Cited by 25Teaching and Learning ProgrammingEducational Robotics and EngineeringArtificial Intelligence in Education

AI from Concrete to Abstract: Demystifying artificial intelligence to the general public

Open access
Lacerda Queiroz, Rubens, Ferrentini Sampaio, Fábio, Lima, Cabral, Machado Vieira Lima, Priscila·2021·AI & SOCIETY

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s00146-021-01151-x

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 51

  1. AAAI (2018) AAAI Launches K-12 Initiative. AI Magazine 39:98. https://doi.org/10.1609/aimag.v39i2. 2820 · DOI
  2. Aleksander I, Thomas W, Bowden P (1984) WISARD• a radical step forward in image recognition Sensor review. https://doi.org/10.1108/eb007637 · DOI
  3. Aleksander I, De Gregorio M., França FMG, Lima PMV, Morton, H (2009) A brief introduction to weightless neural systems. In: Proceedings of the 17 th European Symposium on the Artificial Neural Networks, Computational Intelligence and Machine Learning, pp 299-305
  4. Beard RM (2006) An outline of Piaget's developmental psychology. Routledge, Abingdon.
  5. Beer RD, Chiel HJ, Drushel RF (1999) Using autonomous robotics to teach science and engineering. Communications of the ACM 42:85-92. https://doi.org/ 10.1145/303849.303866 · DOI
  6. Bell T, Alexander J, Freeman I, Grimley M (2009) Computer science unplugged: School students doing real computing without computers. The New Zealand Journal of Applied Computing and Information Technology 13:20-29
  7. Blank D, Kumar D, Meeden L, Yanco, H (2006) The Pyro toolkit for AI and robotics. AI magazine 27: 39-50. https://doi.org/10.1609/aimag.v27i1.1862 · DOI
  8. Breazeal CL (2004) Designing sociable robots. MIT press, Massachusetts
  9. Brown AL, Metz KE, Campione JC (1996) Social interaction and individual understanding in a community of learners: The influence of Piaget and Vygotsky. In: Tryphon A, Vonèche J (ed) Piaget Vygotsky: The Social Genesis Of Thought. Psychology Press, New York, pp 145-170
  10. Budach L (1991) Fundamentals of Computation Theory: 8th International Conference, FCT'91, Gosen, Germany, September 9-13. Proceedings. Springer Science & Business Media, Berlin.
  11. Burnett MM (2002) Software Engineering For Visual Programming Languages. In: Shi-kuo C (ed) Handbook Of Software Engineering And Knowledge Engineering, vol 2. World Scientific, Singapore, pp 77-92
  12. Cardoso DO, Carvalho DS, Alves DS, Souza DF, Carneiro, HC, Pedreira, CE, Lima PMV, França FMG (2016) Financial credit analysis via a clustering weightless neural classifier. Neurocomputing 183: 70-78. https://doi.org/10.1016/j.neucom.2015.06.105 · DOI
  13. Carneiro HC, França FM, Lima, PM (2015) Multilingual part-of-speech tagging with weightless neural networks. Neural Networks 66: 11-21. https://doi.org/10.1016/ j.neunet.2015.02.012 · DOI
  14. Carneiro HC, Pedreira CE, França FMG, Lima PMV (2017) A universal multilingual weightless neural network tagger via quantitative linguistics. Neural Networks 91: 85-101. https://doi.org/10.1016/j.neunet. 2017.04.011 · DOI
  15. Carvalho DS, Carneiro HC, França FM, Lima PM (2013) B-bleaching: Agile overtraining avoidance in the wisard weightless neural classifier. In: Proceedings of the 21 th European Symposium on the Artificial Neural Networks, Computational Intelligence and Machine Learning
  16. Chaudhary V, Agrawal V, Sureka P, Sureka (2016) An experience report on teaching programming and computational thinking to elementary level children using Lego robotics education kit. In: IEEE Eighth International Conference on Technology for Education (T4E). IEEE, pp 38-41. https://doi.org/10.1109/T4E. 2016.016 · DOI
  17. De Gregorio M, Giordano M (2017) Background estimation by weightless neural networks. Pattern Recognition Letters 96: 55-65. https://doi.org/10.1016/ j.patrec.2017.05.029 · DOI
  18. De Gregorio M, Rullo A, Rubinacci S (2012) ISIDIS: an intelligent videosurveillance system. In: Proceedings of the International Working Conference on Advanced Visual Interfaces, pp 800-801. https://doi.org/10.1145/ 2254556.2254721 · DOI
  19. De Luca G, Li Z, Mian S, Chen Y (2018) Visual programming language environment for different IoT and robotics platforms in computer science education CAAI Transactions on Intelligence Technology 3:119- 130. https://doi.org/10.1049/trit.2018.0016 · DOI
  20. Dormehl L (2017) Thinking Machines: The Quest for Artificial Intelligence--and Where It's Taking Us Next. Penguin Publishing Group, New York
  21. Druga S (2018) Growing up with AI: Cognimates: from coding to teaching machines. Dissertation. Massachusetts Institute of Technology.
  22. França F, De Gregorio M, Lima P, de Oliveira W (2014) Advances in weightless neural systems. In: Proceedings of the 22 th European Symposium on the Artificial Neural Networks, Computational Intelligence and Machine Learning, pp 497-504
  23. Gil D, HobsonS, Mojsilović A, Puri R, Smith, JR (2020) AI for Management: An Overview. In: Canals J, Heukamp F (ed) The Future of Management in an AI World. Palgrave Macmillan, Cham. pp 3-19
  24. Gillian N, Paradiso JA (2014) The gesture recognition toolkit. The Journal of Machine Learning Research 15:3483-3487. http://www.jmlr.org/papers/volume15/ gillian14a/gillian14a.pdf. Accessed 25 March 2020
  25. Graupe D (2019) Principles Of Artificial Neural Networks: Basic Designs To Deep Learning, vol 8. World Scientific, Singapore
  26. Greenwald L, Artz D, Mehta Y, Shirmohammadi B (2006) Using educational robotics to motivate complete AI solutions. AI magazine 27: 83-95. https://doi.org/ 10.1609/aimag.v27i1.1865 · DOI
  27. Grieco BP, Lima, PM, De Gregorio M, França FMG (2010) Producing pattern examples from "mental" images. Neurocomputing, 73: pp 1057-1064. https://doi.org/10.1016/j.neucom.2009.11.015 · DOI
  28. Hazzan O (2008) Reflections on teaching abstraction and other soft ideas ACM SIGCSE Bulletin 40:40-43. https://doi.org/10.1145/1383602.1383631 · DOI
  29. Hevner A, Chatterjee S (2010) Design Research in Information Systems: Theory and Practice. In. Integrated Series in Information Systems 22. Springer, New York.
  30. Hitron T, Orlev Y, Wald I, Shamir A, Erel H, Zuckerman O (2019) Can Children Understand Machine Learning Concepts? The Effect of Uncovering Black Boxes. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp 1-11. https://doi.org/10.1145/3290605.3300645 · DOI
  31. Hitron T, Wald I, Erel H, Zuckerman (2018) Introducing children to machine learning concepts through hands-on experience. In: Proceedings of the 17th ACM Conference on Interaction Design and Children, pp 563- 568. https://doi.org/10.1145/3202185.3210776 · DOI
  32. Irgen-Gioro JJZ (2016) Teaching artificial intelligence using Lego. In: Proceedings of the International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS) 209-215. http://worldcomp-proceedings.com/proc/p2016/ FEC3679.pdf. Accessed 25 March 2020
  33. Kandlhofer M, Steinbauer G, Hirschmugl-Gaisch S, Huber P (2016) Artificial intelligence and computer science in education: From kindergarten to university. In: IEEE Frontiers in Education Conference (FIE). IEEE, pp 1-9. https://doi.org/10.1109/FIE.2016.7757570 · DOI · Paper page
  34. Kramer J (2007) Is abstraction the key to computing? Communications of the ACM 50:36-42. https://doi.org/10.1145/1232743.1232745 · DOI
  35. Lima Filho AS, Guarisa GP, Lusquino Filho LAD, Oliveira LFR, Franca FM, Lima PMV(2020) wisardpkg--A library for WiSARD-based models. arXiv: 2005.00887 · arXiv
  36. Lusquino Filho LAD, Oliveira LFR, Lima Filho A, Guarisa GP, Felix LM, Lima PMV, França FMG (2020) Extending the weightless WiSARD classifier for regression. Neurocomputing. https://doi.org/10.1016/ j.neucom.2019.12.134 · DOI
  37. Mano MM (1979) Digital logic and computer design. Prentice Hall, Englewood Cliffs
  38. Marshall JB (2004) An Introductory CS Course for Cognitive Science Students. In AAAI Spring Symposium. https://www.aaai.org/Papers/Symposia/ Spring/2004/SS-04-01/SS04-01-021.pdf. Accessed 25 March 2020
  39. Medina EM (2004) Beyond the ballot box: computer science education and social responsibility SIGCSE Bull 36:7-10. https://doi.org/10.1145/1041624. 1041626 · DOI
  40. Mitchell TM (1997) Machine Learning. McGraw-Hill, New York
  41. Parsons S, Sklar E (2004) Teaching AI using LEGO mindstorms. In: AAAI Spring Symposium. https://www.aaai.org/Papers/Symposia/Spring/2004/SS -04-01/SS04-01-003.pdf. Accessed 25 March 2020
  42. Piaget J (1950) The Psychology of Intelligence. Routledge and Kegan Paul, London
  43. Queiroz RL, de Azeredo Coutinho IB, Xexéo GB, Lima PMV, Sampaio FF (2018) Playing with robots using your brain. In: 17th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), IEEE, pp 197-1977. https://doi.org/10.1109/SBGAMES.2018. 00031 · DOI
  44. Queiroz RL, Sampaio FF, dos Santos MP (2016) DuinoBlocks4Kids: Ensinando conceitos básicos de programação a crianças do Ensino Fundamental I por meio da Robótica Educacional In: Anais dos Workshops do Congresso Brasileiro de Informática na Educação, pp 1169-1178. In Portuguese. http://dx.doi.org/10.5753/ cbie.wcbie.2016.1169 · DOI
  45. Queiroz RL, Sampaio FF, dos Santos MP (2019) DuinoBlocks4Kids: Using Free Technology and Low- Cost Materials for the Exercise of Computational Thinking in Primary School via Programming and Educational Robotics. Brazilian Journal of Computers in Education 27:167-197. http://dx.doi.org/10.5753/ rbie.2019.27.02.167 · DOI
  46. Russell SJ, Norvig P (2010) Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River
  47. Santiago L, Verona L, Rangel F, Firmino F, Menasché DS, Caarls W, Breternitz Jr. M, Kundu S, Lima PMV, França FMG (2020) Weightless Neural Networks as Memory Segmented Bloom Filters. Neurocomputing. https://doi.org/10.1016/j.neucom.2020.01.115 · DOI
  48. Sakulkueakulsuk B, Witoon S, Ngarmkajornwiwat P, Pataranutaporn P, Surareungchai W, Pataranutaporn P, Subsoontorn P (2018) Kids making AI: Integrating Machine Learning, Gamification, and Social Context in STEM Education. In: IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 4-7, pp 1005-1010. https://doi.org/10.1109/ TALE.2018.8615249 · DOI
  49. Vasuki AA, Govindaraju SB (2017) Deep neural networks for image classification. In: Hemanth DJ, EstrelaVV (ed) Deep Learning for Image Processing Applications, vol 31. IOS Press, Amsterdam. pp 27-49
  50. Wieringa RJ (2014) Design Science Methodology for Information Systems and Software Engineering. Springer, Heidelberg
  51. Wing J (2006) Computational thinking. Communications of the ACM 49:33-35. https://doi.org/10.1145/ 1118178.1118215 · DOI · Paper page

Cited by

Sorted by citations

Authors
Lacerda Queiroz, R., Ferrentini Sampaio, F., Lima, C., & Machado Vieira Lima, P.
Affiliations
Universidade Federal do Rio de Janeiro (BR)
Venue
AI & SOCIETY
Published
2021-04-07
Volume
36
Issue
3
Pages
877-893
ISSN
  • 0951-5666 (ISSN-L)
  • 1435-5655
OpenAlex
W3147477878
Cited by
25
References
1
Citations by year
2026: 2 · 2025: 6 · 2024: 2 · 2023: 6 · 2022: 6 · 2021: 3
FWCI
3.36
Type
journal article
Language
en
Open access
Locations
  • AI & Society (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Physical Sciences › Computer Science › Artificial Intelligence › Educational Robotics and Engineering
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
Keywords
artificial intelligence in education, block-based programming, learning machines

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review