1 / 14

Making the Connection Between Classroom and Programmatic Assessment

Food Science & Technology. Dan Smith Department of Food Science & Technology Oregon State University. Making the Connection Between Classroom and Programmatic Assessment. Faculty Assessment Academy, October 5, 2011. FST’s Path to Assessment.

wallis
Download Presentation

Making the Connection Between Classroom and Programmatic Assessment

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Food Science & Technology Dan Smith Department of Food Science & Technology Oregon State University Making the Connection Between Classroom and Programmatic Assessment Faculty Assessment Academy, October 5, 2011

  2. FST’s Path to Assessment • (2000) Learning outcomes assessment mandated by Institute of Food Technologists (professional organization in our discipline) • (2002-2003) Workshops - invited speakers shared experience of other universities • (2005) Collected first assessment data • (2006-present) “Closing the loop” • utilizing data to inform class and curricular changes • redirecting and refining assessments based upon earlier findings Food Science & Technology

  3. Advice from the Pros • Start small, but start!!! • make existing assessments more intentional • Utilize rubrics • Regularly share assessment experiences and results with your faculty • Build on initial results - assessment and class/curricular revision are cyclical Food Science & Technology

  4. Make Every Assessment Count • From the beginning FST sought to design assessments that would have value within individual classes, but could also provide data needed for programmatic assessment • Programmatic learning outcomes requiring assessment (for IFT approval) • disciplinary knowledge • oral and written communication • critical thinking and problem solving Food Science & Technology

  5. Assessing Written Communication Programmatic Assessment Goals • Assess student performance on different kinds of writing assignments • Measure growth in writing during progression through the program Class Assessment Goals • Help students set writing goals, and reflect on writing achievements • Adapt presentation of a given term’s class to needs and aspirations of students • Provide students clear guidance for writing and its evaluation • Evaluate effectiveness of specific assignments Food Science & Technology

  6. Student WritingPre-Class Survey • Objectives • instructor learns about attitudes, experiences and perception of ability of class members • students begin to think about writing and set goals • Mechanism • administer during first week of class • ungraded (can be made anonymous) • review aggregate results with class Food Science & Technology

  7. Student WritingPost-Class Survey • Objectives • students reflect on writing growth • instructor documents student perception of achievements • before and after comparison could be used in publication and/or promotion and tenure • Obtain approval from IRB Food Science & Technology

  8. Instructor (Rubric) BasedWriting Assessment • Objectives • provide students a guide for writing expectations • objective means of writing evaluation • instructor driven evaluation of effectiveness of specific assignments • rubric can be used across assignments or classes • evaluate students’ performance on different kinds of assignments • measure growth in writing skill as students progress through the program Food Science & Technology

  9. FST’s Writing Rubric • Matrix: five dimensions x three levels of achievement • Brief description of characteristics associated with each possible dimension-level combination. • Introduced in Food Science Orientation class and utilized in several courses that require writing • Several years of data collection across several classes resulted in conclusion that FST students were writing adequately in the discipline • Data used to guide modification of writing assignments Food Science & Technology

  10. Core Knowledge Assessment • Grew out of attempt to assess critical thinking • revealed inadequate grasp of underlying concepts • Food Chemistry faculty identified core knowledge in three courses • Each course incorporated core knowledge assessment questions into exams Food Science & Technology

  11. Core Knowledge Assessment • In course and programmatic use of results • reinforced teaching in areas found to be weak • split one class into two • introduced guided discussion and problem solving in recitation • redesigned courses to increase engagement • Bringing Food Chemistry to Life • Andrew Ross blog: http://blogs.oregonstate.edu/deliciousnessw09/ • measured improvement in core knowledge mastery across several classes Food Science & Technology

  12. A Pre-Course Diagnostic • Ungraded quiz on Excel and/or math skills • Results used to direct students with weak preparation to online help or 1-credit class for skill reinforcement • Benefits • Shape of class grading curve no longer has a significant tail of struggling students • Class computational sessions, requiring use of Excel more productive Food Science & Technology

  13. Summarizing FST’s Experience • Class based assessments can be used to improve an individual class as well as provide insights into the functioning of the entire curriculum • Focus assessments on areas where you sense a problem • Design assessments so that they provide information that leads to action • Assessment and intervention should be cyclical • Share assessment techniques and results with colleagues Food Science & Technology

  14. Acknowledgements • Our Mentors in Learning Outcome Assessment • Dr. Barbara Walvoord, Professor Emerita, University of Notre Dame • http://www.theideacenter.org/helpful-resources/consulting-consultant/barbara-walvoord/00283-about-barbara-e-walvoord-phd • Dr. Richard Hartel, Professor, University of Wisconsin, Madison • Dr. Tracey Ann Robinson, OSU School of Mechanical, Industrial and Manufacturing Engineering • FST Colleagues • Drs. Tom Shellhammer, Robert McGorrin, Andrew Ross, Mike Penner, Antonio Torres, Juyun Lim and Lisbeth Goddik Food Science & Technology

More Related