must create the right culture. Blended learning accelerates a good culture and makes it great, but it will also accelerate a bad culture and make it terrible. Schools should also implement their designs with humility and acknowledge that it is unlikely that they will get the design right on the first try. Taking a discovery-driven approach to help school leaders identify and mitigate risks as they kick off a blended-learning program—and iterate accordingly—will help avoid costly mistakes both for students and a school's limited budget.

Blended learning is no panacea. It's a scalable strategy that can break the trade-offs inherent in the traditional school design to allow teachers to reach students in ways never before possible. But for it to work, school leaders must not start with blended learning or technology for its own sake, but instead undertake a careful design process to unlock its potential.

Michael B. Horn is the co-founder and executive director, education, of the Christensen Institute, a nonprofit think tank in San Mateo, Calif. Heather Staker is a senior research fellow at the Christensen Institute. They are the co-authors of Blended: Using Disruptive Innovation to Improve Schools (Jossey-Bass, November 2014).

Vol. 34, Issue 14, Pages 22,28

Wednesday, December 17, 2014

NY Immigrant Child Data Protection

The New York State Board of Regents has adopted emergency regulations aimed at ensuring the recent wave of undocumented minors that arrived in the state can enroll in school.

The state has received several complaints of undocumented students facing barriers to school enrollment and has set up training sessions and issued guidance to help correct the issue. The new regulations were passed to give schools clarity on how to comply with federal law, the Board of Regents said in a release. The regulations specify that schools can't ask about the citizenship or immigration status of students or their parents, and it outlines acceptable documents schools can use to determine childrens' ages when enrolling them in school.

"The Board of Regents has enacted these regulations to protect the right of each and every child to a free public education, no matter where they come from or what they look like," Board of Regents Chancellor Merryl Tisch said “We are resolute in the belief that enrollment obstacles cannot hold back the hopes and aspirations of our children.”

New York state isn't alone in its concerns about barriers for undocumented minors enrolling in school: The federal Education Department has also issued multiple rounds of guidance in recent years reminding states of their obligations when enrolling undocumented students.

HI statewide education metrics

HIDOE will include each school’s Index points and composite scores on the school report card. The Index scores will be used to customize the supports and interventions to meet the school’s needs. Index scores will be provided for the following categories in the Strive Hi Performance System:

Achievement: The Achievement indicators measure whether a school is providing students with the math, reading, and science skills for a solid academic foundation. Math, reading, and science proficiency will be measured by the statewide assessments in grades 3 - 8 and 10. New assessments will be aligned to Common Core Standards. SY 2013-14 will be a “bridge” assessment from the Hawaii State Assessment to Common Core Standards. The Smarter Balance assessment will be administered in SY 2014-15.

Growth: The Growth indicators measure whether a school is improving students’ reading and math scores over time in grades 4 – 8 and 10.
RFP D15-041

Readiness: The Readiness indicators measure whether a school is doing its part in ensuring students are ready to move through the K-12 pipeline prepared to graduate for college and careers.
o For elementary schools, the chronic absenteeism rate is defined as the percentage of students absent for 15 or more days a year (excluding medical emergencies).
o For middle schools, the readiness indicators will be 8th grade ACT scores, which include English, reading, math and science.
o For high schools, the Index will use 11th grade ACT scores (including English, reading, math and science) and graduation and college going rates.

Achievement Gap: The Achievement Gap indicators measure the achievement gap between student subgroups and how well a school is narrowing gaps over time.
o The current year indicator will measure the current year gap, while the multi-year indicator will measure how the school has narrowed the gap over time.
o The Achievement Gap indicators will compare reading and math proficiency between two subgroups: “High-Needs” students and “Non-High Needs” students. The High-Needs category includes students in any one of the federally defined subgroups: disability, language or family income.

Tuesday, December 16, 2014

Does FERPA apply to MOOCs?

Does FERPA apply to MOOCs?
Two weeks ago at a symposium on student privacy, The Chronicle of Higher Education reports that Kathleen Styles, the DOE’s Chief Privacy Officer, said, “‘Data in the higher-education context for MOOCs is seldom Ferpa-protected,’” because MOOCs are rarely funded with Title IV dollars from the federal government. At least one high-profile university and one high-profile commercial MOOC platform appear to disagree with each other on the question: while edX (non-profit) states that it “‘is subject to and will comply with all Ferpa requirements governing the use and redisclosure of personally identifiable information,’” Coursera (for-profit) follows the “‘principles’” of FERPA but “doesn’t think it applies to MOOCs.”

Saturday, December 13, 2014

Blended Learning Resources

Christensen Institute


By Meredith Liu
To illuminate the possibilities for next-generation assessments in K–12 schools, our latest case study profiles the Cisco Networking Academy, which creates comprehensive online training curriculum to teach networking skills. Since 1997, the Cisco Networking Academy has served more than five million high school and college students and now delivers approximately one million online assessments per month in a variety of formats. Its advanced and highly integrated assessment system offers lessons for K–12 technology and assessment.

By Michael B. Horn and Heather Staker
In an article published this week in Education Week, Michael and Heather discuss how blended learning is a scalable strategy that can break the trade-offs inherent in the traditional school design to allow teachers to reach students in ways never before possible. But for it to work, school leaders must not start with blended learning or technology for its own sake, but instead undertake a careful design process to unlock its potential.


December 11, 2014
By Michael B. Horn
Clashes over testing in K–12 schools have grown in intensity in recent years. In some quarters, parents decry the over-testing of their children, for example, whereas others point out the need for testing for accountability over the use of public funds. Fewer talk about how important assessment is for learning—for students and teachers—because our education… Read More

December 10, 2014
By Julia Freeland
This week marks National Computer Science Education Week. Not only are K–12 schools, parents, and leaders around the country engaged in activities like the Hour of Code, but the week is also a chance for advocacy groups like code.org to highlight the beleaguered state of computer science education in America. For example, currently only around… Read More

December 8, 2014
By Michelle R. Weise, PhD
This blog was first published on CompetencyWorks. The running joke about higher education is that change doesn’t come eventually, but glacially. Much of academic inertia stems from the complicated business model of delivering higher education, not to mention the orchestration of multiple stakeholders on campuses: the administration, faculty members, trustees, senate committees, unions, and other… Read More


The BLU is back
The newly expanded Blended Learning Universe—or BLU—is now live! The BLU is a comprehensive online hub packed with blended-learning resources. Whether you’re looking for a primer on the basics or want to dive deep into the supporting research, the BLU has you covered. The site provides helpful tools for practitioners, policymakers, parents, and innovators working to improve education through personalized, student-centered learning. Check it out: www.blendedlearning.org

Co-authored by Michael Horn and Heather Staker, Blended: Using Disruptive Innovation to Improve Schools serves as a design guide for K12 stakeholders looking to effectively embrace the rise of blended learning. This book is a must-have resource for educators, parents, and innovators navigating the future of learning.

Thursday, December 11, 2014

New Google Products in the Works for Kids & Tweens

New Google Products in the Works for Kids & Tweens
According to USA Today’s profile of Pavni Diwanji, Google’s Vice President of engineering, “beginning next year [Google] plans to create specific versions of its most popular products for those 12 and younger.” Probable “candidates are those that are already popular with a broad age group, such as search, YouTube and Chrome.” Diwanji said she “‘expect[s] this [effort] to be controversial,’” but since “‘kids already have the technology in schools and at home...the better approach is to simply see to it that the tech is used in a better way.’" USA Today’s profile of Diwanji touched on potential controversies surrounding the program, such as the fact that “traditionally kids younger than 13 have been off limits” as target markets to tech companies. Diwanji said “she understands those concerns, but [added] that as a parent she ‘is a big believer in coaching moments for kids, rather than just blocking what they can do.’" Developing products for the under 13 crowd must be done in compliance with the Children’s Online Privacy Protection Act (COPPA), which “set[s] forth [heightened] privacy standards and obligations for online service providers that either target children or knowingly collect personal information from children under the age of 13.” According to CNN Money, “A Google spokesperson declined to comment further, but confirmed that the USA Today report was accurate.”

Monday, December 8, 2014


The analysis and visualization platform for learning organizations. You can easily connect multiple data sources and get the analyses you need, right away.



Finally, you can see all your learning data from a variety of sources in a single dashboard. No manual data aggregation.


We provide a quick snapshot of the volume and timing of learning activities across the entire organization.

Score Distributions

For assessments and simulations with scores, Wax provides you with a nice distribution for attained results.

Geo Analysis

Applications sending data to Wax with embedded GeoJSON can be visualized in our Geo Maps feature.

Question Analysis

Analyze the quality of questions and determine if they are conducive to the success of an assessment.

Influencer Analysis

There are subject matter experts in your organization. Discover, reward and leverage them quickly with Wax.


Useful Analysis

You need more than an activity stream of learning data to improve employee effectiveness. Wax is the only Learning Record Store to provide you with useful analysis and visualizations to help better understand all your learning data.


Wax LRS provides you with the highest level of Experience API conformance coupled with best-in-class scalability. We ensure that you don't have to worry about hosting & scaling so you can focus on doing what you do best.

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You only pay for what you use so you don't waste your money. There is no need to pay for plans you may never use or large up-front costs. Start small and scale up as needed. Check out our pricing page for more details.

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Saturday, December 6, 2014

How Game Theory Helped Improve New York City’s High School Application Process

To middle-school students and their parents, the high-school admissions process is a grueling and universally loathed rite of passage. But as awful as it can be, it used to be much worse. In the late 1990s, for instance, tens of thousands of children were shunted off to schools that had nothing going for them, it seemed, beyond empty desks. The process was so byzantine it appeared nothing short of a Nobel Prize-worthy algorithm could fix it.
Which is essentially what happened.
Alvin E. Roth at Stanford University in 2012. Credit Norbert Von Der Groeben/Reuters
About a decade ago, three economists — Atila Abdulkadiroglu (Duke), Parag Pathak (M.I.T.) and Alvin E. Roth (Stanford), all experts in game theory and market design — were invited to attack the sorting problem together. Their solution was a model of mathematical efficiency and elegance, and it helped earn Professor Roth a Nobel Memorial Prize in Economic Science in 2012.
Before the redesign, the application process was a mess. Or, as an economist might say, it was an example of a congested market. Each student submitted a wish list of five schools. Some of them would be matched with one of their choices, and thousands — usually the higher-performing ones — would be matched with more than one school, giving them the luxury of choosing. Nearly half of the city’s eighth graders — many of them lower-performing students from poor families — got no match at all. That some received surplus offers while others got none illustrated the market’s fundamental inefficiency.
Thousands of unlucky teenagers wound up waiting through the summer to get placed, only to be sent to schools they had not listed at all. And those schools, Professor Pathak discovered in a recent analysis, were “worse in all dimensions” — including student achievement, graduation rate and college admissions — than the schools the students had asked to attend.
Even more bizarre, the system encouraged safe, rather than ambitious, choices. Some sought-after schools accepted only the applicants who had made them their first choice. So students who aimed high and listed several such schools but were rejected by the first could blow their chances all the way down the list.
To address this flaw, the Education Department’s high school directory advised students to “determine what your competition is for a seat in this program"— a vexing task for even the best-informed among them.
“It was an allocation problem,” explained Neil Dorosin, the director of high-school admissions at the time of the redesign. The city had a scarce resource — in this case, good schools — and had to work out an equitable way to distribute it. “But unlike a scarce resource like Rolling Stones tickets, where whoever’s willing to pay the most gets the tickets, here we can’t use price,” Mr. Dorosin said.
Professors Roth, Abdulkadiroglu and Pathak modeled their solution to this conundrum on a famous puzzle in economics: the stable marriage problem. In the early 1960s, the economists David Gale and Lloyd Shapley proved that it was theoretically possible to pair an unlimited number of men and women in stable marriages according to their preferences.
In game theory, “stable” means that every player’s preferences are optimized; in this case, no man and no woman matched with another partner would both prefer to be with each other. Professors Gale and Shapley called the mechanism for arranging these fortuitous matches a “deferred acceptance algorithm.”
Parag Pathak of M.I.T. Credit Gretchen Ertl for The New York Times
Here is how it works: Each suitor proposes to his first-choice mate; each woman has her own list of favorites. (The economists worked from the now-quaint premise that men only married women, and did the proposing.) She rejects all proposals except her favorite — but does not give him a firm answer. Each suitor rejected by his most beloved then proposes to his second choice, and each woman being wooed in this round again rejects all but her favorite.
The courting continues until everyone is betrothed. But because each woman has waited to give her final answer (the “deferred acceptance”), she has the opportunity to accept a proposal later from a suitor whom she prefers to someone she had tentatively considered earlier. The later match is preferable for her, and therefore more stable.
The deferred acceptance algorithm, Professor Pathak said, is “one of the great ideas in economics.” It quickly became the basis for a standard lesson in graduate-level economics courses.
Of course, there seldom is much need for mass betrothals. It was Professor Roth who developed the first practical application for this idea. In 1995 he configured a deferred acceptance algorithm to connect graduating medical students with hospital residencies. Professor Shapley shared the Nobel for economics with Professor Roth for his pioneering work on the subject. When officials at the city’s Education Department learned about the residency formula, they realized that something similar might tame the chaotic school-choice system in New York.
Atila Abdulkadiroglu of Duke University Credit Les Todd/Duke University
Playing matchmaker to doctors or students is a little more complex than pairing off couples to be married, since hospitals and schools are, in effect, polygamous — they accept many proposals. But the principle is the same: Students list their favorite schools, in order of preference (they can now list up to 12). The algorithm allows students to “propose” to their favorite school, which accepts or rejects the proposal. In the case of rejection, the algorithm looks to make a match with a student’s second-choice school, and so on. Like the brides and grooms of Professors Gale and Shapley, students and schools connect only tentatively until the very end of the process.
In 2004, the first year that students were sorted in this way, the number who went unmatched plummeted, from 31,000 in 2003 to about 3,000 — still a lot of disappointed teenagers. That year, and every year since, the algorithm has assigned roughly half of all students to their first–choice schools; another third or so have been assigned to their second or third choices. (The city’s nine specialized high schools have their own separate admissions process.)
While those represent pretty good odds, parent chat groups roil with dark speculation about some mercurial trick through which a child may be deprived of her dream school. Parents worry that their children could “waste” the crucial first-place spot if they choose wrong. And they fret that a popular school will fill up with children who ranked it first, before the algorithm has a chance to consider their own, equally qualified, child.
Professor Abdulkadiroglu said he had fielded calls from anguished parents seeking advice on how their children could snare the best match. His advice: “Rank them in true preference order.”
The allocation problem has not disappeared. Good schools remain a scarce resource, especially in poor neighborhoods, and low-income and low-performing children are still more likely to end up in underfunded schools. Sean Corcoran, associate professor of educational economics at New York University’s Steinhardt School of Culture, Education and Human Development, has studied the choices made by low-achieving students, who are disproportionately poor. He found that the algorithm matches low- and high-achieving applicants with their first-choice schools at roughly the same rate. But Professor Corcoran said, “Lower-achieving kids are applying to lower-achieving schools and ranking them as their top choices.”
It seems that most students prefer to go to school close to home, and if nearby schools are underperforming, students will choose them nevertheless. Researching other options is labor intensive, and poor and immigrant children in particular may not get the help they need to do it.
But that is a political problem, and so far, there is no algorithm that can fix it.

CEDS Learning Log


Learner Action Type Updated Element

The type of action taken by the learner.
Option Set
The person gave a correct answer or solution.answered
The person inquired about something, or sought an answer to a question or problemasked
The person made an effort or attempt.attempted
The person was present.attended
The person made or wrote a comment.commented
The person finished or ended the specified activity or object.completed
The person moved out of or departed from interaction with the specified activity or object.exited
The person participated in or underwent.experienced
The person was unsuccessful with the specified activity or object.failed
The person transferred the specified information object into a data store.imported
The person assigned initial value to the specified activity or object.initialized
The person acted with or towards the object of the statement.interacted
The person gave impetus to the object of the statement.launched
The person became completely proficient or skilled in a competency.mastered
The person achieved a successful result from an evaluation or a selection process.passed
The person selected the object as an alternative over another.preferred
The person moved forward.progressed
The person enrolled in or was recorded as a candidate for.registered
The person show a response or a reaction to.responded
The person returned to a previous location or condition within an activity.resumed
The person recorded the result, assigned a grade or rank to an evaluation of the specified object or activity.scored
The person made the specified object available for use by others.shared
The person made the specified object or activity come to an end or stop.suspended
The person brought the object or activity to a final end.terminated
The person declared the object or activity invalid.voided
Related Entities and Categories
Assessments -> Learner Action
K12 -> Assessments -> Learner Action
K12 -> K12 Student -> Learner Action New Association
CEDS Element ID
Element Technical Name

<xs:simpleType name="LearnerActionType">
    <xs:documentation>Usage: Learner Action Type</xs:documentation>
  <xs:restriction base="xs:token">
    <xs:enumeration value="answered"/>
    <xs:enumeration value="asked"/>
    <xs:enumeration value="attempted"/>
    <xs:enumeration value="attended"/>
    <xs:enumeration value="commented"/>
    <xs:enumeration value="completed"/>
    <xs:enumeration value="exited"/>
    <xs:enumeration value="experienced"/>
    <xs:enumeration value="failed"/>
    <xs:enumeration value="imported"/>
    <xs:enumeration value="initialized"/>
    <xs:enumeration value="interacted"/>
    <xs:enumeration value="launched"/>
    <xs:enumeration value="mastered"/>
    <xs:enumeration value="passed"/>
    <xs:enumeration value="preferred"/>
    <xs:enumeration value="progressed"/>
    <xs:enumeration value="registered"/>
    <xs:enumeration value="responded"/>
    <xs:enumeration value="resumed"/>
    <xs:enumeration value="scored"/>
    <xs:enumeration value="shared"/>
    <xs:enumeration value="suspended"/>
    <xs:enumeration value="terminated"/>
    <xs:enumeration value="voided"/></xs:restriction>
Changed option set.
https://ceds.ed.gov/CEDSElementDetails.aspx?TermId=7935   (Email this link)
Common Education Data Standards 

Friday, December 5, 2014

Substantially more teachers are high performers

Substantially more teachers in New York state are coming to the profession with top academic qualifications, according to a new study published in the journal Educational Researcher.
The authors found that the number of new teachers with SAT scores in the top third of all test takers jumped by 13 percentage points from 1999 through 2010. In 2010, a full 42 percent of newly hired teachers came from that elite group.
The study attributed the surge to tougher teacher training and licensure policies implemented in New York starting in 1999. The researchers postulate that the more rigorous standards raised the stature of teaching as a profession and drew higher-performing students to the field.
“These findings signal a resurgence of interest in teaching in public schools as a respected and worthy career,” said Luke Miller, a research professor at the University of Virginia’s Curry School of Education.

Other states have adopted elements of New York state’s reforms to licensure and training. The Education Department has proposed regulations aimed at boosting the quality of teacher training programs nationwide.