personalized contents based in cognitive level of student’s computational thinking for learning...
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Personalized contents based on cognitive level of student’s
computational thinking for learning basic competencies of programming
using an environment b-learning
Arturo Rojas LópezDivision of TIC
Universidad Tecnológica de [email protected]
Francisco García PeñalvoComputer Science Department / Research Institute for Educational Research
GRIAL Research Group University of Salamanca
November 2-4, 2016
CONTEXT AND MOTIVATION Teacher Selecting under his experience and creativity
a learning environment Computer programing
Creates Software Learning in classroom Technologies or support of a technological
medium Right mental abilities to solve problems Personalized educational service
STATE OF THE ART Formulating problems and their solutions
Standards in Computer Science – North America TACCLE3 – Europe Computing our future
To teach To know the cognitive level Early detection of students
Personalized education Take the place of the standard education
Moodle allows blended learning model
HYPOTESIS The participation of students on a b –
learning environment designed base on their uniqueness of learning and personalization content from the cognitive level of computational thinking, contributes to the acquisition of basic skills programming.
RESEARCH OBJETIVES Efficiency environment b – learning Computational thinking of students Current Moodle platform Review the status Determine the parameters for
measuring the efficiency
APPROACH AND METHODS Mixed approach
Quantitative – sequential, deductive and testing process
Qualitative – context the phenomenon and depth of ideas
New students Programming methodology September – December 2016 Least two groups
Measure the skills of computational thinking To determine the content of your personalized
learning A simple no probabilistic
RESULTS The relationship between the CT, teach
programming and Bloom´s taxonomy
UK Bebras Computer Olympiad Talent Search
Bloom’s taxonomy
Skill Thematic unit
Analysis abstraction and decomposition
Basics
Application generalization ExpressionsSynthesis
Evaluation
algorithmic design and evaluation
algorithms and flowcharts
RESULTS Mobile – decomposition Kangaroo – abstraction Spies – generalization Beavers on the run – algorithmic design Puddle jumping – evaluation
RESULTSSCENARIO MODEL EVALUATION RIGHT / WRONG TIME
1 Online Full course online 5 right 15 days
2 Online Full course online W- beavers on the run
1 month
3 Semi distance Counseling Laboratory
W-puddle jumping 1 month
4 Online Online counseling W-beavers and puddle
1 month
5 Online Online W-Spies 1 month
6 Semi distance Academy W-beavers, puddle and spies
Academy
7 Semi distance Departmental Laboratory
R-Kangaroo or Mobile Academy
8 Classroom Academy 5 wrong Academy
9 Semi distance Laboratory W-Mobile and Kangaroo
Free / academy
10 Online / semi Academy Online
R-beavers and puddle 5 weeks part 1Academy
DISSERTATION STATUSActivity 2016 2017
09
10
11
12
01
02
03
04
05
06
07
08
Thesis writing
Administrative transactions
Content application
Analysis of data
Preparation of articles for publication
CURRENT AND EXPECTED CONSTRIBUTIONS 7 of 10 scenarios 65 students Important work of research is
underway
ABSTRACT Efficiency Environment b-learning Skills of programming Customizing Initial programming course Computational thinking
ACKNOWLEDGEMENTS This research work is made within University
of Salamanca PhD Programme on Education in the Knowledge Society scope.