(p. 2) The briefest summary is this: Many charter schools fail to live up to their promise, but one type has repeatedly shown impressive results.
Hannah Larkin, the principal at Match, refers to such schools as “high expectations, high support” schools. They devote more of their resources to classroom teaching and less to almost everything else. They keep students in class for more hours. They set high standards for students and try to instill confidence in them. They focus on giving teachers feedback about their craft and helping them get better.
. . .
The latest batch of evidence about this approach is among the most rigorous. Professors at M.I.T., Columbia, Michigan and Berkeley have tracked thousands of charter-school applicants, through high school and beyond, in Boston, where most charters fit the “high expectations, high support” model.
Crucially, the researchers took several steps to make sure the findings were real. They compared lottery winners with losers, controlling for the fact that families who applied for the lotteries were different from families who didn’t. They also counted as charter students all those who enrolled, including any who later left.
When you talk to the professors about their findings, you hear a degree of excitement that’s uncommon for academic researchers. “Relative to other things that social scientists and education policy people have tried to boost performance — class sizes, tracking, new buildings — these schools are producing spectacular gains,” said Joshua Angrist, an M.I.T. professor.
For the full commentary, see:
Leonhardt, David. “Schools That Work.” The New York Times, SundayReview Section (Sun., NOV. 6, 2016): 2.
(Note: ellipsis added.)
(Note: the online version of the commentary has the date NOV. 4, 2016.)
The “latest batch of evidence” mentioned above, includes:
Angrist, Joshua D., Sarah R. Cohodes, Susan M. Dynarski, Parag A. Pathak, and Christopher R. Walters. “Stand and Deliver: Effects of Boston’s Charter High Schools on College Preparation, Entry, and Choice.” Journal of Labor Economics 34, no. 2 (April 2016): 275-318.