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There is an ongoing debate in the literature about the ways of using technology to enhance students’ Computational Thinking (CT). This special issue further enriches this debate by investigating how educational technology could be used, and for which purposes, to facilitate learning CT. It includes six papers demonstrating the innovative design of curricula and the use of various technologies to teach CT for students in different educational levels. Based on these papers, this special issue points out that more research is needed to investigate the best educational practices that could be used to teach CT rather than focusing on the technology itself. It also reveals that future work could cover smart learning analytics and precision education to better model students’ individual differences, hence effectively supporting learning CT.

Using educational robots (ERs) to integrate computational thinking (CT) with cross-disciplinary content has gone beyond Science, Technology, Engineering, and Mathematics (STEM), to include foreign-language learning (FL) and further cross-context target-language (TL) acquisition. Such integration must not solely emphasise CT problem-solving skills. Rather, it must provide students with interactive learning to support their target-language (TL) interaction while reducing potential TL anxiety. This study aimed to validate the effects of the proposed method of pair programming (PP) along with question-and-response interaction in a board-game activity on young learners’ CT skills and TL learning across contexts. Two Grade 6 classes, one with 16 students who were studying Chinese as a Second Language (CSL) and the other with 16 students who were studying English as a Foreign Language (EFL), participated in the activity. A series of instruments on achievement assessment, questionnaires on CT skills and TL anxiety, and sequential learning behaviour analysis were used to critically examine the results. The main conclusion is that the EFL group showed better social skills of cooperation on CT and lower TL learning anxiety, while the CSL group demonstrated better problem-solving skills in CT, but presented more behaviours of trial-and-error loops. Results not only contribute suggestions for cross-disciplinary learning but also provide support for cross-context instruction beyond educational coursework.

Background: The emergence of ChatGPT in the education literature represents a transformative phase in educational technology research, marked by a surge in publications driven by initial research interest in new topics and media hype. While these publications highlight ChatGPT's potential in education, concerns arise regarding their quality, methodology, and uniqueness. Objective: Our study employs unconventional methods by combining altmetrics and bibliometrics to explore ChatGPT in education comprehensively. Methods: Two scholarly databases, Web of Science and Altmetric, were adopted to retrieve publications with citations and those mentioned on social media, respectively. We used a search query, "ChatGPT," and set the publication date between November 30th, 2022, and August 31st, 2023. Both datasets were within the education-related domains. Through a filtering process, we identified three publication categories: 49 papers with both altmetrics and citations, 60 with altmetrics only, and 66 with citations only. Descriptive statistical analysis was conducted on all three lists of papers, further dividing the entire collection into three distinct periods. All the selected papers underwent detailed coding regarding open access, paper types, subject domains, and learner levels. Furthermore, we analysed the keywords occurring and visualized clusters of the co-occurring keywords. Results and Conclusions: An intriguing finding is the significant correlation between media/social media mentions and academic citations in ChatGPT in education papers, underscoring the transformative potential of ChatGPT and the urgency of its incorporation into practice. Our keyword analysis also reveals distinctions between the themes of the papers that received both mentions and citations and those that received only citations but no mentions. Additionally, we noticed a limitation that authors' choice of keywords might be influenced by individual subjective judgements, potentially skewing results in thematic analysis based solely on author-assigned keywords such as keyword co-occurrence analysis. Henceforth, we advocate for developing a standardized keyword taxonomy in the educational technology field and integrating Large Language Models to enhance keyword analysis in altmetric and bibliometric tools. This study reveals that ChatGPT in education literature is evolving from rapid publication to rigorous research.

Guided by the Boundary Activity based Learning (BABL) principle, mobile technology-supported inquiry learning activities were implemented in a primary four science class in Hong Kong. An exploratory study was conducted to examine the effects of the BABL guided inquiry activities on students’ learning performance and to explore how the key element, the boundary object, operated in different learning spaces. In the study, mixed research methods were used to evaluate students’ conceptual understanding and their engagement in and attitudes toward BABL activities. The reciprocal interactions of students’ cognition were qualitatively analyzed in terms of the forms and functions of boundary objects in the BABL environment. The results showed that students made significant improvements in conceptual understanding and were engaged in BABL activities. The study also revealed that the generation of abstract boundary objects, together with physical boundary objects, promoted students’ learning and thinking as they shuttled between the classroom and the outside. This research contributes to informing educators about how to design and implement technology-supported teaching and learning through the use of boundary objects in crossing learning contexts.

Abstract Numerous studies have shown that learning is enhanced when students show interest in the subject matter. However, educators continue to grapple with the challenges, or simply do not recognize their potential roles, in the development of students’ academic interest and interest in learning in general. This conceptual paper is written under the auspices of the interest-driven creator (IDC) initiative, a theoretical synthesis effort carried out by a group of educational researchers in Asia. The intention is to co-construct a holistic developmental/design framework to guide the students in fostering their learning interests, capabilities in creation, and learning habits—the three anchored concepts of IDC theory. This paper focuses on delineating a three-component “interest loop” to guide the design of a coherent learning process that encompasses a series of learning tasks. The three components are triggering interest, immersing interest, and extending interest. Underpinned by the rich literature on interest development, we will propose suitable design strategies for each of the three components, namely, curiosity, flow, and meaningfulness, respectively. We will then explicate their respective design considerations/principles to maximize the intended effects.

Abstract The interest-driven creator (IDC) theory is being developed as a group endeavor by Asian researchers to articulate a holistic learning design theory for future education in Asia. The theory hypothesizes that students, driven by interest, can be engaged in the creation of knowledge (generating ideas and artifacts). By repeating this creation process in their daily learning routines, they will excel in learning performance, develop twenty-first-century competencies, and form creation habits. We hope that with such practices in education, our future generations will ultimately become lifelong interest-driven creators. In IDC Theory, there are three anchored concepts, namely, interest, creation, and habit. Each anchored concept comprises three component concepts which form a concept loop. For example, the creation loop consists of three component concepts—imitating, combining, and staging. Imitating is concerned with taking in (or inputting) an abundant amount of existing knowledge from the outside world to form one’s background knowledge. Combining refers to delivering (or outputting) new ideas or artifacts prolifically by synthesizing existing information encountered in the world and thoughts arising from the students’ background knowledge. Staging relates to frequently demonstrating the generated ideas or artifacts to the relevant communities and receiving feedback from these communities to improve the novelty and value of the demonstrated outcomes while gaining social recognition and nurturing positive social emotions. This paper focuses on describing the three components of the creation loop. We provide three case studies to illustrate the creation loop at work, as well as how it intertwines with both the interest and habit loops in supporting students to develop their creation capabilities. In presenting this iteration of the creation concept, an anchored concept in IDC theory, we acknowledge the roles played of imitation, combination, and staging in different learning and education contexts—indeed, there are multiple theories that inform and intersect with it.

Despite the increasing presence of computational thinking (CT) in the mathematics context, the connection between CT and mathematics in a practical classroom context is an important area for further research. This study intends to investigate the impact of CT activities in the topic of number patterns on the learning performance of secondary students in Singapore. The Rasch model analysis was employed to assess differences of ability between students from the experimental group and control group. 106 Secondary One students (age 13 years old) from a secondary school in Singapore took part in this study. A quasi-experimental non-equivalent groups design was utilized where 70 students were assigned into the experimental group, and 36 students were assigned into the control group. The experimental group was given intervention with CT-infused activities both on- and off-computer, while the control group received no such intervention. Both groups were administered the pretest before the intervention and the posttest after the intervention. The data gathered were analyzed using the partial credit version of the Rasch model. Analysis of pretest and posttest results revealed that the performance of the experimental group was similar to the control group. The findings did not support the hypothesis that integrating CT in lessons can result in improved mathematics learning. However, the drastic improvement was observed in individual students from the experimental group, while there is no obvious or extreme improvement for the students from the control group. This study provides some new empirical evidence and practical contributions to the infusion of CT practices in the mathematics classroom.

Limited research has been conducted on the influence of computational thinking (CT) dispositions on students' mathematics performance and engagement at the secondary or junior high school level. This study aims to bridge this research gap by developing CT-integrated mathematics lessons that incorporate CT-focused problem-solving and modeling in mathematics education. The study was conducted in a secondary school in Singapore, where students engaged in a mathematics modeling task while learning the four pillars of CT. To investigate the impact of integrating CT dispositions on student engagement and mathematics performance, a one-group posttest design together with a survey was administered. Mixed research methods were employed. Structural Equation Modeling analysis revealed that CT dispositions could enhance students' mathematics performance by fostering greater engagement in math, although a direct effect of CT disposition on mathematics performance was not observed. Additionally, interviews with students highlighted their positive dispositions towards CT, including a sense of capability, inclination, and sensitivity in utilizing CT for the modeling task and other contexts.

In the current era where computational literacy holds significant relevance, a growing number of schools across the globe have placed emphasis on K-12 programming education. This field of education primarily comprises two distinct modalities--the block-based programming modality (BPM) and the text-based programming modality (TPM). Previous research may not have provided a complete understanding of the differences between these two modalities as it did not take into account both the learning process and learning outcomes. This study aimed to compare secondary students' programming behaviors, computational thinking skills, and attitudes toward programming between the two modalities through a quasi-experimental design in a Chinese secondary school. The findings showed that (1) learners in TPM encountered more syntactical errors and spent more time between two clicks of debugging, while learners in BPM had more code-changing behaviors by adjusting programming blocks, made more attempts of debugging, and had more irrelevant behaviors; (2) learners in BPM achieved a higher level of computational thinking skills; (3) learners in both modalities experienced a slight decrease in confidence and enjoyment, while learners in BPM had higher interest levels in programming. (4) Code Changer, Minimal Debugger, Maximal Debugger, Distracted Coder and Average Coder were identified through students' programming behavior in the two programming modalities, and differences in their CT skills and attitudinal data were revealed. Lastly, pedagogical implications based on the findings are also discussed.

Abstract Appropriate design of collaborative learning activities for students using mobile devices can be supported by different forms of scaffolding provided by peers, by the teacher or by the technology. Building on prior studies in mCSCL (mobile computer-supported collaborative learning), we developed Chinese-PP, a novel in-class mobile synchronous collaborative learning game for constructing Chinese characters from components, with the unique characteristic of spontaneous small group formations. In this paper, we propose a distributed scaffolding design framework to guide us in examining and refining/revising the interplay among various forms of scaffolding in the learning model across various design-based research (DBR) cycles of our study on Chinese-PP in a primary school in Singapore. We believe a generalized scaffolding design framework has the potential to inform technology-enhanced learning research with a structure to support the iterative process of enacting and redesigning the socio-techno-pedagogical frameworks developed by individual research projects.

The use of artificial intelligence has played an important role in science teaching and learning. The purpose of this study was to fill a gap in the current review of research on AI in science education (AISE) in the early stage of education by systematically reviewing existing research in this area. This systematic review examined the trends and research foci of AI in the science of early stages of education. This review study employed a bibliometric analysis and content analysis to examine the characteristics of 76 studies on Artificial Intelligence in Science Education (AISE) indexed in Web of Science and Scopus from 2013 to 2023. The analytical tool CiteSpace was utilized for the analysis. The study aimed to provide an overview of the development level of AISE and identify major research trends, keywords, research themes, high-impact journals, institutions, countries/regions, and the impact of AISE studies. The results, based on econometric analyses, indicate that AISE has experienced increasing influence over the past decade. Cluster and timeline analyses of the retrieved keywords revealed that AI in primary and secondary science education can be categorized into 11 main themes, and the chronology of their emergence was identified. Among the most prolific journals in this field are the International Journal of Social Robotics, Educational Technology Research and Development, and others. Furthermore, the analysis identified that institutions and countries/regions located primarily in the United States have made the most significant contributions to AISE research. To explore the learning outcomes and overall impact of AI technologies on learners in primary and secondary schools, content analysis was conducted, identifying five main categories of technology applications. This study provides valuable insights into the advancements and implications of AI in science education at the primary and secondary levels.

This study investigates the role of a collaboration script, the Funnel Model, in supporting students' computer-supported collaborative scientific argumentation, and how the students appropriated the collaboration script in scientific argumentation. In this exploratory case study, a class of 33 Secondary grade four students went through four phases of computer-supported collaborative argumentation activity scripted by the Funnel Model: individual ideation, intra-group synergy, inter-group critique and intra-group refinement. Multiple sources of data were collected including student-generated artefacts online at different phases of collaboration, and the post-intervention interviews with the students. The results show that the Funnel Model facilitated students' computer-supported collaborative argumentation. The students' levels of content mastery, motivation, classroom culture and time allocated for classroom participation affect students' appropriation of the script for effective collaborative argumentation.

The term ‘orchestrating learning’ is being used increasingly often, referring to the coordination activities performed while applying learning technologies to authentic settings. However, there is little consensus about how this notion should be conceptualised, and what aspects it entails. In this paper, a conceptual framework for orchestration-related research is evaluated by an international panel of learning technology experts. The results of this evaluation show that the framework is complete and understandable, and it is particularly useful as an integrative list of aspects to consider when designing and evaluating learning technologies. To illustrate a way in which the framework can be used to help researchers structure their classroom innovation evaluations, an example is presented that follows the adoption of the framework by a group of researchers in Singapore. Finally, a new evolved version of the framework is presented, taking into account the evaluation feedback.

This study focuses on university students' experience of peer tutoring supported by a mobile application called MENTOR (Mobile Education Networked Tutoring On Request) that was developed by the research team. The development of the mobile application was underpinned by theories related to self-directed learning, self-regulated learning, students' help-seeking behaviors, as well as Vygotsky's social-cultural learning theory. Using cultural-historical activity theory (CHAT) as the framework, this study examines the affordances of the mobile application, the student's perception of the application, the uptake of affordances, and the contradictions identified through CHAT. The participants identified tutor's factors (e.g. tutoring skills) and technological factors (e.g. annotatable canvas) that facilitated the process, and appreciated the affordances of convenience, flexibility, physical safety, and psychological safety of the mobile peer tutoring, especially during the COVID-19 situation. A few contradictions were identified through CHAT, which served as the impetus for improvement. Among these are the novelty of mobile peer tutoring and the lack of cues about turn-taking. Some participants did not understand the requirement to indicate the level of cognitive processing. This study contributes to the design and implementation of mobile technology in supporting peer tutoring, an under-researched topic.

Blended learning (BL), an innovative, technology-supported pedagogical approach, has been extensively adopted in schools and universities. The learning effectiveness of BL has been investigated in multiple domains of education, computer science, nursing, engineering, and psychology. To uncover the major trends of BL research, this study embarked on a bibliometric analysis of a total of 719 studies published in the recent 10 years (2013-2022) and indexed in the Web of Science core collection. Adopting a quantitative approach and the visual analytical tool of CiteSpace, the review study identified the development trends, the influential researchers and research institutions, and pivotal studies and topics of the field and informed its future progression. The findings revealed a growing trend in BL research in the past decade as reflected in the exponential growth in the number of publications and citations. Charles R. Graham, Chang Zhu, Robert A. Ellis, and Feifei Han were the most prolific, influential researchers in the field, and the Griffith University, the University of Hong Kong, the Vrije Universiteit Brussel, the Monash University, and the National Taiwan Normal University were the prominent research institutions, which engaged in frequent collaborations with others. The United States, China, and Australia were the top-3 contributors to BL research measured by the number of publications, and the studies conducted and reported by researchers in the USA, Turkey, Taiwan, and Spain were cited the most often. Document co-citation analysis unveiled the pivotal studies and topics of the research field, including blended course designs, institutional adoption, achievement, higher education, active BL, flipped classroom, and communication skills. [ABSTRACT FROM AUTHOR]

Using educational robots (ERs) to integrate computational thinking (CT) with cross-disciplinary content has gone beyond Science, Technology, Engineering, and Mathematics (STEM), to include foreign-language learning (FL) and further cross-context target-language (TL) acquisition. Such integration must not solely emphasise CT problem-solving skills. Rather, it must provide students with interactive learning to support their target-language (TL) interaction while reducing potential TL anxiety. This study aimed to validate the effects of the proposed method of pair programming (PP) along with question-and-response interaction in a board-game activity on young learners' CT skills and TL learning across contexts. Two Grade 6 classes, one with 16 students who were studying Chinese as a Second Language (CSL) and the other with 16 students who were studying English as a Foreign Language (EFL), participated in the activity. A series of instruments on achievement assessment, questionnaires on CT skills and TL anxiety, and sequential learning behaviour analysis were used to critically examine the results. The main conclusion is that the EFL group showed better social skills of cooperation on CT and lower TL learning anxiety, while the CSL group demonstrated better problem-solving skills in CT, but presented more behaviours of trial-and-error loops. Results not only contribute suggestions for cross-disciplinary learning but also provide support for cross-context instruction beyond educational coursework. [ABSTRACT FROM AUTHOR]