O grupo Evante convida todo@s a submeter artigos científicos para a revista BJET British Journal of Educational Technology. Para a edição especial relacionada a Learning Analytics. Clique aqui

With the growing availability of digital resources for educational purposes, and the generation of large amounts of data related to institutional management and student performance, the use of learning analytics (LA) for understanding and optimising learning processes and the environments where they occur gains increasing attention worldwide. In Latin America, LA has become an appealing approach to help institutions understand and overcome essential challenges such as fairly high indices of failure and dropout, and improve the overall quality of education.

However, from an institutional point of view, the implementation of LA approaches and tools effectively is not straightforward and demands the engagement of different stakeholders. The institutional adoption of LA processes in Latin America remains mostly fragmented and isolated. In most cases, datasets about students are largely unexplored and their potential untapped.

For effective LA policies to take place, in addition to the level of maturity of the institution, there are aspects related to infrastructure to be considered, as well as cultural and socio-economic aspects that have a direct impact on students’ achievements and possibilities. These local aspects highlight the importance of creating learning analytics applications that take into consideration not only student achievement but also the needs and context that surround the learning process.

For this special section of BJET, we are seeking submissions that present applications of LA developed in Latin America at all levels of education, within formal or informal learning environments, from a wide range of domains such as: institutional policies and management; frameworks; teaching methods; delivery of feedback; visualisation of information; and forms of interaction and communication mediated by digital tools.

– Abstracts must be sent to: tacianapontual@gmail.com by August 29th, 2019. Abstracts should be one-page long (Times 12, single spacing, excluding references) and include authors’ names and affiliations

– Submissions through BJET system (for accepted abstracts): December 2nd, 2019

– Acceptance notification: March 2020

– Publication: May 2020 (expected)

AI and Robotics in Reshaping the Dynamics of Learning

Guest editors:Hsiu-Ping Yueh, Department of Psychology, Department of Bio-Industry Communication and Development, National Taiwan University, Taiwan

 Research Fellow, Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, Taiwan

Prof.  Feng-Kuang Chiang, Department of Educational Technology, School of Education, Shanghai Normal University, China.

Visiting Scientist, RELATE Lab of Massachusetts Institute of Technology, USA.

Artificial intelligence (AI) and robotics have dominated our vocabulary and pervaded many aspects of our lives in recent times. The two terms have become closely related, in particular, in the context of education. Recent years have seen efforts to implement AI detection, analysis, and prediction techniques that greatly enhance students’ and teachers’ experiences. Similarly, robotic teaching assistants—some virtual and others physical—have been used to engage and excite learners(Jung, 2013; Spolaor & Benitti, 2017; Okita, 2014). Nevertheless, the application of AI and robotics to education still lags behind technical advancement in these fields. There lacks a bridge that effectively connects technological breakthroughs with its potential use in domain-specific classroom practices. Thus, there should be more dialogue between technologists and educators to determine how modern technologies can enhance the learning experience.

In this special issue, we invite empirical researches that critically examine and reflect on the role of AI and robotics in terms of reshaping the dynamics of learning, particularly from the perspective of learning sciences. We seek to understand how these seemingly intelligent yet abstruse tools blend into educational practices across all levels. Topics of interest include, but are not limited to, the following aspects:

• Do AI and robotics simply cause a technological shift in classroom settings but leave the fundamental structure of learning and teaching unchanged? How would these intelligent technologies smoothly blend into classroom practices? And what is lost when they are integrated into classrooms?
• How would AI and robots, either alone or together, impact on every aspect of learning and teaching activities –physical, social, emotional and intellectual? What are the urgent issues or challenges to be addressed?
• Do AI and robots expand one’s horizon of learning or impose additional constraints on learning behaviors? Is there a context-dependent or context-independent framework for educators to follow and build upon?
• How would learning scientists or first-line teachers who do not possess a technical background manage to deal with the emergence of AI or robotics? How do they weigh in on this academic dialogue?

References
Jung, S. (2013). Experiences in Developing an Experimental Robotics Course Program for Undergraduate Education. IEEE Transactions on Education, 56(1), 129-136.

Spolaor, N; Benitti, FBV. (2017). Robotics applications grounded in learning theories on tertiary education: A systematic review. Computers & Education, 112, 97-107.

Okita, S. Y. (2014). The relative merits of transparency: Investigating situations that support the use of robotics in developing student learning adaptability across virtual and physical computing platforms. British Journal of Educational Technology, 45(5).  844-862.

Important Dates:

One-page abstract to Guest Editors: October 1st, 2019

  Notification of Abstract Acceptance and invitation to submit full paper: October 20th, 2019

  Submission deadline for full paper: December 1st, 2019

  Manuscript Acceptance: April 1st 2020

  Issue Publication: July 2020