07-08 General Education Learning Outcomes Assessment - Quantitative Reasoning

 

D. Quantitative Reasoning: Demonstrate the ability to use numerical, geometric and measurement data in computations and reasoning to draw logical conclusions and make well-reasoned decisions.

Gen Ed courses: MAT 1033, MAC 1105, MAC 1114, MAC 1140, MAC 2233, MAC 2311, MAC 2312, MAC 2313, MAP 2302, MGF 1106, MGF 1107, STA 2023

Learning Outcomes

 

Related Courses and Primary Measurement

 

 

Performance Criteria/

Expected Results

Findings

Actions taken

Student will demonstrate the ability to make necessary and appropriate unit/numeric conversions.

 

MAC 1105departmental final exam

 

 

Line item analysis of multiple choice portion of final exam.

 

Identify areas of strength and areas of weakness and choose an area or weakness to address as a department.

Line items #2, 7, 21, and 23 correspond.

 

In summer 2008, we collected our first data set. With an N = 56, we determined we may need more data to make a clear distinction.

 

The percentage of correctly answering all items relative to this learning outcome was 66.5%.

While line item #23 had 85.7% answers correctly, the others need improvement. Line item #2 had 57.1%, #7 had 60.7%, and #21 had 62.5%. Line item #2 decreased our success on this assessment.

 

Revised exam and expanded data collection to MGF 1106 which has a primary goal of teaching unit conversions.

 

Also, need a larger N to show statistically significant results. Large scale data collection will begin Fall, 2008.

 

After of year of data collection, reliability measures will be looked into.

Student will demonstrate the ability to graphically represent relations and functions along with the ability to interpret mathematical models such as formulas, graphs, and tables, and draw inferences from them.

MAC 1105 departmental final exam

Line item analysis of multiple choice portion of final exam.

 

Identify areas of strength and areas of weakness and choose an area or weakness to address as a department.

Line items #1, 3, 5, 9, 10, 11, 12, 15, 17, 22, and 24 correspond.

 

In summer 2008, we collected our first data set. With an N = 56, we determined we may need more data to make a clear distinction.

 

The percentage of correctly answering all items relative to this learning outcome was 73.4%. Four items had weak performance measures -- #9 at 46.4%, #11 at 66.1%, #22 at 67.9%, and #29 at 48.2%. All others scored above 73.2% as follows:

#1 73.2%; #3 98.2%;

#5 91.1%; #10 73.2%;

#12 75%; #15 78.6%;

#17 89.3%.

Revised exam. Had departmental discussions on differences in teaching styles. LCCC Quality Enhancement Plan will also address these issues.

 

Also, need a larger N to show statistically significant results. Large scale data collection will begin Fall, 2008.

 

After of year of data collection, reliability measures will be looked into.

Student will demonstrate the ability to use algebraic skills and solve equations along with the ability to estimate and check answers to problems in order to determine reasonableness, identify alternatives, and select optimal results.

 

MAC 1105 departmental final exam

Line item analysis of multiple choice portion of final exam.

 

Identify areas of strength and areas of weakness and choose an area or weakness to address as a department

Line items #4, 6, 8, 13, 14, 16, 18, 19, 20, and 25 correspond.

In summer 2008, we collected our first data set. With an N = 56, we determined we may need more data to make a clear distinction.

 

The percentage of correctly answering all items relative to this learning outcome was 67.7%. Only four items would be considered good performers items #14 at 78.6%, #16 at 80.4%, #19 at 83.9%, and #20 at 91.1% correct. All others scored below 67.9% as follows:

#4 42.9%; #6 - 53.6%

#18 67.9%; #13 52.6%

#18 66.1%;#25 58.9%

Revised exam. Had departmental discussions on differences in teaching styles. LCCC Quality Enhancement Plan will also address these issues.

 

Also, need a larger N to show statistically significant results. Large scale data collection will begin Fall, 2008.

 

After of year of data collection, reliability measures will be looked into.