The document discusses the challenges students face in learning programming and the traditional methods of assistance. It proposes a model called 'colmena' that utilizes educational data mining and learning analytics to provide real-time feedback on programming errors, enhancing the teaching and learning process. Future work aims to incorporate additional variables to analyze student behavior and make insights available to students.

1. COLMENA: Assistance in computer
programming learning using educational data
mining and learning analytics
ITICSE 2013
Carlos Fernández Medina
Juan Ramón Pérez-Pérez
Mª Puerto Paule-Ruiz
Víctor Manuel Álvarez-García
Pulso research team · University of Oviedo · www.pulso.uniovi.es
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2. Lahtinen, E. et al. (2005)
MOTIVATION
How much do students know about their
own learning process?
How much do teachers know about the
learning process of their students?
Programming is DIFFICULT for students
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3. ASSISTANCE
• Programming tasks require some
ASSISTANCE.
• Traditionally: unaid environments (notepad, pen
and paper).
• Integrated Development Environments (IDEs),
do they give us assistance?
• Some implementations are oriented to
learning (BlueJ)
• Most are not (Eclipse,Visual Studio, NetBeans)
• IDE + assistance = improvement of Teaching-
Learning process
Zeller (2007)
Jadud (2006)
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4. GOAL
To enhance knowledge about the
programming learning process for
teachers and students
Generate feedback
Mory, E.H. (2004)
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5. LEARNING
ANALYTICS
DATA
MINING
SUPPORT &
GUIDANCE
teachers &
PROGRAMMING
LEARNING
ACTIVITIES
students
COLMENA
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6. Fernández-Medina, C. et al. (2011)
Glahn, C. et al. (2008)
PROPOSED MODEL
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7. •Collect compiler errors and
warnings
•Each compilation/save event
starts data collection
EXTRACTION LAYER
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8. EXTRACTION LAYER
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9. • Redundances filter
• Discard errors present in last
collection
• (Unless error line has been edited)
• Persistence mechanisms
FTP, DB, files
PROCESSING LAYER
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10. PROCESSING LAYER
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11. compiler family
Compiler
Taxonomy
explanation
and hints
global group
of errors
The
output
error id concept
Ben-Ari, M. (2007)
conceptual family
global group
of errors
ANALYSIS LAYER
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12. ANALYSIS LAYER
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13. error
conceptfamilies
Teachers
Students
VISUALISATION LAYER
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14. • 43 students
• Algorithms, CS2, 6 weeks
• dynamic programming, backtracking, branch
and bound, divide and conquer
• OOP basics
• 1 practical lesson = 1 session
• Eclipse + Java
APPLICATION CONTEXT
Study of processed errors and creation of concepts
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15. Error/Warning
FamilyFamily
ConceptError/Warning
Compiler error Conceptual
Concept
Value of field/local variable X is not used Internal Type Warning
A variable or field was declared but never was used
(Variables Definition, Scope of Variables)
Syntax error, insert X to complete statement. Syntax Syntax Error
Incomplete code structure, is missing a final semicolon,
bracket, etc. (Code Blocks usage)
X cannot be resolved to a variable Field Syntax Error
A used variable is never declared before (Variables Definition,
Scope of Variables)
X cannot be resolved to a type Type Syntax Error
It is trying to use a variable of a type that does not exist
(Variables Definition, Import Usage)
Type mismatch: cannot convert from X to X Type Semantic Error
Possible loss of precision between variables (Types,
Conversion of Types)
X is a raw type. References to generic type X<T>
should be parameterized
Type Genericity Warning
X interface is used but it is never parameterized with the type
of the object that implements the interface (Genericity, Types,
Types Checking)
The import X is never used Import Import Warning A class not existent in the package or project was imported
References to generic type Y<T> should be
parameterized
Type Genericity Warning
Method X returns a generic type. X return type should be
parameterized
The method X(parameters) is undefined for the
type Y
Method Semantic Error Method X is called, but it is not declared in the Class Y
º
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16. syntax errors decrease
errors depend of the task type
errors related to variables are most frequent.
0
10
20
30
40
50
Field Syntax Type Import Method Constructor Internal
1 2 3 4 5 6
Sessions
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17. • Most IDEs provide insufficient information to
adequately support the learning of programming.
• We propose a flexible assistance model for
programming learning
• Our model collects and provides quantitative and
qualitative feedback on students’ programming
learning experiences
• Teachers can use their knowledge to facilitate the
learning process.
TO SUM UP
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18. FUTURE WORK
Combine more variables and indicators of
the programming learning process
Analyse student behavioural patterns
Make it available to students
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19. COLMENA: Assistance in computer
programming learning using educational data
mining and learning analytics
Carlos Fernández Medina
carlosfernandezmedina@gmail.com
http://www.pulso.uniovi.es
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