assessment research and tools: when, why, how?

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Assessment Research and Tools: when, why, how?. Diane Ebert-May Department of Plant Biology Michigan State University ebertmay@msu.edu http://first2.org. The trouble with our times is that the future is not what it used to be. -Paul Valery, The Art of Poetry. - PowerPoint PPT Presentation

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Assessment Research and

Tools:when, why, how?

Diane Ebert-MayDepartment of Plant Biology

Michigan State University

ebertmay@msu.eduhttp://first2.org

The trouble with our times is that the future is not what it

used to be. -Paul Valery, The Art of Poetry

Q2. What is assessment?

Q1. What is scientific teaching ?

Please write responses on card

Active is participation to learn (accomplish

goals)

Assessment is evidence

Diversity is science for all...

Q1. What is scientific teaching?

Q2. What is assessment? Data collection with the purpose

of answering questions about…students’ understandingstudents’ attitudesstudents’ skillsinstructional design and implementationcurricular reform (at multiple grainsizes)

Q3. Why do assessment?

Improve student learning and development.Provide students and faculty

substantive feedback about student understanding.

Challenge to use disciplinary research strategies to assess learning.

So what are the issues? Claim: Faculty need to change their teaching.Why: Data indicate students are not learning science/math.

Therefore: ... if faculty implement effective scientific teaching, ...data will show learning gains by all.

Faculty change?

Engage

True or False?

Assessing student learning in science parallels what scientists/do as researchers.

1.Description: -What is happening?

2.Cause: -Does ‘x’ (teaching strategy)

affect ‘y’ (understanding)?3.Process or mechanism:

-Why or how does ‘x’ cause ‘y’?

Parallel: ask questions

We collect data to find out what our students know.

Data helps us understand student thinking about concepts and content.

We use data to guide decisions about course/curriculum/innovative instruction

Parallel: collect data

Quantitative data - statistical analysisQualitative data

break into manageable units and define coding categoriessearch for patterns, quantify interpret and synthesize

Valid and repeatable measures

Parallel: analyze data

Ideas and results are peer reviewed - formally and/or informally.

Parallel: peer review

Explore

Guidelines for thinking about research...

What did students learn? (assessment data)Why did students respond a particular way? (research) Significant question?What are the working hypotheses? Relevant theory..What has already been done? Literature says...How and why select methods? Direct investigation...How to analyze and interpret data? What do the results mean? Coherent reasoning...Are findings replicable and generalizable? Critique by peers...

Research Designs

Data collection

Assessment GradientAssessment GradientHigh

Ease ofAssessment

Low

Multiple Choice, T/F

Diagrams, Conceptmaps, Quantitative

response

Short answer

Essay, Researchpapers/ reports

Oral Interview

Low

Potential for

Assessment ofLearning

High

Explain/Elaborate

SystemModel

Final Assessment?

IRD Team at MSUJanet Batzli - Plant Biology [U of Wisconsin]Doug Luckie - PhysiologyScott Harrison - Microbiology (grad student)Tammy Long - Plant BiologyDeb Linton - Plant Biology (postdoc)Rett Weber - Plant BiologyHeejun Lim - Chemistry EducationDuncan Sibley - GeologyRob Pennock - PhilosophyCharles Ofria - EngineeringRich Lenski - Microbiolgy*National Science Foundation

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