1. The document discusses using artificial intelligence to analyze syllabus quality as a way to improve course and program quality. It proposes evaluating syllabi both before and after they are implemented.
2. A prototype system is described that can automate the evaluation process by representing syllabi as graphs and detecting inconsistencies, validity, reliability, and costs.
3. The system demonstrates the potential to objectively measure multi-dimensional syllabus quality and open new opportunities for smart syllabus management and efficient teaching materials development.
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APPLYING ARTIFICIAL INTELLIGENCE TO THE EDUCATIONAL DATA
1. Denis Smolin,
American University in Bosnia and Herzegovina
Sergey Butakov,
SolBridge International School of Business, Daejeon, South Korea
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
2. First many higher education
institutions are striving to be
strategic rather than merely
reactive
Forth, universities must
operate more efficiently
overall.
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
3. Presentation in a glance
We will be talking about using AI to analyze
syllabus quality as a driving force to improve
quality of a course and finally quality of a
program
We will be talking about a priori and a
posteriori evaluations
We will discuss system prototype that allows
us to automate the evaluation process
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
4. Syllabus and its characteristics
Definition of the good syllabus
Syllabus quality management
Syllabus metrics
Syllabus consistency
Student Outcomes as the Syllabus
Quality metrics
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
5. A syllabus that follows acknowledged patterns (Davis,
1993; McKenney, 2001):
A syllabus that promotes good outcomes (Zhao, 2007)
Tailored or negotiated syllabus that fits course
requirements and student learning style (Clarke, 1991)
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
6. Syllabus Quality Depends on
Quality of the
included materials
Instructor Other, often
Motivation & Abilities
Student Unknown &
Motivation & Abilities Uncertain
Scheduling
factors
School
facilities
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
7. If a student has difficulties with
multiple choice tests in Programming I course
Correct the
Component Evaluate
Component
Quality Changes
Structure
Pros: Could improve the
Try to replace some tests with practical
understanding
coding assignments
Cons: Could be more expensive
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
8. If majority of students complain about the textbook
Correct the
Component Evaluate
Component
Quality Changes
Structure
Use another textbook Pros: Increased understanding
Cons: Revision is required for the
practical component of the course
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
9. Components
List of Other Traditional
Schedule Books Tests
topics & New Elements:
subject specific
elements, Web 2.0
apps, etc.
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
10. Overall Syllabus Quality ?
or
The quality of its Components ?
Both!
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
11. Traditional Approach:
Student Surveys / Evaluations
Student Outcomes (e.g. current and final grades)
Evaluations from Accrediting Organizations
Some others, mainly based on Expert Opinions
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
12. How many errors are in the
structure of the syllabus
Calculate Syllabus consistency in the number of
It is valid
Real results are statistically
implementations
close to the expected ones
Calculate Syllabus validity and reliability
lab facilities, supplimentary
materails, etc.
We called the system
Calculate Syllabus Costs Chopin
The task is Complex it requires an Intelligent tool
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
13. COURSE SYLLABUS
FALL, 2011
INSTRUCTOR: JOHN SMITH
A. DESCRIPTION
This course involves a careful examination of
B. ORGANIZATION publisher says that this
The
This is a lecture-lab course in which
book is not available this
C. COURSE OBJECTIVES
To introduce students to the semester
E. TEXT AND REQUIRED SUPPLIES
Required text: Basic Technical Drawing, by Spencer & Dygdon
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
14. It takes a Syllabus (created with the special template), represents it
as a Graph, Detects Consistency Errors and calculates Costs
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
15. Consistency report items:
Check existence of required elements
Check links between elements
(for example, each test should have associated readings)
Required timings and verifies time totals
Distribution of course materials
etc.
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
16. Relation type Typical Problems Possible Examples
(Rule Left Side) (Rule Right Side)
Refers to dead link if it doesnt exist in the appropriate
section of the syllabus.
redundant link if it is never used in the syllabus
sections
maldistribution of links if One topic of the syllabus is
supported with much more (ratio
is more than threshold) links than
others.
Mapping Polysemy if The test for the topic covers more
than this topic or allows different
sequences of tests
non-optimal mapping if Bad correlation between the
names of the learning goals and
the names of topics.
More rules can be added by system user
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
17. Good ?
Enough? If it is Good it should
give the Required results
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
18. N of
results
F D C B A student grade
Grades for the very difficult (non-valid), very simple courses
(non-valid) and a course of required (valid) complexity
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
19. This is the Expert
System, described in this
presentation
to-do list: Expert Database of EDL editor:
goals, links System. Syllabi (EDL calculates
and tests scripts), Tests Consistency, V
Takes EDL
script as the (TDL scripts) alidity and
Professors, ass
input , results, logs, Reliability
istants, and
etc. administrators
Testing A set of data
Expert analysis
System. programs
Takes TDL as
its input TDL Test editor
Student
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
20. 1. Syllabus quality can be objectively measured
if we look at it is at multi-dimensional
function based on the statistical data, which
takes into account the quality of syllabus
elements and the quality of its structure.
2. Defining a good syllabus as a syllabus that
promotes good outcomes we expand this
definition with always, i.e. we define the
quality as validity and reliability.
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
21. 3. Accepting the definition a good syllabus as a
mathematical graph with individual
pathways, we state that the quality has to be
calculated for each branch of the graph.
4. Evaluation of the syllabus quality against validity
and reliability shall be done in two stages: pre-
processing to exclude uncertainty from the
syllabus and post-processing aimed at the analysis
of efficiency.
5. Practical implementation demonstrates efficiency
of the proposed approach and its usability.
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
22. 7. The sound theoretical framework, as well as the
promising results of its implementation in an
intelligent system, opens new opportunities in
the syllabus/course quality management:
Creation of Smart Syllabus Bases;
Creation of efficient teaching materials for
target groups;
Solution is based on data warehouse that
takes from LMS and Smart Syllabi DB
2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.
23. 2nd Intl Conference on Learning Analytics and Knowledge (LAK12): Vancouver, April 29 - May 2, 2012.