The fast development and omnipresence of technology brings great promises for the societal good but also a high level of uncertainty to future life. This uncertainty pushes self-directed learning to the fore since it helps people keep pace with the development and adapt to changes. Self-directed learning, taking responsibility to direct one’s own learning to meet personal goals, is fundamental to living and working in contemporary fast-changing society (Kranzow & Hyland, 2016; Morris, 2019). It is essential to learners’ academic success, engagement and life-long learning (Berger et al., 2021). Self-directed learning depends on both self-direction capacities to enable the overt management of the external learning environment and self-regulation capacities to facilitate the covert management of the cognitive and affective aspects of the internal learning environment (Pilling-Cormick & Garrison, 2007; Rashid & Asghar, 2016). Learners are often found to lack the necessary capacities to engage in self-directed learning (Canty et al., 2019; Gatewood, 2019). Thus, fostering self-directed learning strategies, skills and knowledge is an important educational objective. It is important because it closely relates to essential 21st century skills and lifelong learning skills, which are critical for success in school and workplace. Digital technologies provide rich opportunities for the facilitation of self-directed learning since they make rich information and resources accessible and afford opportunities for independent inquiry and collaborative learning both inside and outside the classroom (Bonk & Lee, 2017; Lai, 2017). Understanding how digital technologies are and can be utilized to facilitate self-directed learning both inside and outside the classroom is an important research agenda.

Recent studies have shown that technology-rich learning environments can provide conducive learning environment for the development of learners’ self-regulated learning skills (Urbina et al., 2021; Sangsawang, 2020; Manganello et al., 2019). Technology use, social media use in particular, is also found to predict levels of self-directedness in learning (Rashid & Asghar, 2016). However, most of these studies have been conducted in the higher education and adult learning contexts. Self-directed learning among younger learners, the manifestation and influencing factors thereof, might be different from that of adult learners. Morris and Rohs (2021) conducted a scoping review of the potential of digital technology in supporting self-directed learning among children, and the review was only able to locate fourteen papers. Despite confirming the potential of digital technology in supporting children’s self-directed learning process, the authors noted the alarmingly limited research on children’s self-directed learning in technological environments in the formal educational contexts. The authors called for more research in the relationship of self-directed learning and technology among younger learners in both formal and informal learning contexts.

Guest Editors:

Dr. Chun Lai

Faculty of Education, The University of Hong Kong, Hong Kong

Dr. Olga Viberg

Department of Human Centered Technology, Royal Institute of Technology KTH, Sweden

Dr. Chunping Zheng

Beijing University of Posts and Telecommunications, China

Feb 16, 2022

Call for papers for a special issue on “Developing Learner Agency in Smart Environments

Learner agency is based on the sociocultural theory indicating that language learning takes place through active engagement in the construction of linguistic knowledge (Gao, 2010). It emphasizes the active role of language learners in the language learning process. Learners should take control over their language learning process by making choices and acting on these choices to achieve personal goals (Martin, 2004). Learner agency is especially essential for learning success in online learning environments where diverse multimodal and interactive digital resources such as Ebooks or language learning websites are provided for students to improve their language performance (Knight, & Barbera, 2018; Moore, 2016). Only when students develop learner agency, they can select and tailor the online multimodal resources into personal learning needs and levels.

Developing learner agency is not an easy task as it involves a series of self-regulated learning tasks for students to conduct in the learning process, including reflection, evaluation, and planning for consecutive learning improvement (Randall, 1999). These self-regulated learning tasks entail the time and efforts from students and the external supports from teachers to teach students to identify learning discrepancy, determine learning goals, arrange learning tasks, and construct clear standards and criteria of evaluation (Bown, 2009; Scanlon, & Connolly, 2021). Challenges facing the students in these tasks consist of their low motivation to hold the responsibility over the learning process and insufficient instructional supports from teachers (Xia, 2014). Most students rely on teachers as capable ones to scaffold their learning process, while teachers found it difficult to provide instructional supports for students with diverse needs.

Guest Editors:

Dr. Sheng-Shiang Tseng

Tamkang University

Dr. Yun Zhou

Shaanxi Normal University

Feb 7, 2022

Call for papers for a special issue on “Designing Microlearning for How People Learn

Although the term microlearning has been around since 2005 (Hug, 2005), its popularity has resurged in recent years as adult learners have become increasingly more mobile and must deal with competing work, family, and educational priorities to invest in lengthy courses or learning materials. Today’s learners can benefit from smaller lessons that deal with a single topic or objective and can be consumed in an accelerated time frame. But what is microlearning exactly? What does a successful microlearning event look like? How long is it? Who is microlearning designed for? And how do you assess the learning in microlearning? These are among the most common questions people ask about the design and implementation of microlearning for today’s learners. Accordingly, the focus of the special issue will be on the design, development, implementation, and assessment of microlearning with an emphasis on designing microlearning with today’s learners in mind.

The benefits of microlearning in training and performance development contexts are well documented as workers need to be able to learn new skills and knowledge quickly to apply them to specific tasks or situations on the job. Microlearning is also starting to take its place in K-12 and higher education. In educational contexts, microlearning strategies can assist in delivering just-in-time informational and instructional content in short, manageable bursts, matching the way learners of all ages are accessing information that interests them in and outside of class.

Guest Editors:

Dr. Joseph Rene Corbeil

Professor of Educational Technology, The University of Texas Rio Grande Valley, USA

Dr. Maria Elena Corbeil

Professor of Educational Technology, The University of Texas Rio Grande Valley, USA

April 19, 2021

With the world is becoming more complex and unpredictable, learners should acquire the basic skills to deal with it. The thinking processes associated with and the problem-solving approach of Computational Thinking (CT) allows learners to better deal with the complexity and open-ended non-trivial problems posed by the world and its emerging technologies (e.g., AI, big data, etc.). Therefore, several research studies advocated considering CT as an essential competence that should be included in all educational levels and in every student’s skill set (Grover & Pea, 2018), as part of pathways to provide CT education and literacy. According to the International Computer and Information Literacy Study (ICILS) 2018, CT can be defined as the “ability to identify a problem, break it down into manageable steps, work out the important details or patterns, shape possible solutions and present these solutions in a way that a computer, human or both can understand” (PISA, 2019).

However, despite the increasing attention towards CT in education, it still has several gaps, from different perspectives, that should be addressed to better understand and advance this field. For example, in a recently published review, Tikva and Tambouris (2021) found that CT curricula are poorly conceptualized. In line with this, Lee et al. (2020) reported that several STEM classrooms are failing to integrate CT into their curricula. De Jong and Jeuring (2020), on the other hand, conducted a recent review of CT in Higher Education and revealed that more investigation is needed to identify the set of CT skills and the assessment methods to measure these skills. Additionally, Lyon and Magana concluded that interest in CT is growing, but there is a need for more concrete definitions and implementations (Lyon & J. Magana, 2020). Particularly, there are a number of challenges in ensuring that computing curricula, tools and environments embody appropriate progression and engender motivation for the topic across the years (Howland et al., 2019).

Guest Editors:

Dr. Ahmed Tlili

Smart Learning Institute of Beijing Normal University, China

Dr. Daniel Burgos

Universidad Internacional de La Rioja (UNIR), Spain

Dr. Chee-Kit Looi

National Institute of Education, Nanyang Technological University, Singapore

November 26, 2019

General Call for Special-Issue Proposals

Educational Technology & Society (ET&S) welcomes special issue proposals on specific themes or topics that address the usage of technology for pedagogical purposes, particularly those reflecting current research trends through in-depth research.

For more information, please visit the Special Issue Proposals page.

The ET&S Editorial Office