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MARC Record from marc_oapen

Record ID marc_oapen/convert_oapen_20201117.mrc:30742264:2851
Source marc_oapen
Download Link /show-records/marc_oapen/convert_oapen_20201117.mrc:30742264:2851?format=raw

LEADER: 02851namaa2200253uu 450
001 http://library.oapen.org/handle/20.500.12657/26061
005 20190121
020 $a9780262518376
041 0 $aEnglish
042 $adc
072 7 $aJNKD$2bicssc
100 1 $aSchwartz, Daniel L.$4auth
700 1 $aArena, Dylan$4auth
245 10 $aMeasuring What Matters Most : Choice-Based Assessments for the Digital Age
260 $aCambridge$bThe MIT Press$c2013
300 $a1 electronic resource (192 p.)
506 0 $aOpen Access$2star$fUnrestricted online access
520 $aAn argument that choice-based, process-oriented educational assessments are more effective than static assessments of fact retrieval.If a fundamental goal of education is to prepare students to act independently in the world—in other words, to make good choices—an ideal educational assessment would measure how well we are preparing students to do so. Current assessments, however, focus almost exclusively on how much knowledge students have accrued and can retrieve. In Measuring What Matters Most, Daniel Schwartz and Dylan Arena argue that choice should be the interpretive framework within which learning assessments are organized. Digital technologies, they suggest, make this possible; interactive assessments can evaluate students in a context of choosing whether, what, how, and when to learn.Schwartz and Arena view choice not as an instructional ingredient to improve learning but as the outcome of learning. Because assessments shape public perception about what is useful and valued in education, choice-based assessments would provide a powerful lever in this reorientation in how people think about learning.Schwartz and Arena consider both theoretical and practical matters. They provide an anchoring example of a computerized, choice-based assessment, argue that knowledge-based assessments are a mismatch for our educational aims, offer concrete examples of choice-based assessments that reveal what knowledge-based assessments cannot, and analyze the practice of designing assessments. Because high variability leads to innovation, they suggest democratizing assessment design to generate as many instances as possible. Finally, they consider the most difficult aspect of assessment: fairness. Choice-based assessments, they argue, shed helpful light on fairness considerations.
540 $aCreative Commons$fby-nc-nd/4.0$2cc$4http://creativecommons.org/licenses/by-nc-nd/4.0
546 $aEnglish
650 7 $aExaminations & assessment$2bicssc
653 $aeducation
856 40 $awww.oapen.org$uhttps://library.oapen.org/bitstream/id/3a2159a6-172c-4e59-9ef6-075f94363a74/1004024.pdf$70$zOAPEN Library: download the publication
856 40 $awww.oapen.org$uhttp://library.oapen.org/handle/20.500.12657/26061$70$zOAPEN Library: description of the publication