Assessing Student Learning in Higher Education

Section 1
 Introduction

Section 2
 
Background and Rationale for Assessment

Section 3
Student Learning Outcomes (SLOs)

Section 4
 Assessment Tools and Data
Quality Data
Defining Terms
Assessment Tools
Grades & Assessment
Primary Trait Analysis
Rubrics
Selecting the Tools
Creating a Tool
Quiz
Your SLOs

Section 5
Course Assessment

Section 6
Program Assessment

 

Section 7
Closing the Loop
 

Section 8
Implementing Assessment Training on Campus

 

Section 9
References & Resources


Definitions

Workbook


Using Materials from this Website

 

Quality Data

In the simplest definition, quality data:
- are based upon best practices,
- answer important questions, and
- benefit the students and institution by providing evidence to complete the assessment loop.

The Assessment Loop

Develop, modify, or review a curriculum, course, program, or service.

 

Develop Student Learning Outcomes (SLOs)

 

Design & Measure Student Learning as a result of the Curriculum, Course, or Program.

 

Collect, discuss, and analyze data.

 

Determine refinements based on data.

  Closing the Assessment Loop

Do you know what really works in your teaching, counseling, student service, etc.? The assessment loop is a data-driven method of decision-making based upon a learning paradigm, in which we are learners about our own methods and institutional processes. The loop begins with questions posed concerning what works and what does not, what enhances student learning and what does not. To determine the answer to the questions an assessment or investigation is initiated. The investigation generates data to answer the question. When carried out as an integrated part of the educational process it is often referred to as the scholarship of teaching. By analyzing our teaching methods and learning outcomes, we can improve the process based on information gleaned through assessment, rather than running on intuition. The goal is to create a culture of evidence for institutional decision-making.
 

The key to this process is quality data. You may have heard these quotes about  statistics and data:
 

Statistics are like bikinis.  What they reveal is suggestive, but what they conceal is vital. 
~Aaron Levenstein

 

Facts are stubborn things, but statistics are more pliable.  ~Author Unknown

There are three kinds of lies - lies, damned lies and statistics.  ~Benjamin Disraeli, commonly misattributed to Mark Twain because he quotes Disraeli in Autobiography (Thank you, Will.)

 

Torture numbers and they'll confess to anything. 
~Gregg Easterbrook

 

From the Quote Garden http://www.quotegarden.com/statistics.html


In this material, quality data are defined as :

Valid - the data accurately represents what you are trying to measure. For instance the number of people that graduate don't necessarily represent good data on what has actually been learned.
 
Reliable - the data are reproducible. Repeated assessment yields the same data.

Authentic - the assessment simulates real-life circumstances. Also see the link to Grant Wiggins article on authentic assessment.

Relevant - the data answers important questions, and is not generated simply because it is easy to measure.

Effective - the data contributes to improving teaching and learning.

Proceed to Defining Terms

Resources and Links

Authentic Assessment
Wiggins, 1990


 


ACCJC-WASC Characteristics of Evidence

 

 

 

 

 

 

 

 

 

 

Using Data from Program Improvement: How Do We Encourage Schools To Do It?
Levisque, Bradby, Rossi, MPR Associates, 1996

 

 

 

 

 

 

Elementary, help with data and statistics.

 

Data-driven School Improvement
Johnson, 1997

 

Janet Fulks
Assessing Student Learning in Community Colleges (2004), Bakersfield College
jfulks@bakersfieldcollege.edu    
07/11/2006