Ron Baird, news editor
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Buffs lose to #1 Arizona
Jan 24th
TUCSON – The Colorado Buffaloes left Arizona’s McKale Center last season doubting they’d lost. The top-ranked Wildcats allowed no room for doubt on Thursday night.
Leading by as many as 20 points midway through the second half, Arizona disposed of CU 69-57, sending the Buffs to their third defeat in their last four Pac-12 Conference games. It was also CU’s fourth loss in six games against ranked opponents this season and its 16th all-time loss (no wins) against a top-ranked foe.
CU will try and salvage this season’s trip to the desert with a 5 p.m. game on Saturday at Arizona State.
The Wildcats (19-0, 6-0) led 39-24 at halftime and posted their first 20-point lead (51-31) on a reverse dunk by freshman Aaron Gordon with 15:02 to play. But the Buffs (15-5, 4-3) kept battling and came as close as 11 (66-55) on an Askia Booker layup with 1:15 remaining.
“We did a good job of battling back, even in the first half we cut it to six, but we couldn’t get over the hump. They are an explosive team,” CU coach Tad Boyle told KOA Radio. “There are some positive things we can take from this, but we have to be a better offensive executing team on the road . . . but when you leave a game like this, you have to focus on the positives. We won the second half (33-30) and that’s a sign of progress.”
The talented Gordon, who scored 12 points, was one of three Wildcats in double figures. Nick Johnson led Arizona with 18 and Brandon Ashley added 15, including seven of the Wildcats’ first 11 points as they raced to an 11-2 lead.
Xavier Johnson led CU with 21 points – one off his career high – and got assistance from Josh Scott (15 points, 11 rebounds) and Booker (11 points). Scott’s double-double was his ninth of the season and fourth in Pac-12 play.
Johnson made four of his five 3-point attempts and all three of his free throw tries. “X. Johnson plays well against these guys,” Boyle said. “There’s something about it; he’s amped for these guys, but we need that every time.”
CU committed 16 turnovers, leading to 23 Arizona points, while the Buffs got only 11 points from seven Wildcats turnovers – and Boyle called the Buffs’ 16 miscues “the tale of the game . . . they got 24 layups, we want that number to be seven or less. And they had 24.”
Arizona, allowing a conference-best 56.7 points a game, held CU to 60 or fewer points for only the second time this season. Baylor defeated the Buffs 72-60 in the season opener. The Wildcats, who shot 49.2 percent from the field, limited the Buffs to 38.5 percent shooting.
CU managed only six assists to Arizona’s 16, but held its own on the boards (32-32). The Buffs limited the Wildcats to two offensive boards in the second half after allowing nine in the first half. Still, Arizona ended the night with a 44-26 scoring edge in the paint.
The Wildcats have athletes, speed, skill and the advantage of a raucous, sold-out (14,545) building where they have now won 16 consecutive games and are 33-7 in Pac-12 games under coach Sean Miller. “When the crowd gets into it we have to be able to handle it,” Boyle said. “We have to learn to win in environments like this.”
With Thursday night’s 19th win of the season, Miller’s fifth UA team tied for the longest streak in program history. The Buffs now are 3-4 against the Wildcats since joining the Pac-12 in 2011.
CU last won in the McKale Center 54 years ago (Dec. 3, 1960), although much of the college hoops world believed the Buffs’ visit last season produced a “W.” But after Sabatino Chen’s 3-pointer at the final horn was waived off, Arizona won 92-83 in overtime.
Thursday night’s outcome never hinged on a buzzer beater.
CU never led, as Arizona jumped to a 9-0 lead and built its advantage to 13-2 before Askia Booker managed the Buffs’ first field goal with 14:35 left before intermission. The Wildcats surged ahead by as many as 14 (18-4) before the Buffs launched a 10-2 run, with Scott scoring seven of the 10 points, and pulled to within six (20-14) at the half’s 9:33 mark.
Instrumental in that CU rally was strategic shift on the defensive end: Boyle dusted off the 2-3 zone last employed in the Buffs 75-72 upset of Kansas in early December. Stunned initially, the Wildcats adjusted offensively and did a defensive clamp down of their own, not allowing a Buffs field goal for the next 6:33.
By then, Arizona had taken its largest lead of the half – 32-16. CU would go to its locker room trailing 39-24 and hoping to find some answers for the final 20 minutes.
The 15-point halftime deficit marked the third time in the past four games the Buffs have trailed by at least 13 points at the break. CU’s 29.6 percent from the field was second only to the 21.2 percent in the first half of the season-opening loss to Baylor.
CU still leads the overall series 11-9, but fell to 2-5 in games played at Arizona. The Wildcats’ win was their first against the Buffs in successive years since 1973 and 1974.
Climate change: Big changes for big mammals
Jan 23rd
in mammal responses to climate change
If you were a shrew snuffling around a North American forest, you would be 27 times less likely to respond to climate change than if you were a moose grazing nearby.
That is just one of the findings of a new University of Colorado Boulder assessment led by Assistant Professor Christy McCain that looked at more than 1,000 different scientific studies on North American mammal responses to human-caused climate change. The CU-Boulder team eventually selected 140 scientific papers containing population responses from 73 North American mammal species for their analysis.
The studies assessed by the team examined seven different responses to climate change by individual mammal species: local extinctions of species known as extirpations, range contractions, range shifts, changes in abundance, seasonal responses, body size and genetic diversity. The researchers used statistical models to uncover whether the responses of the 73 mammals to a changing climate were related to aspects of their physiology and behavior or the location of the study population.
The analysis showed only 52 percent of the mammal species responded as expected to climate change, while 7 percent responded the opposite of expectations and the remaining 41 percent had no detectable response. The two main traits tied to climate change responses in the CU-Boulder study were large mammal body size and restricted times during a 24-hour day when particular mammal species are active, she said.
A paper on the study by McCain and former CU-Boulder postdoctoral fellow Sarah King was published online Jan. 22 in the journal Global Change Biology. The National Science Foundation funded the study. King is currently a research associate at Colorado State University.
While body size was by far the best predictor for response to climate change — almost all of the largest mammals responded negatively — the new study also showed that mammals active only during the day or only at night were twice as likely to respond to climate change as mammals that had flexible activity times, she said.
“This is the first time anyone has identified specific traits that tell us which mammals are responding to climate change and which are not,” said McCain of CU-Boulder’s ecology and evolutionary biology department.
McCain said she and King were surprised by some of the findings. “Overall the study suggests our large, charismatic fauna — animals like foxes, elk, reindeer and bighorn sheep — may be at more risk from climate change,” she said. “The thinking that all animals will respond similarly and uniformly to temperature change is clearly not the case.”
The researchers also found that species with higher latitudinal and elevation ranges, like polar bears, American pikas and shadow chipmunks, were more likely to respond to climate change than mammals living lower in latitude and elevation. The ability of mammals to hibernate, burrow and nest was not a good predictor of whether a species responded to climate change or not. American pikas have been extirpated from some of their previously occupied sites in the West, as have shadow chipmunks, which are in decline in California’s Yosemite National Park.
One of the most intriguing study findings was that some small mammals may shelter from climate change by using a wider array of “micro-climates” available in the vegetation and soil, she said. McCain compared the findings with the events at the K-T boundary 66 million years ago when an asteroid smacked Earth, drastically changing the climate and killing off the big dinosaurs but sparing many of the small mammals that found suitable shelter underground to protect them from the cataclysmic event.
“I think the most fascinating thing about our study is that there may be certain traits like body size and activity behaviors that allow some smaller mammals to expand the range of temperature and humidity available to them,” said McCain, also a curator of vertebrate zoology at the University of Colorado Museum of Natural History. “These areas and conditions are not available to bigger mammals that live above the vegetation and experience only ambient temperatures.”
The new study builds on a growing body of global information documenting the shifting behaviors and environments of organisms like flowers, butterflies and birds in response to a warming world, said McCain.
“If we can determine which mammals are responding to climate change and the ones that are at risk of disappearing, then we can tailor conservation efforts more toward those individual species,” said McCain. “Hopefully, this potential loss or decline of our national iconic mammals will spur more people to curb climate impacts by reducing overuse of fossil fuels.”
For more information on the ecology and evolutionary biology department visit http://ebio.colorado.edu. For more information on the University of Colorado Museum of Natural History visit http://cumuseum-archive.colorado.edu/About/directory.html.
Mining big data for performance clues as a study guide
Jan 21st
forgetting with personalized content review
Computer software similar to that used by online retailers to recommend products to a shopper can help students remember the content they’ve studied, according to a new study by the University of Colorado Boulder.
The software, created by computer scientists at CU-Boulder’s Institute for Cognitive Science, works by tapping a database of past student performance to suggest what material an individual student most needs to review.
For example, the software might know that a student who forgot one particular concept but remembered another three weeks after initially learning them is likely to need to review a third concept six weeks after it was taught. When a student who fits that profile uses the software, the computer can pull up the most useful review questions.
“If you have two students with similar study histories for specific material, and one student couldn’t recall the answer, it’s a reasonable predictor that the other student won’t be able to either, especially when you take into consideration the different abilities of the two students,” said CU-Boulder Professor Michael Mozer, senior author of the study published in the journal Psychological Science.
The process of combing “big data” for performance clues is similar to strategies used by e-commerce sites, Mozer said.
“They know what you browsed and didn’t buy and what you browsed and bought,” Mozer said. “They measure your similarity to other people and use purchases of similar people to predict what you might want to buy. If you substitute ‘buying’ with ‘recalling,’ it’s the same thing.”
The program is rooted in theories that psychologists have developed about the nature of forgetting. Researchers know that knowledge—whether of facts, concepts or skills—slips away without review, and that spacing the review out over time is crucial to obtaining robust and durable memories.
Still, it’s uncommon for students to do the kind of extended review that favors long-term retention. Students typically review material that was presented only in the most recent unit or chapter—often in preparation for a quiz—without reviewing previous units or chapters at the same time.
This leads to rapid forgetting, even for the most motivated learners, Mozer said. For example, a recent study found that medical students forget roughly 25 to 35 percent of basic science knowledge after one year and more than 50 percent by the next year.
Over the last decade, Mozer has worked with University of California, San Diego, psychologist Harold Pashler, also a co-author of the new study, to create a computer model that could predict how spaced review affects memory. The new computer program described in the study is an effort to make practical use of that model.
Robert Lindsey, a CU-Boulder doctoral student collaborating with Mozer, built the personalized review program and then tested it in a middle school Spanish class.
For the study, Lindsey and Mozer divided the material students were learning into three groups. For material in a “massed” group, the students were drilled only on the current chapter. For material in a “generic-spaced” group, the students were drilled on the most recent two chapters. For material in a “personalized-spaced” group, the algorithm determined what material from the entire semester each student would benefit most from reviewing.
In a cumulative test taken a month after the semester’s end, personalized-spaced review boosted remembering by 16.5 percent over massed study and by 10 percent over generic-spaced review.
In a follow-up experiment, Mozer and his colleagues compared their personalized review program to a program that randomly quizzes students on all units that have been covered so far. Preliminary results show that the personalized program also outperforms random reviews of all past material.
So far, the program has been tested only in foreign language classes, but Mozer believes the program could be helpful for improving retention in a wide range of disciplines, including math skills.
It’s not necessary to have a prior database of student behavior to implement the personalized review program. Students can begin by using the program as a traditional review tool that asks random questions, and as students answer, the computer begins to search for patterns in the answers. “It doesn’t take long to get lots and lots of data,” Mozer said.
The research was funded by the National Science Foundation and the McDonnell Foundation.
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