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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

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.