PPTX - IACBE

Report
Using Analytics to Integrate
Critical Thinking and Quantitative Reasoning
Skills in Business Program Curricula
Dr. Alan Burns, Dean of Business, Leadership and Psychology
Dr. Ariane Schauer, Provost
Marymount California University
2014 IACBE Annual Conference and Assembly Meeting
San Diego, California
April 9, 2014
Outline
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Goals of the Project
Quantitative Reasoning
Curriculum Mapping & Assessment
Implementation
Predictive Analytics
Discussion/Questions
Goals of the Project
• Use learning analytics to drive improvement for
curriculum design and delivery
• Measure learning at the student level across the
life of program
• Move toward predictive analytics and agile
development of courses, programs
• Common metrics for assessment, maintaining
flexibility for teaching
• Minimize the burden of faculty
QUANTITATIVE REASONING
MCU BA-Business Program Outcomes
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Quantitative Literacy
Problem Solving
Critical Thinking
Creative Thinking
Integrative Learning
Ethics
Global Perspective
Inquiry
Oral Communication
Written Communication
AAC&U Definitions
• Quantitative Literacy (QL) – also known as Numeracy or
Quantitative Reasoning (QR) – is a "habit of mind," competency,
and comfort in working with numerical data.
• Critical thinking is a habit of mind characterized by the
comprehensive exploration of issues, ideas, artifacts, and events
before accepting or formulating an opinion or conclusion.
• Problem solving is the process of designing, evaluating and
implementing a strategy to answer an open-ended question or
achieve a desired goal.
• Creative thinking is both the capacity to combine or synthesize
existing ideas, images, or expertise in original ways and the
experience of thinking, reacting, and working in an imaginative way
characterized by a high degree of innovation, divergent thinking,
and risk taking.
Quantitative Reasoning
Quantitative Literacy (QL):
comfort, competency, and
"habit of mind" in working with
numerical data.
Quantitative Reasoning (QR):
higher-order reasoning and
critical thinking skills needed to
understand and to create
sophisticated arguments
supported by quantitative data.
from the National Numeracy Network,
http://serc.carleton.edu/nnn/index.html
Elrod, S. & Lindholm, J. (2013). “An Introduction to Quantitative Reasoning and Assessment in Majors”, Retreat on
Core Competencies: Quantitative Reasoning and Assessment in Majors, October 24 - 26, 2013, Pomona, CA.
Quantitative Reasoning Learning Outcomes:
An Example
A graduating fourth-year undergraduate at the University of Virginia will be able to:
1. Interpret mathematical models such as formulas, graphs, tables, and schematics, and draw inferences
from them.
2. Communicate mathematical information symbolically, visually, numerically, and verbally.
3. Use arithmetical, algebraic, and geometric methods to solve problems.
4. Estimate and check answers to mathematical problems in order to determine reasonableness.
5. Solve word problems using quantitative techniques and interpret the results.
6. Apply mathematical/statistical techniques and logical reasoning to produce predictions, identify optima,
and make inferences based on a given set of data or quantitative information.
7. Judge the soundness and accuracy of conclusions derived from quantitative information, recognizing that
mathematical and statistical methods have limits and discriminating between association and causation.
8. Solve multi-step problems.
9. Apply statistics to evaluate claims and current literature.
10. Demonstrate an understanding of the fundamental issues of statistical inference, including measurement
and sampling.
from
http://avillage.web.virginia.edu/iaas/assess/data/competency/quantitativereasoning/quant07-08.shtm
MCU Draft Quantitative Literacy Rubric
• Rubric Criteria
– Interpretation: Ability to explain information presented in
mathematical forms (e.g., equations, graphs, diagrams, tables, words).
– Representation: Ability to convert relevant information into various
mathematical forms (e.g., equations, graphs, diagrams, tables, words).
– Calculation
– Application / Analysis: Ability to make judgments and draw
appropriate conclusions based on the quantitative analysis of data,
while recognizing the limits of this analysis.
– Assumptions: Ability to make and evaluate important assumptions in
estimation, modeling, and data analysis.
– Communication: Expressing quantitative evidence in support of the
argument or purpose of the work (in terms of what evidence is used
and how it is formatted, presented, and contextualized).
Quantitative Literacy Rubric
CURRICULUM MAPPING &
ASSESSMENT
Curriculum Map
• A matrix of Program Outcomes vs. Courses
– How do courses contribute to development of a program
outcome?
– What, where and how do they learn?
• Program Outcomes
– Broad enough to capture higher order learning (and
reusability)
– Specific enough to drive improvement
– Developed over a series of courses
– Competency-based
• Course
– Outcome-Assignment-Rubric nodes
Oral Communication Rubric
• Rubric Criteria
– Central message: The main point/thesis/"bottom line"/"take-away" of
a presentation
– Delivery technique: Posture, gestures, eye contact, and use of the
voice
– Language: Vocabulary, terminology, and sentence structure.
– Organization: The grouping and sequencing of ideas and supporting
material in a presentation.
– Supporting material: Explanations, examples, illustrations, statistics,
analogies, quotations from relevant authorities, and other kinds of
information or analysis that supports the principal ideas of the
presentation.
Adapted from Association of American Colleges & Universities (AAC&U)
Proposed Curriculum Map:
PO#1, Communication
Proposed Outcome:
Students will communicate a central message in informative or persuasive ways
using the appropriate form, channel, structure and style.
Reinforce
Develop / Mastery
Introduce
Develop
ID117 (or ID217)
Art of Being Human
BUS300
Principles of
Management
Various
courses
Assignments:
Sales Pitch presentation
Elevator speech
Assignments:
Email response
assignment
Emerging Theme in
Management paper
Assignments:
Papers,
presentations
Assignments:
Capstone Final Project
Capstone Final Presentation
Outcome:
Varies
Outcome:
Summative Assessment on
outcome
Outcome:
Develop oral communication
and presentation skills
Rubric:
Oral Communication Rubric
Outcome:
Develop written
communication skills
Rubric:
Written
Communication Rubric
Rubrics:
Oral and Written
Communication
Rubrics
BUS498
Business
Capstone
Rubrics:
Oral Communication Rubric
Written Communication Rubric
Oral Communication Assignments
• Develop and deliver a 30 second elevator
speech describing why you should be hired to
an HR manager;
• Develop and deliver an effective 2 minute
sales pitch for a small business opportunity to
a venture capitalist;
Proposed Curriculum Map:
PO#2, Analysis
Proposed Outcome:
Students will use critical thinking to analyze, interpret, represent and communicate
quantitative data and information about financial statements, business performance and
industry trends.
Reinforce
Develop / Mastery
Introduce
Develop
ACCT201
Managerial Accounting
BUS350
Principles of
Marketing
BUS380
Corporate Finance
BUS497
Business Capstone
Proposal
Assignments:
Create balance sheet, income
statement, cash flow statement
Assignments:
Case studies
Assignments:
Outcome paper
Assignments:
Capstone proposal
Outcome:
Analyze, interpret
quantitative data to
draw conclusions
Outcome:
Connect experiential
learning to coursework
Outcome:
Summative Assessment on
outcome
Rubrics:
Quantitative Literacy
Rubric
Rubrics:
Quantitative Literacy Rubric
Outcome:
Analyze, interpret and represent
quantitative data
Rubrics:
Quantitative Literacy Rubric
Rubrics:
Quantitative Literacy
Rubric
Quantitative Literacy Assignments
Course
Assignment
Rubric
Criteria
ECO220
Evaluate GDP trends for different
regions and countries
Quantitative Literacy
Interpret,
Communication
ACCT201
Create financial statements
Quantitative Literacy
Interpret, Represent
BUS380
Calculate the weighted average cost
of capital (WACC)
Quantitative Literacy
Interpretation,
Calculation
BUS350
Analyze Marketing case studies
Quantitative Literacy
Interpretation,
Calculation
Application/Analysis
Assumptions
Communication
BUS498
Final capstone presentation
Quantitative Literacy
Interpretation
Representation
Calculation
Application
Analysis
Assumptions
Communication
IMPLEMENTATION
Learning Analytics Approach
• Learning Management System is Desire2Learn
• Using D2L Analytics to measure learning at the
level of
– Program
– Course
– Course Offering
– Student
D2L Structure
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Program
Course Template
Course Offering
Activity
Rubric
Curriculum Map
Lake Valley University
Individual Student Progress
PREDICTIVE ANALYTICS
Risk Quadrant
Success index designed to let you
visualize and compare key
factors – course access, content
access, social learning,
completion, grades
Sociogram
Visualize social network patterns for class
discussion forums and identify isolated and
connected students
Grades Visualization
Innovative grades visualization provide diagnostic insights
Interactive drill-down and roll-up to view grade patterns
Summary
• Competency-based assessment for program
outcomes
• Goals include improving quantitative
reasoning and literacy skills
• Using learning analytics at the program,
course and student level
• Moving toward predictive analytics in the
classroom
Questions

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