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Campus Wide Assessment Project. Quantitative and Symbolic Reasoning. Assessment Team: David Nelson – Faculty Lead, Math Division Janet Ash, Technology Division Brenda Bindschatel, Business Division Keith Clay, Science Division Sandy Johanson, Humanities Division. Goals of the Project.

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Campus wide assessment project

Campus Wide Assessment Project

Quantitative and Symbolic Reasoning

Assessment Team:

David Nelson – Faculty Lead, Math Division

Janet Ash, Technology Division

Brenda Bindschatel, Business Division

Keith Clay, Science Division

Sandy Johanson, Humanities Division

Goals of the project
Goals of the Project

  • Peer review of the Learning Outcome Tracking System (LOTS) database

  • Campus-wide assessment of the QSR outcome

Quantitative and symbolic reasoning
Quantitative and Symbolic Reasoning

  • Evaluate and interpret quantitative and symbolic reasoning information/data

  • Recognize which quantitative or symbolic reasoning methods are appropriate for solving a given problem, and correctly implement those methods

  • Demonstrate the ability to estimate a solution to a presented problem

  • Translate data into various formats such as symbolic language, equations, graphs and formulas

  • Implement calculator/computer technology to solve problems

  • Demonstrate logical reasoning skills through formal and informal proofs.

Lots database
LOTS Database

Courses are rated by instructors or departments

  • Level 0: Not taught, practiced or assessed

  • Level 1: taught or practiced, but not assessed

  • Level 2: assessed by not taught

  • Level 3: taught and assessed

Peer review of lots
Peer Review of LOTS

  • Review CARS of all courses claiming Level 3 for any of the QSR competencies

Review of lots database
Review of LOTS Database

CHEM 105: Marked QSR Competency 2 and Competency 5 at Level 3

The student will demonstrate proficiency in the following areas:

  • Metric conversions, using dimensional analysis

  • Naming chemical elements, and identifying atomic numbers and mass

  • Writing chemical formulas and naming compounds

  • Calculating molar masses

  • Quantitative composition of compounds

  • Writing and balancing chemical equations

  • Periodic properties

    Individual instructors will chose two (three?) of the following proficiencies as the last unit of the class :

  • Mass relationships in a balanced equation

  • Atomic structure of the first eighteen elements

  • Gas laws

  • Chemical bonds

  • Properties of liquids

Review of lots database1
Review of LOTS Database

NATRS 183 claims QSR 1, 2, and 4

Students will learn:

  • The use of taxonomic keys to identify trees, and shrubs.

  • The use and comprehension of dendrology terminology.

  • Plant morphology

  • Identification of all required plants

  • How to establish grid plots

Quantitative Reasoning: Students will measure physical, biological, and environmental parameters. Additional parameters and results will be obtained by calculations and graphing.

Review of lots database2
Review of LOTS Database

  • 158 CARs claiming Level 3 were reviewed

  • QSR documentation in 14 CARs were deemed inadequate

  • LOC Chair and division rep met with lead instructors and either changed LOTS rating or changed course syllabus

  • 13 of the 14 have been adjusted

  • Issue of authority and control needs to be decided

Campus wide assessment
Campus Wide Assessment

  • Determine an appropriate assessment

  • Implement assessment with the aid of instructors

  • Analyze the data

  • Report to the community

Campus wide qsr assessment
Campus Wide QSR Assessment

  • Competencies 1, 2, 4 and 5

  • 8 classes chosen randomly for each competency

  • Appropriate mix of day, night and distance courses

  • Appropriate mix full-time and adjunct instructors

  • Embedded assessment tool – created by the faculty

  • Scored according to the Community Rubric

Campus wide qsr assessment challenges with the data
Campus Wide QSR AssessmentChallenges with the Data

  • Several instructors did not participate or did not provide data in time for the assessment – 11 of the 35 selected classes

  • Minimal data collected for QSR 5 - 2 of 10 classes provided pre and post assessment data, one provided post assessment data only

  • One day class was substituted for the initial selection of a night class (QSR 1)

  • Difficult to distinguish between Competent & Mastering when there was a single problem

Campus wide assessment project

Campus wide assessment project

Campus wide assessment project

Campus wide assessment project

Campus wide assessment project

Unusual classes
Unusual Classes language, equations, graphs and formulas

Math 97, B A 220 and BIO 100 show improvement, but not nearly as much as other courses.

MATH 97, B A 220 - QSR Competency 1

BIO 100 - QSR Competency 4

Unusual classes1
Unusual Classes language, equations, graphs and formulas

BA 110 and Chem 150 had a large number of competent/mastering students on the pre assessment. (Competency 4)

Full time and adjunct faculty
Full-Time and Adjunct Faculty language, equations, graphs and formulas

Day evening and online classes
Day, Evening and Online Classes language, equations, graphs and formulas

Recommendations language, equations, graphs and formulas

  • Relatively few courses claim Competency 3 and Competency 6. Should we offer more? Do we expect mastering of all competencies?

  • Revise Competency 2, or use better assessment methods. Two different skills are listed.

  • Improve success rate of Competency 1

  • Increase communication between full-time, adjunct, day, evening and online instructors

  • Look at math prerequisites for courses with a minority of students reaching the competent or mastering level.

Recommendations for follow up studies
Recommendations for follow-up studies language, equations, graphs and formulas

  • Check degree requirements with CWOs. Can a student graduate without taking QSR classes?

  • Use appropriate assessments. – Comp. 2

  • Start earlier.

  • Contact instructors of classes selected for sample earlier/more frequently to get a better response rate.