Call for special issue papers (due: Dec 31, 2023)

 

Research and Practice in Technology Enhanced Learning
Call for papers for a Special Issue on
“Revolutionizing learning: The continuing roles of learning companions beyond ChatGPT”

Guest Editors:
Prof. Ying-Tien Wu, National Central University, Taiwan  (Leading Guest Editor)
Prof. Chang-Yen Liao, National Central University, Taiwan
Prof. Siu-Cheung Kong, The Education University of Hong Kong, Hong Kong

The emergence of ChatGPT and generative AI technology signals that the computer will pass the Turing Test one day before our eyes. This indicates that in some situation of our life, we cannot distinguish whether we are interacting with a human or a human-like artificial companion. Indeed, artificial companions, virtual or robotic, will be pervasively around us to support our daily life.

For education, however, the most significant implication of such a great leap of AI technology advancement is, arguably, the advent of intelligent learning companions. These companions can play the role of a peer (such as a fellow classmate or an animal companion), a teacher or a tutor, the delegate of the learner’s human teacher or parent, and many others. How to utilize such technology to build artificial learning companions? With the presence of these companions in the future learning scenarioes, besides supporting learning, one may even ask: What does it mean by ‘learning companionship’? Can learning companionship enhance the learner’s sense of achievement, satisfaction, interest, social relationship, and so forth? In short, how do the design, research and practice of learning companions foster students' learning and well-being? Plenty of research questions can be asked and explored. Nevertheless, at this very moment of renaissance of intelligent learning companion research, a historical context could lead us to see further into the future.

In 1988, Chan and Baskin introduced the concept of artificial learning companion in a paper entitled “Studying with the prince: The computer as a learning companion.” In the learning environment of such an AI-supported learning system, which is often called a learning companion system, there are three characters involved, namely, the human student, the computer learning companion, and the computer teacher. “As implied by its name, the role of the computer learning companion is to act as a learning companion for the student. To this end, the companion learns to perform the learning task at about the same level as the student, and both students can exchange ideas while being presented with the same material. Simulating skill acquisition and actual machine learning are two different approaches to designing the companion of the learning companion system. In the first approach, the performance capability of the companion is controlled by the system, while in the second approach, the companion is required to be able to learn as the student does by using the techniques of machine learning.” (Chan & Baskin, 1988). After exploring the limitations of machine learning at that time, they adopted simulating skill acquisition approach in a prototype of learning companion systems: Integration-Kid (Chan, 1991).

The 1988 paper is also the first technology-enhanced learning research that introduced Vygotsky's sociocultural theory: social interactions play a fundamental role in shaping internal cognitive structures, including the zone of proximal development (ZPD) hypothesis. This leads to the basic assumption that an artificial learning companion with human-like characteristics can promote student learning, even its knowledge is not perfect nor authoritative as the computer teacher should. Since then, abundant research has been conducted on learning companions, sometimes using different names.

Now, after 35 years of learning companion research, empowered by machine learning, generative AI demonstrates super performance in various domains but sometimes gives wrong or biased answers. Artificial companion is almost there! What will happen in the future? Despite academic ethic issues raised, plenty of learning companions will soon be developed. Learners will learn with multiple connected artificial companions in not-too-distant future. Everyone, ultimately, will have lifelong learning companions playing different roles from childhood to adulthood.

Multi-faceted and fertile, research avenues of artificial learning companions are emerging. As one of the initial attempts, this special issue aims to feature original academic papers focusing on five emergent research areas on learning companions:

(1) Learning theories and design principles for learning companions:
Contributions discussing the application of learning theories in designing virtual and robotic learning companions or the development of design principles for learning companions are welcome.

(2) Design-based research on various roles of artificial companions:
A learning companion can take on various roles (e.g., peer tutors, tutees, collaborators, competitors, troublemakers, avatars, and facilitators). In fact, the term “artificial companion” per se is a more general term than “artificial learning companion,” because a virtual or robotic learning companion can be a teaching companion (assuming the role of a teacher or helping the human teacher), tutoring companion, mentoring companion, consulting companion, and so forth. Innovative design and implementation with evaluation to refine various types of artificial companions are welcome.

(3) Empirical studies on the impacts of artificial companions:
Empirical studies of artificial companions and their functions (e.g., scaffolding, prompts, feedback) for elevating student learning outcomes and fostering the well-being of learning, such as interest, satisfaction, positive social interactions, engagement, sense of achievement, and so forth, are welcome.

(4) Learning companions in Metaverse:
As Metaverse platforms gain popularity, we see an opportunity to connect the virtual world with the real world through learning companions. Pioneer research investigating how learning companions could be used to promote learning processes and outcomes within the Metaverse is welcome.

(5) Communicative learning companions in social media research:
This special issue aims to illuminate the growing significance of “communicative artificial companions” in social media research. These AI-empowered autonomous systems engage in quasi-communication with humans, enabling diverse algorithmic functionalities. We invite papers that detail the phenomenon of such companions, like OpenAI's ChatGPT, social bots, and work bots, and their integration into daily life.

Thus, we explore five critical areas: “Learning theories and design principles for learning companions,” investigating how educational theories guide companion design; “Design-based research on various roles artificial companions,” studying the innovative design of diverse roles of these companions and their associated learning activities; “Empirical studies on impacts of artificial companions,” evaluating the learning gain and well-being gain caused by artificial companions; “Learning companions in the Metaverse,” examining the potential of these companions in the emerging Metaverse platforms; and “Communicative learning companions in social media research,” emphasizing the growing importance of communicative learning companions in social media research. Each area provides a unique len to understand the complex effects of learning companions in education.

This special issue welcomes innovative design, empirical, theoretical, and methodological papers contributing to these areas. Submissions from interdisciplinary teams that bring together perspectives from education, psychology, computer science, and other related fields are particularly encouraged.

All submissions of the Special Issue should comply with the Author Guidelines of Research and Practice in Technology Enhanced Learning (RPTEL) – the official journal of The Asia-Pacific Society for Computers in Education (APSCE), available on https://rptel.apsce.net/index.php/RPTEL/about/submissions. The submissions to the special issue should fit within the scope of RPTEL as described in the Aims and Scope of RPTEL (https://rptel.apsce.net/index.php/RPTEL/about). Of the utmost importance is that RPTEL publishes the research that well bridges the pedagogy and practice in advanced technology for evidence-based and meaningful educational applications. Papers collected and analyzed only self-reported data that obtained from interview or questionnaire survey without a meaningful educational treatment are NOT within the scope of RPTEL.

Please submit your anonymous manuscript and title page using the submission system available https://rptel.apsce.net/index.php/RPTEL/about/submissions. When submitting your manuscript, please include a remark in title page: Submission to RPTEL Special Issue on "Revolutionizing learning: The continuing roles of learning companions beyond ChatGPT."

Important Dates

Dec 31, 2023  ---- Manuscript Submission Due Date

Jan 28, 2024   ---- Review Notification

Feb 18, 2024 ---- Revision Submission Due Date

Mar 3, 2024   ---- Final Acceptance Notification

Mar 10, 2024 ---- Final Camera-ready Manuscript Due Date

Publication Date:

---- Issue Date: Vol. 19 (2024)

 

References:

Chan, T. W. & Baskin, A. B. (1988). Studying with the Prince: The Computer as a Learning Companion. The Proceedings of International Conference of Intelligent Tutoring Systems, ITS'88, June, Montreal, Canada, 194-200.

Chan, T. W. (1991). Integration-kid: A learning companion system. In J. Mylopolous & R. Reiter (Eds.). Proceedings of the 12th International Conference On Artificial Intelligence, Vol. 2, 1094-1099. Australia, Morgan: Kaufmann Publishers, Inc.