Online citations, reference lists, and bibliographies.

Smart STEM-Driven Educational Environment For CS Education: A Case Study

Vytautas Stuikys, Renata Burbaite
Published 2018 · Computer Science

Cite This
Download PDF
Analyze on Scholarcy
Share
In this chapter, we firstly discuss some aspects of known smart educational environments (SEEs). Those aspects include a framework in creating SEEs, as well as the architectural and functional aspects. Knowing that, we introduce our SEE. One should treat it as a case study connected to our vision for STEM-driven CS education. We present the architecture and functionality of this SEE. The architecture integrates all smart components discussed so far, i.e. generative (smart) learning objects (GLOs/SLOs), generative scenario and personal generative libraries, educational robot-based workplaces and additional entities, such as knowledge base, to support managing of the whole system. We describe the functionality of the SEE by the communicating processes among indicated components. We also provide an evaluation through the juxtaposition of qualitative features proposed by Hwang and those of our system.
This paper references
10.3102/00346543074002141
New Learning and the Classification of Learning Environments in Secondary Education
A. D. de Kock (2004)
Learner-Centered Assessment on College Campuses: Shifting the Focus from Teaching to Learning
M. Huba (1999)
10.1145/303849.303866
Using autonomous robotics to teach science and engineering
R. Beer (1999)
10.1109/VR.2016.7504736
Using projection AR to add design studio pedagogy to a CS classroom
Blair MacIntyre (2016)
10.1080/15391523.2007.10782481
Robotics as Means to Increase Achievement Scores in an Informal Learning Environment
Bradley S. Barker (2007)
10.1007/S10798-015-9304-5
Robotics in the early childhood classroom: learning outcomes from an 8-week robotics curriculum in pre-kindergarten through second grade
A. Sullivan (2016)
10.1186/s40561-016-0039-x
The design of smart educational environments
B. Gros (2016)
10.1109/SSFC.2016.7447877
Measuring learning outcomes effectively in smart learning environments
Sahar Yassine (2016)
10.1016/j.compedu.2011.01.002
Modelling programming performance: Beyond the influence of learner characteristics
Wilfred W. F. Lau (2011)
10.15388/infedu.2009.14
Teaching and Learning School Informatics: A Concept-Based Pedagogical Approach
Said Hadjerrouit (2009)
10.1145/2713609.2713611
Increasing Adoption of Smart Learning Content for Computer Science Education
Peter Brusilovsky (2014)
Bringing Engineering to Elementary School
C. Rogers (2004)
10.1186/s40561-014-0004-5
Definition, framework and research issues of smart learning environments - a context-aware ubiquitous learning perspective
Gwo-Jen Hwang (2014)
10.3390/s110807835
Smart Learning Services Based on Smart Cloud Computing
Svetlana Kim (2011)
10.1109/RESPECT.2015.7296511
EarSketch: A STEAM approach to broadening participation in computer science principles
Jason Freeman (2015)
10.1007/978-3-319-16913-2
Smart Learning Objects for Smart Education in Computer Science
Vytautas Stuikys (2015)
Augmented Learning: Research and Design of Mobile Educational Games
E. Klopfer (2008)
10.14257/IJUNESST.2014.7.1.07
Study on Service Models of Digital Textbooks in Cloud Computing Environment for SMART Education
SangHyun Jang (2014)
AiboConnect: A Simple Programming Environment for Robotics
Eric Chown (2006)
10.1080/08993408.2013.778040
From boring to scoring – a collaborative serious game for learning and practicing mathematical logic for computer science education
Andreas Schäfer (2013)
10.1109/ICALT.2011.65
Development of a Game-based Learning System Using Toy Robots
Li-Der Chou (2011)
10.1186/s40561-014-0005-4
Conditions for effective smart learning environments
R. Koper (2014)
10.1109/TLT.2014.2329293
Gamification for Engaging Computer Science Students in Learning Activities: A Case Study
María-Blanca Ibáñez-Espiga (2014)
10.28945/1972
Augmenting a Child's Reality: Using Educational Tablet Technology.
P. Tanner (2014)
10.3233/AIS-150328
Customizing smart environments: A tabletop approach
Patricia Pons (2015)
10.1186/s40561-016-0034-2
Introduction to smart learning analytics: foundations and developments in video-based learning
M. Giannakos (2016)
10.1080/00098650109599193
Using Technological Innovation to Improve the Problem-Solving Skills of Middle School Students: Educators' Experiences with the LEGO Mindstorms Robotic Invention System
E. Mauch (2001)
10.1109/CIE.2002.1186176
Mobile learning: cell phones and PDAs for education
C. Houser (2002)
10.1145/2591708.2591714
Teaching a core CS concept through robotics
S. Magnenat (2014)
10.9734/BJESBS/2015/19429
Integrated Science, Technology, Engineering and Mathematics (STEM) Education through Active Experience of Designing Technical Toys in Vietnamese Schools
Le Xuan Quang (2015)
10.1007/978-3-319-16913-2_12
Robot-Based Smart Educational Environments to Teach CS: A Case Study
Vytautas Stuikys (2015)
10.1186/s40561-015-0022-y
Transforming learning for the smart learning environment: lessons learned from the Intel education initiatives
J. Price (2015)
10.1007/978-3-662-44188-6_39
Smart Learning Analytics
David Boulanger (2014)
10.1007/978-3-319-41769-1_9
Computational Thinking and Social Skills in Virtuoso: An Immersive, Digital Game-Based Learning Environment for Youth with Autism Spectrum Disorder
Matthew Schmidt (2016)
10.15388/INFORMATICA.2009.263
Multiple Criteria Comparative Evaluation of E-Learning Systems and Components
Eugenijus Kurilovas (2009)
10.1016/j.scico.2012.12.004
FAMILIAR: A domain-specific language for large scale management of feature models
M. Acher (2013)
10.1016/j.compedu.2011.10.006
Exploring the educational potential of robotics in schools: A systematic review
F. B. V. Benitti (2012)
10.18260/p.26880
EarSketch: An Authentic, STEAM-Based Approach to Computing Education
R. Moore (2016)



Semantic Scholar Logo Some data provided by SemanticScholar