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General Information
ISSN:
2377-2891(Print); 2377-2905(Online)
Frequency:
Bimonthly
Editor-in-Chief:
Prof. Eric C. K. Cheng
Associate Executive Editor:
Ms. Jenny Jiang
DOI:
10.18178/ijlt
Abstracting/Indexing:
Google Scholar; Crossref, CNKI,
etc.
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questions or comments to
IJLT Editorial Office
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Editor-in-Chief
Prof. Eric C. K. Cheng
Professor & Vice President (Academic)
Yew Chung College of Early Childhood Education, Hong Kong, China
As the Editor-in-Chief of IJLT, I invite you to contribute your scholarly work to our esteemed publication. IJLT serves as a beacon for original and impactful academic contributions in the realm of education, fostering multidisciplinary research and development to enhance teaching-learning processes globally. We welcome submissions spanning a wide spectrum of topics, from innovative program development to the integration of digital tools in education. Our scope encompasses areas such as student leadership, diversity in education, and collaborative initiatives, reflecting our commitment to a sustainable and inclusive society. [
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What's New
2024-02-29
Vol. 10, No. 1, 2024 has been published!
2024-02-07
Welcome Prof. Eric C. K. Cheng from Yew Chung College of Early Childhood Education, Hong Kong, China to join IJLT Editorial Board as Editor-in-Chief!
2023-12-13
IJLT will adopt Article-by-Article Work Flow from 2024. For the Bimonthly journal, each issue will be released at the end of the issue month.
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2016
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Volume 2, No. 1, June 2016
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Solving Complex Problems with a Computational Mind: An Alternative to Heuristic Search
Juan Carlos Olabe
1
, Xabier Basogain
2
, and Miguel Ángel Olabe
2
1. Christian Brothers University, Memphis, USA
2. University of the Basque Country, Bilbao, Spain
Abstract
—A critical set of advances in the world of cognitive sciences during the last two decades is redefining the directions of research of cognitive processes. A set of obsolete cognitive principles has been identified and new methods and objectives have been set for the study of complex problems. We investigate in this paper one such problem in an experiment with students (n=192) from four universities in Spain. The experiment reveals that (i) students easily and reliably acquire (appropriately designed) complex algorithms and (ii) students learn and apply these algorithms in an affective state of ease. These students systematically outperformed published results in an isomorphic task (inheritance genetics). These results indicate that appropriate data encoding, explicit algorithmic definition, and the activation of human cognitive primitives is sufficient to accomplish the task.
Index Terms
—heuristic search, computational thinking, object oriented thinking, information encoding, algorithmic thinking
Cite: Juan Carlos Olabe, Xabier Basogain, and Miguel Ángel Olabe, "Solving Complex Problems with a Computational Mind: An Alternative to Heuristic Search," International Journal of Learning and Teaching, Vol. 2, No. 1, pp. 12-19, June 2016. doi: 10.18178/ijlt.2.1.12-19
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