This document discusses a study on using ubiquitous learning to promote meaningful learning in vocational education. The study involved 38 apprentices in a technical computer science and chemistry course who used a ubiquitous learning platform to complete geography challenges on themes like urbanization. Their interactions and responses were analyzed. Results showed that over time more apprentices engaged with the challenges, answering correctly more often. The document concludes by discussing future work using ubiquitous learning to promote heritage education, allowing people to learn about historical places through interactions with others.

1. MEANINGFUL LEARNING IN U-
LEARNING ENVIRONMENTS:
An Experience in Vocational Education
J_. BRITO, L. SEIXAS, I. M. FILHO, A. GOMES, B. MONTEIRO
CENTRO DE INFORMÁTICA, UFPE

2. AGENDA
• I. Ubiquitous learning
• I.A. Meaningful ubiquitous learning
• II. Method
• II.A. Effectiveness evaluation
• III. Results
• IV. Future works
• IV.A. Heritage education

3. I. UBIQUITOUS LEARNING
Definition and infrastructure

4. UBIQUITOUS LEARNING
PLATFORM
DE SOUSA MONTEIRO, Bruno; GOMES, Alex Sandro; NETO, Francisco Milton Mendes.
Youubi: Open software for ubiquitous learning. Computers in Human Behavior, v. 55, p.
1145-1164, 2016.

5. ELEMENTARY
ENTITIES

6. U-LEARNING REFERENCE
ARCHITECTURE
DE SOUSA MONTEIRO, Bruno; GOMES, Alex Sandro; NETO, Francisco Milton Mendes. Youubi: Open
software for ubiquitous learning. Computers in Human Behavior, 2014.

7. LOCATION
• All elements that coordinate events are localized
and can be monitored

8. CREATE
CHALLENGES
• These are presented to people and
get people to go to certain places to
solve the challenges.

9. RECOMMENDATION
• Counted and content suggestions are
sent to users based on their profile data
and the context in which they are
located.
9

10. COMMUNICATION • The Application has a channel for
real-time communication

11. GAMIFICATION
• As the user solves the challenges and
interacts through the system and gains
points in numerous dimensions
11

12. I.A. MEANINGFUL
UBIQUITOUS LEARNING

13. Source: adapted from Huang et al. (2011).
Chang and Z.M. Yeh (2014) reinforce that apprentices do not learn from
technology; However, technologies can support productive thinking and favor
the construction of meanings.

14. Source: adapted from Huang et al. (2011).
EVOLUTIONARY FRAMEWORK
MODEL FOR ASSESSMENT OF
UBIQUITOUS LEARNING

15. II. METHOD

16. CONTEXT AND
PARTICIPANTS
• Context: Federal Institute of
Technological Education
• Course: Technical Course in
Computer Science and Chemistry
• Discipline: Geography, total workload
60 (sixty) hours
• Participants: 38 apprentices.

17. II.B. EFFECTIVENESS
EVALUATION

18. UBIQUITOUS ACTIVITIES

19. UBIQUITOUS LEARNING DATA
ANALYSIS

20. DATA CLASSIFICATION
Category Criteria
1 She/he presents a key concept related to the subject.
2 She/he presents and discusses a key concept related to the subject.
3 She/he relates the context to the local context.
4 She/he presents a problem.
5 She/he presents something simple / superficial related to the subject.
Source: adapted from Huang et al. (2011).

21. III. RESULTS

22. SECOND WEEK

23. The total of 28 apprentices interacted in 08 valid challenges created with a total of
283 attempts to correct answers, 223 correct answers and 60 wrong answers on the
theme of urbanization.
Second week: answer to challenges

24. FORTH WEEK

25. 40 valid challenges were created with a total of 647 responses, of which 375 correct
answers and 272 wrong answers on the theme of urbanization, with a greater
emphasis on Urban Social Problems, Urban Agglomeration, Traffic Disruption, Space
Segregation and Urban Mobility.
Forth week: answer to challenges

26. Pre-test and post-test comparative results
Comparison of paired means (Wilcox test)
The null hypothesis was rejected at a 95% confidence level.

27. IV. FUTURE WORKS
Heritage education

28. “This analytic orientation
inspires four key shifts in
our approach to HCI4D
efforts: generative models
of culture, development
a historical program,
uneven economic
and cultural
epistemologies.”
IRANI, Lilly et al. Postcolonial computing: a lens on design and development.
In: Proceedings of the SIGCHI conference on human factors in computing systems.
ACM, 2010. p. 1311-1320.

29. ETHNOGRAPHIC DESIGN
• (…) participants and ethnographers make knowledge
and places together as they tour the home. This
enables the sensory ethnographer to focus on how the
place(s) she/he seeks to understand are constituted
both in the experience of participants and in the
ethnographic descriptions she or he ultimately creates.
(p. 25:6)
PINK, Sarah et al. Applying the lens of sensory ethnography to sustainable HCI. ACM
Transactions on Computer-Human Interaction (TOCHI), v. 20, n. 4, p. 25, 2013.

30. OBJECTIVE
Promote Heritage Education using a ubiquitous
learning platform
• People know historical places from the point of view of
other people, using their memories
• People can know the city using routes suggested by
another users
• People reflect about their own identity in relation the
the place they live
• People learn curiosities about the historical places
through challenges

31. MEANINGFUL LEARNING IN U-
LEARNING ENVIRONMENTS:
An Experience in Vocational Education
J_. BRITO, L. SEIXAS, I. M. FILHO, A. GOMES, B. MONTEIRO
CENTRO DE INFORMÁTICA, UFPE