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Jared Stein

From Assessment to Accreditation (Software Required) | Inside Higher Ed - 0 views

  • Collect data from different sources; use multiple assessments to create as many data points as possible; evaluate both alumni and employer satisfaction once students graduate; institute program reviews
  • Before an accreditation site visit, a college needs to know that it will be ready with any kind of data it's asked for -- and that requires a systemwide approach, illustrating how specific goals were achieved (or altered) because of assessment data.
  • collecting this data on our behalf from either the admissions office, registrar’s office even our graduate programs, and we track down students all the time who graduated 10-15 years prior so that we can keep up with our needs
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    "faculty should have a central role in planning and evaluating programs; that standards clearly align with each other and with accreditation requirements; and that measures are internally consistent."
Jared Stein

Unbundling vs. Embedding: Approaches to reuse of integrated course objects | Hapgood - 0 views

  • one of the core functions the educator provides is to structure content into a sequence that learners can follow and have trust in. The bargain they make is this – if I do the course you have constructed then I will come out with a certain understanding of the topic.
  • I’ve realized that there are major problems with severing assessment from content, content from interaction, and so on. If you don’t believe me, hop on down to your kid’s school on standardized assessment day.
  • In an embedded model, there is no unbundling. Instead there is “wrapping”.
Jared Stein

How to Uphold Online Learning Standards to Quality Education | MindShift - 1 views

  • the online education model needs to create a more accurate way to assess the quality of the dozens of programs in the space
Jared Stein

How data and analytics can improve education - O'Reilly Radar - 0 views

  • The existing data gathering in schools and universities pales in comparison to the value of data mining and learning analytics opportunities that exist in the distributed social and informational networks that we all participate in on a daily basis. It is here, I think, that most of the novel insights on learning and knowledge growth will occur. When we interact in a learning management system (LMS), we do so purposefully — to learn or to complete an assignment. Our interaction in distributed systems is more "authentic" and can yield novel insights into how we are connected, our sentiments, and our needs in relation to learning success.
  • learners should have access to the same dashboard for analytics that educators and institutions see
  • a learning management system like Moodle or Desire2Learn captures a significant amount of data, including time spent on a resource, frequency of posting, number of logins, etc
  • ...2 more annotations...
  • Much of the current focus on analytics relates to reducing attrition or student dropouts. This is the low-hanging fruit of analytics.
  • learning analytics serve as a foundation for informed change in education, altering how schools and universities create curriculum, deliver it, assess student learning, provide learning support, and even allocate resources.
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